@Article{info:doi/10.2196/19697,
author="Chung, Alicia
and Vieira, Dorice
and Donley, Tiffany
and Tan, Nicholas
and Jean-Louis, Girardin
and Kiely Gouley, Kathleen
and Seixas, Azizi",
title="Adolescent Peer Influence on Eating Behaviors via Social Media: Scoping Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e19697",
keywords="social media",
keywords="eating behaviors",
keywords="adolescent health",
abstract="Background: The influence of social media among adolescent peer groups can be a powerful change agent. Objective: Our scoping review aimed to elucidate the ways in which social media use among adolescent peers influences eating behaviors. Methods: A scoping review of the literature of articles published from journal inception to 2019 was performed by searching PubMed (ie, MEDLINE), Embase, CINAHL, PsycINFO, Web of Science, and other databases. The review was conducted in three steps: (1) identification of the research question and clarification of criteria using the population, intervention, comparison, and outcome (PICO) framework; (2) selection of articles from the literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; and (3) charting and summarizing information from selected articles. PubMed's Medical Subject Headings (MeSH) and Embase's Emtree subject headings were reviewed along with specific keywords to construct a comprehensive search strategy. Subject headings and keywords were based on adolescent age groups, social media platforms, and eating behaviors. After screening 1387 peer-reviewed articles, 37 articles were assessed for eligibility. Participant age, gender, study location, social media channels utilized, user volume, and content themes related to findings were extracted from the articles. Results: Six articles met the final inclusion criteria. A final sample size of 1225 adolescents (aged 10 to 19 years) from the United States, the United Kingdom, Sweden, Norway, Denmark, Portugal, Brazil, and Australia were included in controlled and qualitative studies. Instagram and Facebook were among the most popular social media platforms that influenced healthful eating behaviors (ie, fruit and vegetable intake) as well as unhealthful eating behaviors related to fast food advertising. Online forums served as accessible channels for eating disorder relapse prevention among youth. Social media influence converged around four central themes: (1) visual appeal, (2) content dissemination, (3) socialized digital connections, and (4) adolescent marketer influencers. Conclusions: Adolescent peer influence in social media environments spans the spectrum of healthy eating (ie, pathological) to eating disorders (ie, nonpathological). Strategic network-driven approaches should be considered for engaging adolescents in the promotion of positive dietary behaviors. ",
doi="10.2196/19697",
url="https://www.jmir.org/2021/6/e19697",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081018"
}


@Article{info:doi/10.2196/23473,
author="El Benny, Mariam
and Kabakian-Khasholian, Tamar
and El-Jardali, Fadi
and Bardus, Marco",
title="Application of the eHealth Literacy Model in Digital Health Interventions: Scoping Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e23473",
keywords="eHealth literacy",
keywords="digital health interventions",
keywords="consumer health information",
keywords="scoping review",
keywords="mHealth",
keywords="mobile phone",
abstract="Background: Digital health interventions (DHIs) are increasingly being adopted globally to address various public health issues. DHIs can be categorized according to four main types of technology: mobile based, web based, telehealth, and electronic health records. In 2006, Norman and Skinner introduced the eHealth literacy model, encompassing six domains of skills and abilities (basic, health, information, scientific, media, and computer) needed to effectively understand, process, and act on health-related information. Little is known about whether these domains are assessed or accounted for in DHIs. Objective: This study aims to explore how DHIs assess and evaluate the eHealth literacy model, describe which health conditions are addressed, and which technologies are used. Methods: We conducted a scoping review of the literature on DHIs, based on randomized controlled trial design and reporting the assessment of any domain of the eHealth literacy model. MEDLINE, CINAHL, Embase, and Cochrane Library were searched. A duplicate selection and data extraction process was performed; we charted the results according to the country of origin, health condition, technology used, and eHealth literacy domain. Results: We identified 131 unique DHIs conducted in 26 different countries between 2001 and 2020. Most DHIs were conducted in English-speaking countries (n=81, 61.8\%), delivered via the web (n=68, 51.9\%), and addressed issues related to noncommunicable diseases (n=57, 43.5\%) or mental health (n=26, 19.8\%). None of the interventions assessed all six domains of the eHealth literacy model. Most studies focused on the domain of health literacy (n=96, 73.2\%), followed by digital (n=19, 14.5\%), basic and media (n=4, 3\%), and information and scientific literacy (n=1, 0.7\%). Of the 131 studies, 7 (5.3\%) studies covered both health and digital literacy. Conclusions: Although many selected DHIs assessed health or digital literacy, no studies comprehensively evaluated all domains of the eHealth literacy model; this evidence might be overlooking important factors that can mediate or moderate the effects of these interventions. Future DHIs should comprehensively assess the eHealth literacy model while developing or evaluating interventions to understand how and why interventions can be effective. ",
doi="10.2196/23473",
url="https://www.jmir.org/2021/6/e23473",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081023"
}


@Article{info:doi/10.2196/24564,
author="Wawrzuta, Dominik
and Jaworski, Mariusz
and Gotlib, Joanna
and Panczyk, Mariusz",
title="Characteristics of Antivaccine Messages on Social Media: Systematic Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e24564",
keywords="vaccination",
keywords="social media",
keywords="antivaccination movement",
keywords="vaccination refusal",
keywords="health communication",
keywords="public health",
keywords="vaccines",
abstract="Background: Supporters of the antivaccination movement can easily spread information that is not scientifically proven on social media. Therefore, learning more about their posts and activities is instrumental in effectively reacting and responding to the false information they publish, which is aimed at discouraging people from taking vaccines. Objective: This study aims to gather, assess, and synthesize evidence related to the current state of knowledge about antivaccine social media users' web-based activities. Methods: We systematically reviewed English-language papers from 3 databases (Scopus, Web of Science, and PubMed). A data extraction form was established, which included authors, year of publication, specific objectives, study design, comparison, and outcomes of significance. We performed an aggregative narrative synthesis of the included studies. Results: The search strategy retrieved 731 records in total. After screening for duplicates and eligibility, 18 articles were included in the qualitative synthesis. Although most of the authors analyzed text messages, some of them studied images or videos. In addition, although most of the studies examined vaccines in general, 5 focused specifically on human papillomavirus vaccines, 2 on measles vaccines, and 1 on influenza vaccines. The synthesized studies dealt with the popularity of provaccination and antivaccination content, the style and manner in which messages about vaccines were formulated for the users, a range of topics concerning vaccines (harmful action, limited freedom of choice, and conspiracy theories), and the role and activity of bots in the dissemination of these messages in social media. Conclusions: Proponents of the antivaccine movement use a limited number of arguments in their messages; therefore, it is possible to prepare publications clarifying doubts and debunking the most common lies. Public health authorities should continuously monitor social media to quickly find new antivaccine arguments and then create information campaigns for both health professionals and other users. ",
doi="10.2196/24564",
url="https://www.jmir.org/2021/6/e24564",
url="http://www.ncbi.nlm.nih.gov/pubmed/34085943"
}


@Article{info:doi/10.2196/24712,
author="Shah, Sarwar Syed Ghulam
and Nogueras, David
and van Woerden, Cornelis Hugo
and Kiparoglou, Vasiliki",
title="Evaluation of the Effectiveness of Digital Technology Interventions to Reduce Loneliness in Older Adults: Systematic Review and Meta-analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e24712",
keywords="loneliness",
keywords="older people",
keywords="digital technology",
keywords="effectiveness",
keywords="efficacy",
keywords="evidence",
keywords="systematic review",
keywords="meta-analysis",
abstract="Background: Loneliness is a serious public health issue, and its burden is increasing in many countries. Loneliness affects social, physical, and mental health, and it is associated with multimorbidity and premature mortality. In addition to social interventions, a range of digital technology interventions (DTIs) are being used to tackle loneliness. However, there is limited evidence on the effectiveness of DTIs in reducing loneliness, especially in adults. The effectiveness of DTIs in reducing loneliness needs to be systematically assessed. Objective: The objective of this study is to assess the effectiveness of DTIs in reducing loneliness in older adults. Methods: We conducted electronic searches in PubMed, MEDLINE, CINAHL, Embase, and Web of Science for empirical studies published in English from January 1, 2010, to July 31, 2019. The study selection criteria included interventional studies that used any type of DTIs to reduce loneliness in adults (aged ?18 years) with a minimum intervention duration of 3 months and follow-up measurements at least 3 months after the intervention. Two researchers independently screened articles and extracted data using the PICO (participant, intervention, comparator, and outcome) framework. The primary outcome measure was loneliness. Loneliness scores in both the intervention and control groups at baseline and at follow-up at 3, 4, 6, and 12 months after the intervention were extracted. Data were analyzed via narrative synthesis and meta-analysis using RevMan (The Cochrane Collaboration) software. Results: A total of 6 studies were selected from 4939 screened articles. These studies included 1 before and after study and 5 clinical trials (4 randomized clinical trials and 1 quasi-experimental study). All of these studies enrolled a total of 646 participants (men: n=154, 23.8\%; women: n=427, 66.1\%; no gender information: n=65, 10.1\%) with an average age of 73-78 years (SD 6-11). Five clinical trials were included in the meta-analysis, and by using the random effects model, standardized mean differences (SMDs) were calculated for each trial and pooled across studies at the 3-, 4-, and 6-month follow-ups. The overall effect estimates showed no statistically significant difference in the effectiveness of DTIs compared with that of usual care or non-DTIs at follow-up at 3 months (SMD 0.02; 95\% CI ?0.36 to 0.40; P=.92), 4 months (SMD ?1.11; 95\% CI ?2.60 to 0.38; P=.14), and 6 months (SMD ?0.11; 95\% CI ?0.54 to 0.32; P=.61). The quality of evidence was very low to moderate in these trials. Conclusions: Our meta-analysis shows no evidence supporting the effectiveness of DTIs in reducing loneliness in older adults. Future research may consider randomized controlled trials with larger sample sizes and longer durations for both the interventions and follow-ups. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-032455 ",
doi="10.2196/24712",
url="https://www.jmir.org/2021/6/e24712",
url="http://www.ncbi.nlm.nih.gov/pubmed/34085942"
}


@Article{info:doi/10.2196/25236,
author="Kolotylo-Kulkarni, Malgorzata
and Seale, E. Deborah
and LeRouge, M. Cynthia",
title="Personal Health Information Management Among Older Adults: Scoping Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e25236",
keywords="personal health information management",
keywords="health information management",
keywords="scoping review",
keywords="information management",
keywords="consumer health informatics",
keywords="medical informatics",
keywords="patient participation",
abstract="Background: Older adults face growing health care needs and could potentially benefit from personal health information management (PHIM) and PHIM technology. To ensure effective PHIM and to provide supportive tools, it is crucial to investigate the needs, challenges, processes, and tools used by this subpopulation. The literature on PHIM by older adults, however, remains scattered and has not provided a clear picture of what we know about the elements that play a role in older adults' PHIM. Objective: The goal of our review was to provide a comprehensive overview of extant knowledge on PHIM by older adults, establish the status quo of research on this topic, and identify research gaps. Methods: We carried out a scoping review of the literature from 1998 to 2020, which followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) framework. First, we executed a broad and structured search. We then carried out a qualitative analysis of papers pertinent to the topic taking into consideration the five elements of the patient work system as follows: (1) personal-level factors, (2) PHIM tasks, (3) tools used, (4) physical settings of PHIM activities, and (5) socio-organizational aspects. Results: The review included 22 studies. Consolidated empirical evidence was related to all elements of the patient work system. Multiple personal factors affected PHIM. Various types of personal health information were managed (clinical, patient-generated, and general) and tools were used (electronic, paper-based, and others). Older adults' PHIM was intertwined with their surroundings, and various individuals participated. The largest body of evidence concerned personal factors, while findings regarding the physical environment of PHIM were scarce. Most research has thus far examined older adults as a single group, and scant attention has been paid to age subgroups. Conclusions: Opportunities for further PHIM studies remain across all elements of the patient work system in terms of empirical, design science, or review work. ",
doi="10.2196/25236",
url="https://www.jmir.org/2021/6/e25236",
url="http://www.ncbi.nlm.nih.gov/pubmed/34096872"
}


@Article{info:doi/10.2196/24584,
author="K{\"o}hnen, Moritz
and Kriston, Levente
and H{\"a}rter, Martin
and Baumeister, Harald
and Liebherz, Sarah",
title="Effectiveness and Acceptance of Technology-Based Psychological Interventions for the Acute Treatment of Unipolar Depression: Systematic Review and Meta-analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="13",
volume="23",
number="6",
pages="e24584",
keywords="internet",
keywords="digital health",
keywords="digital mental health",
keywords="telephone",
keywords="psychotherapy",
keywords="depressive disorder",
keywords="systematic review",
keywords="meta-analysis",
keywords="technology-based psychological interventions",
abstract="Background: Evidence on technology-based psychological interventions (TBIs) for the acute treatment of depression is rapidly growing. Despite extensive research in this field, there is a lack of research determining effectiveness and acceptance of TBIs considering different application formats in people with a formally diagnosed depressive disorder. Objective: The goal of the review was to investigate the effectiveness and acceptance of TBIs in people with diagnosed depression with particular focus on application formats (stand-alone interventions, blended treatments, collaborative and/or stepped care interventions). Methods: Studies investigating adults with diagnosed unipolar depressive disorders receiving any kind of psychotherapeutic treatment delivered (at least partly) by a technical medium and conducted as randomized controlled trials (RCTs) were eligible for inclusion. We searched CENTRAL (Cochrane Central Register of Controlled Trials; August 2020), MEDLINE, PsycINFO, PSYNDEX, CINAHL (January 2018), clinical trial registers, and sources of grey literature (January 2019). Two independent authors decided about study inclusion and extracted data. We performed random effects meta-analyses to synthesize the data. Results: Database searches resulted in 15,546 records of which 78 completed studies were included. TBIs delivered as stand-alone interventions showed positive effects on posttreatment depression severity when compared to treatment as usual (SMD --0.44, 95\% CI --0.73 to --0.15, k=10; I{\texttwosuperior}=86\%), attention placebo (SMD --0.51, 95\% CI --0.73 to --0.30; k=12; I{\texttwosuperior}=66\%), and waitlist controls (SMD --1.01, 95\% CI --1.23 to --0.79; k=19; I{\texttwosuperior}=73\%). Superior long-term effects on depression severity were shown when TBIs were compared to treatment as usual (SMD --0.24, 95\% CI --0.41 to --0.07; k=6; I{\texttwosuperior}=48\%) attention placebo (SMD --0.23, 95\% CI --0.40 to --0.07; k=7; I{\texttwosuperior}=21\%) and waitlist controls (SMD --0.74, 95\% CI --1.31 to --0.18; k=3; I{\texttwosuperior}=79\%). TBIs delivered as blended treatments (providing a TBI as an add-on to face-to-face treatment) yielded beneficial effects on posttreatment depression severity (SMD --0.27, 95\% CI --0.48 to --0.05; k=8; I{\texttwosuperior}=53\%) compared to face-to-face treatments only. Additionally, TBIs delivered within collaborative care trials were more effective in reducing posttreatment (SMD --0.20, 95\% CI --0.36 to --0.04; k=2; I{\texttwosuperior}=0\%) and long-term (SMD --0.23, 95\% CI --0.39 to --0.07; k=2; I{\texttwosuperior}=0\%) depression severity than usual care. Dropout rates did not differ between the intervention and control groups in any comparison (all P?.09). Conclusions: We found that TBIs are effective not only when delivered as stand-alone interventions but also when they are delivered as blended treatments or in collaborative care trials for people with diagnosed depression. Our results may be useful to inform routine care, since we focused specifically on different application formats, formally diagnosed patients, and the long-term effectiveness of TBIs. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42016050413; https://www.crd.york.ac.uk/prospero/display\_record.php?ID=CRD42016050413 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2018-028042 ",
doi="10.2196/24584",
url="https://www.jmir.org/2021/6/e24584/",
url="http://www.ncbi.nlm.nih.gov/pubmed/36260395"
}


@Article{info:doi/10.2196/24967,
author="Ridout, Brad
and Kelson, Joshua
and Campbell, Andrew
and Steinbeck, Kate",
title="Effectiveness of Virtual Reality Interventions for Adolescent Patients in Hospital Settings: Systematic Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="28",
volume="23",
number="6",
pages="e24967",
keywords="virtual reality",
keywords="hospital",
keywords="pain",
keywords="anxiety",
keywords="adolescents",
abstract="Background: Given the high level of interest and increasing familiarity with virtual reality among adolescents, there is great potential to use virtual reality to address adolescents' unique health care delivery needs while in hospital. While there have been reviews on the use of virtual reality for specific health conditions and procedures, none to date have reviewed the full scope of virtual reality hospital interventions for adolescents who are often combined with children as a homogenous group, despite the fact that adolescents experience virtual environments different from children. Objective: The aim of this review was to systematically identify available evidence regarding the use of virtual reality interventions for adolescent patients in hospital settings to evaluate effectiveness, suitability, and safety and identify opportunities for future research. Methods: PubMed, PsycINFO, Medline, and Scopus databases were searched using keywords and phrases. Retrieved abstracts (n=1525) were double screened, yielding 276 articles for full-text screening. Of these, 8 articles met inclusion criteria. Data were extracted to a standardized coding sheet, and a narrative synthesis was performed due to the heterogeneity of the studies. Results: Four RCTs and 4 single-case reports were identified for inclusion, all of which aimed to reduce pain or anxiety. The scenarios targeted were burn pain, venipuncture, chemotherapy, preoperative anxiety, and palliative care. Three out of 4 RCTs found significant reductions in pain or anxiety outcomes measures when using virtual reality compared to standard care or other distraction techniques; however, only 1 study combined self-reported experiences of pain or anxiety with any physiological measures. Single-case reports relied primarily upon qualitative feedback, with patients reporting reduced pain or anxiety and a preference for virtual reality to no virtual reality. Conclusions: Virtual reality can provide a safe and engaging way to reduce pain and anxiety in adolescents while in hospital, particularly when virtual reality software is highly immersive and specifically designed for therapeutic purposes. As VR becomes more accessible and affordable for use in hospitals, larger and more diverse studies that capitalize on adolescents' interest in and aptitude for virtual reality, and on the full range of capabilities of this emerging technology, are needed to build on these promising results. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020198760; https://www.crd.york.ac.uk/prospero/display\_record.php?ID=CRD42020198760 ",
doi="10.2196/24967",
url="https://www.jmir.org/2021/6/e24967",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185015"
}


@Article{info:doi/10.2196/18035,
author="De Croon, Robin
and Van Houdt, Leen
and Htun, Nyi Nyi
and {\vS}tiglic, Gregor
and Vanden Abeele, Vero
and Verbert, Katrien",
title="Health Recommender Systems: Systematic Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="29",
volume="23",
number="6",
pages="e18035",
keywords="health recommender systems",
keywords="recommender",
keywords="recommendation system",
keywords="health",
keywords="health care",
keywords="patient",
keywords="layperson",
keywords="systematic review",
keywords="eHealth",
keywords="evaluation",
keywords="recommender technique",
keywords="user interface",
keywords="guidelines",
keywords="mobile phone",
abstract="Background: Health recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior. Objective: We aim to review HRSs targeting nonmedical professionals (laypersons) to better understand the current state of the art and identify both the main trends and the gaps with respect to current implementations. Methods: We conducted a systematic literature review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and synthesized the results. A total of 73 published studies that reported both an implementation and evaluation of an HRS targeted to laypersons were included and analyzed in this review. Results: Recommended items were classified into four major categories: lifestyle, nutrition, general health care information, and specific health conditions. The majority of HRSs use hybrid recommendation algorithms. Evaluations of HRSs vary greatly; half of the studies only evaluated the algorithm with various metrics, whereas others performed full-scale randomized controlled trials or conducted in-the-wild studies to evaluate the impact of HRSs, thereby showing that the field is slowly maturing. On the basis of our review, we derived five reporting guidelines that can serve as a reference frame for future HRS studies. HRS studies should clarify who the target user is and to whom the recommendations apply, what is recommended and how the recommendations are presented to the user, where the data set can be found, what algorithms were used to calculate the recommendations, and what evaluation protocol was used. Conclusions: There is significant opportunity for an HRS to inform and guide health actions. Through this review, we promote the discussion of ways to augment HRS research by recommending a reference frame with five design guidelines. ",
doi="10.2196/18035",
url="https://www.jmir.org/2021/6/e18035",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185014"
}


@Article{info:doi/10.2196/20861,
author="Adriaans, JM Danielle
and Dierick-van Daele, TM Angelique
and van Bakel, Maria Marc Johannes Hubertus
and Nieuwenhuijzen, AP Grard
and Teijink, AW Joep
and Heesakkers, FBM Fanny
and van Laarhoven, WM Hanneke",
title="Digital Self-Management Support Tools in the Care Plan of Patients With Cancer: Review of Randomized Controlled Trials",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="29",
volume="23",
number="6",
pages="e20861",
keywords="web-based intervention",
keywords="digital self-management support tool",
keywords="chronic patient groups",
keywords="review",
keywords="digital health",
keywords="ehealth",
keywords="mhealth",
keywords="cancer patients",
keywords="mobile phone",
abstract="Background: Digital self-management support tools (DSMSTs)---electronic devices or monitoring systems to monitor or improve health status---have become increasingly important in cancer care. Objective: The aim of this review is to analyze published randomized clinical trials to assess the effectiveness of DSMSTs on physical and psychosocial symptoms or other supportive care needs in adult patients with cancer. Methods: Five databases were searched from January 2013 to January 2020. English or Dutch language randomized controlled trials comparing DSMSTs with no intervention, usual care, alternative interventions, or a combination and including patients aged ?18 years with pathologically proven cancer in the active treatment or survivorship phases were included. The results were summarized qualitatively. Results: A total of 19 publications describing 3 types of DSMSTs were included. Although the content, duration, and frequency of interventions varied considerably across studies, the commonly used elements included an assessment component, tailored symptom self-management support, an information section, a communication section, and a diary. Significant positive effects were observed on quality of life in 6 (out of 10) studies, on anxiety in 1 (out of 5) study and depression in 2 (out of 8) studies, on symptom distress in 5 (out of 7) studies, on physical activity in 4 (out of 6) studies, on dietary behavior in 1 (out of 4) study, and on fatigue in 2 (out of 5) studies. Moreover, significant negative effects were observed on anxiety in 1 (out of 5) study and depression in 1 (out of 8) study. Most interventions were web-based interventions; 2 studies used mobile apps, and 1 study used a game as a DSMST. The overall quality of the studies was found to be good, with 13 out of 19 studies classified as high quality. Conclusions: This review suggests that DSMSTs have a beneficial effect on the quality of life. For effects on other patient outcomes (eg, anxiety and depression, symptom distress, physical activity, dietary behavior, and fatigue), the evidence is inconsistent and limited or no effect is suggested. Future research should focus on specific tumor types, study different types of interventions separately, and assess the effects of specific interventions at different stages of disease progression. ",
doi="10.2196/20861",
url="https://www.jmir.org/2021/6/e20861",
url="http://www.ncbi.nlm.nih.gov/pubmed/34184997"
}


@Article{info:doi/10.2196/27105,
author="Lau, Nancy
and O'Daffer, Alison
and Yi-Frazier, Joyce
and Rosenberg, R. Abby",
title="Goldilocks and the Three Bears: A Just-Right Hybrid Model to Synthesize the Growing Landscape of Publicly Available Health-Related Mobile Apps",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e27105",
keywords="telemedicine",
keywords="smartphone",
keywords="mobile phones",
keywords="mHealth",
keywords="mobile apps",
keywords="health services",
doi="10.2196/27105",
url="https://www.jmir.org/2021/6/e27105",
url="http://www.ncbi.nlm.nih.gov/pubmed/34096868"
}


@Article{info:doi/10.2196/17137,
author="An, Ning
and Mattison, John
and Chen, Xinyu
and Alterovitz, Gil",
title="Team Science in Precision Medicine: Study of Coleadership and Coauthorship Across Health Organizations",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e17137",
keywords="precision medicine",
keywords="team science",
abstract="Background: Interdisciplinary collaborations bring lots of benefits to researchers in multiple areas, including precision medicine. Objective: This viewpoint aims at studying how cross-institution team science would affect the development of precision medicine. Methods: Publications of organizations on the eHealth Catalogue of Activities were collected in 2015 and 2017. The significance of the correlation between coleadership and coauthorship among different organizations was calculated using the Pearson chi-square test of independence. Other nonparametric tests examined whether organizations with coleaders publish more and better papers than organizations without coleaders. Results: A total of 374 publications from 69 organizations were analyzed in 2015, and 7064 papers from 87 organizations were analyzed in 2017. Organizations with coleadership published more papers (P<.001, 2015 and 2017), which received higher citations (Z=--13.547, P<.001, 2017), compared to those without coleadership. Organizations with coleaders tended to publish papers together (P<.001, 2015 and 2017). Conclusions: Our findings suggest that organizations in the field of precision medicine could greatly benefit from institutional-level team science. As a result, stronger collaboration is recommended. ",
doi="10.2196/17137",
url="https://www.jmir.org/2021/6/e17137",
url="http://www.ncbi.nlm.nih.gov/pubmed/34125070"
}


@Article{info:doi/10.2196/25946,
author="Wang, Zhengfei
and Wang, Lai
and Xiao, Fu'an
and Chen, Qingsong
and Lu, Liming
and Hong, Jiaming",
title="A Traditional Chinese Medicine Traceability System Based on Lightweight Blockchain",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e25946",
keywords="blockchain",
keywords="traditional Chinese medicine",
keywords="TCM",
keywords="traceability system",
keywords="fake drugs",
keywords="IPFS",
keywords="fraud",
keywords="traceability",
abstract="Background: Recently, the problem of traditional Chinese medicine (TCM) safety has attracted attention worldwide. To prevent the spread of counterfeit drugs, it is necessary to establish a drug traceability system. A traditional drug traceability system can record the whole circulation process of drugs, from planting, production, processing, and warehousing to use by hospitals and patients. Once counterfeit drugs are found, they can be traced back to the source. However, traditional drug traceability systems have some drawbacks, such as failure to prevent tampering and facilitation of sensitive disclosure. Blockchain (including Bitcoin and Ethernet Square) is an effective technology to address the problems of traditional drug traceability systems. However, some risks impact the reliability of blockchain, such as information explosion, sensitive information leakage, and poor scalability. Objective: To avoid the risks associated with the application of blockchain, we propose a lightweight block chain framework. Methods: In this framework, both horizontal and vertical segmentations are performed when designing the blocks, and effective strategies are provided for both segmentations. For horizontal segmentation operations, the header and body of the blockchain are separated and stored in the blockchain, and the body is stored in the InterPlanetary File System. For vertical segmentation operations, the blockchain is cut off according to time or size. For the addition of new blocks, miners only need to copy the latest part of the blockchain and append the tail and vertical segmentation of the block through the consensus mechanism. Results: Our framework could greatly reduce the size of the blockchain and improve the verification efficiency. Conclusions: Experimental results have shown that the efficiency improves compared with ethernet when a new block is added to the blockchain and a search is conducted. ",
doi="10.2196/25946",
url="https://www.jmir.org/2021/6/e25946",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152279"
}


@Article{info:doi/10.2196/26694,
author="Persson, Johanna
and Rydenf{\"a}lt, Christofer",
title="Why Are Digital Health Care Systems Still Poorly Designed, and Why Is Health Care Practice Not Asking for More? Three Paths Toward a Sustainable Digital Work Environment",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="22",
volume="23",
number="6",
pages="e26694",
keywords="digital systems",
keywords="electronic health records",
keywords="digital work environment",
keywords="ergonomics",
keywords="usability",
keywords="human-centered design",
doi="10.2196/26694",
url="https://www.jmir.org/2021/6/e26694",
url="http://www.ncbi.nlm.nih.gov/pubmed/34156336"
}


@Article{info:doi/10.2196/24303,
author="Yang, Nancy
and Wu, Dan
and Zhou, Yi
and Huang, Shanzi
and He, Xi
and Tucker, Joseph
and Li, Xiaofeng
and Smith, M. Kumi
and Jiang, Xiaohui
and Wang, Yehua
and Huang, Wenting
and Fu, Hongyun
and Bao, Huanyu
and Jiang, Hongbo
and Dai, Wencan
and Tang, Weiming",
title="Sexual Health Influencer Distribution of HIV/Syphilis Self-Tests Among Men Who Have Sex With Men in China: Secondary Analysis to Inform Community-Based Interventions",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="1",
volume="23",
number="6",
pages="e24303",
keywords="sexual health influencer",
keywords="men who have sex with men",
keywords="HIV",
keywords="syphilis",
keywords="self-test",
keywords="sexual health",
keywords="influencer",
keywords="social network",
keywords="peers",
abstract="Background: Social network--based strategies can expand HIV/syphilis self-tests among men who have sex with men (MSM). Sexual health influencers are individuals who are particularly capable of spreading information about HIV and other sexually transmitted infections (STIs) within their social networks. However, it remains unknown whether a sexual health influencer can encourage their peers to self-test for HIV/syphilis. Objective: The aims of this study were to examine the impact of MSM sexual health influencers on improving HIV/syphilis self-test uptake within their social networks compared to that of nonsexual health influencers. Methods: In Zhuhai, China, men 16 years or older, born biologically male, who reported ever having had sex with a man, and applying for HIV/syphilis self-tests were enrolled online as indexes and encouraged to distribute self-tests to individuals (alters) in their social network. Indexes scoring >3 on a sexual health influencer scale were considered to be sexual health influencers (Cronbach $\alpha$=.87). The primary outcome was the mean number of alters encouraged to test per index for sexual health influencers compared with the number encouraged by noninfluencers. Results: Participants included 371 indexes and 278 alters. Among indexes, 77 (20.8\%) were sexual health influencers and 294 (79.2\%) were noninfluencers. On average, each sexual health influencer successfully encouraged 1.66 alters to self-test compared to 0.51 alters encouraged by each noninfluencer (adjusted rate ratio 2.07, 95\% CI 1.59-2.69). More sexual health influencers disclosed their sexual orientation (80.5\% vs 67.3\%, P=.02) and were community-based organization volunteers (18.2\% vs 2.7\%, P<.001) than noninfluencers. More alters of sexual health influencers came from a rural area (45.5\% vs 23.8\%, P<.001), had below-college education (57.7\% vs 37.1\%, P<.001), and had multiple casual male sexual partners in the past 6 months (25.2\% vs 11.9\%, P<.001). Conclusions: Being a sexual health influencer was associated with encouraging more alters with less testing access to self-test for HIV/syphilis. Sexual health influencers can be engaged as seeds to expand HIV/syphilis testing coverage. ",
doi="10.2196/24303",
url="https://www.jmir.org/2021/6/e24303",
url="http://www.ncbi.nlm.nih.gov/pubmed/34061035"
}


@Article{info:doi/10.2196/26143,
author="Andersson, Ulrika
and Bengtsson, Ulrika
and Ranerup, Agneta
and Midl{\"o}v, Patrik
and Kjellgren, Karin",
title="Patients and Professionals as Partners in Hypertension Care: Qualitative Substudy of a Randomized Controlled Trial Using an Interactive Web-Based System Via Mobile Phone",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e26143",
keywords="eHealth",
keywords="digital health",
keywords="hypertension",
keywords="mobile phones",
keywords="patient-professional partnership",
keywords="person-centered care",
keywords="self-management",
abstract="Background: The use of technology has the potential to support the patient{\textasciiacute}s active participation regarding treatment of hypertension. This might lead to changes in the roles of the patient and health care professional and affect the partnership between them. Objective: The aim of this qualitative study was to explore the partnership between patients and health care professionals and the roles of patients and professionals in hypertension management when using an interactive web-based system for self-management of hypertension via the patient's own mobile phone. Methods: Focus group interviews were conducted with 22 patients and 15 professionals participating in a randomized controlled trial in Sweden aimed at lowering blood pressure (BP) using an interactive web-based system via mobile phones. The interviews were audiorecorded and transcribed and analyzed using thematic analysis. Results: Three themes were identified: the technology, the patient, and the professional. The technology enabled documentation of BP treatment, mainly for sharing knowledge between the patient and the professional. The patients gained increased knowledge of BP values and their relation to daily activities and treatment. They were able to narrate about their BP treatment and take a greater responsibility, inspired by new insights and motivation for lifestyle changes. Based on the patient's understanding of hypertension, professionals could use the system as an educational tool and some found new ways of communicating BP treatment with patients. Some reservations were raised about using the system, that it might be too time-consuming to function in clinical practice and that too much measuring could result in stress for the patient and an increased workload for the professionals. In addition, not all professionals and patients had adopted the instructions regarding the use of the system, resulting in less realization of its potential. Conclusions: The use of the system led to the patients taking on a more active role in their BP treatment, becoming more of an expert of their BP. When using the system as intended, the professionals experienced it as a useful resource for communication regarding BP and lifestyle. Patients and professionals described a consultation on more equal grounds. The use of technology in hypertension management can promote a constructive and person-centered partnership between patient and professional. However, implementation of a new way of working should bring benefits and not be considered a burden for the professionals. To establish a successful partnership, both the patient and the professional need to be motivated toward a new way of working. Trial Registration: ClinicalTrials.gov NCT03554382; https://clinicaltrials.gov/ct2/show/NCT03554382 ",
doi="10.2196/26143",
url="https://www.jmir.org/2021/6/e26143",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081021"
}


@Article{info:doi/10.2196/25470,
author="Khan, Kareem
and Hollis, Chris
and Hall, L. Charlotte
and Murray, Elizabeth
and Davies, Bethan E.
and Andr{\'e}n, Per
and Mataix-Cols, David
and Murphy, Tara
and Glazebrook, Cris",
title="Fidelity of Delivery and Contextual Factors Influencing Children's Level of Engagement: Process Evaluation of the Online Remote Behavioral Intervention for Tics Trial",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e25470",
keywords="process evaluation",
keywords="implementation fidelity",
keywords="Tourette syndrome",
keywords="chronic tic disorders",
keywords="online behavioral intervention",
keywords="mixed methods",
keywords="children and young people",
abstract="Background: The Online Remote Behavioral Intervention for Tics (ORBIT) study was a multicenter randomized controlled trial of a complex intervention that consisted of a web-based behavioral intervention for children and young people with tic disorders. In the first part of a two-stage process evaluation, we conducted a mixed methods study exploring the reach, dose, and fidelity of the intervention and contextual factors influencing engagement. Objective: This study aims to explore the fidelity of delivery and contextual factors underpinning the ORBIT trial. Methods: Baseline study data and intervention usage metrics from participants in the intervention arm were used as quantitative implementation data (N=112). The experiences of being in the intervention were explored through semistructured interviews with children (n=20) and parent participants (n=20), therapists (n=4), and referring clinicians (n=6). A principal component analysis was used to create a comprehensive, composite measure of children and young people's engagement with the intervention. Engagement factor scores reflected relative uptake as assessed by a range of usage indices, including chapters accessed, number of pages visited, and number of log-ins. The engagement factor score was used as the dependent variable in a multiple linear regression analysis with various contextual variables as independent variables to assess if there were any significant predictors of engagement. Results: The intervention was implemented with high fidelity, and participants deemed the intervention acceptable and satisfactory. The engagement was high, with child participants completing an average of 7.5 of 10 (SD 2.7) chapters, and 88.4\% (99/112) of participants completed the minimum of the first four chapters---the predefined threshold effective dose. Compared with the total population of children with tic disorders, participants in the sample tended to have more educated parents and lived in more economically advantaged areas; however, socioeconomic factors were not related to engagement factor scores. Factors associated with higher engagement factor scores included participants enrolled at the London site versus the Nottingham site (P=.01), self-referred versus clinic referred (P=.04), higher parental engagement as evidenced by the number of parental chapters completed (n=111; $\rho$=0.73; P<.001), and more therapist time for parents (n=111; $\rho$=0.46; P<.001). A multiple linear regression indicated that parents' chapter completion ($\beta$=.69; t110=10.18; P<.001) and therapist time for parents ($\beta$=.19; t110=2.95; P=.004) were the only significant independent predictors of child engagement factor scores. Conclusions: Overall, the intervention had high fidelity of delivery and was evaluated positively by participants, although reach may have been constrained by the nature of the randomized controlled trial. Parental engagement and therapist time for parents were strong predictors of intervention implementation, which has important implications for designing and implementing digital therapeutic interventions in child and adolescent mental health services. International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3974-3 ",
doi="10.2196/25470",
url="https://www.jmir.org/2021/6/e25470",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152270"
}


@Article{info:doi/10.2196/27853,
author="P{\'o}cs, D{\'a}vid
and Adamovits, Ot{\'i}lia
and Watti, Jezdancher
and Kov{\'a}cs, R{\'o}bert
and Kelemen, Oguz",
title="Facebook Users' Interactions, Organic Reach, and Engagement in a Smoking Cessation Intervention: Content Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e27853",
keywords="smoking",
keywords="smoking cessation",
keywords="behavior",
keywords="health behavior",
keywords="internet",
keywords="social media",
keywords="love",
keywords="comment",
keywords="motivation",
keywords="language",
keywords="public health",
abstract="Background: Facebook can be a suitable platform for public health interventions. Facebook users can express their reaction to the given social media content in many ways using interaction buttons. The analysis of these interactions can be advantageous in increasing reach and engagement of public health interventions. Objective: This research aimed at understanding how Facebook users' interactions correlate with organic reach and engagement regarding the same smoking cessation support contents. Methods: The study population consisted of Facebook users who were reached by a public smoking cessation support page without advertising. We included 1025 nonpaid Facebook posts (N=1025) which used smoking cessation strategies based on a motivational interviewing counseling style. The following data were collected from the ``Post Details'': the number of people who saw the given nonpaid content (organic reach) which consisted of fan and nonfan reach according to previous ``page like'' activity; each rate of ``engagement indicators'' (such as the symbols of ``like,'' ``love,'' ``haha,'' ``wow,'' ``sad,'' ``angry''; or other interactions: ``shares,'' ``comments,'' ``clicks''); and the rate of negative Facebook interactions (eg, ``post hides'' or ``unlike of page''). Overall, these data were analyzed with the Spearman correlation method. Results: Surprisingly, we found a significant negative correlation between organic reach and the ``like'' reaction (rs=--0.418; P<.001). The strongest significant positive correlations of organic reach were observed with the ``haha'' reaction (rs=0.396; P<.001), comments (rs=0.368; P<.001), and the ``love'' reaction (rs=0.264; P<.001). Furthermore, nonfan reach correlated positively with ``shares'' (rs=0.388; P<.001) and clicks (rs=0.135; P<.001), while fan reach correlated positively with the ``haha'' reaction (rs=0.457; P<.001), comments (rs=0.393; P<.001), and the ``love'' reaction (rs=0.310; P<.001). Contrary to expectations, the ``like'' reaction was sharply separated by significant negative correlations from ``wow'' (rs=--0.077; P=.013), ``sad'' (rs=--0.120; P<.001), ``angry'' reactions (rs=--0.136; P<.001), and comments (rs=--0.130; P<.001). Additionally, a high rate of negative Facebook interactions was significantly associated with ``wow'' (rs=0.076; P=.016) and ``sad'' reactions (rs=0.091; P=.003). Conclusions: This study has shown that it is possible to hypothesize a disadvantage of the ``like'' reaction and advantages of other interactions (eg, the ``haha'' reaction or ``comments'') in content algorithmic ranking on Facebook. In addition, the correlational analysis revealed a need of a further categorization to fan-specific interactions (eg, ``haha'' or ``love'' reactions) and nonfan-specific interactions (eg, ``shares'' and ``clicks''). Regarding the direction of the correlations, these findings suggest that some interactions (eg, negative Facebook interactions, ``wow,'' ``sad,'' and ``angry'' reactions) may decrease the engagement, while other interactions (``like,'' ``love,'' ``haha'' reactions, ``shares,'' and ``clicks'') may increase the engagement during Facebook-based smoking cessation interventions. This hypothesis-generating research offers an important insight into the relationship between organic reach, engagement, and Facebook users' interactions for public health professionals who design Facebook-based interventions. ",
doi="10.2196/27853",
url="https://www.jmir.org/2021/6/e27853",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152280"
}


@Article{info:doi/10.2196/27218,
author="Kim, Meelim
and Yang, Jaeyeong
and Ahn, Woo-Young
and Choi, Jin Hyung",
title="Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e27218",
keywords="digital phenotype",
keywords="clinical efficacy",
keywords="in-app engagement",
keywords="machine learning analysis",
keywords="mobile phone",
abstract="Background: The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes. Objective: This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy. Methods: We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics. Results: A higher engagement rate was associated with higher weight loss at 8 weeks (r=?0.59; P<.001) and 24 weeks (r=?0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R2 0.416, SD 0.006). The prediction of short-term weight change (mean R2 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R2 0.590, SD 0.011). Conclusions: Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics. Trial Registration: ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306 ",
doi="10.2196/27218",
url="https://www.jmir.org/2021/6/e27218/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34184991"
}


@Article{info:doi/10.2196/18167,
author="Salari, Raheleh
and R Niakan Kalhori, Sharareh
and GhaziSaeedi, Marjan
and Jeddi, Marjan
and Nazari, Mahin
and Fatehi, Farhad",
title="Mobile-Based and Cloud-Based System for Self-management of People With Type 2 Diabetes: Development and Usability Evaluation",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="2",
volume="23",
number="6",
pages="e18167",
keywords="type 2 diabetes",
keywords="mobile health",
keywords="mHealth",
keywords="mobile app, self-management",
keywords="behavior change",
abstract="Background: As the use of smartphones and mobile apps is increasing, mobile health (mHealth) can be used as a cost-effective option to provide behavioral interventions aimed at educating and promoting self-management for chronic diseases such as diabetes. Although many mobile software apps have been developed for this purpose, they usually lack a theoretical foundation and do not follow the guidelines suggested for evidence-based practice. Therefore, this study aimed to develop a theory-based self-management app for people with type 2 diabetes and provide an app based on a needs assessment analysis. Objective: This paper describes the development and usability evaluation of a cloud-based and mobile-based diabetes self-management app designed to help people with diabetes change their health behavior and also enable remote monitoring by health care providers. Methods: The development of this mHealth solution comprises 3 phases. Phase I: feature extraction of the Android apps that had a user rating of 4 stars or more and review of papers related to mHealth for diabetes self-management were performed followed by seeking expert opinions about the extracted features to determine the essential features of the app. Phase II: design and implementation included selecting which behavioral change and structural theories were to be applied the app and design of the website. Phase III: evaluation of the usability and user experience of the mobile app by people with diabetes and the portal by health care providers using the User Experience Questionnaire. Results: The developed mobile app includes modules that support several features. A person's data were entered or collected and viewed in the form of graphs and tables. The theoretical foundation of behavioral intervention is the transtheoretical model. Users were able to receive customized messages based on the behavioral change preparation stage using the Kreuter algorithm. The clinician's portal was used by health care providers to monitor the patients. The results of the usability evaluation revealed overall user satisfaction with the app. Conclusions: Mobile- and cloud-based systems may be an effective tool for facilitating the modification of self-management of chronic care. The results of this study showed that the usability of mobile- and cloud-based systems can be satisfactory and promising. Given that the study used a behavioral model, assessment of the effectiveness of behavior change over time requires further research with long-term follow-up. ",
doi="10.2196/18167",
url="https://www.jmir.org/2021/6/e18167",
url="http://www.ncbi.nlm.nih.gov/pubmed/34076579"
}


@Article{info:doi/10.2196/25069,
author="Poort, Hanneke
and Ryan, Annelise
and MacDougall, Katelyn
and Malinowski, Paige
and MacDonald, Anna
and Markin, Zach
and Pirl, William
and Greer, Joseph
and Fasciano, Karen",
title="Feasibility and Acceptability of a Mobile Phone App Intervention for Coping With Cancer as a Young Adult: Pilot Trial and Thematic Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e25069",
keywords="mobile phone",
keywords="mobile phone application",
keywords="cancer",
keywords="feasibility",
abstract="Background: Many young adult patients do not receive adequate psychosocial services to help them cope with cancer. Objective: This study aims to assess the feasibility and acceptability of a smartphone app (iaya) intervention that was designed to create an engaged community of young adult patients and help them learn emotional coping skills. Methods: For this single-group pilot trial, 25 young adult patients aged 18-39 years who were receiving active cancer treatment were asked to use the iaya app for 12 weeks. To collect app use data, we used Mixpanel, an analytics platform for apps. Feasibility was assessed through rates of app sessions and the number of coping exercises engaged, and intervention acceptability was evaluated by using an app usability questionnaire and through qualitative interviews at study completion. We collected patient-reported outcome data at baseline and at week 12 to explore self-efficacy for coping with cancer, self-efficacy for managing emotions, perceived emotional support, and quality of life. Results: Baseline patient-reported outcome data indicated that participants scored relatively low on perceived emotional support but reasonably high on self-efficacy for coping with cancer and managing emotions as well as quality of life. Participants had a mean of 13 app sessions (SD 14) and 2 coping exercises (SD 3.83) in 12 weeks. Only 9\% (2/23) of participants met our combined feasibility definition of ?10 app sessions and ?3 coping skills from different categories. The participants' mean usability score was 73.7\% (SD 10.84), which exceeded our predefined threshold of ?70\%, and qualitative feedback was generally positive. Conclusions: Although perceived acceptable by patients, the iaya smartphone app did not meet the a priori feasibility criteria as a stand-alone app intervention. Future studies should screen participants for unmet coping needs and consider integrating the app as part of psychosocial care for young adult patients. ",
doi="10.2196/25069",
url="https://www.jmir.org/2021/6/e25069",
url="http://www.ncbi.nlm.nih.gov/pubmed/34114957"
}


@Article{info:doi/10.2196/25958,
author="Lauffenburger, C. Julie
and Barlev, A. Renee
and Sears, S. Ellen
and Keller, A. Punam
and McDonnell, E. Marie
and Yom-Tov, Elad
and Fontanet, P. Constance
and Hanken, Kaitlin
and Haff, Nancy
and Choudhry, K. Niteesh",
title="Preferences for mHealth Technology and Text Messaging Communication in Patients With Type 2 Diabetes: Qualitative Interview Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e25958",
keywords="diabetes",
keywords="technology",
keywords="mobile health",
keywords="medication adherence",
keywords="mobile phone",
abstract="Background: Individuals with diabetes need regular support to help them manage their diabetes on their own, ideally delivered via mechanisms that they already use, such as their mobile phones. One reason for the modest effectiveness of prior technology-based interventions may be that the patient perspective has been insufficiently incorporated. Objective: This study aims to understand patients' preferences for mobile health (mHealth) technology and how that technology can be integrated into patients' routines, especially with regard to medication use. Methods: We conducted semistructured qualitative individual interviews with patients with type 2 diabetes from an urban health care system to elicit and explore their perspectives on diabetes medication--taking behaviors, daily patterns of using mobile technology, use of mHealth technology for diabetes care, acceptability of text messages to support medication adherence, and preferred framing of information within text messages to support diabetes care. The interviews were digitally recorded and transcribed. The data were analyzed using codes developed by the study team to generate themes, with representative quotations selected as illustrations. Results: We conducted interviews with 20 participants, of whom 12 (60\%) were female and 9 (45\%) were White; in addition, the participants' mean glycated hemoglobin A1c control was 7.8 (SD 1.1). Overall, 5 key themes were identified: patients try to incorporate cues into their routines to help them with consistent medication taking; many patients leverage some form of technology as a cue to support adherence to medication taking and diabetes self-management behaviors; patients value simplicity and integration of technology solutions used for diabetes care, managing medications, and communicating with health care providers; some patients express reluctance to rely on mobile technology for these diabetes care behaviors; and patients believe they prefer positively framed communication, but communication preferences are highly individualized. Conclusions: The participants expressed some hesitation about using mobile technology in supporting diabetes self-management but have largely incorporated it or are open to incorporating it as a cue to make medication taking more automatic and less burdensome. When using technology to support diabetes self-management, participants exhibited individualized preferences, but overall, they preferred simple and positively framed communication. mHealth interventions may be improved by focusing on integrating them easily into daily routines and increasing the customization of content. ",
doi="10.2196/25958",
url="https://www.jmir.org/2021/6/e25958",
url="http://www.ncbi.nlm.nih.gov/pubmed/34114964"
}


@Article{info:doi/10.2196/27076,
author="Singleton, Anna
and Raeside, Rebecca
and Partridge, R. Stephanie
and Hayes, Molly
and Maka, Katherine
and Hyun, K. Karice
and Thiagalingam, Aravinda
and Chow, K. Clara
and Sherman, A. Kerry
and Elder, Elisabeth
and Redfern, Julie",
title="Co-designing a Lifestyle-Focused Text Message Intervention for Women After Breast Cancer Treatment: Mixed Methods Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e27076",
keywords="breast neoplasms",
keywords="cancer survivors",
keywords="text messaging",
keywords="telemedicine",
keywords="mobile health",
keywords="co-design",
abstract="Background: Breast cancer is the most common cancer among women globally. Recovery from breast cancer treatment can be mentally and physically challenging. SMS text message programs offer a novel way to provide health information and support, but few programs are co-designed with consumer representatives. Objective: This study aims to report the procedures and outcomes of a co-design process of a lifestyle-focused SMS text message program to support women's mental and physical health after breast cancer treatment. Methods: We followed an iterative mixed methods two-step process: (1) co-design workshop with consumers and health professionals and researchers to draft text messages and (2) evaluation of message content, which was scored (5-point Likert scale; 1=strongly disagree to 5=strongly agree) for ease of understanding, usefulness, and appropriateness, and readability (Flesch-Kincaid score). Additional free-text responses and semistructured interviews were coded into themes. Messages were edited or deleted based on the evaluations, with consumers' evaluations prioritized. Results: In step 1, co-designed text messages (N=189) were semipersonalized, and the main content themes were (1) physical activity and healthy eating, (2) medications and side effects, (3) mental health, and (4) general breast cancer information. In step 2, consumers (n=14) and health professionals and researchers (n=14) provided 870 reviews of 189 messages and found that most messages were easy to understand (799/870, 91.8\%), useful (746/870, 85.7\%), and appropriate (732/870, 84.1\%). However, consumers rated 50 messages differently from health professionals and researchers. On the basis of evaluations, 37.6\% (71/189) of messages were deleted, 36.5\% (69/189) were edited, and 12 new messages related to fatigue, self-care, and cognition were created. The final 130 text messages had a mean 7.12 (SD 2.8) Flesch-Kincaid grade level and 68.9 (SD 15.5) ease-of-reading score, which represents standard reading ease. Conclusions: Co-designing and evaluating a bank of evidence-based mental and physical health-themed text messages with breast cancer survivors, health professionals, and researchers was feasible and resulted in a bank of 130 text messages evaluated highly by participants. Some consumer evaluations differed from health professionals and researchers, supporting the importance of co-design. ",
doi="10.2196/27076",
url="https://www.jmir.org/2021/6/e27076",
url="http://www.ncbi.nlm.nih.gov/pubmed/34125072"
}


@Article{info:doi/10.2196/25522,
author="Song, Ting
and Liu, Fang
and Deng, Ning
and Qian, Siyu
and Cui, Tingru
and Guan, Yingping
and Arnolda, Leonard
and Zhang, Zhenyu
and Yu, Ping",
title="A Comprehensive 6A Framework for Improving Patient Self-Management of Hypertension Using mHealth Services: Qualitative Thematic Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e25522",
keywords="patient experience",
keywords="mHealth",
keywords="mobile phone",
keywords="mobile app",
keywords="intervention",
keywords="self-management",
keywords="high blood pressure",
keywords="chronic disease management",
keywords="qualitative research",
abstract="Background: Hypertension affects over 15\% of the world's population and is a significant global public health and socioeconomic challenge. Mobile health (mHealth) services have been increasingly introduced to support hypertensive patients to improve their self-management behaviors, such as adherence to pharmacotherapy and lifestyle modifications. Objective: This study aims to explore patients' perceptions of mHealth services and the mechanisms by which the services support them to self-manage their hypertension. Methods: A semistructured, in-depth interview study was conducted with 22 outpatients of the General Hospital of Ningxia Medical University from March to May 2019. In 2015, the hospital introduced an mHealth service to support community-dwelling outpatients with self-management of hypertension. Content analysis was conducted by following a grounded theory approach for inductive thematic extraction. Constant comparison and categorization classified the first-level codes with similar meanings into higher-level themes. Results: The patient-perceived mechanisms by which the mHealth service supported their self-management of hypertension were summarized as 6A: access, assessment, assistance, awareness, ability, and activation. With the portability of mobile phones and digitization of information, the mHealth service provided outpatients with easy access to assess their vital signs and self-management behaviors. The assessment results gave the patients real-time awareness of their health conditions and self-management performance, which activated their self-management behaviors. The mHealth service also gave outpatients access to assistance, which included health education and self-management reminders. Both types of assistance could also be activated by abnormal assessment results, that is, uncontrolled or deteriorating blood pressure values, discomfort symptoms, or not using the service for a long period. With its scalable use to handle any possible information and services, the mHealth service provided outpatients with educational materials to learn at their own pace. This led to an improvement in self-management awareness and ability, again activating their self-management behaviors. The patients would like to see further improvements in the service to provide more useful, personalized information and reliable services. Conclusions: The mHealth service extended the traditional hypertension care model beyond the hospital and clinician's office. It provided outpatients with easy access to otherwise inaccessible hypertension management services. This led to process improvement for outpatients to access health assessment and health care assistance and improved their awareness and self-management ability, which activated their hypertension self-management behaviors. Future studies can apply the 6A framework to guide the design, implementation, and evaluation of mHealth services for outpatients to self-manage chronic conditions. ",
doi="10.2196/25522",
url="https://www.jmir.org/2021/6/e25522",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152272"
}


@Article{info:doi/10.2196/26771,
author="Mehta, Ashish
and Niles, Nicole Andrea
and Vargas, Hamilton Jose
and Marafon, Thiago
and Couto, Dotta Diego
and Gross, Jonathan James",
title="Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="22",
volume="23",
number="6",
pages="e26771",
keywords="digital mental health treatment",
keywords="acceptability",
keywords="effectiveness",
keywords="anxiety",
keywords="depression",
abstract="Background: Youper is a widely used, commercially available mobile app that uses artificial intelligence therapy for the treatment of anxiety and depression. Objective: Our study examined the acceptability and effectiveness of Youper. Further, we tested the cumulative regulation hypothesis, which posits that cumulative emotion regulation successes with repeated intervention engagement will predict longer-term anxiety and depression symptom reduction. Methods: We examined data from paying Youper users (N=4517) who allowed their data to be used for research. To characterize the acceptability of Youper, we asked users to rate the app on a 5-star scale and measured retention statistics for users' first 4 weeks of subscription. To examine effectiveness, we examined longitudinal measures of anxiety and depression symptoms. To test the cumulative regulation hypothesis, we used the proportion of successful emotion regulation attempts to predict symptom reduction. Results: Youper users rated the app highly (mean 4.36 stars, SD 0.84), and 42.66\% (1927/4517) of users were retained by week 4. Symptoms decreased in the first 2 weeks of app use (anxiety: d=0.57; depression: d=0.46). Anxiety improvements were maintained in the subsequent 2 weeks, but depression symptoms increased slightly with a very small effect size (d=0.05). A higher proportion of successful emotion regulation attempts significantly predicted greater anxiety and depression symptom reduction. Conclusions: Youper is a low-cost, completely self-guided treatment that is accessible to users who may not otherwise access mental health care. Our findings demonstrate the acceptability and effectiveness of Youper as a treatment for anxiety and depression symptoms and support continued study of Youper in a randomized clinical trial. ",
doi="10.2196/26771",
url="https://www.jmir.org/2021/6/e26771",
url="http://www.ncbi.nlm.nih.gov/pubmed/34155984"
}


@Article{info:doi/10.2196/25256,
author="Sutherland, Rachel
and Brown, Alison
and Nathan, Nicole
and Yoong, Serene
and Janssen, Lisa
and Chooi, Amelia
and Hudson, Nayerra
and Wiggers, John
and Kerr, Nicola
and Evans, Nicole
and Gillham, Karen
and Oldmeadow, Christopher
and Searles, Andrew
and Reeves, Penny
and Davies, Marc
and Reilly, Kathryn
and Cohen, Brad
and Wolfenden, Luke",
title="A Multicomponent mHealth-Based Intervention (SWAP IT) to Decrease the Consumption of Discretionary Foods Packed in School Lunchboxes: Type I Effectiveness--Implementation Hybrid Cluster Randomized Controlled Trial",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e25256",
keywords="childhood obesity",
keywords="lunchboxes",
keywords="children",
keywords="child nutrition",
keywords="mHealth",
keywords="schools",
keywords="hybrid",
keywords="randomized controlled trial",
keywords="technology",
abstract="Background: There is significant opportunity to improve the nutritional quality of foods packed in children's school lunchboxes. Interventions that are effective and scalable targeting the school and home environment are therefore warranted. Objective: This study aimed to assess the effectiveness of a multicomponent, mobile health--based intervention, SWAP IT, in reducing the energy contribution of discretionary (ie, less healthy) foods and drinks packed for children to consume at school. Methods: A type I effectiveness--implementation hybrid cluster randomized controlled trial was conducted in 32 primary schools located across 3 local health districts in New South Wales, Australia, to compare the effects of a 6-month intervention targeting foods packed in children's lunchboxes with those of a usual care control. Primary schools were eligible if they were not participating in other nutrition studies and used the required school communication app. The Behaviour Change Wheel was used to co-design the multicomponent SWAP IT intervention, which consisted of the following: school lunchbox nutrition guidelines, curriculum lessons, information pushed to parents digitally via an existing school communication app, and additional parent resources to address common barriers to packing healthy lunchboxes. The primary outcome, mean energy (kilojoules) content of discretionary lunchbox foods and drinks packed in lunchboxes, was measured via observation using a validated school food checklist at baseline (May 2019) and at 6-month follow-up (October 2019). Additional secondary outcomes included mean lunchbox energy from discretionary foods consumed, mean total lunchbox energy packed and consumed, mean energy content of core lunchbox foods packed and consumed, and percentage of lunchbox energy from discretionary and core foods, all of which were also measured via observation using a validated school food checklist. Measures of school engagement, consumption of discretionary foods outside of school hours, and lunchbox cost were also collected at baseline and at 6-month follow-up. Data were analyzed via hierarchical linear regression models, with controlling for clustering, socioeconomic status, and remoteness. Results: A total of 3022 (3022/7212, 41.90\%) students consented to participate in the evaluation (mean age 7.8 years; 1487/3022, 49.22\% girls). There were significant reductions between the intervention and control groups in the primary trial outcome, mean energy (kilojoules) content of discretionary foods packed in lunchboxes (--117.26 kJ; 95\% CI --195.59 to --39.83; P=.003). Relative to the control, the intervention also significantly reduced secondary outcomes regarding the mean total lunchbox energy (kilojoules) packed (--88.38 kJ; 95\% CI --172.84 to --3.92; P=.04) and consumed (--117.17 kJ; 95\% CI --233.72 to --0.62; P=.05). There was no significant difference between groups in measures of student engagement, consumption of discretionary foods outside of school hours, or cost of foods packed in children's lunchboxes. Conclusions: The SWAP IT intervention was effective in reducing the energy content of foods packed for and consumed by primary school--aged children at school. Dissemination of the SWAP IT program at a population level has the potential to influence a significant proportion of primary school--aged children, impacting weight status and associated health care costs. Trial Registration: Australian Clinical Trials Registry ACTRN12618001731280; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=376191\&isReview=true International Registered Report Identifier (IRRID): RR2-10.1186/s12889-019-7725-x ",
doi="10.2196/25256",
url="https://www.jmir.org/2021/6/e25256/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185013"
}


@Article{info:doi/10.2196/24458,
author="Lam, Esther
and Moreno, Megan
and Bennett, Elizabeth
and Rowhani-Rahbar, Ali",
title="Receptiveness and Responsiveness Toward Using Social Media for Safe Firearm Storage Outreach: Mixed Methods Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="18",
volume="23",
number="6",
pages="e24458",
keywords="firearm storage",
keywords="gun safety",
keywords="public health outreach",
keywords="social media",
keywords="mixed methods",
keywords="family",
abstract="Background: Childhood and adolescent firearm injury and death rates have increased over the past decade and remain major public health concerns in the United States. Safe firearm storage has proven to be an effective measure to prevent firearm injury and death among youth. Social media has been used as an avenue to promote safe firearm storage, but perceptions of this tool remain unknown. Objective: The aim of this study was to determine receptiveness and responsiveness in promoting firearm lock box and trigger lock giveaway events on social media, and to describe the characteristics of participants who learned of these events through social media. Methods: We performed a mixed methods study combining a content analysis of Facebook event post comments, quantitative analysis of positive and negative feedback on social media, and a descriptive analysis of event participant characteristics. Through a qualitative content analysis approach, we thematically coded comments from each event's social media page posting. Interrater reliability and $\kappa$ statistics were calculated. We calculated the prevalence of positive and negative feedback data. Further, we calculated descriptive statistics for demographic characteristics gathered from day-of-event intake surveys. Differences between collected measures were analyzed with $\chi$2 and t tests according to how the participant found out about the event (social media vs other means). Using concurrent analysis, we synthesized the results from both the qualitative and quantitative aims. Results: Through qualitative content analysis, 414 comments from 13 events were coded. Seven themes emerged through the comment coding process with the most common being ``positive receptiveness'' (294/414, 71.0\%). From quantitative analysis of the social media content, we found higher levels of positive feedback compared to negative feedback. The average number of event post ``likes'' was 1271.3 per event, whereas the average count in which ``hide post'' was clicked was 72.3 times per event. Overall, 35.9\% (1457/4054) of participants found out about the event through social media. The participants who learned about the event through social media were on average significantly younger than those who learned about the event through other means (--6.4 years, 95\% CI --5.5 to --7.3). Among the group that learned of the event through social media, 43.9\% (629/1433) identified as female, whereas 35.5\% (860/2420) identified as female among the group that learned of the event through other means. Conclusions: There was overall positive receptiveness and responsiveness toward firearm lock box and trigger lock giveaway events when promoted on social media. Compared with other promotional tools, social media has the ability to reach those who are younger and those who identify as female. Future studies should extend this research to determine whether there is a difference between rural and urban settings, and consider other social media platforms in the analysis. ",
doi="10.2196/24458",
url="https://www.jmir.org/2021/6/e24458",
url="http://www.ncbi.nlm.nih.gov/pubmed/34142974"
}


@Article{info:doi/10.2196/25199,
author="Galatzer-Levy, Isaac
and Abbas, Anzar
and Ries, Anja
and Homan, Stephanie
and Sels, Laura
and Koesmahargyo, Vidya
and Yadav, Vijay
and Colla, Michael
and Scheerer, Hanne
and Vetter, Stefan
and Seifritz, Erich
and Scholz, Urte
and Kleim, Birgit",
title="Validation of Visual and Auditory Digital Markers of Suicidality in Acutely Suicidal Psychiatric Inpatients: Proof-of-Concept Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e25199",
keywords="digital phenotyping",
keywords="digital biomarkers",
keywords="digital health",
keywords="depression",
keywords="suicidal ideation",
keywords="digital markers",
keywords="digital",
keywords="facial",
keywords="suicide",
keywords="suicide risk",
keywords="visual",
keywords="auditory",
abstract="Background: Multiple symptoms of suicide risk have been assessed based on visual and auditory information, including flattened affect, reduced movement, and slowed speech. Objective quantification of such symptomatology from novel data sources can increase the sensitivity, scalability, and timeliness of suicide risk assessment. Objective: We aimed to examine measurements extracted from video interviews using open-source deep learning algorithms to quantify facial, vocal, and movement behaviors in relation to suicide risk severity in recently admitted patients following a suicide attempt. Methods: We utilized video to quantify facial, vocal, and movement markers associated with mood, emotion, and motor functioning from a structured clinical conversation in 20 patients admitted to a psychiatric hospital following a suicide risk attempt. Measures were calculated using open-source deep learning algorithms for processing facial expressivity, head movement, and vocal characteristics. Derived digital measures of flattened affect, reduced movement, and slowed speech were compared to suicide risk with the Beck Scale for Suicide Ideation controlling for age and sex, using multiple linear regression. Results: Suicide severity was associated with multiple visual and auditory markers, including speech prevalence ($\beta$=?0.68, P=.02, r2=0.40), overall expressivity ($\beta$=?0.46, P=.10, r2=0.27), and head movement measured as head pitch variability ($\beta$=?1.24, P=.006, r2=0.48) and head yaw variability ($\beta$=?0.54, P=.06, r2=0.32). Conclusions: Digital measurements of facial affect, movement, and speech prevalence demonstrated strong effect sizes and linear associations with the severity of suicidal ideation. ",
doi="10.2196/25199",
url="https://www.jmir.org/2021/6/e25199",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081022"
}


@Article{info:doi/10.2196/27132,
author="Martin-Key, Anna Nayra
and Spadaro, Benedetta
and Schei, Sofie Thea
and Bahn, Sabine",
title="Proof-of-Concept Support for the Development and Implementation of a Digital Assessment for Perinatal Mental Health: Mixed Methods Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e27132",
keywords="COM-B",
keywords="COVID-19",
keywords="digital mental health",
keywords="maternal mental health",
keywords="paternal mental health",
keywords="perinatal mental health",
keywords="mental health",
keywords="support",
keywords="development",
keywords="implementation",
keywords="assessment",
keywords="mother",
keywords="women",
abstract="Background: Perinatal mental health symptoms commonly remain underdiagnosed and undertreated in maternity care settings in the United Kingdom, with outbreaks of disease, like the COVID-19 pandemic, further disrupting access to adequate mental health support. Digital technologies may offer an innovative way to support the mental health needs of women and their families throughout the perinatal period, as well as assist midwives in the recognition of perinatal mental health concerns. However, little is known about the acceptability and perceived benefits and barriers to using such technologies. Objective: The aim of this study was to conduct a mixed methods evaluation of the current state of perinatal mental health care provision in the United Kingdom, as well as users' (women and partners) and midwives' interest in using a digital mental health assessment throughout the perinatal period. Methods: Women, partners, and midwives were recruited to participate in the study, which entailed completing an online survey. Quantitative data were explored using descriptive statistics. Open-ended response data were first investigated using thematic analysis. Resultant themes were then mapped onto the components of the Capability, Opportunity, and Motivation Behavior model and summarized using descriptive statistics. Results: A total of 829 women, 103 partners, and 90 midwives participated in the study. The provision of adequate perinatal mental health care support was limited, with experiences varying significantly across respondents. There was a strong interest in using a digital mental health assessment to screen, diagnose, and triage perinatal mental health concerns, particularly among women and midwives. The majority of respondents (n=781, 76.42\%) expressed that they would feel comfortable or very comfortable using or recommending a digital mental health assessment. The majority of women and partners showed a preference for in-person consultations (n=417, 44.74\%), followed by a blended care approach (ie, both in-person and online consultations) (n=362, 38.84\%), with fewer participants preferring online-only consultations (n=120, 12.88\%). Identified benefits and barriers mainly related to physical opportunity (eg, accessibility), psychological capability (eg, cognitive skills), and automatic motivation (eg, emotions). Conclusions: This study provides proof-of-concept support for the development and implementation of a digital mental health assessment to inform clinical decision making in the assessment of perinatal mental health concerns in the United Kingdom. ",
doi="10.2196/27132",
url="https://www.jmir.org/2021/6/e27132",
url="http://www.ncbi.nlm.nih.gov/pubmed/34033582"
}


@Article{info:doi/10.2196/24088,
author="Yokotani, Kenji",
title="A Change Talk Model for Abstinence Based on Web-Based Anonymous Gambler Chat Meeting Data by Using an Automatic Change Talk Classifier: Development Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e24088",
keywords="problem gambling",
keywords="web-based anonymous gambler chat meetings",
keywords="self-help group",
keywords="change talk classifier",
keywords="computerized text analysis",
keywords="long-term data with dropout gamblers",
keywords="recovery gradient",
keywords="gradient descent method",
keywords="gambling",
keywords="addiction",
keywords="abstinence",
abstract="Background: Change and sustain talks (negative and positive comments) on gambling have been relevant for determining gamblers' outcomes but they have not been used to clarify the abstinence process in anonymous gambler meetings. Objective: The aim of this study was to develop a change talk model for abstinence based on data extracted from web-based anonymous gambler chat meetings by using an automatic change talk classifier. Methods: This study used registry data from the internet. The author accessed web-based anonymous gambler chat meetings in Japan and sampled 1.63 million utterances (two-sentence texts) from 267 abstinent gamblers who have remained abstinent for at least three years and 1625 nonabstinent gamblers. The change talk classifier in this study automatically classified gamblers' utterances into change and sustain talks. Results: Abstinent gamblers showed higher proportions of change talks and lower probability of sustain talks compared with nonabstinent gamblers. The change talk model for abstinence, involving change and sustain talks, classified abstinent and nonabstinent gamblers through the use of a support vector machine with a radial basis kernel function. The model also indicated individual evaluation scores for abstinence and the ideal proportion of change talks for all participants according to their previous utterances. Conclusions: Abstinence likelihood among gamblers can be increased by providing personalized evaluation values and indicating the optimal proportion of change talks. Moreover, this may help to prevent severe mental, social, and financial problems caused by the gambling disorder. ",
doi="10.2196/24088",
url="https://www.jmir.org/2021/6/e24088",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152282"
}


@Article{info:doi/10.2196/26385,
author="Rotter, Dominik
and Doebler, Philipp
and Schmitz, Florian",
title="Interests, Motives, and Psychological Burdens in Times of Crisis and Lockdown: Google Trends Analysis to Inform Policy Makers",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="1",
volume="23",
number="6",
pages="e26385",
keywords="coronavirus",
keywords="Google Trends",
keywords="infodemiology",
keywords="infoveillance",
keywords="pandemic",
keywords="information search",
keywords="trend",
keywords="COVID-19",
keywords="burden",
keywords="mental health",
keywords="policy",
keywords="online health information",
abstract="Background: In the face of the COVID-19 pandemic, the German government and the 16 German federal states implemented a variety of nonpharmaceutical interventions (NPIs) to decelerate the spread of the SARS-CoV-2 virus and thus prevent a collapse of the health care system. These measures comprised, among others, social distancing, the temporary closure of shops and schools, and a ban of large public gatherings and meetings with people not living in the same household. Objective: It is fair to assume that the issued NPIs have heavily affected social life and psychological functioning. We therefore aimed to examine possible effects of this lockdown in conjunction with daily new infections and the state of the national economy on people's interests, motives, and other psychological states. Methods: We derived 249 keywords from the Google Trends database, tapping into 27 empirically and rationally selected psychological domains. To overcome issues with reliability and specificity of individual indicator variables, broad factors were derived by means of time series factor analysis. All domains were subjected to a change point analysis and time series regression analysis with infection rates, NPIs, and the state of the economy as predictors. All keywords and analyses were preregistered prior to analysis. Results: With the pandemic arriving in Germany, significant increases in people's search interests were observed in virtually all domains. Although most of the changes were short-lasting, each had a distinguishable onset during the lockdown period. Regression analysis of the Google Trends data confirmed pronounced autoregressive effects for the investigated variables, while forecasting by means of the tested predictors (ie, daily new infections, NPIs, and the state of economy) was moderate at best. Conclusions: Our findings indicate that people's interests, motives, and psychological states are heavily affected in times of crisis and lockdown. Specifically, disease- and virus-related domains (eg, pandemic disease, symptoms) peaked early, whereas personal health strategies (eg, masks, homeschooling) peaked later during the lockdown. Domains addressing social life and psychosocial functioning showed long-term increases in public interest. Renovation was the only domain to show a decrease in search interest with the onset of the lockdown. As changes in search behavior are consistent over multiple domains, a Google Trends analysis may provide information for policy makers on how to adapt and develop intervention, information, and prevention strategies, especially when NPIs are in effect. ",
doi="10.2196/26385",
url="https://www.jmir.org/2021/6/e26385",
url="http://www.ncbi.nlm.nih.gov/pubmed/33999837"
}


@Article{info:doi/10.2196/25579,
author="Allem, Jon-Patrick
and Dormanesh, Allison
and Majmundar, Anuja
and Unger, B. Jennifer
and Kirkpatrick, G. Matthew
and Choube, Akshat
and Aithal, Aneesh
and Ferrara, Emilio
and Boley Cruz, Tess",
title="Topics of Nicotine-Related Discussions on Twitter: Infoveillance Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e25579",
keywords="nicotine",
keywords="electronic cigarettes",
keywords="Twitter",
keywords="social media",
keywords="social bots",
keywords="cessation",
abstract="Background: Cultural trends in the United States, the nicotine consumer marketplace, and tobacco policies are changing. Objective: The goal of this study was to identify and describe nicotine-related topics of conversation authored by the public and social bots on Twitter, including any misinformation or misconceptions that health education campaigns could potentially correct. Methods: Twitter posts containing the term ``nicotine'' were obtained from September 30, 2018 to October 1, 2019. Methods were used to distinguish between posts from social bots and nonbots. Text classifiers were used to identify topics in posts (n=300,360). Results: Prevalent topics of posts included vaping, smoking, addiction, withdrawal, nicotine health risks, and quit nicotine, with mentions of going ``cold turkey'' and needing help in quitting. Cessation was a common topic, with mentions of quitting and stopping smoking. Social bots discussed unsubstantiated health claims including how hypnotherapy, acupuncture, magnets worn on the ears, and time spent in the sauna can help in smoking cessation. Conclusions: Health education efforts are needed to correct unsubstantiated health claims on Twitter and ultimately direct individuals who want to quit smoking to evidence-based cessation strategies. Future interventions could be designed to follow these topics of discussions on Twitter and engage with members of the public about evidence-based cessation methods in near real time when people are contemplating cessation. ",
doi="10.2196/25579",
url="https://www.jmir.org/2021/6/e25579",
url="http://www.ncbi.nlm.nih.gov/pubmed/34096875"
}


@Article{info:doi/10.2196/25028,
author="Lee, Ji-Hyun
and Park, Hyeoun-Ae
and Song, Tae-Min",
title="A Determinants-of-Fertility Ontology for Detecting Future Signals of Fertility Issues From Social Media Data: Development of an Ontology",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e25028",
keywords="ontology",
keywords="fertility",
keywords="public policy",
keywords="South Korea",
keywords="social media",
keywords="future",
keywords="infodemiology",
keywords="infoveillance",
abstract="Background: South Korea has the lowest fertility rate in the world despite considerable governmental efforts to boost it. Increasing the fertility rate and achieving the desired outcomes of any implemented policies requires reliable data on the ongoing trends in fertility and preparations for the future based on these trends. Objective: The aims of this study were to (1) develop a determinants-of-fertility ontology with terminology for collecting and analyzing social media data; (2) determine the description logics, content coverage, and structural and representational layers of the ontology; and (3) use the ontology to detect future signals of fertility issues. Methods: An ontology was developed using the Ontology Development 101 methodology. The domain and scope of the ontology were defined by compiling a list of competency questions. The terms were collected from Korean government reports, Korea's Basic Plan for Low Fertility and Aging Society, a national survey about marriage and childbirth, and social media postings on fertility issues. The classes and their hierarchy were defined using a top-down approach based on an ecological model. The internal structure of classes was defined using the entity-attribute-value model. The description logics of the ontology were evaluated using Prot{\'e}g{\'e} (version 5.5.0), and the content coverage was evaluated by comparing concepts extracted from social media posts with the list of ontology classes. The structural and representational layers of the ontology were evaluated by experts. Social media data were collected from 183 online channels between January 1, 2011, and June 30, 2015. To detect future signals of fertility issues, 2 classes of the ontology, the socioeconomic and cultural environment, and public policy, were identified as keywords. A keyword issue map was constructed, and the defined keywords were mapped to identify future signals. R software (version 3.5.2) was used to mine for future signals. Results: A determinants-of-fertility ontology comprised 236 classes and terminology comprised 1464 synonyms of the 236 classes. Concept classes in the ontology were found to be coherently and consistently defined. The ontology included more than 90\% of the concepts that appeared in social media posts on fertility policies. Average scores for all of the criteria for structural and representations layers exceeded 4 on a 5-point scale. Violence and abuse (socioeconomic and cultural factor) and flexible working arrangement (fertility policy) were weak signals, suggesting that they could increase rapidly in the future. Conclusions: The determinants-of-fertility ontology developed in this study can be used as a framework for collecting and analyzing social media data on fertility issues and detecting future signals of fertility issues. The future signals identified in this study will be useful for policy makers who are developing policy responses to low fertility. ",
doi="10.2196/25028",
url="https://www.jmir.org/2021/6/e25028",
url="http://www.ncbi.nlm.nih.gov/pubmed/34125068"
}


@Article{info:doi/10.2196/27052,
author="Naik, Hiten
and Johnson, Dimitri Maximilian Desmond
and Johnson, Roger Michael",
title="Internet Interest in Colon Cancer Following the Death of Chadwick Boseman: Infoveillance Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e27052",
keywords="colon cancer",
keywords="Google",
keywords="Wikipedia",
keywords="infodemiology",
abstract="Background: Compared with White Americans, Black Americans have higher colon cancer mortality rates but lower up-to-date screening rates. Chadwick Boseman was a prominent Black American actor who died of colon cancer on August 28, 2020. As announcements of celebrity diagnoses often result in increased awareness, Boseman's death may have resulted in greater interest in colon cancer on the internet, particularly among Black Americans. Objective: This study aims to quantify the impact of Chadwick Boseman's death on web-based search interest in colon cancer and determine whether there was an increase in interest in regions of the United States with a greater proportion of Black Americans. Methods: We conducted an infoveillance study using Google Trends (GT) and Wikipedia pageview analysis. Using an autoregressive integrated moving average algorithm, we forecasted the weekly relative search volume (RSV) for GT search topics and terms related to colon cancer that would have been expected had his death not occurred and compared it with observed RSV data. This analysis was also conducted for the number of page views on the Wikipedia page for colorectal cancer. We then delineated GT RSV data for the term colon cancer for states and metropolitan areas in the United States and determined how the RSV values for these regions correlated with the percentage of Black Americans in that region. Differences in these correlations before and after Boseman's death were compared to determine whether there was a shift in the racial demographics of the individuals conducting the searches. Results: The observed RSVs for the topics colorectal cancer and colon cancer screening increased by 598\% and 707\%, respectively, and were on average 121\% (95\% CI 72\%-193\%) and 256\% (95\% CI 35\%-814\%) greater than expected during the first 3 months following Boseman's death. Daily Wikipedia page view volume during the 2 months following Boseman's death was on average 1979\% (95\% CI 1375\%-2894\%) greater than expected, and it was estimated that this represented 547,354 (95\% CI 497,708-585,167) excess Wikipedia page views. Before Boseman's death, there were negative correlations between the percentage of Black Americans living in a state or metropolitan area and the RSV for colon cancer in that area (r=?0.18 and r=?0.05, respectively). However, in the 2 weeks following his death, there were positive correlations between the RSV for colon cancer and the percentage of Black Americans per state and per metropolitan area (r=0.73 and r=0.33, respectively). These changes persisted for 4 months and were all statistically significant (P<.001). Conclusions: There was a significant increase in web-based activity related to colon cancer following Chadwick Boseman's death, particularly in areas with a higher proportion of Black Americans. This reflects a heightened public awareness that can be leveraged to further educate the public. ",
doi="10.2196/27052",
url="https://www.jmir.org/2021/6/e27052",
url="http://www.ncbi.nlm.nih.gov/pubmed/34128824"
}


@Article{info:doi/10.2196/28328,
author="Brkic, F. Faris
and Besser, Gerold
and Schally, Martin
and Schmid, M. Elisabeth
and Parzefall, Thomas
and Riss, Dominik
and Liu, T. David",
title="Biannual Differences in Interest Peaks for Web Inquiries Into Ear Pain and Ear Drops: Infodemiology Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="20",
volume="23",
number="6",
pages="e28328",
keywords="otitis media",
keywords="otitis externa",
keywords="otalgia",
keywords="Google Trends",
keywords="infodemiology",
keywords="infoveillance",
keywords="infodemic",
keywords="social listening",
abstract="Background: The data retrieved with the online search engine, Google Trends, can summarize internet inquiries into specified search terms. This engine may be used for analyzing inquiry peaks for different medical conditions and symptoms. Objective: The aim of this study was to analyze World Wide Web interest peaks for ``ear pain,'' ``ear infection,'' and ``ear drops.'' Methods: We used Google Trends to assess the public online interest for search terms ``ear pain,'' ``ear infection,'' and ``ear drops'' in 5 English and non--English-speaking countries from both hemispheres based on time series data. We performed our analysis for the time frame between January 1, 2004, and December 31, 2019. First, we assessed whether our search terms were most relevant to the topics of ear pain, ear infection, and ear drops. We then tested the reliability of Google Trends time series data using the intraclass correlation coefficient. In a second step, we computed univariate time series plots to depict peaks in web-based interest. In the last step, we used the cosinor analysis to test the statistical significance of seasonal interest peaks. Results: In the first part of the study, it was revealed that ``ear infection,'' ``ear pain,'' and ``ear drops'' were the most relevant search terms in the noted time frame. Next, the intraclass correlation analysis showed a moderate to excellent reliability for all 5 countries' 3 primary search terms. The subsequent analysis revealed winter interest peaks for ``ear infection'' and ``ear pain''. On the other hand, the World Wide Web search for ``ear drops'' peaked annually during the summer months. All peaks were statistically significant as revealed by the cosinor model (all P values <.001). Conclusions: It can be concluded that individuals affected by otitis media or externa, possibly the majority, look for medical information online. Therefore, there is a need for accurate and easily accessible information on these conditions in the World Wide Web, particularly on differentiating signs and therapy options. Meeting this need may facilitate timely diagnosis, proper therapy, and eventual circumvention of potentially life-threatening complications. ",
doi="10.2196/28328",
url="https://www.jmir.org/2021/6/e28328/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185016"
}


@Article{info:doi/10.2196/26991,
author="Stampe, Kathrine
and Kishik, Sharon
and M{\"u}ller, Dueholm Sune",
title="Mobile Health in Chronic Disease Management and Patient Empowerment: Exploratory Qualitative Investigation Into Patient-Physician Consultations",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e26991",
keywords="compliance",
keywords="empowerment",
keywords="mHealth",
keywords="patient-physician consultation",
keywords="power",
abstract="Background: Chronic diseases often present severe consequences for those affected. The management and treatment of chronic diseases largely depend on patients' lifestyle choices and how they cope with the disease in their everyday lives. Accordingly, the ability of patients to self-manage diseases is a highly relevant topic. In relation to self-management, studies refer to patient empowerment as strengthening patients' voices and enabling them to assert control over their health and treatment. Mobile health (mHealth) provides cost-efficient means to support self-management and foster empowerment. Objective: There is a scarcity of research investigating how mHealth affects patient empowerment during patient-physician consultations. The objective of this study is to address this knowledge gap by investigating how mHealth affects consultations and patient empowerment. Methods: We relied on data from an ethnographic field study of 6 children and adolescents diagnosed with juvenile idiopathic arthritis. We analyzed 6 patient-physician consultations and drew on Michel Foucault's concepts of power and power technology. Results: Our results suggest that the use of mHealth constitutes practices that structure the consultations around deviations and noncompliant patient behavior. Our analysis shows how mHealth is used to discipline patients and correct their behavior. We argue that the use of mHealth during consultations may unintentionally lead to relevant aspects of patients' lives related to the disease being ignored; thus, inadvertently, patients' voices may be silenced. Conclusions: Our results show that concrete uses of mHealth may conflict with extant literature on empowerment, which emphasizes the importance of strengthening the patients' voices and enabling patients to take more control of their health and treatment. We contribute to the state-of-the-art knowledge by showing that the use of mHealth may have unintended consequences that do not lead to empowerment. Our analysis underscores the need for further research to investigate how mHealth impacts patient empowerment during consultations. ",
doi="10.2196/26991",
url="https://www.jmir.org/2021/6/e26991",
url="http://www.ncbi.nlm.nih.gov/pubmed/34128817"
}


@Article{info:doi/10.2196/18488,
author="Rose, Susannah
and Hurwitz, McKee Heather
and Mercer, Beth Mary
and Hizlan, Sabahat
and Gali, Kari
and Yu, Pei-Chun
and Franke, Caroline
and Martinez, Kathryn
and Stanton, Matthew
and Faiman, Matthew
and Rasmussen, Peter
and Boissy, Adrienne",
title="Patient Experience in Virtual Visits Hinges on Technology and the Patient-Clinician Relationship: A Large Survey Study With Open-ended Questions",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e18488",
keywords="telehealth",
keywords="virtual visit",
keywords="patient experience",
keywords="mobile phone",
abstract="Background: Patient satisfaction with in-person medical visits includes patient-clinician engagement. However, communication, empathy, and other relationship-centered care measures in virtual visits have not been adequately investigated. Objective: This study aims to comprehensively consider patient experience, including relationship-centered care measures, to assess patient satisfaction during virtual visits. Methods: We conducted a large survey study with open-ended questions to comprehensively assess patients' experiences with virtual visits in a diverse patient population. Adults with a virtual visit between June 21, 2017, and July 12, 2017, were invited to complete a survey of 21 Likert-scale items and textboxes for comments following their visit. Factor analysis of the survey items revealed three factors: experience with technology, patient-clinician engagement, and overall satisfaction. Multivariable logistic regression was used to test the associations among the three factors and patient demographics, clinician type, and prior relationship with the clinician. Using qualitative framework analysis, we identified recurrent themes in survey comments, quantitatively coded comments, and computed descriptive statistics of the coded comments. Results: A total of 65.7\% (426/648) of the patients completed the survey; 64.1\% (273/426) of the respondents were women, and the average age was 46 (range 18-86) years. The sample was geographically diverse: 70.2\% (299/426) from Ohio, 6.8\% (29/426) from Florida, 4.2\% (18/426) from Pennsylvania, and 18.7\% (80/426) from other states. With regard to insurance coverage, 57.5\% (245/426) were undetermined, 23.7\% (101/426) had the hospital's employee health insurance, and 18.7\% (80/426) had other private insurance. Types of virtual visits and clinicians varied. Overall, 58.4\% (249/426) of patients had an on-demand visit, whereas 41.5\% (177/426) had a scheduled visit. A total of 41.8\% (178/426) of patients had a virtual visit with a family physician, 20.9\% (89/426) with an advanced practice provider, and the rest had a visit with a specialist. Most patients (393/423, 92.9\%) agreed that their virtual visit clinician was interested in them as a person, and their virtual visit made it easy to get the care they needed (383/421, 90.9\%). A total of 81.9\% (344/420) of respondents agreed or strongly agreed that their virtual visit was as good as an in-person visit by a clinician. Having a prior relationship with their virtual visit clinician was associated with less comfort and ease with virtual technology among patients (odds ratio 0.58, 95\% CI 0.35-0.98). In terms of technology, patients found the interface easy to use (392/423, 92.7\%) and felt comfortable using it (401/423, 94.8\%). Technical difficulties were associated with lower odds of overall satisfaction (odds ratio 0.46, 95\% CI 0.28-0.76). Conclusions: Patient-clinician engagement in virtual visits was comparable with in-person visits. This study supports the value and acceptance of virtual visits. Evaluations of virtual visits should include assessments of technology and patient-clinician engagement, as both are likely to influence patient satisfaction. ",
doi="10.2196/18488",
url="https://www.jmir.org/2021/6/e18488",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152276"
}


@Article{info:doi/10.2196/28944,
author="Saig{\'i}-Rubi{\'o}, Francesc
and Vidal-Alaball, Josep
and Torrent-Sellens, Joan
and Jim{\'e}nez-Zarco, Ana
and L{\'o}pez Segui, Francesc
and Carrasco Hernandez, Marta
and Alzaga Reig, Xavier
and Bonet Sim{\'o}, Maria Josep
and Abizanda Gonz{\'a}lez, Mercedes
and Piera-Jimenez, Jordi
and Solans, Oscar",
title="Determinants of Catalan Public Primary Care Professionals' Intention to Use Digital Clinical Consultations (eConsulta) in the Post--COVID-19 Context: Mixed Methods Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e28944",
keywords="COVID-19",
keywords="teleconsultation",
keywords="eConsultation",
keywords="eHealth",
keywords="intention to use",
keywords="digital health",
keywords="Technology Acceptance Model",
keywords="TAM",
keywords="remote consultation",
keywords="telemedicine",
keywords="digital technology",
keywords="intention",
keywords="technology assessment",
keywords="telehealth",
keywords="pandemic",
keywords="digital tool",
abstract="Background: Telemedicine has become a necessary component of clinical practice for the purpose of providing safer patient care during lockdowns due to the COVID-19 pandemic. It has been used to support the health care needs of patients with COVID-19 and routine primary care patients alike. However, this change has not been fully consolidated. Objective: The objective of this study was to analyze the determinants of health care professionals' intention to use the eConsulta digital clinical consultation tool in the post--COVID-19 context. Methods: A literature review of the Technology Acceptance Model allowed us to construct a theoretical model and establish a set of hypotheses on the influence of a variety of different factors relating to health care professionals, as well as the institutions where they work, on their intention to use eConsulta. In order to confirm the proposed model, a mixed qualitative and quantitative methodology was used, and a questionnaire was designed to serve as the data collection instrument. The data were analyzed using univariate and bivariate analysis techniques. To confirm the theoretical model, exploratory factor analysis and binary logistic regression were applied. Results: The most important variables were related to perceived benefits (B=2.408) and the type of use that individuals habitually made of eConsulta (B=0.715). Environmental pressure (B=0.678), experience with technology (B=0.542), gender (B=0.639), and the degree to which eConsulta had been implemented (B=0.266) were other variables influencing the intention to use the tool in the post--COVID-19 context. When replicating the previous analysis according to professional group, experience with technology and gender in the physician group, and experience with tool use and the center where a professional worked in the nurse group, were found to be of considerable importance. Conclusions: The implementation and use of eConsulta had increased significantly as a consequence of the COVID-19 pandemic, and the majority of health care professionals were satisfied with its use in practice and planned to incorporate it into their practices in the post--COVID-19 context. Perceived benefits and environmental pressure were determining factors in their attitude toward and intention to use eConsulta. ",
doi="10.2196/28944",
url="https://www.jmir.org/2021/6/e28944/"
}


@Article{info:doi/10.2196/24947,
author="Oshima, M. Sachiko
and Tait, D. Sarah
and Thomas, M. Samantha
and Fayanju, M. Oluwadamilola
and Ingraham, Kearston
and Barrett, J. Nadine
and Hwang, Shelley E.",
title="Association of Smartphone Ownership and Internet Use With Markers of Health Literacy and Access: Cross-sectional Survey Study of Perspectives From Project PLACE (Population Level Approaches to Cancer Elimination)",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="9",
volume="23",
number="6",
pages="e24947",
keywords="telehealth",
keywords="technology",
keywords="health literacy",
keywords="access to health care",
keywords="mobile phone",
abstract="Background: Telehealth is an increasingly important component of health care delivery in response to the COVID-19 pandemic. However, well-documented disparities persist in the use of digital technologies. Objective: This study aims to describe smartphone and internet use within a diverse sample, to assess the association of smartphone and internet use with markers of health literacy and health access, and to identify the mediating factors in these relationships. Methods: Surveys were distributed to a targeted sample designed to oversample historically underserved communities from April 2017 to December 2017. Multivariate logistic regression was used to estimate the association of internet and smartphone use with outcomes describing health care access and markers of health literacy for the total cohort and after stratifying by personal history of cancer. Health care access was captured using multiple variables, including the ability to obtain medical care when needed. Markers of health literacy included self-reported confidence in obtaining health information. Results: Of the 2149 participants, 1319 (61.38\%) were women, 655 (30.48\%) were non-Hispanic White, and 666 (30.99\%) were non-Hispanic Black. The median age was 51 years (IQR 38-65). Most respondents reported using the internet (1921/2149, 89.39\%) and owning a smartphone (1800/2149, 83.76\%). Compared with the respondents with smartphone or internet access, those without smartphone or internet access were more likely to report that a doctor was their most recent source of health information (344/1800, 19.11\% vs 116/349, 33.2\% for smartphone and 380/1921, 19.78\% vs 80/228, 35.1\% for internet, respectively; both P<.001). Internet use was associated with having looked for information on health topics from any source (odds ratio [OR] 3.81, 95\% CI 2.53-5.75) and confidence in obtaining health information when needed (OR 1.83, 95\% CI 1.00-3.34) compared with noninternet users. Smartphone owners had lower odds of being unable to obtain needed medical care (OR 0.62, 95\% CI 0.40-0.95) than nonsmartphone owners. Among participants with a prior history of cancer, smartphone ownership was significantly associated with higher odds of confidence in ability to obtain needed health information (OR 5.63, 95\% CI 1.05-30.23) and lower odds of inability to obtain needed medical care (OR 0.17, 95\% CI 0.06-0.47), although these associations were not significant among participants without a prior history of cancer. Conclusions: We describe widespread use of digital technologies in a community-based cohort, although disparities persist. In this cohort, smartphone ownership was significantly associated with ability to obtain needed medical care, suggesting that the use of smartphone technology may play a role in increasing health care access. Similarly, major illnesses such as cancer have the potential to amplify health engagement. Finally, special emphasis must be placed on reaching patient populations with limited digital access, so these patients are not further disadvantaged in the new age of telehealth. ",
doi="10.2196/24947",
url="https://www.jmir.org/2021/6/e24947",
url="http://www.ncbi.nlm.nih.gov/pubmed/34106076"
}


@Article{info:doi/10.2196/20988,
author="Kouvonen, Anne
and Kemppainen, Laura
and Ketonen, Eeva-Leena
and Kemppainen, Teemu
and Olakivi, Antero
and Wrede, Sirpa",
title="Digital Information Technology Use, Self-Rated Health, and Depression: Population-Based Analysis of a Survey Study on Older Migrants",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e20988",
keywords="digital information technology",
keywords="older adults",
keywords="migrants",
keywords="health",
keywords="depression",
keywords="mobile phone",
abstract="Background: Previous studies have found that in general, poor health is associated with a lower likelihood of internet use in older adults, but it is not well known how different indicators of health are associated with different types of digital information technology (DIT) use. Moreover, little is known about the relationship between health and the types of DIT use in older ethnic minority and migrant populations. Objective: The aim of this study is to examine the associations among depressive symptoms and self-rated health (SRH) with different dimensions of DIT use in older migrants. Methods: We analyzed data from the Care, Health and Ageing of Russian-speaking Minority (CHARM) study, which is based on a nationally representative sample of community-dwelling, Russian-speaking adults aged 50 years or older residing permanently in Finland (men: 616/1082, 56.93\%; age: mean 63.2 years, SD 8.4 years; response rate: 1082/3000, 36.07\%). Data were collected in 2019 using a postal survey. Health was measured using depressive symptoms (measured using the Center for Epidemiologic Studies Depression Scale) and SRH. Binary logistic regression analyses were used to investigate the associations between the two health indicators and the following six outcomes: daily internet use, smartphone ownership, the use of the internet for messages and calls, social media use, the use of the internet for personal health data, and obtaining health information from the internet. A number of sociodemographic and socioeconomic factors were controlled for in the logistic regression regression analysis. Analyses were performed with weights accounting for the survey design and nonresponse. Results: After adjusting for sociodemographic and socioeconomic factors, depressive symptoms (odds ratio [OR] 2.68, 95\% CI 1.37-5.24; P=.004) and poor SRH (OR 7.90, 95\% CI 1.88-33.11; P=.005) were associated with a higher likelihood of not using the internet daily. Depressive symptoms (OR 1.88, 95\% CI 1.06-3.35; P=.03) and poor SRH (OR 5.05, 95\% CI 1.58-16.19; P=.006) also increased the likelihood of smartphone nonuse. Depressive symptoms were additionally associated with a lower likelihood of social media use, and poor SRH was associated with a lower likelihood of using the internet for messaging and calling. Conclusions: Poor SRH and depressive symptoms are associated with a lower likelihood of DIT use in older adults. Longitudinal studies are required to determine the directions of these relationships. ",
doi="10.2196/20988",
url="https://www.jmir.org/2021/6/e20988",
url="http://www.ncbi.nlm.nih.gov/pubmed/34125069"
}


@Article{info:doi/10.2196/26242,
author="Okoye, M. Safiyyah
and Mulcahy, F. John
and Fabius, D. Chanee
and Burgdorf, G. Julia
and Wolff, L. Jennifer",
title="Neighborhood Broadband and Use of Telehealth Among Older Adults: Cross-sectional Study of National Survey Data Linked With Census Data",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e26242",
keywords="aging",
keywords="broadband internet",
keywords="neighborhood",
keywords="telehealth",
abstract="Background: The COVID-19 pandemic has amplified the role of telehealth in health care delivery. Regional variation in internet access and telehealth use are well-documented, but the effect of neighborhood factors, including the pervasiveness of broadband internet, on older adults' telehealth usage in the context of internet access is not known. Objective: This study aimed to investigate how individual and neighborhood characteristics, including the pervasiveness of neighborhood broadband internet subscription, are associated with engagement in telehealth among older adults with internet access. Methods: In this cross-sectional study, we included 5117 community-living older adults aged ?65 years, who participated in the 2017 National Health and Aging Trends Study with census tract--level data for participants' places of residence from the American Community Survey. Results: Of an estimated 35.3 million community-living older adults, 21.1 million (59.7\%) were internet users, and of this group, more than one-third (35.8\%) engaged in telehealth. In a multivariable regression model adjusted for individual- and neighborhood-level factors, age, education, income, and the pervasiveness of neighborhood broadband internet subscription were associated with engagement in telehealth, while race, health, county metropolitan status, and neighborhood social deprivation were not. Among internet users, living in a neighborhood at the lowest (versus highest) tertile of broadband internet subscription was associated with being 40\% less likely to engage in telehealth (adjusted odds ratio 0.61, 95\% CI 0.42-0.87), all else equal. Conclusions: Neighborhood broadband internet stands out as a mutable characteristic that is consequential to engagement in telehealth. ",
doi="10.2196/26242",
url="https://www.jmir.org/2021/6/e26242",
url="http://www.ncbi.nlm.nih.gov/pubmed/34125071"
}


@Article{info:doi/10.2196/26085,
author="Bernier, Th{\'e}r{\`e}se
and Shah, Amika
and Ross, E. Lori
and Logie, H. Carmen
and Seto, Emily",
title="The Use of Information and Communication Technologies by Sex Workers to Manage Occupational Health and Safety: Scoping Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e26085",
keywords="sex work",
keywords="smartphone",
keywords="mobile phone",
keywords="occupational health and safety",
keywords="online",
keywords="internet",
keywords="website",
abstract="Background: In many countries, sex work is criminalized, driving sex work underground and leaving sex workers vulnerable to a number of occupational health and safety risks, including violence, assault, and robbery. With the advent of widely accessible information and communication technologies (ICTs), sex workers have begun to use electronic occupational health and safety tools to mitigate these risks. Objective: This study aims to explore the use of ICTs by sex workers for managing occupational health and safety risks and strategies for reducing these risks. This paper aims to answer the following question: what is known about sex workers' use of ICTs in the delivery of occupational health and safety strategies? Methods: A literature review following the methodological framework for scoping reviews was conducted to analyze studies describing the use of ICTs by sex workers to mitigate occupational health and safety risks. Experimental, observational, and descriptive studies, as well as protocol papers, were included in this scoping review. Results: Of the 2477 articles initially identified, 41 (1.66\%) met the inclusion criteria. Of these studies, 71\% (29/41) were published between 2015 and 2019. In these studies, the internet was the predominant ICT (24/41, 58\%), followed by text messaging (10/41, 24\%) and assorted communication technologies associated with mobile phones without internet access (7/41, 17\%; eg, voice mail). In 56\% (23/41) of the studies, sex workers located in high-income countries created occupational health and safety strategies (eg, bad date lists) and shared them through the internet. In 24\% (10/41) of the studies, mostly in low- and middle-income countries, organizations external to sex work developed and sent (through text messages) occupational health and safety strategies focused on HIV. In 20\% (8/41) of the studies, external organizations collaborated with the sex worker community in the development of occupational health and safety strategies communicated through ICTs; through this collaboration, concerns other than HIV (eg, mental health) emerged. Conclusions: Although there has been an increase in the number of studies on the use of ICTs by sex workers for managing occupational health and safety over the past 5 years, knowledge of how to optimally leverage ICTs for this purpose remains scarce. Recommendations for expanding the use of ICTs by sex workers for occupational health and safety include external organizations collaborating with sex workers in the design of ICT interventions to mitigate occupational health and safety risks; to examine whether ICTs used in low- and middle-income countries would have applications in high-income countries as a substitute to the internet for sharing occupational health and safety strategies; and to explore the creation of innovative, secure, web-based communities that use existing or alternative digital technologies that could be used by sex workers to manage their occupational health and safety. ",
doi="10.2196/26085",
url="https://www.jmir.org/2021/6/e26085/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185001"
}


@Article{info:doi/10.2196/25247,
author="Hu, Hao-Chun
and Chang, Shyue-Yih
and Wang, Chuen-Heng
and Li, Kai-Jun
and Cho, Hsiao-Yun
and Chen, Yi-Ting
and Lu, Chang-Jung
and Tsai, Tzu-Pei
and Lee, Kuang-Sheng Oscar",
title="Deep Learning Application for Vocal Fold Disease Prediction Through Voice Recognition: Preliminary Development Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e25247",
keywords="artificial intelligence",
keywords="convolutional neural network",
keywords="dysphonia",
keywords="pathological voice",
keywords="vocal fold disease",
keywords="voice pathology identification",
abstract="Background: Dysphonia influences the quality of life by interfering with communication. However, a laryngoscopic examination is expensive and not readily accessible in primary care units. Experienced laryngologists are required to achieve an accurate diagnosis. Objective: This study sought to detect various vocal fold diseases through pathological voice recognition using artificial intelligence. Methods: We collected 189 normal voice samples and 552 samples of individuals with voice disorders, including vocal atrophy (n=224), unilateral vocal paralysis (n=50), organic vocal fold lesions (n=248), and adductor spasmodic dysphonia (n=30). The 741 samples were divided into 2 sets: 593 samples as the training set and 148 samples as the testing set. A convolutional neural network approach was applied to train the model, and findings were compared with those of human specialists. Results: The convolutional neural network model achieved a sensitivity of 0.66, a specificity of 0.91, and an overall accuracy of 66.9\% for distinguishing normal voice, vocal atrophy, unilateral vocal paralysis, organic vocal fold lesions, and adductor spasmodic dysphonia. Compared with the accuracy of human specialists, the overall accuracy rates were 60.1\% and 56.1\% for the 2 laryngologists and 51.4\% and 43.2\% for the 2 general ear, nose, and throat doctors. Conclusions: Voice alone could be used for common vocal fold disease recognition through a deep learning approach after training with our Mandarin pathological voice database. This approach involving artificial intelligence could be clinically useful for screening general vocal fold disease using the voice. The approach includes a quick survey and a general health examination. It can be applied during telemedicine in areas with primary care units lacking laryngoscopic abilities. It could support physicians when prescreening cases by allowing for invasive examinations to be performed only for cases involving problems with automatic recognition or listening and for professional analyses of other clinical examination results that reveal doubts about the presence of pathologies. ",
doi="10.2196/25247",
url="https://www.jmir.org/2021/6/e25247",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100770"
}


@Article{info:doi/10.2196/20710,
author="Zhu, Y. Tracy
and Rothenb{\"u}hler, Martina
and Hamvas, Gy{\"o}rgyi
and Hofmann, Anja
and Welter, JoEllen
and Kahr, Maike
and Kimmich, Nina
and Shilaih, Mohaned
and Leeners, Brigitte",
title="The Accuracy of Wrist Skin Temperature in Detecting Ovulation Compared to Basal Body Temperature: Prospective Comparative Diagnostic Accuracy Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e20710",
keywords="ovulation",
keywords="basal body temperature",
keywords="BBT",
keywords="oral temperature",
keywords="wrist skin temperature",
keywords="diagnostic accuracy",
keywords="thermometer",
keywords="fertility",
keywords="menstruation",
keywords="wearable",
keywords="sensor",
keywords="mobile phone",
abstract="Background: As a daily point measurement, basal body temperature (BBT) might not be able to capture the temperature shift in the menstrual cycle because a single temperature measurement is present on the sliding scale of the circadian rhythm. Wrist skin temperature measured continuously during sleep has the potential to overcome this limitation. Objective: This study compares the diagnostic accuracy of these two temperatures for detecting ovulation and to investigate the correlation and agreement between these two temperatures in describing thermal changes in menstrual cycles. Methods: This prospective study included 193 cycles (170 ovulatory and 23 anovulatory) collected from 57 healthy women. Participants wore a wearable device (Ava Fertility Tracker bracelet 2.0) that continuously measured the wrist skin temperature during sleep. Daily BBT was measured orally and immediately upon waking up using a computerized fertility tracker with a digital thermometer (Lady-Comp). An at-home luteinizing hormone test was used as the reference standard for ovulation. The diagnostic accuracy of using at least one temperature shift detected by the two temperatures in detecting ovulation was evaluated. For ovulatory cycles, repeated measures correlation was used to examine the correlation between the two temperatures, and mixed effect models were used to determine the agreement between the two temperature curves at different menstrual phases. Results: Wrist skin temperature was more sensitive than BBT (sensitivity 0.62 vs 0.23; P<.001) and had a higher true-positive rate (54.9\% vs 20.2\%) for detecting ovulation; however, it also had a higher false-positive rate (8.8\% vs 3.6\%), resulting in lower specificity (0.26 vs 0.70; P=.002). The probability that ovulation occurred when at least one temperature shift was detected was 86.2\% for wrist skin temperature and 84.8\% for BBT. Both temperatures had low negative predictive values (8.8\% for wrist skin temperature and 10.9\% for BBT). Significant positive correlation between the two temperatures was only found in the follicular phase (rmcorr correlation coefficient=0.294; P=.001). Both temperatures increased during the postovulatory phase with a greater increase in the wrist skin temperature (range of increase: 0.50 {\textdegree}C vs 0.20 {\textdegree}C). During the menstrual phase, the wrist skin temperature exhibited a greater and more rapid decrease (from 36.13 {\textdegree}C to 35.80 {\textdegree}C) than BBT (from 36.31 {\textdegree}C to 36.27 {\textdegree}C). During the preovulatory phase, there were minimal changes in both temperatures and small variations in the estimated daily difference between the two temperatures, indicating an agreement between the two curves. Conclusions: For women interested in maximizing the chances of pregnancy, wrist skin temperature continuously measured during sleep is more sensitive than BBT for detecting ovulation. The difference in the diagnostic accuracy of these methods was likely attributed to the greater temperature increase in the postovulatory phase and greater temperature decrease during the menstrual phase for the wrist skin temperatures. ",
doi="10.2196/20710",
url="https://www.jmir.org/2021/6/e20710",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100763"
}


@Article{info:doi/10.2196/27407,
author="Yuan, Jing
and Libon, J. David
and Karjadi, Cody
and Ang, A. Alvin F.
and Devine, Sherral
and Auerbach, H. Sanford
and Au, Rhoda
and Lin, Honghuang",
title="Association Between the Digital Clock Drawing Test and Neuropsychological Test Performance: Large Community-Based Prospective Cohort (Framingham Heart Study)",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e27407",
keywords="clock drawing test",
keywords="neuropsychological test",
keywords="cognition",
keywords="technology",
keywords="digital assessment",
keywords="mild cognitive impairment",
keywords="association",
keywords="neurology",
keywords="Framingham Heart Study",
abstract="Background: The Clock Drawing Test (CDT) has been widely used in clinic for cognitive assessment. Recently, a digital Clock Drawing Text (dCDT) that is able to capture the entire sequence of clock drawing behaviors was introduced. While a variety of domain-specific features can be derived from the dCDT, it has not yet been evaluated in a large community-based population whether the features derived from the dCDT correlate with cognitive function. Objective: We aimed to investigate the association between dCDT features and cognitive performance across multiple domains. Methods: Participants from the Framingham Heart Study, a large community-based cohort with longitudinal cognitive surveillance, who did not have dementia were included. Participants were administered both the dCDT and a standard protocol of neuropsychological tests that measured a wide range of cognitive functions. A total of 105 features were derived from the dCDT, and their associations with 18 neuropsychological tests were assessed with linear regression models adjusted for age and sex. Associations between a composite score from dCDT features were also assessed for associations with each neuropsychological test and cognitive status (clinically diagnosed mild cognitive impairment compared to normal cognition). Results: The study included 2062 participants (age: mean 62, SD 13 years, 51.6\% women), among whom 36 were diagnosed with mild cognitive impairment. Each neuropsychological test was associated with an average of 50 dCDT features. The composite scores derived from dCDT features were significantly associated with both neuropsychological tests and mild cognitive impairment. Conclusions: The dCDT can potentially be used as a tool for cognitive assessment in large community-based populations. ",
doi="10.2196/27407",
url="https://www.jmir.org/2021/6/e27407",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100766"
}


@Article{info:doi/10.2196/23294,
author="Thomas, E. Beena
and Kumar, Vignesh J.
and Periyasamy, Murugesan
and Khandewale, Subhash Amit
and Hephzibah Mercy, J.
and Raj, Michael E.
and Kokila, S.
and Walgude, Shashikant Apurva
and Gaurkhede, Rahul Gunjan
and Kumbhar, Dattatraya Jagannath
and Ovung, Senthanro
and Paul, Mariyamma
and Rajkumar, Sathyan B.
and Subbaraman, Ramnath",
title="Acceptability of the Medication Event Reminder Monitor for Promoting Adherence to Multidrug-Resistant Tuberculosis Therapy in Two Indian Cities: Qualitative Study of Patients and Health Care Providers",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="10",
volume="23",
number="6",
pages="e23294",
keywords="tuberculosis",
keywords="drug-resistant",
keywords="medication adherence",
keywords="mHealth",
keywords="digital adherence technologies",
keywords="India",
abstract="Background: Patients with multidrug-resistant tuberculosis (MDR-TB) face challenges adhering to medications, given that treatment is prolonged and has a high rate of adverse effects. The Medication Event Reminder Monitor (MERM) is a digital pillbox that provides pill-taking reminders and facilitates the remote monitoring of medication adherence. Objective: This study aims to assess the MERM's acceptability to patients and health care providers (HCPs) during pilot implementation in India's public sector MDR-TB program. Methods: From October 2017 to September 2018, we conducted qualitative interviews with patients who were undergoing MDR-TB therapy and were being monitored with the MERM and HCPs in the government program in Chennai and Mumbai. Interview transcripts were independently coded by 2 researchers and analyzed to identify the emergent themes. We organized findings by using the Unified Theory of Acceptance and Use of Technology (UTAUT), which outlines 4 constructs that predict technology acceptance---performance expectancy, effort expectancy, social influence, and facilitating conditions. Results: We interviewed 65 patients with MDR-TB and 10 HCPs. In patient interviews, greater acceptance of the MERM was related to perceptions that the audible and visual reminders improved medication adherence and that remote monitoring reduced the frequency of clinic visits (performance expectancy), that the device's organization and labeling of medications made it easier to take them correctly (effort expectancy), that the device facilitated positive family involvement in the patient's care (social influences), and that remote monitoring made patients feel more cared for by the health system (facilitating conditions). Lower patient acceptance was related to problems with the durability of the MERM's cardboard construction and difficulties with portability and storage because of its large size (effort expectancy), concerns regarding stigma and the disclosure of patients' MDR-TB diagnoses (social influences), and the incorrect understanding of the MERM because of suboptimal counseling (facilitating conditions). In their interviews, HCPs reported that MERM implementation resulted in fewer in-person interactions with patients and thus allowed HCPs to dedicate more time to other tasks, which improved job satisfaction. Conclusions: Several features of the MERM support its acceptability among patients with MDR-TB and HCPs, and some barriers to patient use could be addressed by improving the design of the device. However, some barriers, such as disease-related stigma, are more difficult to modify and may limit use of the MERM among some patients with MDR-TB. Further research is needed to assess the accuracy of MERM for measuring adherence, its effectiveness for improving treatment outcomes, and patients' sustained use of the device in larger scale implementation. ",
doi="10.2196/23294",
url="https://www.jmir.org/2021/6/e23294",
url="http://www.ncbi.nlm.nih.gov/pubmed/34110300"
}


@Article{info:doi/10.2196/22395,
author="Zhang, Fuguo
and Xue, Bingyu
and Li, Yiran
and Li, Hui
and Liu, Qihua",
title="Effect of Textual Features on the Success of Medical Crowdfunding: Model Development and Econometric Analysis from the Tencent Charity Platform",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e22395",
keywords="medical crowdfunding",
keywords="textual features",
keywords="project title",
keywords="project details",
keywords="fundraising success",
keywords="theory of persuasion",
abstract="Background: Medical crowdfunding utilizes the internet to raise medical funds. Medical crowdfunding has developed rapidly worldwide; however, most medical crowdfunding projects fail to raise the targeted funds. Therefore, a very important research problem that has not received sufficient attention from the existing literature is identifying which factors affect the success of medical crowdfunding projects. Objective: The aim of this study was to examine the effect of textual features of medical crowdfunding projects on their success rate using 4903 real projects from the Tencent Charity platform, a well-known medical crowdfunding platform in China. In particular, according to Aristotle's theory of persuasion, we divided the project text of medical crowdfunding into the project title and project details, which were analyzed from two perspectives (existence and extent) to explore their respective impacts. Methods: We established a research framework to meet our research goals. The process was divided into five main parts. We first collected data from Tencent Charity using Python programs and cleaned the datasets. Second, we selected variables and built the research model based on previous studies and the theory of persuasion. Next, the selected variables were extracted from the project text. We then performed econometric analysis using multiple regression analysis. Finally, we evaluated the results of econometric analysis to extract knowledge. Results: In the project title, the presence of the patient's disease (P=.04) and occupation (P=.01) had a positive impact on the success rate of fundraising, whereas the presence of age (P<.001), gender (P=.001), and negative emotions (P=.04) had a negative impact. In the project details, the presence of the patient's occupation (P=.01), monetary evidence (P=.02), and negative emotions (P=.04) played a positive role in the fundraising success rate, whereas the presence of age (P<.001) and positive emotions (P<.001) played a negative role. Moreover, in the project details, high-frequency monetary evidence (P=.02) and negative words (P=.02), as well as a short narrative length (P=.01) were conducive to succeeding in medical crowdfunding. Younger patients were more likely to obtain a higher success rate in medical crowdfunding. For patients whose occupations were national civil servant, professional skill worker, clerk, business and service worker, solider, child, student, and public-spirited person, the success rate of fundraising decreased sequentially. Conclusions: This study collected 4903 valid data from Tencent Charity, and identified which factors in the project text play an important role in the success rate of medical crowdfunding from the perspective of existence and extent. We found that in addition to the project details, the features of the project title also have an important impact on the success rate of fundraising. These findings provide important theoretical and managerial implications for medical crowdfunding. ",
doi="10.2196/22395",
url="https://www.jmir.org/2021/6/e22395",
url="http://www.ncbi.nlm.nih.gov/pubmed/34114959"
}


@Article{info:doi/10.2196/25913,
author="Verdonck, Micha{\"e}l
and Carvalho, Hugo
and Berghmans, Johan
and Forget, Patrice
and Poelaert, Jan",
title="Exploratory Outlier Detection for Acceleromyographic Neuromuscular Monitoring: Machine Learning Approach",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e25913",
keywords="neuromuscular monitoring",
keywords="outlier analysis",
keywords="acceleromyography",
keywords="postoperative residual curarization",
keywords="train-of-four",
keywords="monitoring devices",
keywords="neuromuscular",
keywords="machine learning",
keywords="monitors",
keywords="anesthesiology",
abstract="Background: Perioperative quantitative monitoring of neuromuscular function in patients receiving neuromuscular blockers hasbecome internationally recognized as an absolute and core necessity in modern anesthesia care. Because of their kinetic nature, artifactual recordings of acceleromyography-based neuromuscular monitoring devices are not unusual. These generate a great deal of cynicism among anesthesiologists, constituting an obstacle toward their widespread adoption. Through outlier analysis techniques, monitoring devices can learn to detect and flag signal abnormalities. Outlier analysis (or anomaly detection) refers to the problem of finding patterns in data that do not conform to expected behavior. Objective: This study was motivated by the development of a smartphone app intended for neuromuscular monitoring based on combined accelerometric and angular hand movement data. During the paired comparison stage of this app against existing acceleromyography monitoring devices, it was noted that the results from both devices did not always concur.  This study aims to engineer a set of features that enable the detection of outliers in the form of erroneous train-of-four (TOF) measurements from an acceleromyographic-based device. These features are tested for their potential in the detection of erroneous TOF measurements by developing an outlier detection algorithm. Methods: A data set encompassing 533 high-sensitivity TOF measurements from 35 patients was created based on a multicentric open label trial of a purpose-built accelero- and gyroscopic-based neuromuscular monitoring app. A basic set of features was extracted based on raw data while a second set of features was purpose engineered based on TOF pattern characteristics. Two cost-sensitive logistic regression (CSLR) models were deployed to evaluate the performance of these features. The final output of the developed models was a binary classification, indicating if a TOF measurement was an outlier or not. Results: A total of 7 basic features were extracted based on raw data, while another 8 features were engineered based on TOF pattern characteristics. The model training and testing were based on separate data sets: one with 319 measurements (18 outliers) and a second with 214 measurements (12 outliers). The F1 score (95\% CI) was 0.86 (0.48-0.97) for the CSLR model with engineered features, significantly larger than the CSLR model with the basic features (0.29 [0.17-0.53]; P<.001). Conclusions: The set of engineered features and their corresponding incorporation in an outlier detection algorithm have the potential to increase overall neuromuscular monitoring data consistency. Integrating outlier flagging algorithms within neuromuscular monitors could potentially reduce overall acceleromyography-based reliability issues. Trial Registration: ClinicalTrials.gov NCT03605225; https://clinicaltrials.gov/ct2/show/NCT03605225 ",
doi="10.2196/25913",
url="https://www.jmir.org/2021/6/e25913/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152273"
}


@Article{info:doi/10.2196/25482,
author="Feusner, D. Jamie
and Mohideen, Reza
and Smith, Stephen
and Patanam, Ilyas
and Vaitla, Anil
and Lam, Christopher
and Massi, Michelle
and Leow, Alex",
title="Semantic Linkages of Obsessions From an International Obsessive-Compulsive Disorder Mobile App Data Set: Big Data Analytics Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e25482",
keywords="OCD",
keywords="natural language processing",
keywords="clinical subtypes",
keywords="semantic",
keywords="word embedding",
keywords="clustering",
abstract="Background: Obsessive-compulsive disorder (OCD) is characterized by recurrent intrusive thoughts, urges, or images (obsessions) and repetitive physical or mental behaviors (compulsions). Previous factor analytic and clustering studies suggest the presence of three or four subtypes of OCD symptoms. However, these studies have relied on predefined symptom checklists, which are limited in breadth and may be biased toward researchers' previous conceptualizations of OCD. Objective: In this study, we examine a large data set of freely reported obsession symptoms obtained from an OCD mobile app as an alternative to uncovering potential OCD subtypes. From this, we examine data-driven clusters of obsessions based on their latent semantic relationships in the English language using word embeddings. Methods: We extracted free-text entry words describing obsessions in a large sample of users of a mobile app, NOCD. Semantic vector space modeling was applied using the Global Vectors for Word Representation algorithm. A domain-specific extension, Mittens, was also applied to enhance the corpus with OCD-specific words. The resulting representations provided linear substructures of the word vector in a 100-dimensional space. We applied principal component analysis to the 100-dimensional vector representation of the most frequent words, followed by k-means clustering to obtain clusters of related words. Results: We obtained 7001 unique words representing obsessions from 25,369 individuals. Heuristics for determining the optimal number of clusters pointed to a three-cluster solution for grouping subtypes of OCD. The first had themes relating to relationship and just-right; the second had themes relating to doubt and checking; and the third had themes relating to contamination, somatic, physical harm, and sexual harm. All three clusters showed close semantic relationships with each other in the central area of convergence, with themes relating to harm. An equal-sized split-sample analysis across individuals and a split-sample analysis over time both showed overall stable cluster solutions. Words in the third cluster were the most frequently occurring words, followed by words in the first cluster. Conclusions: The clustering of naturally acquired obsessional words resulted in three major groupings of semantic themes, which partially overlapped with predefined checklists from previous studies. Furthermore, the closeness of the overall embedded relationships across clusters and their central convergence on harm suggests that, at least at the level of self-reported obsessional thoughts, most obsessions have close semantic relationships. Harm to self or others may be an underlying organizing theme across many obsessions. Notably, relationship-themed words, not previously included in factor-analytic studies, clustered with just-right words. These novel insights have potential implications for understanding how an apparent multitude of obsessional symptoms are connected by underlying themes. This observation could aid exposure-based treatment approaches and could be used as a conceptual framework for future research. ",
doi="10.2196/25482",
url="https://www.jmir.org/2021/6/e25482",
url="http://www.ncbi.nlm.nih.gov/pubmed/33892466"
}


@Article{info:doi/10.2196/23839,
author="Jones, Tarsha
and Guzman, Ashlee
and Silverman, Thomas
and Freeman, Katherine
and Kukafka, Rita
and Crew, Katherine",
title="Perceptions of Racially and Ethnically Diverse Women at High Risk of Breast Cancer Regarding the Use of a Web-Based Decision Aid for Chemoprevention: Qualitative Study Nested Within a Randomized Controlled Trial",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e23839",
keywords="breast cancer",
keywords="chemoprevention",
keywords="qualitative",
keywords="decision support",
keywords="cancer",
keywords="estrogen receptor",
keywords="web-based",
keywords="cancer risk",
abstract="Background: Chemopreventive agents such as selective estrogen receptor modulators and aromatase inhibitors have proven efficacy in reducing breast cancer risk by 41\% to 79\% in high-risk women. Women at high risk of developing breast cancer face the complex decision of whether to take selective estrogen receptor modulators or aromatase inhibitors for breast cancer chemoprevention. RealRisks is a patient-centered, web-based decision aid (DA) designed to promote the understanding of breast cancer risk and to engage diverse women in planning a preference-sensitive course of decision making about taking chemoprevention. Objective: This study aims to understand the perceptions of women at high risk of developing breast cancer regarding their experience with using RealRisks---a DA designed to promote the uptake of breast cancer chemoprevention---and to understand their information needs. Methods: We completed enrollment to a randomized controlled trial among 300 racially and ethnically diverse women at high risk of breast cancer who were assigned to standard educational materials alone or such materials in combination with RealRisks. We conducted semistructured interviews with a subset of 21 high-risk women enrolled in the intervention arm of the randomized controlled trial who initially accessed the tool (on average, 1 year earlier) to understand how they interacted with the tool. All interviews were audio recorded, transcribed verbatim, and compared with digital audio recordings to ensure the accuracy of the content. We used content analysis to generate themes. Results: The mean age of the 21 participants was 58.5 (SD 10.1) years. The participants were 5\% (1/21) Asian, 24\% (5/21) Black or African American, and 71\% (15/21) White; 10\% (2/21) of participants were Hispanic or Latina. All participants reported using RealRisks after being granted access to the DA. In total, 4 overarching themes emerged from the qualitative analyses: the acceptability of the intervention, specifically endorsed elements of the DA, recommendations for improvements, and information needs. All women found RealRisks to be acceptable and considered it to be helpful (21/21, 100\%). Most women (13/21, 62\%) reported that RealRisks was easy to navigate, user-friendly, and easily accessible on the web. The majority of women (18/21, 86\%) felt that RealRisks improved their knowledge about breast cancer risk and chemoprevention options and that RealRisks informed their (17/21, 81\%) decision about whether or not to take chemoprevention. Some women (9/21, 43\%) shared recommendations for improvements, as they wanted more tailoring based on user characteristics, felt that the DA was targeting a narrow population of Hispanic or Latina by using graphic novel--style narratives, wanted more understandable terminology, and felt that the tool placed a strong emphasis on chemoprevention drugs. Conclusions: This qualitative study demonstrated the acceptability of the RealRisks web-based DA among a diverse group of high-risk women, who provided some recommendations for improvement. ",
doi="10.2196/23839",
url="https://www.jmir.org/2021/6/e23839",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100769"
}


@Article{info:doi/10.2196/26019,
author="Zhang, Hongjie Thomas
and Tham, Sern Jen",
title="Calls to Action (Mobilizing Information) on Cancer in Online News: Content Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e26019",
keywords="mobilizing information",
keywords="online cancer news",
keywords="quantitative content analysis",
keywords="Malaysia",
keywords="online news",
keywords="cancer",
keywords="infodemiology",
keywords="media",
keywords="digital media",
keywords="digital health",
keywords="health information",
keywords="cancer health information",
abstract="Background: The health belief model explains that individual intentions and motivation of health behaviors are mostly subject to externalcues to action, such as from interpersonal communications and media consumptions. The concept of mobilizing information (MI) refers to a type of mediated information that could call individuals to carry out particular health actions. Different media channels, especially digital media outlets, play an essential role as a health educator to disseminate cancer health information and persuade and mobilize cancer prevention in the community. However, little is known about calls to action (or MI) in online cancer news, especially from Asian media outlets. Objective: This study aimed at analyzing cancer news articles that contain MI and their news components on the selected Malaysian English and Chinese newspapers with online versions. Methods: The Star Online and Sin Chew Online were selected for analysis because the two newspaper websites enjoy the highest circulation and readership in the English language and the Chinese language streams, respectively. Two bilingual coders searched the cancer news articles based on sampling keywords and then read and coded each news article accordingly. Five coding variables were conceptualized from previous studies (ie, cancer type, news source, news focus, cancer risk factors, and MI), and a good consistency using Cohen kappa was built between coders. Descriptive analysis was used to examine the frequency and percentage of each coding item; chi-square test (confidence level at 95\%) was applied to analyze the differences between two newspaper websites, and the associations between variables and the presence of MI were examined through binary logistic regression. Results: Among 841 analyzed news articles, 69.6\% (585/841) presented MI. News distributions were unbalanced throughout the year in both English and Chinese newspaper websites; some months occupied peaks (ie, February and October), but cancer issues and MI for cancer prevention received minimal attention in other months. The news articles from The Star Online and Sin Chew Online were significantly different in several news components, such as the MI present rates ($\chi$2=9.25, P=.003), providing different types of MI (interactive MI: $\chi$2=12.08, P=.001), interviewing different news sources (government agency: $\chi$2=12.05, P=.001), concerning different news focus (primary cancer prevention: $\chi$2=10.98, P=.001), and mentioning different cancer risks (lifestyle risks: $\chi$2=7.43, P=.007). Binary logistic regression results reported that online cancer news articles were more likely to provide MI when interviewing nongovernmental organizations, focusing on topics related to primary cancer prevention, and highlighting lifestyle risks (odds ratio [OR] 2.77, 95\% CI 1.89-4.05; OR 97.70, 95\% CI 46.97-203.24; OR 186.28; 95\% CI 44.83-773.96; P=.001, respectively). Conclusions: This study provided new understandings regarding MI in cancer news coverage. This could wake and trigger individuals' preexisting attitudes and intentions on cancer prevention. Thus, health professionals, health journalists, and health campaign designers should concentrate on MI when distributing health information to the community. ",
doi="10.2196/26019",
url="https://www.jmir.org/2021/6/e26019",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152283"
}


@Article{info:doi/10.2196/27820,
author="Ordaz, H. Omar
and Croff, L. Raina
and Robinson, D. LaTroy
and Shea, A. Steven
and Bowles, P. Nicole",
title="Optimization of Primary Care Among Black Americans Using Patient Portals: Qualitative Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e27820",
keywords="health promotion",
keywords="patient engagement",
keywords="telehealth",
keywords="telemedicine",
keywords="health disparities",
keywords="technology acceptance model",
keywords="health belief model",
abstract="Background: Reduced patient portal use has previously been reported among Black Americans when compared with that of the general population. This statistic is concerning because portals have been shown to improve the control of chronic conditions that are more prevalent and severe in Black Americans. At their very simplest, portals allow patients to access their electronic health records and often provide tools for patients to interact with their own health information, treatment team members, and insurance companies. However, research suggests that Black American patients have greater concerns over a lack of support, loss of privacy, and reduced personalization of care compared with other Americans, which results in a disparity of portal use.  Objective: This qualitative investigation of primary care experiences of Black Americans from across the United States who participated in remote focus groups in April and May 2020 aims to explore the use and perceived value of patient portals to better understand any barriers to optimized treatment in the primary care setting. Methods: We performed an inductive thematic analysis of 8 remote focus group interviews with 29 Black American patients aged 30-60 years to qualitatively assess the experiences of Black American patients with regular access to portals.  Results: Thematic analysis uncovered the following interrelated themes regarding patient portals in primary care: the optimization of care, patient empowerment, patient-provider communication, and patient burden.  Conclusions: In contrast to what has been described regarding the reluctance of Black Americans to engage with patient portals, our focus groups revealed the general acceptance of patient portals, which were described overwhelmingly as tools with the potential for providing exceptional, personalized care that may even work to mitigate the unfair burden of disease for Black Americans in primary care settings. Thus, opportunities for better health care will clearly arise with increased communication, experience, and adoption of remote health care practices among Black Americans. ",
doi="10.2196/27820",
url="https://www.jmir.org/2021/6/e27820",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081016"
}


@Article{info:doi/10.2196/25794,
author="Chia, Airu
and Chew, Sheng Muhammad Naeem Jia
and Tan, Xuan Sarah Yi
and Chan, Jun Mei
and T Colega, Marjorelee
and Toh, Ying Jia
and Natarajan, Padmapriya
and Lan{\c{c}}a, Carla
and Shek, P. Lynette
and Saw, Seang-Mei
and M{\"u}ller-Riemenschneider, Falk
and Chong, Foong-Fong Mary",
title="A Web-Based Time-Use Application to Assess Diet and Movement Behavior in Asian Schoolchildren: Development and Usability Study of My E-Diary for Activities and Lifestyle (MEDAL)",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="9",
volume="23",
number="6",
pages="e25794",
keywords="time use",
keywords="web-based",
keywords="diet",
keywords="movement behaviors",
keywords="usability",
keywords="schoolchildren",
abstract="Background: Web-based time-use diaries for schoolchildren are limited, and existing studies focus mostly on capturing physical activities and sedentary behaviors but less comprehensively on dietary behaviors. Objective: This study aims to describe the development of My E-Diary for Activities and Lifestyle (MEDAL)---a self-administered, web-based time-use application to assess diet and movement behavior---and to evaluate its usability in schoolchildren in Singapore. Methods: MEDAL was developed through formative research and an iterative user-centric design approach involving small groups of schoolchildren (ranging from n=5 to n=15, aged 7-13 years). To test the usability, children aged 10-11 years were recruited from 2 primary schools in Singapore to complete MEDAL for 2 weekdays and 2 weekend days and complete a 10-item usability questionnaire. Results: The development process revealed that younger children (aged <9 years) were less able to complete MEDAL independently. Of the 204 participants (118/204, 57.8\% boys, and 31/201, 15.4\% overweight) in the usability study, 57.8\% (118/204) completed 3 to 4 days of recording, whereas the rest recorded for 2 days or less. The median time taken to complete MEDAL was 14.2 minutes per day. The majority of participants agreed that instructions were clear (193/203, 95.1\%), that MEDAL was easy to use (173/203, 85.2\%), that they liked the application (172/202, 85.1\%), and that they preferred recording their activities on the web than on paper (167/202, 82.7\%). Among all the factors evaluated, recording for 4 days was the least satisfactory component reported. Compared with boys, girls reported better recall ability and agreed that the time spent on completing 1-day entry was appropriate. Conclusions: MEDAL appears to be a feasible application to capture diet and movement behaviors in children aged 10-12 years, particularly in the Asian context. Some gender differences in usability performance were observed, but the majority of the participants had a positive experience using MEDAL. The validation of the data collected through the application is in progress. ",
doi="10.2196/25794",
url="https://www.jmir.org/2021/6/e25794",
url="http://www.ncbi.nlm.nih.gov/pubmed/34106084"
}


@Article{info:doi/10.2196/24723,
author="Plackett, Ruth
and Kassianos, P. Angelos
and Timmis, Jessica
and Sheringham, Jessica
and Schartau, Patricia
and Kambouri, Maria",
title="Using Virtual Patients to Explore the Clinical Reasoning Skills of Medical Students: Mixed Methods Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e24723",
keywords="computer simulation",
keywords="web-based patient simulation",
keywords="computer-assisted instruction",
keywords="educational technology",
keywords="medical education",
keywords="clinical decision support systems",
keywords="clinical decision making",
keywords="clinical reasoning",
keywords="clinical skills",
keywords="primary care",
keywords="diagnosis",
abstract="Background: Improving clinical reasoning skills---the thought processes used by clinicians to formulate appropriate questions and diagnoses---is essential for reducing missed diagnostic opportunities. The electronic Clinical Reasoning Educational Simulation Tool (eCREST) was developed to improve the clinical reasoning of future physicians. A feasibility trial demonstrated acceptability and potential impacts; however, the processes by which students gathered data were unknown. Objective: This study aims to identify the data gathering patterns of final year medical students while using eCREST and how eCREST influences the patterns. Methods: A mixed methods design was used. A trial of eCREST across 3 UK medical schools (N=148) measured the potential effects of eCREST on data gathering. A qualitative think-aloud and semistructured interview study with 16 medical students from one medical school identified 3 data gathering strategies: Thorough, Focused, and Succinct. Some had no strategy. Reanalysis of the trial data identified the prevalence of data gathering patterns and compared patterns between the intervention and control groups. Patterns were identified based on 2 variables that were measured in a patient case 1 month after the intervention: the proportion of Essential information students identified and the proportion of irrelevant information gathered (Relevant). Those who scored in the top 3 quartiles for Essential but in the lowest quartile for Relevant displayed a Thorough pattern. Those who scored in the top 3 quartiles for Relevant but in the lowest quartile for Essential displayed a Succinct pattern. Those who scored in the top 3 quartiles on both variables displayed a Focused pattern. Those whose scores were in the lowest quartile on both variables displayed a Nonspecific pattern. Results: The trial results indicated that students in the intervention group were more thorough than those in the control groups when gathering data. The qualitative data identified data gathering strategies and the mechanisms by which eCREST influenced data gathering. Students reported that eCREST promoted thoroughness by prompting them to continuously reflect and allowing them to practice managing uncertainty. However, some found eCREST to be less useful, and they randomly gathered information. Reanalysis of the trial data revealed that the intervention group was significantly more likely to display a Thorough data gathering pattern than controls (21/78, 27\% vs 6/70, 9\%) and less likely to display a Succinct pattern (13/78, 17\% vs 20/70, 29\%; $\chi$23=9.9; P=.02). Other patterns were similar across groups. Conclusions: Qualitative data suggested that students applied a range of data gathering strategies while using eCREST and that eCREST encouraged thoroughness by continuously prompting the students to reflect and manage their uncertainty. Trial data suggested that eCREST led students to demonstrate more Thorough data gathering patterns. Virtual patients that encourage thoroughness could help future physicians avoid missed diagnostic opportunities and enhance the delivery of clinical reasoning teaching. ",
doi="10.2196/24723",
url="https://www.jmir.org/2021/6/e24723",
url="http://www.ncbi.nlm.nih.gov/pubmed/34085940"
}


@Article{info:doi/10.2196/25367,
author="Chen, Qin
and Jin, Jiahua
and Zhang, Tingting
and Yan, Xiangbin",
title="The Effects of Log-in Behaviors and Web Reviews on Patient Consultation in Online Health Communities: Longitudinal Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e25367",
keywords="online health communities",
keywords="digital health",
keywords="patient consultation",
keywords="log-in behavior",
keywords="web reviews",
keywords="offline status",
abstract="Background: With the rapid development of information technology and web-based communities, a growing number of patients choose to consult physicians in online health communities (OHCs) for information and treatment. Although extant research has primarily discussed factors that influence the consulting choices of OHC patients, there is still a lack of research on the effects of log-in behaviors and web reviews on patient consultation. Objective: This study aims to explore the impact of physicians' log-in behavior and web reviews on patient consultation. Methods: We conducted a longitudinal study to examine the effects of physicians' log-in behaviors and web reviews on patient consultation by analyzing short-panel data from 911 physicians over five periods in a Chinese OHC. Results: The results showed that the physician's log-in behavior had a positive effect on patient consultation. The maximum number of days with no log-ins for a physician should be 20. The two web signals (log-in behavior and web reviews) had no complementary relationship. Moreover, the offline signal (ie, offline status) has different moderating effects on the two web signals, positively moderating the relationship between web reviews and patient consultation. Conclusions: Our study contributes to the eHealth literature and advances the understanding of physicians' web-based behaviors. This study also provides practical implications, showing that physicians' log-in behavior alone can affect patient consultation rather than complementing web reviews. ",
doi="10.2196/25367",
url="https://www.jmir.org/2021/6/e25367",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081008"
}


@Article{info:doi/10.2196/25409,
author="Braune, Katarina
and Gajewska, Anna Katarzyna
and Thieffry, Axel
and Lewis, Michelle Dana
and Froment, Timoth{\'e}e
and O'Donnell, Shane
and Speight, Jane
and Hendrieckx, Christel
and Schipp, Jasmine
and Skinner, Timothy
and Langstrup, Henriette
and Tappe, Adrian
and Raile, Klemens
and Cleal, Bryan",
title="Why \#WeAreNotWaiting---Motivations and Self-Reported Outcomes Among Users of Open-source Automated Insulin Delivery Systems: Multinational Survey",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e25409",
keywords="diabetes",
keywords="artificial pancreas",
keywords="automated insulin delivery",
keywords="open-source",
keywords="patient-led",
keywords="user-led",
keywords="peer support",
keywords="online communities",
keywords="diabetes technology",
keywords="digital health",
keywords="mobile health",
keywords="medical device regulation",
keywords="motivation",
keywords="sleep quality",
keywords="do-it-yourself",
abstract="Background: Automated insulin delivery (AID) systems have been shown to be safe and effective in reducing hyperglycemia and hypoglycemia but are not universally available, accessible, or affordable. Therefore, user-driven open-source AID systems are becoming increasingly popular. Objective: This study aims to investigate the motivations for which people with diabetes (types 1, 2, and other) or their caregivers decide to build and use a personalized open-source AID. Methods: A cross-sectional web-based survey was conducted to assess personal motivations and associated self-reported clinical outcomes. Results: Of 897 participants from 35 countries, 80.5\% (722) were adults with diabetes and 19.5\% (175) were caregivers of children with diabetes. Primary motivations to commence open-source AID included improving glycemic outcomes (476/509 adults, 93.5\%, and 95/100 caregivers, 95\%), reducing acute (443/508 adults, 87.2\%, and 96/100 caregivers, 96\%) and long-term (421/505 adults, 83.3\%, and 91/100 caregivers, 91\%) complication risk, interacting less frequently with diabetes technology (413/509 adults, 81.1\%; 86/100 caregivers, 86\%), improving their or child's sleep quality (364/508 adults, 71.6\%, and 80/100 caregivers, 80\%), increasing their or child's life expectancy (381/507 adults, 75.1\%, and 84/100 caregivers, 84\%), lack of commercially available AID systems (359/507 adults, 70.8\%, and 79/99 caregivers, 80\%), and unachieved therapy goals with available therapy options (348/509 adults, 68.4\%, and 69/100 caregivers, 69\%). Improving their own sleep quality was an almost universal motivator for caregivers (94/100, 94\%). Significant improvements, independent of age and gender, were observed in self-reported glycated hemoglobin (HbA1c), 7.14\% (SD 1.13\%; 54.5 mmol/mol, SD 12.4) to 6.24\% (SD 0.64\%; 44.7 mmol/mol, SD 7.0; P<.001), and time in range (62.96\%, SD 16.18\%, to 80.34\%, SD 9.41\%; P<.001). Conclusions: These results highlight the unmet needs of people with diabetes, provide new insights into the evolving phenomenon of open-source AID technology, and indicate improved clinical outcomes. This study may inform health care professionals and policy makers about the opportunities provided by open-source AID systems. International Registered Report Identifier (IRRID): RR2-10.2196/15368 ",
doi="10.2196/25409",
url="https://www.jmir.org/2021/6/e25409",
url="http://www.ncbi.nlm.nih.gov/pubmed/34096874"
}


@Article{info:doi/10.2196/26867,
author="Zhong, Bu
and Liu, Qian",
title="Medical Insights from Posts About Irritable Bowel Syndrome by Adolescent Patients and Their Parents: Topic Modeling and Social Network Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="9",
volume="23",
number="6",
pages="e26867",
keywords="irritable bowel syndrome",
keywords="health care forum",
keywords="adolescent",
keywords="parents",
keywords="topic modeling",
keywords="social network analysis",
abstract="Background: Adolescents with irritable bowel syndrome (IBS) are increasingly seeking and sharing information about their symptoms in web-based health care forums. Their posts and those from their parents contain critical insights that can be used by patients, physicians, and caregivers to manage IBS symptoms. Objective: The aim of this study is to examine the posts from adolescent patients and their parents in a health forum, IBS Group, to better understand the key challenges, concerns, and issues of interest to young patients with IBS and their caregivers. Methods: Using topic modeling and social network analysis, in this study, we analyzed all the messages (over 750 topics and 3400 replies) posted on the IBS Group forum from 2010-2019 by adolescents with IBS aged 13-17 years and parents having children with IBS. We first detected 6 major topics in the posts by adolescent patients and parents on teenagers' IBS symptoms and the interaction between the topics. Social network analysis was then performed to gain insights into the nature of web-based interaction patterns among patients and caregivers. Results: Using the Latent Dirichlet Allocation algorithm and a latent Dirichlet allocation visualization tool, this study revealed 6 leading topics of concern in adolescents with IBS: school life, treatment or diet, symptoms, boys' ties to doctors, social or friend issues, and girls' ties to doctors. The top 6 topics in the parents' discussions were school life, girls' issues, boys' issues, diet choice, symptoms, and stress. The analyses show that the adolescent patients themselves are most concerned about the effect of IBS on their everyday activities and social lives. For parents having daughters with IBS, their top concerns were related to the girls' school performance and how much help they received at school. For their sons, the parents were more concerned about the pain and suffering that their sons had to endure. Both parents and adolescents gained social support from the web-based platform. Topic modeling shows that IBS affects teenagers the most in the areas of pain and school life. Furthermore, the issues raised by parents suggest that girls are bothered more by school performance over pain, whereas boys show exactly the opposite: pain is of greater concern than school performance. Conclusions: This study represents the first attempt to leverage both machine learning approaches and social network analysis to identify top IBS concerns from the perspectives of adolescent patients and caregivers in the same health forum. Young patients with IBS must face the challenges of social influences and anxiety associated with this health disorder in addition to physical pain and other symptoms. Boys and girls are affected differently by pain and school performance and view the IBS impacts differently from the parents. ",
doi="10.2196/26867",
url="https://www.jmir.org/2021/6/e26867",
url="http://www.ncbi.nlm.nih.gov/pubmed/34106078"
}


@Article{info:doi/10.2196/25741,
author="Madar, Ronni
and Ugon, Adrien
and Ivankovi{\'c}, Damir
and Tsopra, Rosy",
title="A Web Interface for Antibiotic Prescription Recommendations in Primary Care: User-Centered Design Approach",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e25741",
keywords="clinical decision support system",
keywords="visualization",
keywords="usability",
keywords="clinical practice guidelines",
keywords="antibiotic",
keywords="primary care",
abstract="Background: Antibiotic misuse is a serious public health problem worldwide. National health authorities release clinical practice guidelines (CPGs) to guide general practitioners (GPs) in their choice of antibiotics. However, despite the large-scale dissemination of CPGs, GPs continue to prescribe antibiotics that are not recommended as first-line treatments. This nonadherence to recommendations may be due to GPs misunderstanding the CPGs. A web interface displaying antibiotic prescription recommendations and their justifications could help to improve the comprehensibility and readability of CPGs, thereby increasing the adoption of recommendations regarding antibiotic treatment. Objective: This study aims to design and evaluate a web interface for antibiotic prescription displaying both the recommended antibiotics and their justifications in the form of antibiotic properties. Methods: A web interface was designed according to the same principles as e-commerce interfaces and was assessed by 117 GPs. These GPs were asked to answer 17 questions relating to the usefulness, user-friendliness, and comprehensibility and readability of the interface, and their satisfaction with it. Responses were recorded on a 4-point Likert scale (ranging from ``absolutely disagree'' to ``absolutely agree''). At the end of the evaluation, the GPs were allowed to provide optional, additional free comments. Results: The antibiotic prescription web interface consists of three main sections: a clinical summary section, a filter section, and a recommended antibiotics section. The majority of GPs appreciated the clinical summary (90/117, 76.9\%) and filter (98/117, 83.8\%) sections, whereas 48.7\% (57/117) of them reported difficulty reading some of the icons in the recommended antibiotics section. Overall, 82.9\% (97/117) of GPs found the display of drug properties useful, and 65.8\% (77/117) reported that the web interface improved their understanding of CPG recommendations. Conclusions: The web interface displaying antibiotic recommendations and their properties can help doctors understand the rationale underlying CPG recommendations regarding antibiotic treatment, but further improvements are required before its implementation into a clinical decision support system. ",
doi="10.2196/25741",
url="https://www.jmir.org/2021/6/e25741",
url="http://www.ncbi.nlm.nih.gov/pubmed/34114958"
}


@Article{info:doi/10.2196/26892,
author="Deng, Lizong
and Chen, Luming
and Yang, Tao
and Liu, Mi
and Li, Shicheng
and Jiang, Taijiao",
title="Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e26892",
keywords="knowledge graph",
keywords="knowledge granularity",
keywords="machine learning",
keywords="high-fidelity phenotyping",
keywords="phenotyping",
keywords="phenotype",
keywords="semantic",
abstract="Background: Phenotypes characterize the clinical manifestations of diseases and provide important information for diagnosis. Therefore, the construction of phenotype knowledge graphs for diseases is valuable to the development of artificial intelligence in medicine. However, phenotype knowledge graphs in current knowledge bases such as WikiData and DBpedia are coarse-grained knowledge graphs because they only consider the core concepts of phenotypes while neglecting the details (attributes) associated with these phenotypes. Objective: To characterize the details of disease phenotypes for clinical guidelines, we proposed a fine-grained semantic information model named PhenoSSU (semantic structured unit of phenotypes). Methods: PhenoSSU is an ``entity-attribute-value'' model by its very nature, and it aims to capture the full semantic information underlying phenotype descriptions with a series of attributes and values. A total of 193 clinical guidelines for infectious diseases from Wikipedia were selected as the study corpus, and 12 attributes from SNOMED-CT were introduced into the PhenoSSU model based on the co-occurrences of phenotype concepts and attribute values. The expressive power of the PhenoSSU model was evaluated by analyzing whether PhenoSSU instances could capture the full semantics underlying the descriptions of the corresponding phenotypes. To automatically construct fine-grained phenotype knowledge graphs, a hybrid strategy that first recognized phenotype concepts with the MetaMap tool and then predicted the attribute values of phenotypes with machine learning classifiers was developed. Results: Fine-grained phenotype knowledge graphs of 193 infectious diseases were manually constructed with the BRAT annotation tool. A total of 4020 PhenoSSU instances were annotated in these knowledge graphs, and 3757 of them (89.5\%) were found to be able to capture the full semantics underlying the descriptions of the corresponding phenotypes listed in clinical guidelines. By comparison, other information models, such as the clinical element model and the HL7 fast health care interoperability resource model, could only capture the full semantics underlying 48.4\% (2034/4020) and 21.8\% (914/4020) of the descriptions of phenotypes listed in clinical guidelines, respectively. The hybrid strategy achieved an F1-score of 0.732 for the subtask of phenotype concept recognition and an average weighted accuracy of 0.776 for the subtask of attribute value prediction. Conclusions: PhenoSSU is an effective information model for the precise representation of phenotype knowledge for clinical guidelines, and machine learning can be used to improve the efficiency of constructing PhenoSSU-based knowledge graphs. Our work will potentially shift the focus of medical knowledge engineering from a coarse-grained level to a more fine-grained level. ",
doi="10.2196/26892",
url="https://www.jmir.org/2021/6/e26892",
url="http://www.ncbi.nlm.nih.gov/pubmed/34128811"
}


@Article{info:doi/10.2196/26139,
author="Woodman, John Richard
and Bryant, Kimberley
and Sorich, J. Michael
and Pilotto, Alberto
and Mangoni, Aleksander Arduino",
title="Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e26139",
keywords="machine learning",
keywords="Multidimensional Prognostic Index",
keywords="mortality",
keywords="diagnostic accuracy",
keywords="XGBoost",
abstract="Background: The Multidimensional Prognostic Index (MPI) is an aggregate, comprehensive, geriatric assessment scoring system derived from eight domains that predict adverse outcomes, including 12-month mortality. However, the prediction accuracy of using the three MPI categories (mild, moderate, and severe risk) was relatively poor in a study of older hospitalized Australian patients. Prediction modeling using the component domains of the MPI together with additional clinical features and machine learning (ML) algorithms might improve prediction accuracy. Objective: This study aims to assess whether the accuracy of prediction for 12-month mortality using logistic regression with maximum likelihood estimation (LR-MLE) with the 3-category MPI together with age and gender (feature set 1) can be improved with the addition of 10 clinical features (sodium, hemoglobin, albumin, creatinine, urea, urea-to-creatinine ratio, estimated glomerular filtration rate, C-reactive protein, BMI, and anticholinergic risk score; feature set 2) and the replacement of the 3-category MPI in feature sets 1 and 2 with the eight separate MPI domains (feature sets 3 and 4, respectively), and to assess the prediction accuracy of the ML algorithms using the same feature sets. Methods: MPI and clinical features were collected from patients aged 65 years and above who were admitted to either the general medical or acute care of the elderly wards of a South Australian hospital between September 2015 and February 2017. The diagnostic accuracy of LR-MLE was assessed together with nine ML algorithms: decision trees, random forests, extreme gradient boosting (XGBoost), support-vector machines, na{\"i}ve Bayes, K-nearest neighbors, ridge regression, logistic regression without regularization, and neural networks. A 70:30 training set:test set split of the data and a grid search of hyper-parameters with 10-fold cross-validation---was used during model training. The area under the curve was used as the primary measure of accuracy. Results: A total of 737 patients (female: 370/737, 50.2\%; male: 367/737, 49.8\%) with a median age of 80 (IQR 72-86) years had complete MPI data recorded on admission and had completed the 12-month follow-up. The area under the receiver operating curve for LR-MLE was 0.632, 0.688, 0.738, and 0.757 for feature sets 1 to 4, respectively. The best overall accuracy for the nine ML algorithms was obtained using the XGBoost algorithm (0.635, 0.706, 0.756, and 0.757 for feature sets 1 to 4, respectively). Conclusions: The use of MPI domains with LR-MLE considerably improved the prediction accuracy compared with that obtained using the traditional 3-category MPI. The XGBoost ML algorithm slightly improved accuracy compared with LR-MLE, and adding clinical data improved accuracy. These results build on previous work on the MPI and suggest that implementing risk scores based on MPI domains and clinical data by using ML prediction models can support clinical decision-making with respect to risk stratification for the follow-up care of older hospitalized patients. ",
doi="10.2196/26139",
url="https://www.jmir.org/2021/6/e26139",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152274"
}


@Article{info:doi/10.2196/26946,
author="Lee, Hung-Yi Andy
and Aaronson, Emily
and Hibbert, A. Kathryn
and Flynn, H. Micah
and Rutkey, Hayley
and Mort, Elizabeth
and Sonis, D. Jonathan
and Safavi, C. Kyan",
title="Design and Implementation of a Real-time Monitoring Platform for Optimal Sepsis Care in an Emergency Department: Observational Cohort Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e26946",
keywords="electronic monitoring platform",
keywords="sepsis",
keywords="quality improvement",
abstract="Background: Sepsis is the leading cause of death in US hospitals. Compliance with bundled care, specifically serial lactates, blood cultures, and antibiotics, improves outcomes but is often delayed or missed altogether in a busy practice environment. Objective: This study aims to design, implement, and validate a novel monitoring and alerting platform that provides real-time feedback to frontline emergency department (ED) providers regarding adherence to bundled care. Methods: This single-center, prospective, observational study was conducted in three phases: the design and technical development phase to build an initial version of the platform; the pilot phase to test and refine the platform in the clinical setting; and the postpilot rollout phase to fully implement the study intervention. Results: During the design and technical development, study team members and stakeholders identified the criteria for patient inclusion, selected bundle measures from the Center for Medicare and Medicaid Sepsis Core Measure for alerting, and defined alert thresholds, message content, delivery mechanisms, and recipients. Additional refinements were made based on 70 provider survey results during the pilot phase, including removing alerts for vasopressor initiation and modifying text in the pages to facilitate patient identification. During the 48 days of the postpilot rollout phase, 15,770 ED encounters were tracked and 711 patient encounters were included in the active monitoring cohort. In total, 634 pages were sent at a rate of 0.98 per attending physician shift. Overall, 38.3\% (272/711) patients had at least one page. The missing bundle elements that triggered alerts included: antibiotics 41.6\% (136/327), repeat lactate 32.4\% (106/327), blood cultures 20.8\% (68/327), and initial lactate 5.2\% (17/327). Of the missing Sepsis Core Measures elements for which a page was sent, 38.2\% (125/327) were successfully completed on time. Conclusions: A real-time sepsis care monitoring and alerting platform was created for the ED environment. The high proportion of patients with at least one alert suggested the significant potential for such a platform to improve care, whereas the overall number of alerts per clinician suggested a low risk of alarm fatigue. The study intervention warrants a more rigorous evaluation to ensure that the added alerts lead to better outcomes for patients with sepsis. ",
doi="10.2196/26946",
url="https://www.jmir.org/2021/6/e26946/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185009"
}


@Article{info:doi/10.2196/26631,
author="Jungkunz, Martin
and K{\"o}ngeter, Anja
and Mehlis, Katja
and Winkler, C. Eva
and Schickhardt, Christoph",
title="Secondary Use of Clinical Data in Data-Gathering, Non-Interventional Research or Learning Activities: Definition, Types, and a Framework for Risk Assessment",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e26631",
keywords="secondary use",
keywords="risk assessment",
keywords="clinical data",
keywords="ethics",
keywords="risk factors",
keywords="risks",
keywords="privacy",
keywords="electronic health records",
keywords="research",
keywords="patient data",
abstract="Background: The secondary use of clinical data in data-gathering, non-interventional research or learning activities (SeConts) has great potential for scientific progress and health care improvement. At the same time, it poses relevant risks for the privacy and informational self-determination of patients whose data are used. Objective: Since the current literature lacks a tailored framework for risk assessment in SeConts as well as a clarification of the concept and practical scope of SeConts, we aim to fill this gap. Methods: In this study, we analyze each element of the concept of SeConts to provide a synthetic definition, investigate the practical relevance and scope of SeConts through a literature review, and operationalize the widespread definition of risk (as a harmful event of a certain magnitude that occurs with a certain probability) to conduct a tailored analysis of privacy risk factors typically implied in SeConts. Results: We offer a conceptual clarification and definition of SeConts and provide a list of types of research and learning activities that can be subsumed under the definition of SeConts. We also offer a proposal for the classification of SeConts types into the categories non-interventional (observational) clinical research, quality control and improvement, or public health research. In addition, we provide a list of risk factors that determine the probability or magnitude of harm implied in SeConts. The risk factors provide a framework for assessing the privacy-related risks for patients implied in SeConts. We illustrate the use of risk assessment by applying it to a concrete example. Conclusions: In the future, research ethics committees and data use and access committees will be able to rely on and apply the framework offered here when reviewing projects of secondary use of clinical data for learning and research purposes. ",
doi="10.2196/26631",
url="https://www.jmir.org/2021/6/e26631",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100760"
}


@Article{info:doi/10.2196/29395,
author="Grande, David
and Luna Marti, Xochitl
and Merchant, M. Raina
and Asch, A. David
and Dolan, Abby
and Sharma, Meghana
and Cannuscio, C. Carolyn",
title="Consumer Views on Health Applications of Consumer Digital Data and Health Privacy Among US Adults: Qualitative Interview Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="9",
volume="23",
number="6",
pages="e29395",
keywords="health privacy",
keywords="digital health privacy",
keywords="privacy law",
keywords="health law",
keywords="digital epidemiology",
abstract="Background: In 2020, the number of internet users surpassed 4.6 billion. Individuals who create and share digital data can leave a trail of information about their habits and preferences that collectively generate a digital footprint. Studies have shown that digital footprints can reveal important information regarding an individual's health status, ranging from diet and exercise to depression. Uses of digital applications have accelerated during the COVID-19 pandemic where public health organizations have utilized technology to reduce the burden of transmission, ultimately leading to policy discussions about digital health privacy. Though US consumers report feeling concerned about the way their personal data is used, they continue to use digital technologies. Objective: This study aimed to understand the extent to which consumers recognize possible health applications of their digital data and identify their most salient concerns around digital health privacy. Methods: We conducted semistructured interviews with a diverse national sample of US adults from November 2018 to January 2019. Participants were recruited from the Ipsos KnowledgePanel, a nationally representative panel. Participants were asked to reflect on their own use of digital technology, rate various sources of digital information, and consider several hypothetical scenarios with varying sources and health-related applications of personal digital information. Results: The final cohort included a diverse national sample of 45 US consumers. Participants were generally unaware what consumer digital data might reveal about their health. They also revealed limited knowledge of current data collection and aggregation practices. When responding to specific scenarios with health-related applications of data, they had difficulty weighing the benefits and harms but expressed a desire for privacy protection. They saw benefits in using digital data to improve health, but wanted limits to health programs' use of consumer digital data. Conclusions: Current privacy restrictions on health-related data are premised on the notion that these data are derived only from medical encounters. Given that an increasing amount of health-related data is derived from digital footprints in consumer settings, our findings suggest the need for greater transparency of data collection and uses, and broader health privacy protections. ",
doi="10.2196/29395",
url="https://www.jmir.org/2021/6/e29395",
url="http://www.ncbi.nlm.nih.gov/pubmed/34106074"
}


@Article{info:doi/10.2196/26368,
author="Lee, Jinhee
and Kwan, Yunna
and Lee, Young Jun
and Shin, Il Jae
and Lee, Hwa Keum
and Hong, Hwi Sung
and Han, Joo Young
and Kronbichler, Andreas
and Smith, Lee
and Koyanagi, Ai
and Jacob, Louis
and Choi, SungWon
and Ghayda, Abou Ramy
and Park, Myung-Bae",
title="Public Interest in Immunity and the Justification for Intervention in the Early Stages of the COVID-19 Pandemic: Analysis of Google Trends Data",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="18",
volume="23",
number="6",
pages="e26368",
keywords="COVID-19",
keywords="social big data",
keywords="infodemiology",
keywords="infoveillance",
keywords="social listening",
keywords="immune",
keywords="vitamin",
keywords="big data",
keywords="public interest",
keywords="intervention",
keywords="immune system",
keywords="immunity",
keywords="trends",
keywords="Google Trends",
keywords="internet",
keywords="digital health",
keywords="web-based health information",
keywords="correlation",
keywords="social media",
keywords="infectious disease",
abstract="Background: The use of social big data is an important emerging concern in public health. Internet search volumes are useful data that can sensitively detect trends of the public's attention during a pandemic outbreak situation. Objective: Our study aimed to analyze the public's interest in COVID-19 proliferation, identify the correlation between the proliferation of COVID-19 and interest in immunity and products that have been reported to confer an enhancement of immunity, and suggest measures for interventions that should be implemented from a health and medical point of view. Methods: To assess the level of public interest in infectious diseases during the initial days of the COVID-19 outbreak, we extracted Google search data from January 20, 2020, onward and compared them to data from March 15, 2020, which was approximately 2 months after the COVID-19 outbreak began. In order to determine whether the public became interested in the immune system, we selected coronavirus, immune, and vitamin as our final search terms. Results: The increase in the cumulative number of confirmed COVID-19 cases that occurred after January 20, 2020, had a strong positive correlation with the search volumes for the terms coronavirus (R=0.786; P<.001), immune (R=0.745; P<.001), and vitamin (R=0.778; P<.001), and the correlations between variables were all mutually statistically significant. Moreover, these correlations were confirmed on a country basis when we restricted our analyses to the United States, the United Kingdom, Italy, and Korea. Our findings revealed that increases in search volumes for the terms coronavirus and immune preceded the actual occurrences of confirmed cases. Conclusions: Our study shows that during the initial phase of the COVID-19 crisis, the public's desire and actions of strengthening their own immune systems were enhanced. Further, in the early stage of a pandemic, social media platforms have a high potential for informing the public about potentially helpful measures to prevent the spread of an infectious disease and provide relevant information about immunity, thereby increasing the public's knowledge. ",
doi="10.2196/26368",
url="https://www.jmir.org/2021/6/e26368",
url="http://www.ncbi.nlm.nih.gov/pubmed/34038375"
}


@Article{info:doi/10.2196/26421,
author="Andrade, Q. Andre
and Beleigoli, Alline
and Diniz, Fatima Maria De
and Ribeiro, Luiz Antonio",
title="Influence of Baseline User Characteristics and Early Use Patterns (24-Hour) on Long-Term Adherence and Effectiveness of a Web-Based Weight Loss Randomized Controlled Trial: Latent Profile Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e26421",
keywords="obesity",
keywords="overweight",
keywords="web platform",
keywords="digital health",
keywords="engagement",
keywords="latent profile analysis",
keywords="online interventions",
keywords="use data",
keywords="weight loss",
keywords="weight loss platform",
abstract="Background: Low adherence to real-world online weight loss interventions reduces long-term efficacy. Baseline characteristics and use patterns are determinants of long-term adherence, but we lack cohesive models to guide how to adapt interventions to users' needs. We also lack information whether very early use patterns (24 hours) help describe users and predict interventions they would benefit from. Objective: We aim to understand the impact of users' baseline characteristics and early (initial 24 hours) use patterns of a web platform for weight loss on user adherence and weight loss in the long term (24 weeks). Methods: We analyzed data from the POEmaS randomized controlled trial, a study that compared the effectiveness of a weight loss platform with or without coaching and a control approach. Data included baseline behavior and use logs from the initial 24 hours after platform access. Latent profile analysis (LPA) was used to identify classes, and Kruskal-Wallis was used to test whether class membership was associated with long-term (24 weeks) adherence and weight loss. Results: Among 828 participants assigned to intervention arms, 3 classes were identified through LPA: class 1 (better baseline health habits and high 24-hour platform use); class 2 (better than average health habits, but low 24-hour platform use); class 3 (worse baseline health habits and low 24-hour platform use). Class membership was associated with long-term adherence (P<.001), and class 3 members had the lowest adherence. Weight loss was not associated with class membership (P=.49), regardless of the intervention arm (platform only or platform + coach). However, class 2 users assigned to platform + coach lost more weight than those assigned to platform only (P=.02). Conclusions: Baseline questionnaires and use data from the first 24 hours after log-in allowed distinguishing classes, which were associated with long-term adherence. This suggests that this classification might be a useful guide to improve adherence and assign interventions to individual users. Trial Registration: ClinicalTrials.gov NCT03435445; https://clinicaltrials.gov/ct2/show/NCT03435445 International Registered Report Identifier (IRRID): RR2-10.1186/s12889-018-5882-y ",
doi="10.2196/26421",
url="https://www.jmir.org/2021/6/e26421",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081012"
}


@Article{info:doi/10.2196/26749,
author="Goldberg, B. Simon
and Bolt, M. Daniel
and Davidson, J. Richard",
title="Data Missing Not at Random in Mobile Health Research: Assessment of the Problem and a Case for Sensitivity Analyses",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e26749",
keywords="missing data",
keywords="randomized controlled trial",
keywords="differential attrition",
keywords="sensitivity analysis",
keywords="statistical methodology",
keywords="mobile phone",
abstract="Background: Missing data are common in mobile health (mHealth) research. There has been little systematic investigation of how missingness is handled statistically in mHealth randomized controlled trials (RCTs). Although some missing data patterns (ie, missing at random [MAR]) may be adequately addressed using modern missing data methods such as multiple imputation and maximum likelihood techniques, these methods do not address bias when data are missing not at random (MNAR). It is typically not possible to determine whether the missing data are MAR. However, higher attrition in active (ie, intervention) versus passive (ie, waitlist or no treatment) conditions in mHealth RCTs raise a strong likelihood of MNAR, such as if active participants who benefit less from the intervention are more likely to drop out. Objective: This study aims to systematically evaluate differential attrition and methods used for handling missingness in a sample of mHealth RCTs comparing active and passive control conditions. We also aim to illustrate a modern model-based sensitivity analysis and a simpler fixed-value replacement approach that can be used to evaluate the influence of MNAR. Methods: We reanalyzed attrition rates and predictors of differential attrition in a sample of 36 mHealth RCTs drawn from a recent meta-analysis of smartphone-based mental health interventions. We systematically evaluated the design features related to missingness and its handling. Data from a recent mHealth RCT were used to illustrate 2 sensitivity analysis approaches (pattern-mixture model and fixed-value replacement approach). Results: Attrition in active conditions was, on average, roughly twice that of passive controls. Differential attrition was higher in larger studies and was associated with the use of MAR-based multiple imputation or maximum likelihood methods. Half of the studies (18/36, 50\%) used these modern missing data techniques. None of the 36 mHealth RCTs reviewed conducted a sensitivity analysis to evaluate the possible consequences of data MNAR. A pattern-mixture model and fixed-value replacement sensitivity analysis approaches were introduced. Results from a recent mHealth RCT were shown to be robust to missing data, reflecting worse outcomes in missing versus nonmissing scores in some but not all scenarios. A review of such scenarios helps to qualify the observations of significant treatment effects. Conclusions: MNAR data because of differential attrition are likely in mHealth RCTs using passive controls. Sensitivity analyses are recommended to allow researchers to assess the potential impact of MNAR on trial results. ",
doi="10.2196/26749",
url="https://www.jmir.org/2021/6/e26749",
url="http://www.ncbi.nlm.nih.gov/pubmed/34128810"
}


@Article{info:doi/10.2196/26963,
author="Seals, Ayanna
and Olaosebikan, Monsurat
and Otiono, Jennifer
and Shaer, Orit
and Nov, Oded",
title="Effects of Self-focused Augmented Reality on Health Perceptions During the COVID-19 Pandemic: A Web-Based Between-Subject Experiment",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="29",
volume="23",
number="6",
pages="e26963",
keywords="COVID-19",
keywords="health behavior",
keywords="augmented reality",
keywords="self-focused attention",
keywords="vicarious reinforcement",
keywords="human-computer interactions",
keywords="hand hygiene",
keywords="perception",
abstract="Background: Self-focused augmented reality (AR) technologies are growing in popularity and present an opportunity to address health communication and behavior change challenges. Objective: We aimed to examine the impact of self-focused AR and vicarious reinforcement on psychological predictors of behavior change during the COVID-19 pandemic. In addition, our study included measures of fear and message minimization to assess potential adverse reactions to the design interventions. Methods: A between-subjects web-based experiment was conducted to compare the health perceptions of participants in self-focused AR and vicarious reinforcement design conditions to those in a control condition. Participants were randomly assigned to the control group or to an intervention condition (ie, self-focused AR, reinforcement, self-focus AR {\texttimes} reinforcement, and avatar). Results: A total of 335 participants were included in the analysis. We found that participants who experienced self-focused AR and vicarious reinforcement scored higher in perceived threat severity (P=.03) and susceptibility (P=.01) when compared to the control. A significant indirect effect of self-focused AR and vicarious reinforcement on intention was found with perceived threat severity as a mediator (b=.06, 95\% CI 0.02-0.12, SE .02). Self-focused AR and vicarious reinforcement did not result in higher levels of fear (P=.32) or message minimization (P=.42) when compared to the control. Conclusions: Augmenting one's reflection with vicarious reinforcement may be an effective strategy for health communication designers. While our study's results did not show adverse effects in regard to fear and message minimization, utilization of self-focused AR as a health communication strategy should be done with care due to the possible adverse effects of heightened levels of fear. ",
doi="10.2196/26963",
url="https://www.jmir.org/2021/6/e26963",
url="http://www.ncbi.nlm.nih.gov/pubmed/33878017"
}


@Article{info:doi/10.2196/25868,
author="Hermes-DeSantis, R. Evelyn
and Hunter, T. Robert
and Welch, Julie
and Bhavsar, Roma
and Boulos, Daniel
and Noue, Marie-Ange",
title="Preferences for Accessing Medical Information in the Digital Age: Health Care Professional Survey",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="19",
volume="23",
number="6",
pages="e25868",
keywords="information-seeking behavior",
keywords="access to information",
keywords="internet",
keywords="physicians",
keywords="nurses",
keywords="pharmacists",
keywords="medical literature",
keywords="databases",
keywords="search tools",
keywords="medical information",
abstract="Background: Health care professionals (HCPs) routinely have questions concerning the medications they are recommending. There are numerous resources available; however, each has its own advantages and disadvantages. Objective: The purpose of this survey was to gain knowledge of the preferred methods and sources HCPs use to obtain information concerning medications. Methods: A total of 511 HCPs (202 physicians, 105 pharmacists, 100 advance practice nurses, 53 registered nurses, and 51 physician assistants) were surveyed through a third-party market research firm. All participants were practicing in the United States. Individuals working for a pharmaceutical company were excluded. The survey collected demographics, frequency of searching medical information, types of questions searched, sources of medical information, and rationale for preferred and nonpreferred sources of medical information. Use of medical information resources were rated on a 5-point ordinal scale. Data were analyzed with descriptive statistics. Results: Of the 511 respondents, 88.5\% (452/511) searched for medical information either daily or several times per week. The most common questions involved dosing and administration, drug-drug interactions, adverse events and safety, clinical practice guidelines, and disease state information. The main rationale for using specific medical websites or apps and general online search engines frequently or very frequently was ease of use (medical websites or apps: 269/356, 75.6\%; general online search engines: 248/284, 87.3\%). Accuracy was the main rationale for frequent or very frequent use of medical literature search databases (163/245, 66.5\%), prescribing labels or information (122/213, 57.3\%), and professional literature (120/195, 61.5\%). The main reason for rarely or never using specific medical websites or apps and medical literature search databases was unfamiliarity (medical websites or apps: 16/48, 33\%; medical literature search databases: 35/78, 45\%); for general online search engines, inaccuracy (34/54, 63\%); and for prescribing labels or information and professional literature, excessive time (prescribing labels or information : 54/102, 52.9\%; professional literature: 66/106, 62.3\%). The pharmaceutical company was sometimes used as a resource for medical information. When the medical information department was used, the call center and the website were considered thorough and complete (call center: 14/25, 56\%; website: 33/55, 60\%). However, the rationale for not using the call center was the time required (199/346, 57.5\%) and the website being unfamiliar (129/267, 48.3\%). Conclusions: The driving forces in the selection of resources are accuracy and ease of use. There is an opportunity to increase awareness of all the appropriate resources for HCPs which may aid in their daily clinical decisions. Specifically, pharmaceutical company medical information departments can help fulfill this need by addressing two major challenges with use of the pharmaceutical company: lack of awareness of medical information services and the speed at which responses are disseminated. Overall, there is lack of understanding or appreciation of the range of pathways to obtain published information and knowledge from pharmaceutical company medical information services. Among the many challenges resource champions will face are the ability to effectively make resources and their platforms accessible, known, and useful to the scientific community. ",
doi="10.2196/25868",
url="https://www.jmir.org/2021/6/e25868/",
url="http://www.ncbi.nlm.nih.gov/pubmed/36260374"
}


@Article{info:doi/10.2196/27860,
author="Hodges, William Paul
and Hall, Leanne
and Setchell, Jenny
and French, Simon
and Kasza, Jessica
and Bennell, Kim
and Hunter, David
and Vicenzino, Bill
and Crofts, Samuel
and Dickson, Chris
and Ferreira, Manuela",
title="Effect of a Consumer-Focused Website for Low Back Pain on Health Literacy, Treatment Choices, and Clinical Outcomes: Randomized Controlled Trial",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e27860",
keywords="low back pain",
keywords="randomized controlled trial",
keywords="internet resources",
keywords="health literacy",
abstract="Background: The internet is used for information related to health conditions, including low back pain (LBP), but most LBP websites provide inaccurate information. Few studies have investigated the effectiveness of internet resources in changing health literacy or treatment choices. Objective: This study aims to evaluate the effectiveness of the MyBackPain website compared with unguided internet use on health literacy, choice of treatments, and clinical outcomes in people with LBP. Methods: This was a pragmatic, web-based, participant- and assessor-blinded randomized trial of individuals with LBP stratified by duration. Participants were randomly allocated to have access to the evidence-based MyBackPain website, which was designed with input from consumers and expert consensus or unguided internet use. The coprimary outcomes were two dimensions of the Health Literacy Questionnaire (dimension 2: ``having sufficient information to manage my health;'' dimension 3: ``actively managing my health;'' converted to scores 1-100) at 3 months. Secondary outcomes included additional Health Literacy Questionnaire dimensions, quality of treatment choices, and clinical outcomes. Results: A total of 453 participants were recruited, and 321 (70.9\%) completed the primary outcomes. Access to MyBackPain was not superior to unguided internet use on primary outcomes (dimension 2: mean difference ?0.87 units, 95\% CI ?3.56 to 1.82; dimension 3: mean difference ?0.41 units, 95\% CI ?2.78 to 1.96). Between-group differences in other secondary outcomes had inconsistent directions and were unlikely to be clinically important, although a small improvement of unclear importance in the quality of stated treatment choices at 1 month was found (mean difference 0.93 units, 95\% CI 0.03 to 1.84). Conclusions: MyBackPain was not superior to unguided internet use for health literacy, but data suggest some short-term improvement in treatment choices. Future research should investigate if greater interactivity and engagement with the website may enhance its impact. Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12617001292369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372926 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2018-027516 ",
doi="10.2196/27860",
url="https://www.jmir.org/2021/6/e27860",
url="http://www.ncbi.nlm.nih.gov/pubmed/34128822"
}


@Article{info:doi/10.2196/17095,
author="Dong, Shengjie
and Millar, Ross
and Shi, Chenshu
and Dong, Minye
and Xiao, Yuyin
and Shen, Jie
and Li, Guohong",
title="Rating Hospital Performance in China: Review of Publicly Available Measures and Development of a Ranking System",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="17",
volume="23",
number="6",
pages="e17095",
keywords="hospital ranking",
keywords="performance measurement",
keywords="health care quality",
keywords="China health care reform",
abstract="Background: In China, significant emphasis and investment in health care reform since 2009 has brought with it increasing scrutiny of its public hospitals. Calls for greater accountability in the quality of hospital care have led to increasing attention toward performance measurement and the development of hospital ratings. Despite such interest, there has yet to be a comprehensive analysis of what performance information is publicly available to understand the performance of hospitals in China. Objective: This study aims to review the publicly available performance information about hospitals in China to assess options for ranking hospital performance. Methods: A review was undertaken to identify performance measures based on publicly available data. Following several rounds of expert consultation regarding the utility of these measures, we clustered the available options into three key areas: research and development, academic reputation, and quality and safety. Following the identification and clustering of the available performance measures, we set out to translate these into a practical performance ranking system to assess variation in hospital performance. Results: A new hospital ranking system termed the China Hospital Development Index (CHDI) is thus presented. Furthermore, we used CHDI for ranking well-known tertiary hospitals in China. Conclusions: Despite notable limitations, our assessment of available measures and the development of a new ranking system break new ground in understanding hospital performance in China. In doing so, CHDI has the potential to contribute to wider discussions and debates about assessing hospital performance across global health care systems. ",
doi="10.2196/17095",
url="https://www.jmir.org/2021/6/e17095",
url="http://www.ncbi.nlm.nih.gov/pubmed/34137724"
}


@Article{info:doi/10.2196/22151,
author="Rayward, T. Anna
and Vandelanotte, Corneel
and Van Itallie, Anetta
and Duncan, J. Mitch",
title="The Association Between Logging Steps Using a Website, App, or Fitbit and Engaging With the 10,000 Steps Physical Activity Program: Observational Study        ",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="18",
volume="23",
number="6",
pages="e22151",
keywords="physical activity intervention",
keywords="activity trackers",
keywords="engagement",
keywords="Fitbit",
keywords="pedometer",
keywords="eHealth",
keywords="mobile phone",
abstract="Background: Engagement is positively associated with the effectiveness of digital health interventions. It is unclear whether tracking devices that automatically synchronize data (eg, Fitbit) produce different engagement levels compared with manually entering data. Objective: This study examines how different step logging methods in the freely available 10,000 Steps physical activity program differ according to age and gender and are associated with program engagement. Methods: A subsample of users (n=22,142) of the free 10,000 Steps physical activity program were classified into one of the following user groups based on the step-logging method: Website Only (14,617/22,142, 66.01\%), App Only (2100/22,142, 9.48\%), Fitbit Only (1705/22,142, 7.7\%), Web and App (2057/22,142, 9.29\%), and Fitbit Combination (combination of web, app, and Fitbit; 1663/22,142, 7.51\%). Generalized linear regression and binary logistic regression were used to examine differences between user groups' engagement and participation parameters. The time to nonusage attrition was assessed using Cox proportional hazards regression. Results: App Only users were significantly younger and Fitbit user groups had higher proportions of women compared with other groups. The following outcomes were significant and relative to the Website Only group. The App Only group had fewer website sessions (odds ratio [OR] ?6.9, 95\% CI ?7.6 to ?6.2), whereas the Fitbit Only (OR 10.6, 95\% CI 8.8-12.3), Web and App (OR 1.5, 95\% CI 0.4-2.6), and Fitbit Combination (OR 8.0; 95\% CI 6.2-9.7) groups had more sessions. The App Only (OR ?0.7, 95\% CI ?0.9 to ?0.4) and Fitbit Only (OR ?0.5, 95\% CI ?0.7 to ?0.2) groups spent fewer minutes on the website per session, whereas the Fitbit Combination group (OR 0.2, 95\% CI 0.0-0.5) spent more minutes. All groups, except the Fitbit Combination group, viewed fewer website pages per session. The mean daily step count was lower for the App Only (OR ?201.9, 95\% CI ?387.7 to ?116.0) and Fitbit Only (OR ?492.9, 95\% CI ?679.9 to ?305.8) groups but higher for the Web and App group (OR 258.0, 95\% CI 76.9-439.2). The Fitbit Only (OR 5.0, 95\% CI 3.4-6.6), Web and App (OR 7.2, 95\% CI 5.9-8.6), and Fitbit Combination (OR 15.6, 95\% CI 13.7-17.5) groups logged a greater number of step entries. The App Only group was less likely (OR 0.65, 95\% CI 0.46-0.94) and other groups were more likely to participate in Challenges. The mean time to nonusage attrition was 35 (SD 26) days and was lower than average in the Website Only and App Only groups and higher than average in the Web and App and Fitbit Combination groups. Conclusions: Using a Fitbit in combination with the 10,000 Steps app or website enhanced engagement with a real-world physical activity program. Integrating tracking devices that synchronize data automatically into real-world physical activity interventions is one strategy for improving engagement. ",
doi="10.2196/22151",
url="https://www.jmir.org/2021/6/e22151",
url="http://www.ncbi.nlm.nih.gov/pubmed/34142966"
}


@Article{info:doi/10.2196/25591,
author="Sardana, Mayank
and Lin, Honghuang
and Zhang, Yuankai
and Liu, Chunyu
and Trinquart, Ludovic
and Benjamin, J. Emelia
and Manders, S. Emily
and Fusco, Kelsey
and Kornej, Jelena
and Hammond, M. Michael
and Spartano, Nicole
and Pathiravasan, H. Chathurangi
and Kheterpal, Vik
and Nowak, Christopher
and Borrelli, Belinda
and Murabito, M. Joanne
and McManus, D. David",
title="Association of Habitual Physical Activity With Home Blood Pressure in the Electronic Framingham Heart Study (eFHS): Cross-sectional Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e25591",
keywords="hypertension",
keywords="primary prevention",
keywords="eCohort",
keywords="physical activity",
keywords="smartwatch",
keywords="Apple Watch",
keywords="home blood pressure",
abstract="Background: When studied in community-based samples, the association of physical activity with blood pressure (BP) remains controversial and is perhaps dependent on the intensity of physical activity. Prior studies have not explored the association of smartwatch-measured physical activity with home BP. Objective: We aimed to study the association of habitual physical activity with home BP. Methods: Consenting electronic Framingham Heart Study (eFHS) participants were provided with a study smartwatch (Apple Watch Series 0) and Bluetooth-enabled home BP cuff. Participants were instructed to wear the watch daily and transmit BP values weekly. We measured habitual physical activity as the average daily step count determined by the smartwatch. We estimated the cross-sectional association between physical activity and average home BP using linear mixed effects models adjusting for age, sex, wear time, antihypertensive drug use, and familial structure. Results: We studied 660 eFHS participants (mean age 53 years, SD 9 years; 387 [58.6\%] women; 602 [91.2\%] White) who wore the smartwatch 5 or more hours per day for 30 or more days and transmitted three or more BP readings. The mean daily step count was 7595 (SD 2718). The mean home systolic and diastolic BP (mmHg) were 122 (SD 12) and 76 (SD 8). Every 1000 increase in the step count was associated with a 0.49 mmHg lower home systolic BP (P=.004) and 0.36 mmHg lower home diastolic BP (P=.003). The association, however, was attenuated and became statistically nonsignificant with further adjustment for BMI. Conclusions: In this community-based sample of adults, higher daily habitual physical activity measured by a smartwatch was associated with a moderate, but statistically significant, reduction in home BP. Differences in BMI among study participants accounted for the majority of the observed association. ",
doi="10.2196/25591",
url="https://www.jmir.org/2021/6/e25591/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34185019"
}


@Article{info:doi/10.2196/25929,
author="Ji, Mengting
and Genchev, Z. Georgi
and Huang, Hengye
and Xu, Ting
and Lu, Hui
and Yu, Guangjun",
title="Evaluation Framework for Successful Artificial Intelligence--Enabled Clinical Decision Support Systems: Mixed Methods Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="2",
volume="23",
number="6",
pages="e25929",
keywords="artificial intelligence",
keywords="AI",
keywords="clinical decision support systems",
keywords="evaluation framework",
abstract="Background: Clinical decision support systems are designed to utilize medical data, knowledge, and analysis engines and to generate patient-specific assessments or recommendations to health professionals in order to assist decision making. Artificial intelligence--enabled clinical decision support systems aid the decision-making process through an intelligent component. Well-defined evaluation methods are essential to ensure the seamless integration and contribution of these systems to clinical practice. Objective: The purpose of this study was to develop and validate a measurement instrument and test the interrelationships of evaluation variables for an artificial intelligence--enabled clinical decision support system evaluation framework. Methods: An artificial intelligence--enabled clinical decision support system evaluation framework consisting of 6 variables was developed. A Delphi process was conducted to develop the measurement instrument items. Cognitive interviews and pretesting were performed to refine the questions. Web-based survey response data were analyzed to remove irrelevant questions from the measurement instrument, to test dimensional structure, and to assess reliability and validity. The interrelationships of relevant variables were tested and verified using path analysis, and a 28-item measurement instrument was developed. Measurement instrument survey responses were collected from 156 respondents. Results: The Cronbach $\alpha$ of the measurement instrument was 0.963, and its content validity was 0.943. Values of average variance extracted ranged from 0.582 to 0.756, and values of the heterotrait-monotrait ratio ranged from 0.376 to 0.896. The final model had a good fit ($\chi$262=36.984; P=.08; comparative fit index 0.991; goodness-of-fit index 0.957; root mean square error of approximation 0.052; standardized root mean square residual 0.028). Variables in the final model accounted for 89\% of the variance in the user acceptance dimension. Conclusions: User acceptance is the central dimension of artificial intelligence--enabled clinical decision support system success. Acceptance was directly influenced by perceived ease of use, information quality, service quality, and perceived benefit. Acceptance was also indirectly influenced by system quality and information quality through perceived ease of use. User acceptance and perceived benefit were interrelated. ",
doi="10.2196/25929",
url="https://www.jmir.org/2021/6/e25929",
url="http://www.ncbi.nlm.nih.gov/pubmed/34076581"
}


@Article{info:doi/10.2196/26022,
author="Lehmann, Jens
and Buhl, Petra
and Giesinger, M. Johannes
and Wintner, M. Lisa
and Sztankay, Monika
and Neppl, Lucia
and Willenbacher, Wolfgang
and Weger, Roman
and Weyrer, Walpurga
and Rumpold, Gerhard
and Holzner, Bernhard",
title="Using the Computer-based Health Evaluation System (CHES) to Support Self-management of Symptoms and Functional Health: Evaluation of Hematological Patient Use of a Web-Based Patient Portal",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e26022",
keywords="quality of life",
keywords="monitoring",
keywords="patient portals",
keywords="multiple myeloma",
keywords="chronic lymphocytic leukemia",
keywords="patient-reported outcome measures",
keywords="eHealth",
keywords="mHealth",
abstract="Background: Patient portals offer the possibility to assess patient-reported outcome measures (PROMs) remotely, and first evidence has demonstrated their potential benefits. Objective: In this study, we evaluated patient use of a web-based patient portal that provides patient information and allows online completion of PROMs. A particular focus was on patient motivation for (not) using the portal. The portal was developed to supplement routine monitoring at the Department of Internal Medicine V in Innsbruck. Methods: We included patients with multiple myeloma and chronic lymphocytic leukemia who were already participating in routine monitoring at the hospital for use of the patient portal. Patients were introduced to the portal and asked to complete questionnaires prior to their next hospital visits. We used system access logs and 3 consecutive semistructured interviews to analyze patient use and evaluation of the portal. Results: Between July 2017 and August 2020, we approached 122 patients for participation in the study, of whom 83.6\% (102/122) consented to use the patient portal. Patients were on average 60 (SD 10.4) years old. Of patients providing data at all study time points, 37\% (26/71) consistently used the portal prior to their hospital visits. The main reason for not completing PROMs was forgetting to do so in between visits (25/84, 29\%). During an average session, patients viewed 5.3 different pages and spent 9.4 minutes logged on to the portal. Feedback from interviews was largely positive with no patients reporting difficulties navigating the survey and 50\% of patients valuing the self-management tools provided in the portal. Regarding the portal content, patients were interested in reviewing their own results and reported high satisfaction with the dynamic self-management advice, also reflected in the high number of clicks on those pages. Conclusions: Patient portals can contribute to patient empowerment by offering sought-after information and self-management advice. In our study, the majority of our patients were open to using the portal. The low number of technical complaints and average time spent in the portal demonstrate the feasibility of our patient portal. While initial interest was high, long-term use was considerably lower and identified as the main area for improvement. In a next step, we will improve several aspects of the patient portal (eg, including a reminder to visit the portal before the next appointment and closer PROM symptom monitoring via an onconurse). ",
doi="10.2196/26022",
url="https://www.jmir.org/2021/6/e26022",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100765"
}


@Article{info:doi/10.2196/28856,
author="Ullah, Zahid
and Saleem, Farrukh
and Jamjoom, Mona
and Fakieh, Bahjat",
title="Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e28856",
keywords="machine learning",
keywords="prediction model",
keywords="health care",
keywords="cesarean",
keywords="delivery",
keywords="decision making",
abstract="Background: The use of artificial intelligence has revolutionized every area of life such as business and trade, social and electronic media, education and learning, manufacturing industries, medicine and sciences, and every other sector. The new reforms and advanced technologies of artificial intelligence have enabled data analysts to transmute raw data generated by these sectors into meaningful insights for an effective decision-making process. Health care is one of the integral sectors where a large amount of data is generated daily, and making effective decisions based on these data is therefore a challenge. In this study, cases related to childbirth either by the traditional method of vaginal delivery or cesarean delivery were investigated. Cesarean delivery is performed to save both the mother and the fetus when complications related to vaginal birth arise. Objective: The aim of this study was to develop reliable prediction models for a maternity care decision support system to predict the mode of delivery before childbirth. Methods: This study was conducted in 2 parts for identifying the mode of childbirth: first, the existing data set was enriched and second, previous medical records about the mode of delivery were investigated using machine learning algorithms and by extracting meaningful insights from unseen cases. Several prediction models were trained to achieve this objective, such as decision tree, random forest, AdaBoostM1, bagging, and k-nearest neighbor, based on original and enriched data sets. Results: The prediction models based on enriched data performed well in terms of accuracy, sensitivity, specificity, F-measure, and receiver operating characteristic curves in the outcomes. Specifically, the accuracy of k-nearest neighbor was 84.38\%, that of bagging was 83.75\%, that of random forest was 83.13\%, that of decision tree was 81.25\%, and that of AdaBoostM1 was 80.63\%. Enrichment of the data set had a good impact on improving the accuracy of the prediction process, which supports maternity care practitioners in making decisions in critical cases. Conclusions: Our study shows that enriching the data set improves the accuracy of the prediction process, thereby supporting maternity care practitioners in making informed decisions in critical cases. The enriched data set used in this study yields good results, but this data set can become even better if the records are increased with real clinical data. ",
doi="10.2196/28856",
url="https://www.jmir.org/2021/6/e28856",
url="http://www.ncbi.nlm.nih.gov/pubmed/34085938"
}


@Article{info:doi/10.2196/17551,
author="Bayen, Eleonore
and Nickels, Shirley
and Xiong, Glen
and Jacquemot, Julien
and Subramaniam, Raghav
and Agrawal, Pulkit
and Hemraj, Raheema
and Bayen, Alexandre
and Miller, L. Bruce
and Netscher, George",
title="Reduction of Time on the Ground Related to Real-Time Video Detection of Falls in Memory Care Facilities: Observational Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="17",
volume="23",
number="6",
pages="e17551",
keywords="artificial intelligence",
keywords="video monitoring",
keywords="real-time video detection",
keywords="fall",
keywords="time on the ground",
keywords="Alzheimer disease",
keywords="dementia",
keywords="memory care facilities",
abstract="Background: Lying on the floor for a long period of time has been described as a critical determinant of prognosis following a fall. In addition to fall-related injuries due to the trauma itself, prolonged immobilization on the floor results in a wide range of comorbidities and may double the risk of death in elderly. Thus, reducing the length of Time On the Ground (TOG) in fallers seems crucial in vulnerable individuals with cognitive disorders who cannot get up independently. Objective: This study aimed to examine the effect of a new technology called SafelyYou Guardian (SYG) on early post-fall care including reduction of Time Until staff Assistance (TUA) and TOG. Methods: SYG uses continuous video monitoring, artificial intelligence, secure networks, and customized computer applications to detect and notify caregivers about falls in real time while providing immediate access to video footage of falls. The present observational study was conducted in 6 California memory care facilities where SYG was installed in bedrooms of consenting residents and families. Fall events were video recorded over 10 months. During the baseline installation period (November 2017 to December 2017), SYG video captures of falls were not provided on a regular basis to facility staff review. During a second period (January 2018 to April 2018), video captures were delivered to facility staff on a regular weekly basis. During the third period (May 2018 to August 2018), real-time notification (RTN) of any fall was provided to facility staff. Two digital markers (TUA, TOG) were automatically measured and compared between the baseline period (first 2 months) and the RTN period (last 4 months). The total number of falls including those happening outside of the bedroom (such as common areas and bathrooms) was separately reported by facility staff. Results: A total of 436 falls were recorded in 66 participants suffering from Alzheimer disease or related dementias (mean age 87 years; minimum 65, maximum 104 years). Over 80\% of the falls happened in bedrooms, with two-thirds occurring overnight (8 PM to 8 AM). While only 8.1\% (22/272) of falls were scored as moderate or severe, fallers were not able to stand up alone in 97.6\% (247/253) of the cases. Reductions of 28.3 (CI 19.6-37.1) minutes in TUA and 29.6 (CI 20.3-38.9) minutes in TOG were observed between the baseline and RTN periods. The proportion of fallers with TOG >1 hour fell from 31\% (8/26; baseline) to zero events (RTN period). During the RTN period, 76.6\% (108/141) of fallers received human staff assistance in less than 10 minutes, and 55.3\% (78/141) of them spent less than 10 minutes on the ground. Conclusions: SYG technology is capable of reducing TOG and TUA while efficiently covering the area (bedroom) and time zone (nighttime) that are at highest risk. After 6 months of SYG monitoring, TOG was reduced by a factor of 3. The drastic reduction of TOG is likely to decrease secondary comorbid complications, improve post-fall prognosis, and reduce health care costs. ",
doi="10.2196/17551",
url="https://www.jmir.org/2021/6/e17551",
url="http://www.ncbi.nlm.nih.gov/pubmed/34137723"
}


@Article{info:doi/10.2196/26391,
author="Nichol, A. Ariadne
and Batten, N. Jason
and Halley, C. Meghan
and Axelrod, K. Julia
and Sankar, L. Pamela
and Cho, K. Mildred",
title="A Typology of Existing Machine Learning--Based Predictive Analytic Tools Focused on Reducing Costs and Improving Quality in Health Care: Systematic Search and Content Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="22",
volume="23",
number="6",
pages="e26391",
keywords="machine learning",
keywords="artificial intelligence",
keywords="ethics",
keywords="regulation",
keywords="health care quality",
keywords="costs",
abstract="Background: Considerable effort has been devoted to the development of artificial intelligence, including machine learning--based predictive analytics (MLPA) for use in health care settings. The growth of MLPA could be fueled by payment reforms that hold health care organizations responsible for providing high-quality, cost-effective care. Policy analysts, ethicists, and computer scientists have identified unique ethical and regulatory challenges from the use of MLPA in health care. However, little is known about the types of MLPA health care products available on the market today or their stated goals. Objective: This study aims to better characterize available MLPA health care products, identifying and characterizing claims about products recently or currently in use in US health care settings that are marketed as tools to improve health care efficiency by improving quality of care while reducing costs. Methods: We conducted systematic database searches of relevant business news and academic research to identify MLPA products for health care efficiency meeting our inclusion and exclusion criteria. We used content analysis to generate MLPA product categories and characterize the organizations marketing the products. Results: We identified 106 products and characterized them based on publicly available information in terms of the types of predictions made and the size, type, and clinical training of the leadership of the companies marketing them. We identified 5 categories of predictions made by MLPA products based on publicly available product marketing materials: disease onset and progression, treatment, cost and utilization, admissions and readmissions, and decompensation and adverse events. Conclusions: Our findings provide a foundational reference to inform the analysis of specific ethical and regulatory challenges arising from the use of MLPA to improve health care efficiency. ",
doi="10.2196/26391",
url="https://www.jmir.org/2021/6/e26391",
url="http://www.ncbi.nlm.nih.gov/pubmed/34156338"
}


@Article{info:doi/10.2196/27344,
author="Nam, Min Sang
and Peterson, A. Thomas
and Seo, Yul Kyoung
and Han, Wook Hyun
and Kang, In Jee",
title="Discovery of Depression-Associated Factors From a Nationwide Population-Based Survey: Epidemiological Study Using Machine Learning and Network Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="24",
volume="23",
number="6",
pages="e27344",
keywords="depression",
keywords="epidemiology",
keywords="machine learning",
keywords="network",
keywords="prediction model",
keywords="XGBoost",
abstract="Background: In epidemiological studies, finding the best subset of factors is challenging when the number of explanatory variables is large. Objective: Our study had two aims. First, we aimed to identify essential depression-associated factors using the extreme gradient boosting (XGBoost) machine learning algorithm from big survey data (the Korea National Health and Nutrition Examination Survey, 2012-2016). Second, we aimed to achieve a comprehensive understanding of multifactorial features in depression using network analysis. Methods: An XGBoost model was trained and tested to classify ``current depression'' and ``no lifetime depression'' for a data set of 120 variables for 12,596 cases. The optimal XGBoost hyperparameters were set by an automated machine learning tool (TPOT), and a high-performance sparse model was obtained by feature selection using the feature importance value of XGBoost. We performed statistical tests on the model and nonmodel factors using survey-weighted multiple logistic regression and drew a correlation network among factors. We also adopted statistical tests for the confounder or interaction effect of selected risk factors when it was suspected on the network. Results: The XGBoost-derived depression model consisted of 18 factors with an area under the weighted receiver operating characteristic curve of 0.86. Two nonmodel factors could be found using the model factors, and the factors were classified into direct (P<.05) and indirect (P?.05), according to the statistical significance of the association with depression. Perceived stress and asthma were the most remarkable risk factors, and urine specific gravity was a novel protective factor. The depression-factor network showed clusters of socioeconomic status and quality of life factors and suggested that educational level and sex might be predisposing factors. Indirect factors (eg, diabetes, hypercholesterolemia, and smoking) were involved in confounding or interaction effects of direct factors. Triglyceride level was a confounder of hypercholesterolemia and diabetes, smoking had a significant risk in females, and weight gain was associated with depression involving diabetes. Conclusions: XGBoost and network analysis were useful to discover depression-related factors and their relationships and can be applied to epidemiological studies using big survey data. ",
doi="10.2196/27344",
url="https://www.jmir.org/2021/6/e27344/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34184998"
}


@Article{info:doi/10.2196/25006,
author="Ruggiano, Nicole
and Brown, L. Ellen
and Roberts, Lisa
and Framil Suarez, Victoria C.
and Luo, Yan
and Hao, Zhichao
and Hristidis, Vagelis",
title="Chatbots to Support People With Dementia and Their Caregivers: Systematic Review of Functions and Quality",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e25006",
keywords="dementia",
keywords="caregivers",
keywords="chatbots",
keywords="conversation agents",
keywords="mobile apps",
keywords="mobile phone",
abstract="Background: Over the past decade, there has been an increase in the use of information technologies to educate and support people with dementia and their family caregivers. At the same time, chatbot technologies have become increasingly popular for use by the public and have been identified as having benefits for health care delivery. However, little is known about how chatbot technologies may benefit people with dementia and their caregivers. Objective: This study aims to identify the types of current commercially available chatbots that are designed for use by people with dementia and their caregivers and to assess their quality in terms of features and content. Methods: Chatbots were identified through a systematic search on Google Play Store, Apple App Store, Alexa Skills, and the internet. An evidence-based assessment tool was used to evaluate the features and content of the identified apps. The assessment was conducted through interrater agreement among 4 separate reviewers. Results: Of the 505 initial chatbots identified, 6 were included in the review. The chatbots assessed varied significantly in terms of content and scope. Although the chatbots were generally found to be easy to use, some limitations were noted regarding their performance and programmed content for dialog. Conclusions: Although chatbot technologies are well established and commonly used by the public, their development for people with dementia and their caregivers is in its infancy. Given the successful use of chatbots in other health care settings and for other applications, there are opportunities to integrate this technology into dementia care. However, more evidence-based chatbots that have undergone end user evaluation are needed to evaluate their potential to adequately educate and support these populations. ",
doi="10.2196/25006",
url="https://www.jmir.org/2021/6/e25006",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081019"
}


@Article{info:doi/10.2196/27807,
author="Beilharz, Francesca
and Sukunesan, Suku
and Rossell, L. Susan
and Kulkarni, Jayashri
and Sharp, Gemma",
title="Development of a Positive Body Image Chatbot (KIT) With Young People and Parents/Carers: Qualitative Focus Group Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="16",
volume="23",
number="6",
pages="e27807",
keywords="body image",
keywords="eating disorder",
keywords="chatbot",
keywords="conversational agent",
keywords="artificial intelligence",
keywords="mental health",
keywords="digital health",
keywords="design",
abstract="Background: Body image and eating disorders represent a significant public health concern; however, many affected individuals never access appropriate treatment. Conversational agents or chatbots reflect a unique opportunity to target those affected online by providing psychoeducation and coping skills, thus filling the gap in service provision. Objective: A world-first body image chatbot called ``KIT'' was designed. The aim of this study was to assess preliminary acceptability and feasibility via the collection of qualitative feedback from young people and parents/carers regarding the content, structure, and design of the chatbot, in accordance with an agile methodology strategy. The chatbot was developed in collaboration with Australia's national eating disorder support organization, the Butterfly Foundation. Methods: A conversation decision tree was designed that offered psychoeducational information on body image and eating disorders, as well as evidence-based coping strategies. A version of KIT was built as a research prototype to deliver these conversations. Six focus groups were conducted using online semistructured interviews to seek feedback on the KIT prototype. This included four groups of people seeking help for themselves (n=17; age 13-18 years) and two groups of parents/carers (n=8; age 46-57 years). Participants provided feedback on the cartoon chatbot character design, as well as the content, structure, and design of the chatbot webchat. Results: Thematic analyses identified the following three main themes from the six focus groups: (1) chatbot character and design, (2) content presentation, and (3) flow. Overall, the participants provided positive feedback regarding KIT, with both young people and parents/carers generally providing similar reflections. The participants approved of KIT's character and engagement. Specific suggestions were made regarding the brevity and tone to increase KIT's interactivity. Conclusions: Focus groups provided overall positive qualitative feedback regarding the content, structure, and design of the body image chatbot. Incorporating the feedback of lived experience from both individuals and parents/carers allowed the refinement of KIT in the development phase as per an iterative agile methodology. Further research is required to evaluate KIT's efficacy. ",
doi="10.2196/27807",
url="https://www.jmir.org/2021/6/e27807",
url="http://www.ncbi.nlm.nih.gov/pubmed/34132644"
}


@Article{info:doi/10.2196/20981,
author="Hendrie, A. Gilly
and Baird, L. Danielle
and Brindal, Emily
and Williams, Gemma
and Brand-Miller, Jennie
and Muhlhausler, Beverly",
title="Weight Loss and Usage of an Online Commercial Weight Loss Program (the CSIRO Total Wellbeing Diet Online) Delivered in an Everyday Context: Five-Year Evaluation in a Community Cohort",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e20981",
keywords="obesity",
keywords="obesity management",
keywords="weight loss",
keywords="internet-based intervention",
abstract="Background: Obesity is a global public health challenge, and there is a need for more evidence-based self-management programs that support longer-term, sustained weight loss. Objective: This study used data from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Total Wellbeing Diet Online program to determine the reach and weight loss results over its first 5 years. Methods: Participants were adults who joined the commercial weight loss program of their own volition between October 2014 and September 2019 (N=61,164). Information collected included year of birth, sex, height, weight, and usage data (eg, entries into the food diary, views of the menu, and program content). Weight loss and percentage of starting body weight lost were calculated. Members were divided into 2 groups for analysis: ``stayers'' were members who signed up for at least 12 weeks of the program and recorded a weight entry at baseline and at the end of the program, while ``starters'' began the program but did not record a weight after 12 weeks. Descriptive statistics and multiple linear regression were used to describe weight loss and determine the member and program characteristics associated with weight loss. Results: Data were available from 59,686 members for analysis. Members were predominately female (48,979/59,686, 82.06\%) with an average age of 50 years (SD 12.6). The average starting weight was 90.2 kg (SD 19.7), and over half of all members (34,195/59,688, 57.29\%) were classified as obese. At week 12, 94.56\% (56,438/59,686) of the members had a paid program membership, which decreased to 41.48\% (24,756/59,686) at 24 weeks. At week 12, 52.03\% (29,115/55,958) of the remaining members were actively using the platform, and by week 24, 26.59\% (14,880/55,958) were using the platform. The average weight loss for all members was 2.8 kg or 3.1\% of their starting body weight. Stayers lost 4.9 kg (5.3\% of starting body weight) compared to starters, who lost 1.6 kg (1.7\% of starting body weight). Almost half (11,082/22,658, 48.91\%) the members who stayed on the program lost 5\% or more of their starting body weight, and 15.48\% (3507/22,658) achieved a weight loss of 10\% or more. Of the members who were classified as class 1 obese when they joined the program, 41.39\% (3065/7405) who stayed on the program were no longer classified as obese at the end, and across all categories of obesity, 24\% (3180/13,319) were no longer classified as obese at the end of the program. Based on multiple linear regression, platform usage was the strongest predictor of weight loss ($\beta$=.263; P<.001), with higher usage associated with greater weight loss. Conclusions: This comprehensive evaluation of a commercial, online weight loss program showed that it was effective for weight loss, particularly for members who finished the program and were active in using the platform and tools provided. If the results demonstrated here can be achieved at an even greater scale, the potential social and economic benefits will be extremely significant. ",
doi="10.2196/20981",
url="https://www.jmir.org/2021/6/e20981",
url="http://www.ncbi.nlm.nih.gov/pubmed/34096869"
}


@Article{info:doi/10.2196/25529,
author="Vuorinen, Anna-Leena
and Helander, Elina
and Pietil{\"a}, Julia
and Korhonen, Ilkka",
title="Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="28",
volume="23",
number="6",
pages="e25529",
keywords="self-monitoring",
keywords="self-weighing",
keywords="weight change, weight loss, normal weight, overweight, obese, temporal weight change",
abstract="Background: Frequent self-weighing is associated with successful weight loss and weight maintenance during and after weight loss interventions. Less is known about self-weighing behaviors and associated weight change in free-living settings. Objective: This study aimed to investigate the association between the frequency of self-weighing and changes in body weight in a large international cohort of smart scale users. Methods: This was an observational cohort study with 10,000 randomly selected smart scale users who had used the scale for at least 1 year. Longitudinal weight measurement data were analyzed. The association between the frequency of self-weighing and weight change over the follow-up was investigated among normal weight, overweight, and obese users using Pearson's correlation coefficient and linear models. The association between the frequency of self-weighing and temporal weight change was analyzed using linear mixed effects models. Results: The eligible sample consisted of 9768 participants (6515/9768, 66.7\% men; mean age 41.5 years; mean BMI 26.8 kg/m2). Of the participants, 4003 (4003/9768, 41.0\%), 3748 (3748/9768, 38.4\%), and 2017 (2017/9768, 20.6\%) were normal weight, overweight, and obese, respectively. During the mean follow-up time of 1085 days, the mean weight change was --0.59 kg, and the mean percentage of days with a self-weigh was 39.98\%, which equals 2.8 self-weighs per week. The percentage of self-weighing days correlated inversely with weight change, r=--0.111 (P<.001). Among normal weight, overweight, and obese individuals, the correlations were r=--0.100 (P<.001), r=--0.125 (P<.001), and r=--0.148 (P<.001), respectively. Of all participants, 72.5\% (7085/9768) had at least one period of ?30 days without weight measurements. During the break, weight increased, and weight gains were more pronounced among overweight and obese individuals: 0.58 kg in the normal weight group, 0.93 kg in the overweight group, and 1.37 kg in the obese group (P<.001). Conclusions: Frequent self-weighing was associated with favorable weight loss outcomes also in an uncontrolled, free-living setting, regardless of specific weight loss interventions. The beneficial associations of regular self-weighing were more pronounced for overweight or obese individuals. ",
doi="10.2196/25529",
url="https://www.jmir.org/2021/6/e25529",
url="http://www.ncbi.nlm.nih.gov/pubmed/34075879"
}


@Article{info:doi/10.2196/23471,
author="Chiu, Ching-Ju
and Hsieh, Shiuan
and Li, Chia-Wei",
title="Needs and Preferences of Middle-Aged and Older Adults in Taiwan for Companion Robots and Pets: Survey Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e23471",
keywords="middle-aged adults",
keywords="older adults",
keywords="companionship demand",
keywords="robot",
keywords="pet",
keywords="acceptance",
abstract="Background: In recent years, robots have been considered a new tech industry that can be used to solve the shortage in human resources in the field of health care. Also, animal-assisted therapy has been used to provide assistance, companionship, and interaction among the elderly and has been shown to have a positive impact on their emotional and psychological well-being. Both pets and robots can provide dynamic communication and positive interaction patterns. However, preferences for middle-aged and older adults in this regard are not clear. Objective: This study explored the degree of acceptance of robots and pets as partners in later life and to determine the needs and preferences of elderly individuals related to companion robots. Methods: A total of 273 middle-aged and older adults aged ?45 years and living in the community were invited to answer a structured questionnaire after watching a companion robot video. Sociodemographic data, physical health status and activities, experience with technology, eHealth literacy, and acceptance and attitude toward robots and pets were recorded and analyzed using multinomial logistic regression analysis. Results: Age, level of education, type of dwelling, occupation, retirement status, number of comorbidities, experience with pets, experience using apps, and eHealth literacy were significantly associated with acceptance of robots and pets. Middle-aged and older women preferred robots with an animal-like appearance, while men preferred robots that resembled a human adult. In terms of robot functions, participants preferred a companion robot with dancing, singing, storytelling, or news-reporting functions. Participants' marital status and whether or not they lived alone affected their preference of functions in the companion robot. Conclusions: Findings from this study inform the development of social robots with regard to their appearance and functions to address loneliness in later life in fast-aging societies. ",
doi="10.2196/23471",
url="https://www.jmir.org/2021/6/e23471/",
url="http://www.ncbi.nlm.nih.gov/pubmed/34347621"
}


@Article{info:doi/10.2196/24601,
author="Dang, Ha Thu
and Nguyen, Anh Tuan
and Hoang Van, Minh
and Santin, Olinda
and Tran, Thi Oanh Mai
and Schofield, Penelope",
title="Patient-Centered Care: Transforming the Health Care System in Vietnam With Support of Digital Health Technology",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e24601",
keywords="building blocks",
keywords="digital health",
keywords="eHealth",
keywords="patient-centered care",
keywords="telemedicine",
keywords="Vietnam",
abstract="Background: Over the recent decades, Vietnam has attained remarkable achievements in all areas of health care. However, shortcomings including health disparities persist particularly with a rapidly aging population. This has resulted in a shift in the disease burden from communicable to noncommunicable diseases such as dementia, cancer, and diabetes. These medical conditions require long-term care, which causes an accelerating crisis for the health sector and society. The current health care system in Vietnam is unlikely to cope with these challenges. Objective: The aim of this paper was to explore the opportunities, challenges, and necessary conditions for Vietnam in transforming toward a patient-centered care model to produce better health for people and reduce health care costs. Methods: We examine the applicability of a personalized and integrated Bespoke Health Care System (BHS) for Vietnam using a strength, weakness, opportunity, and threat analysis and examining the successes or failures of digital health care innovations in Vietnam. We then make suggestions for successful adoption of the BHS model in Vietnam. Results: The BHS model of patient-centered care empowers patients to become active participants in their own health care. Vietnam's current policy, social, technological, and economic environment favors the transition of its health care system toward the BHS model. Nevertheless, the country is in an early stage of health care digitalization. The legal and regulatory system to protect patient privacy and information security is still lacking. The readiness to implement electronic medical records, a core element of the BHS, varies across health providers and clinical practices. The scarcity of empirical evidence and evaluation regarding the effectiveness and sustainability of digital health initiatives is an obstacle to the Vietnamese government in policymaking, development, and implementation of health care digitalization. Conclusions: Implementing a personalized and integrated health care system may help Vietnam to address health care needs, reduce pressure on the health care system and society, improve health care delivery, and promote health equity. However, in order to adopt the patient-centered care system and digitalized health care, a whole-system approach in transformation and operation with a co-design in the whole span of a digital health initiative developing process are necessary. ",
doi="10.2196/24601",
url="https://www.jmir.org/2021/6/e24601",
url="http://www.ncbi.nlm.nih.gov/pubmed/34085939"
}


@Article{info:doi/10.2196/27345,
author="Huang, Mian
and Wang, Jian
and Nicholas, Stephen
and Maitland, Elizabeth
and Guo, Ziyue",
title="Development, Status Quo, and Challenges to China's Health Informatization During COVID-19: Evaluation and Recommendations",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="17",
volume="23",
number="6",
pages="e27345",
keywords="health informatization",
keywords="COVID-19",
keywords="health policy",
keywords="digital health",
keywords="health information technology",
keywords="China",
doi="10.2196/27345",
url="https://www.jmir.org/2021/6/e27345",
url="http://www.ncbi.nlm.nih.gov/pubmed/34061761"
}


@Article{info:doi/10.2196/23715,
author="Archer, Norman
and Lokker, Cynthia
and Ghasemaghaei, Maryam
and DiLiberto, Deborah",
title="eHealth Implementation Issues in Low-Resource Countries: Model, Survey, and Analysis of User Experience",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="18",
volume="23",
number="6",
pages="e23715",
keywords="eHealth",
keywords="low-resource countries",
keywords="eHealth implementation effectiveness",
keywords="end user survey",
keywords="eHealth utilization",
abstract="Background: The implementation of eHealth in low-resource countries (LRCs) is challenged by limited resources and infrastructure, lack of focus on eHealth agendas, ethical and legal considerations, lack of common system interoperability standards, unreliable power, and shortage of trained workers. Objective: The aim of this study is to describe and study the current situation of eHealth implementation in a small number of LRCs from the perspectives of their professional eHealth users. Methods: We developed a structural equation model that reflects the opinions of professional eHealth users who work on LRC health care front lines. We recruited country coordinators from 4 LRCs to help recruit survey participants: India, Egypt, Nigeria, and Kenya. Through a web-based survey that focused on barriers to eHealth implementation, we surveyed 114 participants. We analyzed the information using a structural equation model to determine the relationships among the constructs in the model, including the dependent variable, eHealth utilization. Results: Although all the model constructs were important to participants, some constructs, such as user characteristics, perceived privacy, and perceived security, did not play a significant role in eHealth utilization. However, the constructs related to technology infrastructure tended to reduce the impact of concerns and uncertainties (path coefficient=?0.32; P=.001), which had a negative impact on eHealth utilization (path coefficient=?0.24; P=.01). Constructs that were positively related to eHealth utilization were implementation effectiveness (path coefficient=0.45; P<.001), the countries where participants worked (path coefficient=0.29; P=.004), and whether they worked for privately or publicly funded institutions (path coefficient=0.18; P<.001). As exploratory research, the model had a moderately good fit for eHealth utilization (adjusted R2=0.42). Conclusions: eHealth success factors can be categorized into 5 groups; our study focused on frontline eHealth workers' opinions concerning 2 of these groups: technology and its support infrastructure and user acceptance. We found significant disparities among the responses from different participant groups. Privately funded organizations tended to be further ahead with eHealth utilization than those that were publicly funded. Moreover, participant comments identified the need for more use of telemedicine in remote and rural regions in these countries. An understanding of these differences can help regions or countries that are lagging in the implementation and use of eHealth technologies. Our approach could also be applied to detailed studies of the other 3 categories of success factors: short- and long-term funding, organizational factors, and political or legislative aspects. ",
doi="10.2196/23715",
url="https://www.jmir.org/2021/6/e23715",
url="http://www.ncbi.nlm.nih.gov/pubmed/34142967"
}


@Article{info:doi/10.2196/25331,
author="Iorfino, Frank
and Occhipinti, Jo-An
and Skinner, Adam
and Davenport, Tracey
and Rowe, Shelley
and Prodan, Ante
and Sturgess, Julie
and Hickie, B. Ian",
title="The Impact of Technology-Enabled Care Coordination in a Complex Mental Health System: A Local System Dynamics Model",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="30",
volume="23",
number="6",
pages="e25331",
keywords="medical informatics",
keywords="internet",
keywords="care coordination",
keywords="complex systems",
keywords="simulation",
keywords="health systems",
keywords="policy",
keywords="mental health",
abstract="Background: Prior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond. Objective: This study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes. Methods: A system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health--related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20\%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre-- and post--COVID-19 social and economic conditions. Results: Technology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71\% (95\% interval 5.63\%-7.87\%), mental health--related ED presentations by 10.33\% (95\% interval 8.58\%-12.19\%), and the prevalence of high psychological distress by 1.76 percentage points (95\% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20\% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post--COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce  the negative impact of the pandemic on mental health and suicide. Conclusions: The use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie,  increasing service capacity growth rate by 20\% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed. ",
doi="10.2196/25331",
url="https://www.jmir.org/2021/6/e25331",
url="http://www.ncbi.nlm.nih.gov/pubmed/34077384"
}


@Article{info:doi/10.2196/25968,
author="Kim, Gyungha
and Jeon, Hwawoo
and Park, Kee Sung
and Choi, Suk Yong
and Lim, Yoonseob",
title="A Care Knowledge Management System Based on an Ontological Model of Caring for People With Dementia: Knowledge Representation and Development Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="8",
volume="23",
number="6",
pages="e25968",
keywords="caregiver",
keywords="caregiver for person with dementia",
keywords="knowledge model",
keywords="ontology",
keywords="knowledge management",
keywords="semantic reasoning",
abstract="Background: Caregivers of people with dementia find it extremely difficult to choose the best care method because of complex environments and the variable symptoms of dementia. To alleviate this care burden, interventions have been proposed that use computer- or web-based applications. For example, an automatic diagnosis of the condition can improve the well-being of both the person with dementia and the caregiver. Other interventions support the individual with dementia in living independently. Objective: The aim of this study was to develop an ontology-based care knowledge management system for people with dementia that will provide caregivers with a care guide suited to the environment and to the individual patient's symptoms. This should also enable knowledge sharing among caregivers. Methods: To build the care knowledge model, we reviewed existing ontologies that contain concepts and knowledge descriptions relating to the care of those with dementia, and we considered dementia care manuals. The basic concepts of the care ontology were confirmed by experts in Korea. To infer the different care methods required for the individual dementia patient, the reasoning rules as defined in Semantic Web Rule Languages and Prolog were utilized. The accuracy of the care knowledge in the ontological model and the usability of the proposed system were evaluated by using the Pellet reasoner and OntOlogy Pitfall Scanner!, and a survey and interviews were conducted with caregivers working in care centers in Korea. Results: The care knowledge model contains six top-level concepts: care knowledge, task, assessment, person, environment, and medical knowledge. Based on this ontological model of dementia care, caregivers at a dementia care facility in Korea were able to access the care knowledge easily through a graphical user interface. The evaluation by the care experts showed that the system contained accurate care knowledge and a level of assessment comparable to normal assessment tools. Conclusions: In this study, we developed a care knowledge system that can provide caregivers with care guides suited to individuals with dementia. We anticipate that the system could reduce the workload of caregivers. ",
doi="10.2196/25968",
url="https://www.jmir.org/2021/6/e25968",
url="http://www.ncbi.nlm.nih.gov/pubmed/34100762"
}


@Article{info:doi/10.2196/27259,
author="Matthewman, Spencer
and Spencer, Sarah
and Lavergne, Ruth M.
and McCracken, K. Rita
and Hedden, Lindsay",
title="An Environmental Scan of Virtual ``Walk-In'' Clinics in Canada: Comparative Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e27259",
keywords="virtual care",
keywords="primary care",
keywords="Canada",
keywords="virtual health",
keywords="patients",
keywords="physicians",
abstract="Background: Canada has been slow to implement virtual care relative to other countries. However, in recent years, the availability of on-demand, ``walk-in'' virtual clinics has increased, with the COVID-19 pandemic contributing to the increased demand and provision of virtual care nationwide. Although virtual care facilitates access to physicians while maintaining physical distancing, there are concerns regarding the continuity and quality of care as well as equitable access. There is a paucity of research documenting the availability of virtual care in Canada, thus hampering the efforts to evaluate the impacts of its relatively rapid emergence on the broader health care system and on individual health. Objective: We conducted a national environmental scan to determine the availability and scope of virtual walk-in clinics, cataloging the services they offer and whether they are operating through public or private payment. Methods: We developed a power term and implemented a structured Google search to identify relevant clinics. From each clinic meeting our inclusion criteria, we abstracted data on the payment model, region of operation, services offered, and continuity of care. We compared clinics operating under different payment models using Fisher exact tests. Results: We identified 18 virtual walk-in clinics. Of the 18 clinics, 10 (56\%) provided some services under provincial public insurance, although 44\% (8/18) operated on a fully private payment model while an additional 39\% (7/18) charged patients out of pocket for some services. The most common supplemental services offered included dermatology (15/18, 83\%), mental health services (14/18, 78\%), and sexual health (11/18, 61\%). Continuity, information sharing, or communication with the consumers' existing primary care providers were mentioned by 22\% (4/18) of the clinics. Conclusions: Virtual walk-in clinics have proliferated; however, concerns about equitable access, continuity of care, and diversion of physician workforce within these models highlight the importance of supporting virtual care options within the context of longitudinal primary care. More research is needed to support quality virtual care and understand its effects on patient and provider experiences and the overall health system utilization and costs. ",
doi="10.2196/27259",
url="https://www.jmir.org/2021/6/e27259",
url="http://www.ncbi.nlm.nih.gov/pubmed/34114963"
}


@Article{info:doi/10.2196/27664,
author="Gambril, Alan John
and Boyd, J. Carter
and Egbaria, Jamal",
title="The Numerous Benefits of Social Media for Medicine. Comment on ``Documenting Social Media Engagement as Scholarship: A New Model for Assessing Academic Accomplishment for the Health Professions''",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="9",
volume="23",
number="6",
pages="e27664",
keywords="social media",
keywords="medical education",
keywords="internet",
keywords="academic medicine",
keywords="promotion",
keywords="tenure",
keywords="health professions",
keywords="scholarship",
keywords="medicine",
keywords="research",
keywords="accomplishment",
keywords="crowd source",
keywords="contribution",
keywords="innovation",
keywords="education",
keywords="dissemination",
doi="10.2196/27664",
url="https://www.jmir.org/2021/6/e27664",
url="http://www.ncbi.nlm.nih.gov/pubmed/34106082"
}


@Article{info:doi/10.2196/26514,
author="Gilbert, Stephen
and Fenech, Matthew
and Idris, Anisa
and T{\"u}rk, Ewelina",
title="Periodic Manual Algorithm Updates and Generalizability: A Developer's Response. Comment on ``Evaluation of Four Artificial Intelligence--Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study''",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="16",
volume="23",
number="6",
pages="e26514",
keywords="artificial intelligence",
keywords="machine learning",
keywords="mobile apps",
keywords="medical diagnosis",
keywords="mHealth",
keywords="symptom assessment",
doi="10.2196/26514",
url="https://www.jmir.org/2021/6/e26514",
url="http://www.ncbi.nlm.nih.gov/pubmed/34132641"
}


@Article{info:doi/10.2196/29336,
author="{\'C}irkovi{\'c}, Aleksandar",
title="Author's Reply to: Periodic Manual Algorithm Updates and Generalizability: A Developer's Response. Comment on ``Evaluation of Four Artificial Intelligence--Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study''",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="16",
volume="23",
number="6",
pages="e29336",
keywords="artificial intelligence",
keywords="machine learning",
keywords="mobile apps",
keywords="medical diagnosis",
keywords="mHealth",
keywords="symptom assessment",
doi="10.2196/29336",
url="https://www.jmir.org/2021/6/e29336",
url="http://www.ncbi.nlm.nih.gov/pubmed/34132643"
}


@Article{info:doi/10.2196/28990,
author="Resnik, Philip
and De Choudhury, Munmun
and Musacchio Schafer, Katherine
and Coppersmith, Glen",
title="Bibliometric Studies and the Discipline of Social Media Mental Health Research. Comment on ``Machine Learning for Mental Health in Social Media: Bibliometric Study''",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="17",
volume="23",
number="6",
pages="e28990",
keywords="bibliometric analysis",
keywords="machine learning",
keywords="mental health",
keywords="social media",
keywords="bibliometrics",
doi="10.2196/28990",
url="https://www.jmir.org/2021/6/e28990",
url="http://www.ncbi.nlm.nih.gov/pubmed/34137722"
}


@Article{info:doi/10.2196/29549,
author="Kim, Jina
and Lee, Daeun
and Park, Eunil",
title="Authors' Reply to: Bibliometric Studies and the Discipline of Social Media Mental Health Research. Comment on ``Machine Learning for Mental Health in Social Media: Bibliometric Study''",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="17",
volume="23",
number="6",
pages="e29549",
keywords="bibliometric analysis",
keywords="machine learning",
keywords="mental health",
keywords="social media",
keywords="bibliometrics",
doi="10.2196/29549",
url="https://www.jmir.org/2021/6/e29549",
url="http://www.ncbi.nlm.nih.gov/pubmed/34137721"
}


@Article{info:doi/10.2196/31044,
author="Laur, Violet Celia
and Agarwal, Payal
and Mukerji, Geetha
and Goulbourne, Elaine
and Baranek, Hayley
and Pus, Laura
and Bhatia, Sacha R.
and Martin, Danielle
and Bhattacharyya, Onil",
title="Correction: Building Health Services in a Rapidly Changing Landscape: Lessons in Adaptive Leadership and Pivots in a COVID-19 Remote Monitoring Program",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="10",
volume="23",
number="6",
pages="e31044",
doi="10.2196/31044",
url="https://www.jmir.org/2021/6/e31044",
url="http://www.ncbi.nlm.nih.gov/pubmed/34111020"
}


@Article{info:doi/10.2196/31370,
author="Dong, Shengjie
and Millar, Ross
and Shi, Chenshu
and Dong, Minye
and Xiao, Yuyin
and Shen, Jie
and Li, Guohong",
title="Correction: Rating Hospital Performance in China: Review of Publicly Available Measures and Development of a Ranking System",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="22",
volume="23",
number="6",
pages="e31370",
doi="10.2196/31370",
url="https://www.jmir.org/2021/6/e31370/"
}


@Article{info:doi/10.2196/31268,
author="Millen, Elizabeth
and Gilsdorf, Andreas
and Fenech, Matthew
and Gilbert, Stephen",
title="Correction: Screening Tools: Their Intended Audiences and Purposes. Comment on ``Diagnostic Accuracy of Web-Based COVID-19 Symptom Checkers: Comparison Study''",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="18",
volume="23",
number="6",
pages="e31268",
doi="10.2196/31268",
url="https://www.jmir.org/2021/6/e31268/"
}


@Article{info:doi/10.2196/29776,
author="van Herpen, Marjolein Merel
and Boeschoten, A. Manon
and te Brake, Hans
and van der Aa, Niels
and Olff, Miranda",
title="Correction: Mobile Insight in Risk, Resilience, and Online Referral (MIRROR): Psychometric Evaluation of an Online Self-Help Test",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e29776",
doi="10.2196/29776",
url="https://www.jmir.org/2021/6/e29776",
url="http://www.ncbi.nlm.nih.gov/pubmed/34086592"
}


@Article{info:doi/10.2196/30764,
author="Lau, Francis
and Antonio, Marcy
and Davison, Kelly
and Queen, Roz
and Bryski, Katie",
title="Correction: An Environmental Scan of Sex and Gender in Electronic Health Records: Analysis of Public Information Sources",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e30764",
doi="10.2196/30764",
url="https://www.jmir.org/2021/6/e30764",
url="http://www.ncbi.nlm.nih.gov/pubmed/34086590"
}


@Article{info:doi/10.2196/29645,
author="Bailey, Eleanor
and Robinson, Jo
and Alvarez-Jimenez, Mario
and Nedeljkovic, Maja
and Valentine, Lee
and Bendall, Sarah
and D'Alfonso, Simon
and Gilbertson, Tamsyn
and McKechnie, Ben
and Rice, Simon",
title="Correction: Moderated Online Social Therapy for Young People With Active Suicidal Ideation: Qualitative Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="10",
volume="23",
number="6",
pages="e29645",
doi="10.2196/29645",
url="https://www.jmir.org/2021/6/e29645",
url="http://www.ncbi.nlm.nih.gov/pubmed/34111019"
}


@Article{info:doi/10.2196/30828,
author="Oh, Soyeon Sarah
and Kim, Kyoung-A
and Kim, Minsu
and Oh, Jaeuk
and Chu, Hui Sang
and Choi, JiYeon",
title="Correction: Measurement of Digital Literacy Among Older Adults: Systematic Review",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e30828",
doi="10.2196/30828",
url="https://www.jmir.org/2021/6/e30828",
url="http://www.ncbi.nlm.nih.gov/pubmed/34129513"
}


@Article{info:doi/10.2196/31253,
author="V{\"o}lkel, Gunnar
and F{\"u}rstberger, Axel
and Schwab, D. Julian
and Werle, D. Silke
and Ikonomi, Nensi
and Gscheidmeier, Thomas
and Kraus, M. Johann
and Gro{\ss}, Alexander
and Holderried, Martin
and Balig, Julien
and Jobst, Franz
and Kuhn, Peter
and Kuhn, A. Klaus
and Kohlbacher, Oliver
and Kaisers, X. Udo
and Seufferlein, Thomas
and Kestler, A. Hans",
title="Metadata Correction: Patient Empowerment During the COVID-19 Pandemic by Ensuring Safe and Fast Communication of Test Results: Implementation and Performance of a Tracking System",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e31253",
doi="10.2196/31253",
url="https://www.jmir.org/2021/6/e31253",
url="http://www.ncbi.nlm.nih.gov/pubmed/34152993"
}


@Article{info:doi/10.2196/29730,
author="Afzal, Muhammad
and Hussain, Maqbool
and Hussain, Jamil
and Bang, Jaehun
and Lee, Sungyoung",
title="COVID-19 Knowledge Resource Categorization and Tracking: Conceptual Framework Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="1",
volume="23",
number="6",
pages="e29730",
keywords="information organization",
keywords="resource management",
keywords="knowledge graphs",
keywords="interactive dashboard",
keywords="dependency tracking",
keywords="COVID-19",
keywords="pandemic",
keywords="information technology",
keywords="tracing information",
keywords="dashboards",
keywords="digital health",
abstract="Background: Since the declaration of COVID-19 as a global pandemic by the World Health Organization, the disease has gained momentum with every passing day. Various private and government sectors of different countries allocated funding for research in multiple capacities. A significant portion of efforts has been devoted to information technology and service infrastructure development, including research on developing intelligent models and techniques for alerts, monitoring, early diagnosis, prevention, and other relevant services. As a result, many information resources have been created globally and are available for use. However, a defined structure to organize these resources into categories based on the nature and origin of the data is lacking. Objective: This study aims to organize COVID-19 information resources into a well-defined structure to facilitate the easy identification of a resource, tracking information workflows, and to provide a guide for a contextual dashboard design and development. Methods: A sequence of action research was performed that involved a review of COVID-19 efforts and initiatives on a global scale during the year 2020. Data were collected according to the defined structure of primary, secondary, and tertiary categories. Various techniques for descriptive statistical analysis were employed to gain insights into the data to help develop a conceptual framework to organize resources and track interactions between different resources. Results: Investigating diverse information at the primary, secondary, and tertiary levels enabled us to develop a conceptual framework for COVID-19--related efforts and initiatives. The framework of resource categorization provides a gateway to access global initiatives with enriched metadata, and assists users in tracking the workflow of tertiary, secondary, and primary resources with relationships between various fragments of information. The results demonstrated mapping initiatives at the tertiary level to secondary level and then to the primary level to reach firsthand data, research, and trials. Conclusions: Adopting the proposed three-level structure allows for a consistent organization and management of existing COVID-19 knowledge resources and provides a roadmap for classifying future resources. This study is one of the earliest studies to introduce an infrastructure for locating and placing the right information at the right place. By implementing the proposed framework according to the stated guidelines, this study allows for the development of applications such as interactive dashboards to facilitate the contextual identification and tracking of interdependent COVID-19 knowledge resources. ",
doi="10.2196/29730",
url="https://www.jmir.org/2021/6/e29730",
url="http://www.ncbi.nlm.nih.gov/pubmed/33999833"
}


@Article{info:doi/10.2196/27989,
author="Kahnbach, Leonie
and Lehr, Dirk
and Brandenburger, Jessica
and Mallwitz, Tim
and Jent, Sophie
and Hannibal, Sandy
and Funk, Burkhardt
and Janneck, Monique",
title="Quality and Adoption of COVID-19 Tracing Apps and Recommendations for Development: Systematic Interdisciplinary Review of European Apps",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="2",
volume="23",
number="6",
pages="e27989",
keywords="COVID-19",
keywords="contact tracing",
keywords="app-based tracing",
keywords="Mobile App Rating Scale",
keywords="user engagement",
keywords="human--computer interaction",
abstract="Background: Simulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps. Objective: This study's primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified. Methods: Eligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human--computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted. Results: We discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9\% (SD 12.5\%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5\% and 43.6\%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity. Conclusions: European national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app's engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development. ",
doi="10.2196/27989",
url="https://www.jmir.org/2021/6/e27989",
url="http://www.ncbi.nlm.nih.gov/pubmed/33890867"
}


@Article{info:doi/10.2196/28253,
author="Krawczyk, Konrad
and Chelkowski, Tadeusz
and Laydon, J. Daniel
and Mishra, Swapnil
and Xifara, Denise
and Gibert, Benjamin
and Flaxman, Seth
and Mellan, Thomas
and Schw{\"a}mmle, Veit
and R{\"o}ttger, Richard
and Hadsund, T. Johannes
and Bhatt, Samir",
title="Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="2",
volume="23",
number="6",
pages="e28253",
keywords="text mining",
keywords="COVID-19",
keywords="infoveillance",
keywords="sentiment analysis",
keywords="public health",
abstract="Background: Before the advent of an effective vaccine, nonpharmaceutical interventions, such as mask-wearing, social distancing, and lockdowns, have been the primary measures to combat the COVID-19 pandemic. Such measures are highly effective when there is high population-wide adherence, which requires information on current risks posed by the pandemic alongside a clear exposition of the rules and guidelines in place. Objective: Here we analyzed online news media coverage of COVID-19. We quantified the total volume of COVID-19 articles, their sentiment polarization, and leading subtopics to act as a reference to inform future communication strategies. Methods: We collected 26 million news articles from the front pages of 172 major online news sources in 11 countries (available online at SciRide). Using topic detection, we identified COVID-19--related content to quantify the proportion of total coverage the pandemic received in 2020. The sentiment analysis tool Vader was employed to stratify the emotional polarity of COVID-19 reporting. Further topic detection and sentiment analysis was performed on COVID-19 coverage to reveal the leading themes in pandemic reporting and their respective emotional polarizations. Results: We found that COVID-19 coverage accounted for approximately 25.3\% of all front-page online news articles between January and October 2020. Sentiment analysis of English-language sources revealed that overall COVID-19 coverage was not exclusively negatively polarized, suggesting wide heterogeneous reporting of the pandemic. Within this heterogenous coverage, 16\% of COVID-19 news articles (or 4\% of all English-language articles) can be classified as highly negatively polarized, citing issues such as death, fear, or crisis. Conclusions: The goal of COVID-19 public health communication is to increase understanding of distancing rules and to maximize the impact of governmental policy. The extent to which the quantity and quality of information from different communication channels (eg, social media, government pages, and news) influence public understanding of public health measures remains to be established. Here we conclude that a quarter of all reporting in 2020 covered COVID-19, which is indicative of information overload. In this capacity, our data and analysis form a quantitative basis for informing health communication strategies along traditional news media channels to minimize the risks of COVID-19 while vaccination is rolled out. ",
doi="10.2196/28253",
url="https://www.jmir.org/2021/6/e28253",
url="http://www.ncbi.nlm.nih.gov/pubmed/33900934"
}


@Article{info:doi/10.2196/27300,
author="Guntuku, Chandra Sharath
and Purtle, Jonathan
and Meisel, F. Zachary
and Merchant, M. Raina
and Agarwal, Anish",
title="Partisan Differences in Twitter Language Among US Legislators During the COVID-19 Pandemic: Cross-sectional Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="3",
volume="23",
number="6",
pages="e27300",
keywords="Twitter",
keywords="COVID-19",
keywords="digital health",
keywords="US legislators",
keywords="natural language processing",
keywords="policy makers",
keywords="social media",
keywords="policy",
keywords="politics",
keywords="language",
keywords="cross-sectional",
keywords="content",
keywords="sentiment",
keywords="infodemiology",
keywords="infoveillance",
abstract="Background: As policy makers continue to shape the national and local responses to the COVID-19 pandemic, the information they choose to share and how they frame their content provide key insights into the public and health care systems. Objective: We examined the language used by the members of the US House and Senate during the first 10 months of the COVID-19 pandemic and measured content and sentiment based on the tweets that they shared. Methods: We used Quorum (Quorum Analytics Inc) to access more than 300,000 tweets posted by US legislators from January 1 to October 10, 2020. We used differential language analyses to compare the content and sentiment of tweets posted by legislators based on their party affiliation. Results: We found that health care--related themes in Democratic legislators' tweets focused on racial disparities in care (odds ratio [OR] 2.24, 95\% CI 2.22-2.27; P<.001), health care and insurance (OR 1.74, 95\% CI 1.7-1.77; P<.001), COVID-19 testing (OR 1.15, 95\% CI 1.12-1.19; P<.001), and public health guidelines (OR 1.25, 95\% CI 1.22-1.29; P<.001). The dominant themes in the Republican legislators' discourse included vaccine development (OR 1.51, 95\% CI 1.47-1.55; P<.001) and hospital resources and equipment (OR 1.22, 95\% CI 1.18-1.25). Nonhealth care--related topics associated with a Democratic affiliation included protections for essential workers (OR 1.55, 95\% CI 1.52-1.59), the 2020 election and voting (OR 1.31, 95\% CI 1.27-1.35), unemployment and housing (OR 1.27, 95\% CI 1.24-1.31), crime and racism (OR 1.22, 95\% CI 1.18-1.26), public town halls (OR 1.2, 95\% CI 1.16-1.23), the Trump Administration (OR 1.22, 95\% CI 1.19-1.26), immigration (OR 1.16, 95\% CI 1.12-1.19), and the loss of life (OR 1.38, 95\% CI 1.35-1.42). The themes associated with the Republican affiliation included China (OR 1.89, 95\% CI 1.85-1.92), small business assistance (OR 1.27, 95\% CI 1.23-1.3), congressional relief bills (OR 1.23, 95\% CI 1.2-1.27), press briefings (OR 1.22, 95\% CI 1.19-1.26), and economic recovery (OR 1.2, 95\% CI 1.16-1.23). Conclusions: Divergent language use on social media corresponds to the partisan divide in the first several months of the course of the COVID-19 public health crisis. ",
doi="10.2196/27300",
url="https://www.jmir.org/2021/6/e27300",
url="http://www.ncbi.nlm.nih.gov/pubmed/33939620"
}


@Article{info:doi/10.2196/28892,
author="Mack, L. Dante
and DaSilva, W. Alex
and Rogers, Courtney
and Hedlund, Elin
and Murphy, I. Eilis
and Vojdanovski, Vlado
and Plomp, Jane
and Wang, Weichen
and Nepal, K. Subigya
and Holtzheimer, E. Paul
and Wagner, D. Dylan
and Jacobson, C. Nicholas
and Meyer, L. Meghan
and Campbell, T. Andrew
and Huckins, F. Jeremy",
title="Mental Health and Behavior of College Students During the COVID-19 Pandemic: Longitudinal Mobile Smartphone and Ecological Momentary Assessment Study, Part II",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="4",
volume="23",
number="6",
pages="e28892",
keywords="anxiety",
keywords="college",
keywords="COVID-19",
keywords="COVID fatigue",
keywords="depression",
keywords="George Floyd",
keywords="mobile sensing",
keywords="phone usage",
keywords="sleep",
keywords="digital phenotyping",
abstract="Background: Since late 2019, the lives of people across the globe have been disrupted by COVID-19. Millions of people have become infected with the disease, while billions of people have been continually asked or required by local and national governments to change their behavioral patterns. Previous research on the COVID-19 pandemic suggests that it is associated with large-scale behavioral and mental health changes; however, few studies have been able to track these changes with frequent, near real-time sampling or compare these changes to previous years of data for the same individuals. Objective: By combining mobile phone sensing and self-reported mental health data in a cohort of college-aged students enrolled in a longitudinal study, we seek to understand the behavioral and mental health impacts associated with the COVID-19 pandemic, measured by interest across the United States in the search terms coronavirus and COVID fatigue. Methods: Behaviors such as the number of locations visited, distance traveled, duration of phone use, number of phone unlocks, sleep duration, and sedentary time were measured using the StudentLife mobile smartphone sensing app. Depression and anxiety were assessed using weekly self-reported ecological momentary assessments, including the Patient Health Questionnaire-4. The participants were 217 undergraduate students. Differences in behaviors and self-reported mental health collected during the Spring 2020 term, as compared to previous terms in the same cohort, were modeled using mixed linear models. Results: Linear mixed models demonstrated differences in phone use, sleep, sedentary time and number of locations visited associated with the COVID-19 pandemic. In further models, these behaviors were strongly associated with increased interest in COVID fatigue. When mental health metrics (eg, depression and anxiety) were added to the previous measures (week of term, number of locations visited, phone use, sedentary time), both anxiety and depression (P<.001) were significantly associated with interest in COVID fatigue. Notably, these behavioral and mental health changes are consistent with those observed around the initial implementation of COVID-19 lockdowns in the spring of 2020. Conclusions: In the initial lockdown phase of the COVID-19 pandemic, people spent more time on their phones, were more sedentary, visited fewer locations, and exhibited increased symptoms of anxiety and depression. As the pandemic persisted through the spring, people continued to exhibit very similar changes in both mental health and behaviors. Although these large-scale shifts in mental health and behaviors are unsurprising, understanding them is critical in disrupting the negative consequences to mental health during the ongoing pandemic. ",
doi="10.2196/28892",
url="https://www.jmir.org/2021/6/e28892",
url="http://www.ncbi.nlm.nih.gov/pubmed/33900935"
}


@Article{info:doi/10.2196/25259,
author="Zhao, Lina
and Sznajder, Kristin
and Cheng, Dan
and Wang, Shimeng
and Cui, Can
and Yang, Xiaoshi",
title="Coping Styles for Mediating the Effect of Resilience on Depression Among Medical Students in Web-Based Classes During the COVID-19 Pandemic: Cross-sectional Questionnaire Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e25259",
keywords="resilience",
keywords="coping styles",
keywords="depression",
keywords="medical students",
keywords="COVID-19",
keywords="coping",
keywords="mediation",
keywords="web-based education",
keywords="e-learning",
keywords="smartphone",
keywords="cross-sectional",
abstract="Background: Due to strict, nationwide, comprehensive COVID-19 protective measures, including home quarantine, all Chinese medical students began taking web-based classes beginning in the spring semester of 2020. Home quarantine, web-based classes, and the stress surrounding the COVID-19 pandemic may have triggered an increased incidence of mental health problems among medical students. Although there have been increasing amounts of literature on depression among medical students, studies focusing on positive psychological resources, such as resilience during the COVID-19 pandemic, still need to be expanded. Objective: This study aims to assess depression among medical students who are taking web-based classes during the COVID-19 pandemic and to investigate the role of coping styles as mediators between resilience and depression. Methods: A cross-sectional study of 666 medical students involving stratified sampling in Shenyang, Liaoning Province, China, was completed between March 20 and April 10, 2020. The participants responded to a self-administered, smartphone-based questionnaire, which included the Patient Health Questionnaire-9, Simplified Coping Style Questionnaire, and Ego Resilience 89 Scale. Hierarchical linear regression and structural equation modeling were used in this study. Results: The prevalence of depression among the participants was 9.6\% (64/666) in this study. The regression analysis revealed that grade (the year in which the medical student was in training) (P=.013), how well students adapted to web-based classes (P<.001), their levels of resilience (P=.04), and their coping styles were independent predictors for depression (P<.001). Resilience and positive coping styles were negatively related to depression (resilience: P=.04; positive coping styles: P<.001), and negative coping styles were positively related to depression (P<.001). The structural equation modeling analysis showed that the effect of resilience on depression was partially mediated by coping styles (P=.007). Conclusions: In this study, it was found that the prevalence of depression was slightly low and coping styles mediated the association between resilience and depression among medical students during the COVID-19 pandemic. These findings have significant implications for future studies. Future studies and interventions should aim to improve resilience and promote positive coping styles. ",
doi="10.2196/25259",
url="https://www.jmir.org/2021/6/e25259",
url="http://www.ncbi.nlm.nih.gov/pubmed/34033579"
}


@Article{info:doi/10.2196/27348,
author="V{\"o}lkel, Gunnar
and F{\"u}rstberger, Axel
and Schwab, D. Julian
and Werle, D. Silke
and Ikonomi, Nensi
and Gscheidmeier, Thomas
and Kraus, M. Johann
and Gro{\ss}, Alexander
and Holderried, Martin
and Balig, Julien
and Jobst, Franz
and Kuhn, Peter
and Kuhn, A. Klaus
and Kohlbacher, Oliver
and Kaisers, X. Udo
and Seufferlein, Thomas
and Kestler, A. Hans",
title="Patient Empowerment During the COVID-19 Pandemic by Ensuring Safe and Fast Communication of Test Results: Implementation and Performance of a Tracking System",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="7",
volume="23",
number="6",
pages="e27348",
keywords="process optimization",
keywords="patient empowerment",
keywords="data security",
keywords="COVID-19",
keywords="clinical information system",
keywords="platform independent",
keywords="eHealth",
keywords="telemedicine",
keywords="quality management",
abstract="Background: Overcoming the COVID-19 crisis requires new ideas and strategies for online communication of personal medical information and patient empowerment. Rapid testing of a large number of subjects is essential for monitoring and delaying the spread of SARS-CoV-2 in order to mitigate the pandemic's consequences. People who do not know that they are infected may not stay in quarantine and, thus, risk infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that conduct throat swabs and communicate the results. Objective: The goal of this study was to reduce the communication burden for health care professionals. We developed a secure and easy-to-use tracking system to report COVID-19 test results online that is simple to understand for the tested subjects as soon as these results become available. Instead of personal calls, the system updates the status and the results of the tests automatically. This aims to reduce the delay when informing testees about their results and, consequently, to slow down the virus spread. Methods: The application in this study draws on an existing tracking tool. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person and the testing units (eg, hospitals or the public health care system). The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. Results: The test statuses and results are published on a secured webpage, enabling regular status checks by patients; status checks are performed without the use of smartphones, which has some importance, as smartphone usage diminishes with age. Stress tests and statistics show the performance of our software. CTest is currently running at two university hospitals in Germany---University Hospital Ulm and University Hospital T{\"u}bingen---with thousands of tests being performed each week. Results show a mean number of 10 (SD 2.8) views per testee. Conclusions: CTest runs independently of existing infrastructures, aims at straightforward integration, and aims for the safe transmission of information. The system is easy to use for testees. QR (Quick Response) code links allow for quick access to the test results. The mean number of views per entry indicates a reduced amount of time for both health care professionals and testees. The system is quite generic and can be extended and adapted to other communication tasks. ",
doi="10.2196/27348",
url="https://www.jmir.org/2021/6/e27348",
url="http://www.ncbi.nlm.nih.gov/pubmed/33999836"
}


@Article{info:doi/10.2196/26285,
author="Wu, Xue
and Nazari, Nabi
and Griffiths, D. Mark",
title="Using Fear and Anxiety Related to COVID-19 to Predict Cyberchondria: Cross-sectional Survey Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="9",
volume="23",
number="6",
pages="e26285",
keywords="COVID-19",
keywords="cyberchondria",
keywords="COVID-19 fear",
keywords="COVID-19 anxiety",
keywords="anxiety sensitivity",
keywords="anxiety",
keywords="intolerance of uncertainty",
keywords="mental health",
keywords="survey",
keywords="SEM",
abstract="Background: Studies have highlighted that fear and anxiety generated by COVID-19 are important psychological factors that affect all populations. There currently remains a lack of research on specific amplification factors regarding fear and anxiety in the context of the COVID-19 pandemic. Despite established associations between anxiety sensitivity, intolerance of uncertainty, and cyberchondria, empirical data investigating the associations between these three variables, particularly in the context of the COVID-19 pandemic, are currently lacking. Urgent research is needed to better understand the role of repeated media consumption concerning COVID-19 in amplifying fear and anxiety related to COVID-19. Objective: This study investigated the associations between fear of COVID-19, COVID-19 anxiety, and cyberchondria. Methods: Convenience sampling was used to recruit respondents to participate in an online survey. The survey, which was distributed via social media and academic forums, comprised the Cyberchondria Severity Scale, Fear of COVID-19 Scale, Coronavirus Anxiety Scale, Anxiety Sensitivity Index, and Intolerance of Uncertainty Scale. Multiple mediation analyses were conducted using structural equation modeling. Results: A total of 694 respondents (males: n=343, females: n=351) completed the online survey. The results showed that fear and anxiety generated by COVID-19 predicted cyberchondria (fear: $\beta$=.39, SE 0.04, P<.001, t=11.16, 95\% CI 0.31-0.45; anxiety: $\beta$=.25, SE 0.03, P<.001, t=7.67, 95\% CI 0.19-0.32). In addition, intolerance of uncertainty and anxiety sensitivity mediated the relationship between fear and anxiety generated by COVID-19 with cyberchondria. In a reciprocal model, the standardized total effects of cyberchondria on fear of COVID-19 ($\beta$=.45, SE 0.04, P<.001, t=15.31, 95\% CI 0.39-0.51) and COVID-19 anxiety ($\beta$=.36, SE 0.03, P<.001, t=11.29, 95\% CI 0.30-0.41) were statistically significant, with moderate effect sizes. Compared to males, females obtained significantly higher scores for cyberchondria (t1,692=--2.85, P=.004, Cohen d=0.22), COVID-19 anxiety (t1,692=--3.32, P<.001, Cohen d=0.26), and anxiety sensitivity (t1,692=--3.69, P<.001, Cohen d=0.29). Conclusions: The findings provide a better understanding of the role of COVID-19 in amplifying cyberchondria. Based on these results, cyberchondria must be viewed as a significant public health issue. Importantly, increasing awareness about cyberchondria and online behavior at both the individual and collective levels must be prioritized to enhance preparedness and to reduce the adverse effects of current and future medical crises. ",
doi="10.2196/26285",
url="https://www.jmir.org/2021/6/e26285",
url="http://www.ncbi.nlm.nih.gov/pubmed/34014833"
}


@Article{info:doi/10.2196/27632,
author="Hou, Zhiyuan
and Tong, Yixin
and Du, Fanxing
and Lu, Linyao
and Zhao, Sihong
and Yu, Kexin
and Piatek, J. Simon
and Larson, J. Heidi
and Lin, Leesa",
title="Assessing COVID-19 Vaccine Hesitancy, Confidence, and Public Engagement: A Global Social Listening Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e27632",
keywords="COVID-19 vaccine",
keywords="hesitancy",
keywords="infoveillance",
keywords="infodemiology",
keywords="confidence",
keywords="acceptance",
keywords="engagement",
keywords="social media",
keywords="COVID-19",
abstract="Background: Monitoring public confidence and hesitancy is crucial for the COVID-19 vaccine rollout. Social media listening (infoveillance) can not only monitor public attitudes on COVID-19 vaccines but also assess the dissemination of and public engagement with these opinions. Objective: This study aims to assess global hesitancy, confidence, and public engagement toward COVID-19 vaccination. Methods: We collected posts mentioning the COVID-19 vaccine between June and July 2020 on Twitter from New York (United States), London (United Kingdom), Mumbai (India), and Sao Paulo (Brazil), and Sina Weibo posts from Beijing (China). In total, we manually coded 12,886 posts from the five global metropolises with high COVID-19 burdens, and after assessment, 7032 posts were included in the analysis. We manually double-coded these posts using a coding framework developed according to the World Health Organization's Confidence, Complacency, and Convenience model of vaccine hesitancy, and conducted engagement analysis to investigate public communication about COVID-19 vaccines on social media. Results: Among social media users, 36.4\% (571/1568) in New York, 51.3\% (738/1440) in London, 67.3\% (144/214) in Sao Paulo, 69.8\% (726/1040) in Mumbai, and 76.8\% (2128/2770) in Beijing indicated that they intended to accept a COVID-19 vaccination. With a high perceived risk of getting COVID-19, more tweeters in New York and London expressed a lack of confidence in vaccine safety, distrust in governments and experts, and widespread misinformation or rumors. Tweeters from Mumbai, Sao Paulo, and Beijing worried more about vaccine production and supply, whereas tweeters from New York and London had more concerns about vaccine distribution and inequity. Negative tweets expressing lack of vaccine confidence and misinformation or rumors had more followers and attracted more public engagement online. Conclusions: COVID-19 vaccine hesitancy is prevalent worldwide, and negative tweets attract higher engagement on social media. It is urgent to develop an effective vaccine campaign that boosts public confidence and addresses hesitancy for COVID-19 vaccine rollouts. ",
doi="10.2196/27632",
url="https://www.jmir.org/2021/6/e27632",
url="http://www.ncbi.nlm.nih.gov/pubmed/34061757"
}


@Article{info:doi/10.2196/29802,
author="Neely, Stephen
and Eldredge, Christina
and Sanders, Ron",
title="Health Information Seeking Behaviors on Social Media During the COVID-19 Pandemic Among American Social Networking Site Users: Survey Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="11",
volume="23",
number="6",
pages="e29802",
keywords="social media",
keywords="internet",
keywords="communication",
keywords="public health",
keywords="COVID-19",
keywords="usage",
keywords="United States",
keywords="information seeking",
keywords="web-based health information",
keywords="survey",
keywords="mistrust",
abstract="Background: In recent years, medical journals have emphasized the increasingly critical role that social media plays in the dissemination of public health information and disease prevention guidelines. However, platforms such as Facebook and Twitter continue to pose unique challenges for clinical health care providers and public health officials alike. In order to effectively communicate during public health emergencies, such as the COVID-19 pandemic, it is increasingly critical for health care providers and public health officials to understand how patients gather health-related information on the internet and adjudicate the merits of such information. Objective: With that goal in mind, we conducted a survey of 1003 US-based adults to better understand how health consumers have used social media to learn and stay informed about the COVID-19 pandemic, the extent to which they have relied on credible scientific information sources, and how they have gone about fact-checking pandemic-related information. Methods: A web-based survey was conducted with a sample that was purchased through an industry-leading market research provider. The results were reported with a 95\% confidence level and a margin of error of 3. Participants included 1003 US-based adults (aged ?18 years). Participants were selected via a stratified quota sampling approach to ensure that the sample was representative of the US population. Balanced quotas were determined (by region of the country) for gender, age, race, and ethnicity. Results: The results showed a heavy reliance on social media during the COVID-19 pandemic; more than three-quarters of respondents (762/1003, 76\%) reported that they have relied on social media at least ``a little,'' and 59.2\% (594/1003) of respondents indicated that they read information about COVID-19 on social media at least once per week. According to the findings, most social media users (638/1003, 63.6\%) were unlikely to fact-check what they see on the internet with a health professional, despite the high levels of mistrust in the accuracy of COVID-19--related information on social media. We also found a greater likelihood of undergoing vaccination among those following more credible scientific sources on social media during the pandemic ($\chi$216=50.790; $\phi$=0.258; P<.001). Conclusions: The findings suggest that health professionals will need to be both strategic and proactive when engaging with health consumers on social media if they hope to counteract the deleterious effects of misinformation and disinformation. Effective training, institutional support, and proactive collaboration can help health professionals adapt to the evolving patterns of health information seeking. ",
doi="10.2196/29802",
url="https://www.jmir.org/2021/6/e29802",
url="http://www.ncbi.nlm.nih.gov/pubmed/34043526"
}


@Article{info:doi/10.2196/24285,
author="Peng, Yuanyuan
and Li, Cuilian
and Rong, Yibiao
and Pang, Pui Chi
and Chen, Xinjian
and Chen, Haoyu",
title="Real-time Prediction of the Daily Incidence of COVID-19 in 215 Countries and Territories Using Machine Learning: Model Development and Validation",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e24285",
keywords="COVID-19",
keywords="daily incidence",
keywords="real-time prediction",
keywords="machine learning",
keywords="Google Trends",
keywords="infoveillance",
keywords="infodemiology",
keywords="digital health",
keywords="digital public health",
keywords="surveillance",
keywords="prediction",
keywords="incidence",
keywords="policy",
keywords="prevention",
keywords="model",
abstract="Background: Advanced prediction of the daily incidence of COVID-19 can aid policy making on the prevention of disease spread, which can profoundly affect people's livelihood. In previous studies, predictions were investigated for single or several countries and territories. Objective: We aimed to develop models that can be applied for real-time prediction of COVID-19 activity in all individual countries and territories worldwide. Methods: Data of the previous daily incidence and infoveillance data (search volume data via Google Trends) from 215 individual countries and territories were collected. A random forest regression algorithm was used to train models to predict the daily new confirmed cases 7 days ahead. Several methods were used to optimize the models, including clustering the countries and territories, selecting features according to the importance scores, performing multiple-step forecasting, and upgrading the models at regular intervals. The performance of the models was assessed using the mean absolute error (MAE), root mean square error (RMSE), Pearson correlation coefficient, and Spearman correlation coefficient. Results: Our models can accurately predict the daily new confirmed cases of COVID-19 in most countries and territories. Of the 215 countries and territories under study, 198 (92.1\%) had MAEs <10 and 187 (87.0\%) had Pearson correlation coefficients >0.8. For the 215 countries and territories, the mean MAE was 5.42 (range 0.26-15.32), the mean RMSE was 9.27 (range 1.81-24.40), the mean Pearson correlation coefficient was 0.89 (range 0.08-0.99), and the mean Spearman correlation coefficient was 0.84 (range 0.2-1.00). Conclusions: By integrating previous incidence and Google Trends data, our machine learning algorithm was able to predict the incidence of COVID-19 in most individual countries and territories accurately 7 days ahead. ",
doi="10.2196/24285",
url="https://www.jmir.org/2021/6/e24285",
url="http://www.ncbi.nlm.nih.gov/pubmed/34081607"
}


@Article{info:doi/10.2196/22999,
author="Tyrovolas, Stefanos
and Gin{\'e}-V{\'a}zquez, Iago
and Fern{\'a}ndez, Daniel
and Morena, Marianthi
and Koyanagi, Ai
and Janko, Mark
and Haro, Maria Josep
and Lin, Yang
and Lee, Paul
and Pan, William
and Panagiotakos, Demosthenes
and Molassiotis, Alex",
title="Estimating the COVID-19 Spread Through Real-time Population Mobility Patterns: Surveillance in Low- and Middle-Income Countries",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e22999",
keywords="COVID-19",
keywords="transmission",
keywords="digital public health",
keywords="social distancing",
keywords="policy",
keywords="mobile data",
keywords="estimate",
keywords="real-time",
keywords="pattern",
keywords="surveillance",
keywords="low and middle-income countries",
keywords="emerging countries",
keywords="database",
abstract="Background: On January 21, 2020, the World Health Organization reported the first case of severe acute respiratory syndrome coronavirus 2, which rapidly evolved to the COVID-19 pandemic. Since then, the virus has also rapidly spread among Latin American, Caribbean, and African countries. Objective: The first aim of this study is to identify new emerging COVID-19 clusters over time and space (from January 21 to mid-May 2020) in Latin American, Caribbean, and African regions, using a prospective space--time scan measurement approach. The second aim is to assess the impact of real-time population mobility patterns between January 21 and May 18, 2020, under the implemented government interventions, measurements, and policy restrictions on COVID-19 spread among those regions and worldwide. Methods: We created a global COVID-19 database, of 218 countries and territories, merging the World Health Organization daily case reports with other measures such as population density and country income levels for January 21 to May 18, 2020. A score of government policy interventions was created for low, intermediate, high, and very high interventions. The population's mobility patterns at the country level wereobtained from Google community mobility reports. The prospective space--time scan statistic method was applied in five time periods between January and May 2020, and a regression mixed model analysis was used. Results: We found that COVID-19 emerging clusters within these five periods of time increased from 7 emerging clusters to 28 by mid-May 2020. We also detected various increasing and decreasing relative risk estimates of COVID-19 spread among Latin American, Caribbean, and African countries within the period of analysis. Globally, population mobility to parks and similar leisure areas during at least a minimum of implemented intermediate-level control policies (when compared to low-level control policies) was related to accelerated COVID-19 spread. Results were almost consistent when regional stratified analysis was applied. In addition, worldwide population mobility due to working during high implemented control policies and very high implemented control policies, when compared to low-level control policies, was related to positive COVID-19 spread. Conclusions: The prospective space--time scan is an approach that low-income and middle-income countries could use to detect emerging clusters in a timely manner and implement specific control policies and interventions to slow down COVID-19 transmission. In addition, real-time population mobility obtained from crowdsourced digital data could be useful for current and future targeted public health and mitigation policies at a global and regional level. ",
doi="10.2196/22999",
url="https://www.jmir.org/2021/6/e22999",
url="http://www.ncbi.nlm.nih.gov/pubmed/33950850"
}


@Article{info:doi/10.2196/26692,
author="Rao, Ashwin
and Morstatter, Fred
and Hu, Minda
and Chen, Emily
and Burghardt, Keith
and Ferrara, Emilio
and Lerman, Kristina",
title="Political Partisanship and Antiscience Attitudes in Online Discussions About COVID-19: Twitter Content Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="14",
volume="23",
number="6",
pages="e26692",
keywords="COVID-19",
keywords="Twitter",
keywords="infodemiology",
keywords="infodemic",
keywords="infoveillance",
keywords="multidimensional polarization",
keywords="social media",
keywords="social network",
abstract="Background: The novel coronavirus pandemic continues to ravage communities across the United States. Opinion surveys identified the importance of political ideology in shaping perceptions of the pandemic and compliance with preventive measures. Objective: The aim of this study was to measure political partisanship and antiscience attitudes in the discussions about the pandemic on social media, as well as their geographic and temporal distributions. Methods: We analyzed a large set of tweets from Twitter related to the pandemic, collected between January and May 2020, and developed methods to classify the ideological alignment of users along the moderacy (hardline vs moderate), political (liberal vs conservative), and science (antiscience vs proscience) dimensions. Results: We found a significant correlation in polarized views along the science and political dimensions. Moreover, politically moderate users were more aligned with proscience views, while hardline users were more aligned with antiscience views. Contrary to expectations, we did not find that polarization grew over time; instead, we saw increasing activity by moderate proscience users. We also show that antiscience conservatives in the United States tended to tweet from the southern and northwestern states, while antiscience moderates tended to tweet from the western states. The proportion of antiscience conservatives was found to correlate with COVID-19 cases. Conclusions: Our findings shed light on the multidimensional nature of polarization and the feasibility of tracking polarized opinions about the pandemic across time and space through social media data. ",
doi="10.2196/26692",
url="https://www.jmir.org/2021/6/e26692",
url="http://www.ncbi.nlm.nih.gov/pubmed/34014831"
}


@Article{info:doi/10.2196/29036,
author="Oksa, Reetta
and Kaakinen, Markus
and Savela, Nina
and Hakanen, J. Jari
and Oksanen, Atte",
title="Professional Social Media Usage and Work Engagement Among Professionals in Finland Before and During the COVID-19 Pandemic: Four-Wave Follow-Up Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="15",
volume="23",
number="6",
pages="e29036",
keywords="COVID-19",
keywords="engagement",
keywords="mental health",
keywords="moderator",
keywords="predictor",
keywords="psychological distress",
keywords="social media",
keywords="social support",
keywords="support",
keywords="task resources",
keywords="usage",
keywords="work engagement",
abstract="Background: The COVID-19 pandemic has changed work life profoundly and concerns regarding the mental well-being of employees' have arisen. Organizations have made rapid digital advancements and have started to use new collaborative tools such as social media platforms overnight. Objective: Our study aimed to investigate how professional social media communication has affected work engagement before and during the COVID-19 pandemic and the role of perceived social support, task resources, and psychological distress as predictors and moderators of work engagement. Methods: Nationally representative longitudinal survey data were collected in 2019-2020, and 965 respondents participated in all 4 surveys. Measures included work engagement, perceived social support and task resources, and psychological distress. The data were analyzed using a hybrid linear regression model.? Results: Work engagement remained stable and only decreased in autumn 2020. Within-person changes in social media communication at work, social support, task resources, and psychological distress were all associated with work engagement. The negative association between psychological distress and work engagement was stronger in autumn 2020 than before the COVID-19 outbreak. Conclusions: The COVID-19 pandemic has exerted pressure on mental health at work. Fostering social support and task resources at work is important in maintaining work engagement. Social media communication could help maintain a supportive work environment. ",
doi="10.2196/29036",
url="https://www.jmir.org/2021/6/e29036",
url="http://www.ncbi.nlm.nih.gov/pubmed/34048356"
}


@Article{info:doi/10.2196/26956,
author="Taneja, L. Sonia
and Passi, Monica
and Bhattacharya, Sumona
and Schueler, A. Samuel
and Gurram, Sandeep
and Koh, Christopher",
title="Social Media and Research Publication Activity During Early Stages of the COVID-19 Pandemic: Longitudinal Trend Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="17",
volume="23",
number="6",
pages="e26956",
keywords="coronavirus",
keywords="COVID-19",
keywords="social media",
keywords="gastroenterology",
keywords="SARS-CoV-2",
keywords="research",
keywords="literature",
keywords="dissemination",
keywords="Twitter",
keywords="preprint",
abstract="Background: The COVID-19 pandemic has highlighted the importance of rapid dissemination of scientific and medical discoveries. Current platforms available for the distribution of scientific and clinical research data and information include preprint repositories and traditional peer-reviewed journals. In recent times, social media has emerged as a helpful platform to share scientific and medical discoveries. Objective: This study aimed to comparatively analyze activity on social media (specifically, Twitter) and that related to publications in the form of preprint and peer-reviewed journal articles in the context of COVID-19 and gastroenterology during the early stages of the COVID-19 pandemic. Methods: COVID-19--related data from Twitter (tweets and user data) and articles published in preprint servers (bioRxiv and medRxiv) as well as in the PubMed database were collected and analyzed during the first 6 months of the pandemic, from December 2019 through May 2020. Global and regional geographic and gastrointestinal organ--specific social media trends were compared to preprint and publication activity. Any relationship between Twitter activity and preprint articles published and that between Twitter activity and PubMed articles published overall, by organ system, and by geographic location were identified using Spearman's rank-order correlation. Results: Over the 6-month period, 73,079 tweets from 44,609 users, 7164 journal publications, and 4702 preprint publications were retrieved. Twitter activity (ie, number of tweets) peaked in March 2020, whereas preprint and publication activity (ie, number of articles published) peaked in April 2020. Overall, strong correlations were identified between trends in Twitter activity and preprint and publication activity (P<.001 for both). COVID-19 data across the three platforms mainly concentrated on pulmonology or critical care, but when analyzing the field of gastroenterology specifically, most tweets pertained to pancreatology, most publications focused on hepatology, and most preprints covered hepatology and luminal gastroenterology. Furthermore, there were significant positive associations between trends in Twitter and publication activity for all gastroenterology topics (luminal gastroenterology: P=.009; hepatology and inflammatory bowel disease: P=.006; gastrointestinal endoscopy: P=.007), except pancreatology (P=.20), suggesting that Twitter activity did not correlate with publication activity for this topic. Finally, Twitter activity was the highest in the United States (7331 tweets), whereas PubMed activity was the highest in China (1768 publications). Conclusions: The COVID-19 pandemic has highlighted the potential of social media as a vehicle for disseminating scientific information during a public health crisis. Sharing and spreading information on COVID-19 in a timely manner during the pandemic has been paramount; this was achieved at a much faster pace on social media, particularly on Twitter. Future investigation could demonstrate how social media can be used to augment and promote scholarly activity, especially as the world begins to increasingly rely on digital or virtual platforms. Scientists and clinicians should consider the use of social media in augmenting public awareness regarding their scholarly pursuits. ",
doi="10.2196/26956",
url="https://www.jmir.org/2021/6/e26956",
url="http://www.ncbi.nlm.nih.gov/pubmed/33974550"
}


@Article{info:doi/10.2196/28648,
author="Pollack, C. Catherine
and Gilbert-Diamond, Diane
and Alford-Teaster, A. Jennifer
and Onega, Tracy",
title="Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e28648",
keywords="telemedicine",
keywords="telehealth",
keywords="COVID-19 pandemic",
keywords="social media",
keywords="sentiment analysis",
keywords="Twitter",
keywords="COVID-19",
keywords="pandemic",
abstract="Background: The COVID-19 pandemic has necessitated a rapid shift in how individuals interact with and receive fundamental services, including health care. Although telemedicine is not a novel technology, previous studies have offered mixed opinions surrounding its utilization. However, there exists a dearth of research on how these opinions have evolved over the course of the current pandemic. Objective: This study aims to evaluate how the language and sentiment surrounding telemedicine has evolved throughout the COVID-19 pandemic. Methods: Tweets published between January 1, 2020, and April 24, 2021, containing at least one telemedicine-related and one COVID-19--related search term (``telemedicine-COVID'') were collected from the Twitter full archive search (N=351,718). A comparator sample containing only COVID-19 terms (``general-COVID'') was collected and sampled based on the daily distribution of telemedicine-COVID tweets. In addition to analyses of retweets and favorites, sentiment analysis was performed on both data sets in aggregate and within a subset of tweets receiving the top 100 most and least retweets. Results: Telemedicine gained prominence during the early stages of the pandemic (ie, March through May 2020) before leveling off and reaching a steady state from June 2020 onward. Telemedicine-COVID tweets had a 21\% lower average number of retweets than general-COVID tweets (incidence rate ratio 0.79, 95\% CI 0.63-0.99; P=.04), but there was no difference in favorites. A majority of telemedicine-COVID tweets (180,295/351,718, 51.3\%) were characterized as ``positive,'' compared to only 38.5\% (135,434/351,401) of general-COVID tweets (P<.001). This trend was also true on a monthly level from March 2020 through April 2021. The most retweeted posts in both telemedicine-COVID and general-COVID data sets were authored by journalists and politicians. Whereas the majority of the most retweeted posts within the telemedicine-COVID data set were positive (55/101, 54.5\%), a plurality of the most retweeted posts within the general-COVID data set were negative (44/89, 49.4\%; P=.01). Conclusions: During the COVID-19 pandemic, opinions surrounding telemedicine evolved to become more positive, especially when compared to the larger pool of COVID-19--related tweets. Decision makers should capitalize on these shifting public opinions to invest in telemedicine infrastructure and ensure its accessibility and success in a postpandemic world. ",
doi="10.2196/28648",
url="https://www.jmir.org/2021/6/e28648",
url="http://www.ncbi.nlm.nih.gov/pubmed/34086591"
}


@Article{info:doi/10.2196/26655,
author="Massey, Daisy
and Huang, Chenxi
and Lu, Yuan
and Cohen, Alina
and Oren, Yahel
and Moed, Tali
and Matzner, Pini
and Mahajan, Shiwani
and Caraballo, C{\'e}sar
and Kumar, Navin
and Xue, Yuchen
and Ding, Qinglan
and Dreyer, Rachel
and Roy, Brita
and Krumholz, Harlan",
title="Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="21",
volume="23",
number="6",
pages="e26655",
keywords="COVID-19",
keywords="public perception",
keywords="social media",
keywords="infodemiology",
keywords="infoveillance",
keywords="infodemic",
keywords="social media research",
keywords="social listening",
keywords="social media analysis",
keywords="natural language processing",
keywords="Reddit data",
keywords="Facebook data",
keywords="COVID-19 public health measures",
keywords="public health",
keywords="surveillance",
keywords="engagement",
keywords="United States",
keywords="cross-sectional",
keywords="Reddit",
keywords="Facebook",
keywords="behavior",
keywords="perception",
keywords="NLP",
abstract="Background: COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. Objective: The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic. Methods: Natural language processing (NLP) algorithms were used to identify COVID-19--related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States. Results: The final sample size included 9,065,733 posts, 70\% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69\%), compared with COVID-19 in general (n=3,390,139, 37\%) and COVID-19 public health measures (n=1,836,200, 20\%). Conclusions: There was a decline in COVID-19--related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue. ",
doi="10.2196/26655",
url="https://www.jmir.org/2021/6/e26655",
url="http://www.ncbi.nlm.nih.gov/pubmed/34086593"
}


@Article{info:doi/10.2196/24435,
author="Lyu, Chen Joanne
and Han, Le Eileen
and Luli, K. Garving",
title="COVID-19 Vaccine--Related Discussion on Twitter: Topic Modeling and Sentiment Analysis",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="29",
volume="23",
number="6",
pages="e24435",
keywords="COVID-19",
keywords="vaccine",
keywords="vaccination",
keywords="Twitter",
keywords="infodemiology",
keywords="infoveillance",
keywords="topic",
keywords="sentiment",
keywords="opinion",
keywords="discussion",
keywords="communication",
keywords="social media",
keywords="perception",
keywords="concern",
keywords="emotion",
abstract="Background: Vaccination is a cornerstone of the prevention of communicable infectious diseases; however, vaccines have traditionally met with public fear and hesitancy, and COVID-19 vaccines are no exception. Social media use has been demonstrated to play a role in the low acceptance of vaccines. Objective: The aim of this study is to identify the topics and sentiments in the public COVID-19 vaccine--related discussion on social media and discern the salient changes in topics and sentiments over time to better understand the public perceptions, concerns, and emotions that may influence the achievement of herd immunity goals. Methods: Tweets were downloaded from a large-scale COVID-19 Twitter chatter data set from March 11, 2020, the day the World Health Organization declared COVID-19 a pandemic, to January 31, 2021. We used R software to clean the tweets and retain tweets that contained the keywords vaccination, vaccinations, vaccine, vaccines, immunization, vaccinate, and vaccinated. The final data set included in the analysis consisted of 1,499,421 unique tweets from 583,499 different users. We used R to perform latent Dirichlet allocation for topic modeling as well as sentiment and emotion analysis using the National Research Council of Canada Emotion Lexicon. Results: Topic modeling of tweets related to COVID-19 vaccines yielded 16 topics, which were grouped into 5 overarching themes. Opinions about vaccination (227,840/1,499,421 tweets, 15.2\%) was the most tweeted topic and remained a highly discussed topic during the majority of the period of our examination. Vaccine progress around the world became the most discussed topic around August 11, 2020, when Russia approved the world's first COVID-19 vaccine. With the advancement of vaccine administration, the topic of instruction on getting vaccines gradually became more salient and became the most discussed topic after the first week of January 2021. Weekly mean sentiment scores showed that despite fluctuations, the sentiment was increasingly positive in general. Emotion analysis further showed that trust was the most predominant emotion, followed by anticipation, fear, sadness, etc. The trust emotion reached its peak on November 9, 2020, when Pfizer announced that its vaccine is 90\% effective. Conclusions: Public COVID-19 vaccine--related discussion on Twitter was largely driven by major events about COVID-19 vaccines and mirrored the active news topics in mainstream media. The discussion also demonstrated a global perspective. The increasingly positive sentiment around COVID-19 vaccines and the dominant emotion of trust shown in the social media discussion may imply higher acceptance of COVID-19 vaccines compared with previous vaccines. ",
doi="10.2196/24435",
url="https://www.jmir.org/2021/6/e24435",
url="http://www.ncbi.nlm.nih.gov/pubmed/34115608"
}


@Article{info:doi/10.2196/26004,
author="Ferrar, Jennifer
and Griffith, J. Gareth
and Skirrow, Caroline
and Cashdollar, Nathan
and Taptiklis, Nick
and Dobson, James
and Cree, Fiona
and Cormack, K. Francesca
and Barnett, H. Jennifer
and Munaf{\`o}, R. Marcus",
title="Developing Digital Tools for Remote Clinical Research: How to Evaluate the Validity and Practicality of Active Assessments in Field Settings",
journal="J Med Internet Res",
year="2021",
month="Jun",
day="18",
volume="23",
number="6",
pages="e26004",
keywords="digital assessment",
keywords="remote research",
keywords="measurement validity",
keywords="clinical outcomes",
keywords="ecological momentary assessment",
keywords="mobile phone",
doi="10.2196/26004",
url="https://www.jmir.org/2021/6/e26004",
url="http://www.ncbi.nlm.nih.gov/pubmed/34142972"
}