TY - JOUR AU - Kraaijkamp, M. Jules J. AU - van Dam van Isselt, F. Eléonore AU - Persoon, Anke AU - Versluis, Anke AU - Chavannes, H. Niels AU - Achterberg, P. Wilco PY - 2021/8/19 TI - eHealth in Geriatric Rehabilitation: Systematic Review of Effectiveness, Feasibility, and Usability JO - J Med Internet Res SP - e24015 VL - 23 IS - 8 KW - geriatric rehabilitation KW - eHealth KW - mHealth KW - digital health KW - effectiveness KW - feasibility KW - usability KW - systematic review N2 - Background: eHealth has the potential to improve outcomes such as physical activity or balance in older adults receiving geriatric rehabilitation. However, several challenges such as scarce evidence on effectiveness, feasibility, and usability hinder the successful implementation of eHealth in geriatric rehabilitation. Objective: The aim of this systematic review was to assess evidence on the effectiveness, feasibility, and usability of eHealth interventions in older adults in geriatric rehabilitation. Methods: We searched 7 databases for randomized controlled trials, nonrandomized studies, quantitative descriptive studies, qualitative research, and mixed methods studies that applied eHealth interventions during geriatric rehabilitation. Included studies investigated a combination of effectiveness, usability, and feasibility of eHealth in older patients who received geriatric rehabilitation, with a mean age of ?70 years. Quality was assessed using the Mixed Methods Appraisal Tool and a narrative synthesis was conducted using a harvest plot. Results: In total, 40 studies were selected, with clinical heterogeneity across studies. Of 40 studies, 15 studies (38%) found eHealth was at least as effective as non-eHealth interventions (56% of the 27 studies with a control group), 11 studies (41%) found eHealth interventions were more effective than non-eHealth interventions, and 1 study (4%) reported beneficial outcomes in favor of the non-eHealth interventions. Of 17 studies, 16 (94%) concluded that eHealth was feasible. However, high exclusion rates were reported in 7 studies of 40 (18%). Of 40 studies, 4 (10%) included outcomes related to usability and indicated that there were certain aging-related barriers to cognitive ability, physical ability, or perception, which led to difficulties in using eHealth. Conclusions: eHealth can potentially improve rehabilitation outcomes for older patients receiving geriatric rehabilitation. Simple eHealth interventions were more likely to be feasible for older patients receiving geriatric rehabilitation, especially, in combination with another non-eHealth intervention. However, a lack of evidence on usability might hamper the implementation of eHealth. eHealth applications in geriatric rehabilitation show promise, but more research is required, including research with a focus on usability and participation. UR - https://www.jmir.org/2021/8/e24015 UR - http://dx.doi.org/10.2196/24015 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420918 ID - info:doi/10.2196/24015 ER - TY - JOUR AU - Kim, Mi Chan AU - van der Heide, M. Esther AU - van Rompay, L. Thomas J. AU - Verkerke, J. Gijsbertus AU - Ludden, S. Geke D. PY - 2021/8/26 TI - Overview and Strategy Analysis of Technology-Based Nonpharmacological Interventions for In-Hospital Delirium Prevention and Reduction: Systematic Scoping Review JO - J Med Internet Res SP - e26079 VL - 23 IS - 8 KW - intensive care unit KW - delirium KW - delirium prevention KW - delirium reduction KW - delirium treatment KW - technology KW - technology-based intervention KW - strategy KW - nonpharmacological KW - systematic scoping review N2 - Background: Delirium prevention is crucial, especially in critically ill patients. Nonpharmacological multicomponent interventions for preventing delirium are increasingly recommended and technology-based interventions have been developed to support them. Despite the increasing number and diversity in technology-based interventions, there has been no systematic effort to create an overview of these interventions for in-hospital delirium prevention and reduction. Objective: This systematic scoping review was carried out to answer the following questions: (1) what are the technologies currently used in nonpharmacological technology-based interventions for preventing and reducing delirium? and (2) what are the strategies underlying these currently used technologies? Methods: A systematic search was conducted in Scopus and Embase between 2015 and 2020. A selection was made in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Studies were eligible if they contained any type of technology-based interventions and assessed delirium-/risk factor?related outcome measures in a hospital setting. Data extraction and quality assessment were performed using a predesigned data form. Results: A total of 31 studies were included and analyzed focusing on the types of technology and the strategies used in the interventions. Our review revealed 8 different technology types and 14 strategies that were categorized into the following 7 pathways: (1) restore circadian rhythm, (2) activate the body, (3) activate the mind, (4) induce relaxation, (5) provide a sense of security, (6) provide a sense of control, and (7) provide a sense of being connected. For all technology types, significant positive effects were found on either or both direct and indirect delirium outcomes. Several similarities were found across effective interventions: using a multicomponent approach or including components comforting the psychological needs of patients (eg, familiarity, distraction, soothing elements). Conclusions: Technology-based interventions have a high potential when multidimensional needs of patients (eg, physical, cognitive, emotional) are incorporated. The 7 pathways pinpoint starting points for building more effective technology-based interventions. Opportunities were discussed for transforming the intensive care unit into a healing environment as a powerful tool to prevent delirium. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020175874; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=175874 UR - https://www.jmir.org/2021/8/e26079 UR - http://dx.doi.org/10.2196/26079 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435955 ID - info:doi/10.2196/26079 ER - TY - JOUR AU - Wu, Y. Jania J. AU - Ahmad, Nurulhuda AU - Samuel, Miny AU - Logan, Susan AU - Mattar, Z. Citra N. PY - 2021/8/26 TI - The Influence of Web-Based Tools on Maternal and Neonatal Outcomes in Pregnant Adolescents or Adolescent Mothers: Mixed Methods Systematic Review JO - J Med Internet Res SP - e26786 VL - 23 IS - 8 KW - pregnancy in adolescence KW - teenagers KW - adolescents KW - pregnancy KW - postpartum KW - internet KW - digital health KW - digital media KW - new digital media KW - eHealth KW - social media KW - social network KW - communications media N2 - Background: Pregnant adolescent women increasingly seek support during pregnancy and the puerperium through digital platforms instead of the traditional support system of family, friends, and the community. However, it is uncertain whether digital, web-based tools are reliable and effective in providing information to the user on a variety of topics such as fetal development, pregnancy outcomes, delivery, and breastfeeding to improve maternal and infant outcomes. Objective: We aimed to identify web-based tools designed to promote knowledge, attitudes, and skills of pregnant adolescents or adolescent mothers and determine the efficacy of such web-based tools compared with conventional resources in promoting good pregnancy and infant outcomes. Methods: A systematic search was conducted using Medline, Scopus, CINAHL, and PsycINFO for articles published from January 2004 to November 2020 to identify randomized trials and observational studies that evaluated digital, web-based platforms to deliver resources to pregnant adolescents. All articles written in the author?s languages were included. Two authors independently reviewed abstracts and full-text articles for inclusion and assessed study quality. Risk of bias in each study was assessed using appropriate tools recommended by PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) and the Joanna Briggs Institute. We adopted a qualitative synthesis and presented the results in a narrative format due to the heterogenous nature of the studies. Results: Seven articles met the inclusion criteria and were analyzed. The majority of the studies were graded to be of low to moderate risk for bias. The research methodologies represented were varied, ranging from randomized (n=1) and nonrandomized controlled trials (n=1) and prospective cohort studies (n=1) to mixed methods studies (n=1) and longitudinal surveys (n=3). Four studies included active web-based interventions, and 3 described exposure to web-based tools, including the use of social media and/or other internet content. Web-based tools positively influenced treatment-seeking intentions (intervention 17.1%, control 11.5%, P=.003) and actual treatment-seeking behavior for depression among postpartum adolescents (intervention 14.1%, control 6.5%, P<.001). In contrast, readily available information on the internet may leave adolescents with increased anxiety. The critical difference lies in information curated by health care professionals specifically to address targeted concerns versus self-acquired data sourced from various websites. Conclusions: Despite almost universal web use, few studies have used this platform for health promotion and disease prevention. Social media interventions or web-based tools have the potential to positively influence both maternal and infant outcomes in adolescent pregnancy, but there is a need for more well-conducted studies to demonstrate the effectiveness of these support programs. The vastness of the information available on the web limits the ability of health care professionals to monitor or control sources of information sought by patients. Thus, it is important to create professionally curated platforms to prevent or limit exposure to potentially misleading or harmful information on the internet while imparting useful knowledge to the user. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020195854; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=195854 UR - https://www.jmir.org/2021/8/e26786 UR - http://dx.doi.org/10.2196/26786 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435961 ID - info:doi/10.2196/26786 ER - TY - JOUR AU - Vassolo, Santiago Roberto AU - Mac Cawley, Francisco Alejandro AU - Tortorella, Luz Guilherme AU - Fogliatto, Sanson Flavio AU - Tlapa, Diego AU - Narayanamurthy, Gopalakrishnan PY - 2021/8/26 TI - Hospital Investment Decisions in Healthcare 4.0 Technologies: Scoping Review and Framework for Exploring Challenges, Trends, and Research Directions JO - J Med Internet Res SP - e27571 VL - 23 IS - 8 KW - healthcare 4.0 KW - scoping review KW - investments KW - real options KW - health technology assessment KW - technological bundles KW - decision-makers KW - hospital KW - public health KW - technology KW - health technology KW - smart technology KW - hospital management KW - health care investment KW - decision making KW - new technologies N2 - Background: Alternative approaches to analyzing and evaluating health care investments in state-of-the-art technologies are being increasingly discussed in the literature, especially with the advent of Healthcare 4.0 (H4.0) technologies or eHealth. Such investments generally involve computer hardware and software that deal with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision-making. Besides, the use of these technologies significantly increases when addressed in bundles. However, a structured and holistic approach to analyzing investments in H4.0 technologies is not available in the literature. Objective: This study aims to analyze previous research related to the evaluation of H4.0 technologies in hospitals and characterize the most common investment approaches used. We propose a framework that organizes the research associated with hospitals? H4.0 technology investment decisions and suggest five main research directions on the topic. Methods: To achieve our goal, we followed the standard procedure for scoping reviews. We performed a search in the Crossref, PubMed, Scopus, and Web of Science databases with the keywords investment, health, industry 4.0, investment, health technology assessment, healthcare 4.0, and smart in the title, abstract, and keywords of research papers. We retrieved 5701 publications from all the databases. After removing papers published before 2011 as well as duplicates and performing further screening, we were left with 244 articles, from which 33 were selected after in-depth analysis to compose the final publication portfolio. Results: Our findings show the multidisciplinary nature of the research related to evaluating hospital investments in H4.0 technologies. We found that the most common investment approaches focused on cost analysis, single technology, and single decision-maker involvement, which dominate bundle analysis, H4.0 technology value considerations, and multiple decision-maker involvement. Conclusions: Some of our findings were unexpected, given the interrelated nature of H4.0 technologies and their multidimensional impact. Owing to the absence of a more holistic approach to H4.0 technology investment decisions, we identified five promising research directions for the topic: development of economic valuation methodologies tailored for H4.0 technologies; accounting for technology interrelations in the form of bundles; accounting for uncertainties in the process of evaluating such technologies; integration of administrative, medical, and patient perspectives into the evaluation process; and balancing and handling complexity in the decision-making process. UR - https://www.jmir.org/2021/8/e27571 UR - http://dx.doi.org/10.2196/27571 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435967 ID - info:doi/10.2196/27571 ER - TY - JOUR AU - Nazarian, Scarlet AU - Lam, Kyle AU - Darzi, Ara AU - Ashrafian, Hutan PY - 2021/8/27 TI - Diagnostic Accuracy of Smartwatches for the Detection of Cardiac Arrhythmia: Systematic Review and Meta-analysis JO - J Med Internet Res SP - e28974 VL - 23 IS - 8 KW - wearables KW - smartwatch KW - cardiac arrhythmia KW - atrial fibrillation KW - cardiology KW - mHealth KW - wearable devices KW - screening KW - diagnostics KW - accuracy N2 - Background: Significant morbidity, mortality, and financial burden are associated with cardiac rhythm abnormalities. Conventional investigative tools are often unsuccessful in detecting cardiac arrhythmias because of their episodic nature. Smartwatches have gained popularity in recent years as a health tool for the detection of cardiac rhythms. Objective: This study aims to systematically review and meta-analyze the diagnostic accuracy of smartwatches in the detection of cardiac arrhythmias. Methods: A systematic literature search of the Embase, MEDLINE, and Cochrane Library databases was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies reporting the use of a smartwatch for the detection of cardiac arrhythmia. Summary estimates of sensitivity, specificity, and area under the curve were attempted using a bivariate model for the diagnostic meta-analysis. Studies were examined for quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Results: A total of 18 studies examining atrial fibrillation detection, bradyarrhythmias and tachyarrhythmias, and premature contractions were analyzed, measuring diagnostic accuracy in 424,371 subjects in total. The signals analyzed by smartwatches were based on photoplethysmography. The overall sensitivity, specificity, and accuracy of smartwatches for detecting cardiac arrhythmias were 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97), and 97% (95% CI 0.96-0.99), respectively. The pooled positive predictive value and negative predictive value for detecting cardiac arrhythmias were 85% (95% CI 0.79-0.90) and 100% (95% CI 1.0-1.0), respectively. Conclusions: This review demonstrates the evolving field of digital disease detection. The current diagnostic accuracy of smartwatch technology for the detection of cardiac arrhythmias is high. Although the innovative drive of digital devices in health care will continue to gain momentum toward screening, the process of accurate evidence accrual and regulatory standards ready to accept their introduction is strongly needed. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020213237; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213237. UR - https://www.jmir.org/2021/8/e28974 UR - http://dx.doi.org/10.2196/28974 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448706 ID - info:doi/10.2196/28974 ER - TY - JOUR AU - Chaney, Cunard Sarah AU - Mechael, Patricia AU - Thu, Myo Nay AU - Diallo, S. Mamadou AU - Gachen, Carine PY - 2021/8/3 TI - Every Child on the Map: A Theory of Change Framework for Improving Childhood Immunization Coverage and Equity Using Geospatial Data and Technologies JO - J Med Internet Res SP - e29759 VL - 23 IS - 8 KW - geospatial data KW - immunization KW - health information systems KW - service delivery KW - equity mapping KW - theory KW - framework KW - children KW - vaccine KW - equity KW - geospatial KW - data KW - outcome KW - coverage KW - low- and middle-income KW - LMIC UR - https://www.jmir.org/2021/8/e29759 UR - http://dx.doi.org/10.2196/29759 UR - http://www.ncbi.nlm.nih.gov/pubmed/34342584 ID - info:doi/10.2196/29759 ER - TY - JOUR AU - Newman, Julliana AU - Liew, Andrew AU - Bowles, Jon AU - Soady, Kelly AU - Inglis, Steven PY - 2021/8/27 TI - Podcasts for the Delivery of Medical Education and Remote Learning JO - J Med Internet Res SP - e29168 VL - 23 IS - 8 KW - digital KW - hepatitis C virus KW - health care professionals KW - hepatology KW - HIV KW - continuous professional development KW - podcasts KW - remote learning KW - virology UR - https://www.jmir.org/2021/8/e29168 UR - http://dx.doi.org/10.2196/29168 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448719 ID - info:doi/10.2196/29168 ER - TY - JOUR AU - Sparidaens, Marie Ellen AU - Hermens, M. Rosella P. AU - Braat, M. Didi D. AU - Nelen, M. Willianne L. D. AU - Fleischer, Kathrin PY - 2021/8/3 TI - Web-Based Guidance Through Assisted Reproductive Technology (myFertiCare): Patient-Centered App Development and Qualitative Evaluation JO - J Med Internet Res SP - e25389 VL - 23 IS - 8 KW - eHealth KW - infertility KW - interactive KW - mobile apps KW - patient education KW - patient-centered care KW - personalized KW - topic N2 - Background: Providing patient-centered fertility care is known to improve quality of life and can reduce anxiety and depression. In a previous study, we established the need for a web-based app providing personalized information and interactive functionalities among couples undergoing intracytoplasmic sperm injection with surgically retrieved sperm. Objective: This study aimed to design, develop, and qualitatively evaluate a multifaceted web-based app for infertile couples undergoing intracytoplasmic sperm injection with surgically retrieved sperm during their treatment trajectory. Methods: The web-based app was developed in three phases: (1) we established a patient-centered functional design, (2) developed the app in collaboration with medical and technical professionals, and (3) qualitatively evaluated the app among couples using a think-aloud method. Results: The basis of the app is the couple?s visualized treatment trajectory. The app provides personalized and interactive functionalities; for example, customized information and communication options. During qualitative evaluation, myFertiCare was highly appreciated and received a median score of 8 out of 10. The main improvements made upon conclusion of the think-aloud sessions were related to faster login and easier app navigation. Conclusions: A patient-centered web-based app aimed at guiding couples through their fertility treatment course was systematically designed, developed, and positively evaluated by patients and medical and technical professionals. UR - https://www.jmir.org/2021/8/e25389 UR - http://dx.doi.org/10.2196/25389 UR - http://www.ncbi.nlm.nih.gov/pubmed/34342591 ID - info:doi/10.2196/25389 ER - TY - JOUR AU - Kershaw, Steph AU - Birrell, Louise AU - Deen, Hannah AU - Newton, C. Nicola AU - Stapinski, A. Lexine AU - Champion, E. Katrina AU - Kay-Lambkin, Frances AU - Teesson, Maree AU - Chapman, Cath PY - 2021/8/10 TI - Evaluation of a Digital Health Initiative in Illicit Substance Use: Cross-sectional Survey Study JO - J Med Internet Res SP - e29026 VL - 23 IS - 8 KW - methamphetamine KW - eHealth KW - substance-related disorders KW - internet KW - preventive psychiatry KW - health education KW - mobile phone N2 - Background: The Cracks in the Ice (CITI) community toolkit was developed to provide evidence-based, up-to-date information and resources about crystal methamphetamine to Australians. Given the high rates of internet use in the community and the potential for misinformation, CITI has the potential to play an important role in improving knowledge and challenging misconceptions surrounding crystal methamphetamine. Objective: This study aims to determine (1) whether the CITI toolkit is achieving its aim of disseminating evidence-based information and resources to people who use crystal methamphetamine, their family and friends, health professionals, and the general community and (2) examine the association between the use of CITI and the knowledge and attitudes about crystal methamphetamine. Methods: A cross-sectional web-based survey, open to Australian residents (aged ?18 years), was conducted from November 2018 to March 2019. People who had previously visited the website (referred to as ?website visitors? in this study) and those who had not (?naïve?) were recruited. At baseline, knowledge, attitudes, and demographics were assessed. CITI website visitors then completed a series of site evaluation questions, including the System Usability Scale (SUS), and naïve participants were asked to undertake a guided site tour of a replicated version of the site before completing the evaluation questions and repeating knowledge and attitude scales. Results: Of a total 2108 participants, 564 (26.7%) reported lifetime use of crystal methamphetamine, 434 (20.6%) were family/friends, 288 (13.7%) were health professionals, and 822 (38.9%) were community members. The average SUS score was 73.49 (SD 13.30), indicating good site usability. Health professionals reported significantly higher SUS scores than community members (P=.02) and people who used crystal methamphetamine (P<.001). Website visitors had significantly higher baseline knowledge than naïve participants (P<.001). Among naïve participants, knowledge scores increased following exposure to the website (mean 15.2, SE 0.05) compared to baseline (mean 14.4, SE 0.05; P<.001). The largest shifts in knowledge were observed for items related to prevalence, legal issues, and the effects of the drug. Stigmatizing attitude scores among the naïve group were significantly lower following exposure to CITI (mean 41.97, SE 0.21) compared to baseline (mean 44.3, SE 0.21; P<.001). Conclusions: This study provides an innovative evaluation of a national eHealth resource. CITI is achieving its aim of disseminating evidence-based, nonstigmatizing, and useful information and resources about crystal methamphetamine to key end user groups and has received good usability scores across its target groups. Interaction with CITI led to immediate improvements in knowledge about crystal methamphetamine and a decrease in stigmatizing attitudes. CITI demonstrates the important role of digital information and support platforms for translating evidence into practice and improving knowledge and reducing stigma. UR - https://www.jmir.org/2021/8/e29026 UR - http://dx.doi.org/10.2196/29026 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383690 ID - info:doi/10.2196/29026 ER - TY - JOUR AU - Albers, Eline AU - Nijhof, N. Linde AU - Berkelbach van der Sprenkel, E. Emma AU - van de Putte, M. Elise AU - Nijhof, L. Sanne AU - Knoop, Hans PY - 2021/8/13 TI - Effectiveness of Internet-Based Cognitive Behavior Therapy (Fatigue in Teenagers on the Internet) for Adolescents With Chronic Fatigue Syndrome in Routine Clinical Care: Observational Study JO - J Med Internet Res SP - e24839 VL - 23 IS - 8 KW - Fatigue in Teenagers on the Internet KW - cognitive behavior therapy KW - fatigue KW - chronic fatigue syndrome KW - adolescents KW - implementation N2 - Background: Internet-based cognitive behavior therapy (I-CBT) for adolescents with chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) has been shown to be effective in a randomized controlled trial (RCT; Fatigue in Teenagers on the Internet [FITNET]). FITNET can cause a significant reduction in fatigue and disability. Objective: We aimed to investigate whether FITNET treatment implemented in routine clinical care (IMP-FITNET) was as effective, using the outcomes of the FITNET RCT as the benchmark. Methods: Outcomes of CFS/ME adolescents who started IMP-FITNET between October 2012 and March 2018 as part of routine clinical care were compared to the outcomes in the FITNET RCT. The primary outcome was fatigue severity assessed posttreatment. The secondary outcomes were self-reported physical functioning, school attendance, and recovery rates. Clinically relevant deterioration was assessed posttreatment, and for this outcome, a face-to-face CBT trial was used as the benchmark. The attitude of therapists toward the usability of IMP-FITNET was assessed through semistructured interviews. The number of face-to-face consultations during IMP-FITNET was registered. Results: Of the 384 referred adolescents with CFS/ME, 244 (63.5%) started IMP-FITNET, 84 (21.9%) started face-to-face CBT, and 56 (14.6%) were not eligible for CBT. Posttreatment scores for fatigue severity (mean 26.0, SD 13.8), physical functioning (mean 88.2, SD 15.0), and full school attendance (mean 84.3, SD 26.5) fell within the 95% CIs of the FITNET RCT. Deterioration of fatigue and physical functioning after IMP-FITNET was observed at rates of 1.2% (n=3) and 4.1% (n=10), respectively, which is comparable to a waiting list condition (fatigue: 1.2% vs 5.7%, ?21=3.5, P=.06; physical functioning: 4.1% vs 11.4%, ?21=3.3, P=.07). Moreover, 41 (16.8%) IMP-FITNET patients made use of face-to-face consultations. Conclusions: IMP-FITNET is an effective and safe treatment for adolescents with CFS/ME in routine clinical care. UR - https://www.jmir.org/2021/8/e24839 UR - http://dx.doi.org/10.2196/24839 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397389 ID - info:doi/10.2196/24839 ER - TY - JOUR AU - Zhu, Zhihui AU - Li, Chenyu AU - Shen, Jinglun AU - Wu, Kaisheng AU - Li, Yuehuan AU - Liu, Kun AU - Zhang, Fan AU - Zhang, Zhenhua AU - Li, Yan AU - Han, Jie AU - Qin, Ying AU - Yang, Yu AU - Fan, Guangpu AU - Zhang, Huajun AU - Ding, Zheng AU - Xu, Dong AU - Chen, Yu AU - Zheng, Yingli AU - Zheng, Zhe AU - Meng, Xu AU - Zhang, Haibo PY - 2021/8/13 TI - New Internet-Based Warfarin Anticoagulation Management Approach After Mechanical Heart Valve Replacement: Prospective, Multicenter, Randomized Controlled Trial JO - J Med Internet Res SP - e29529 VL - 23 IS - 8 KW - RCT KW - warfarin KW - telemedicine KW - TTR KW - complication N2 - Background: Mechanical heart valve replacement (MHVR) is an effective method for the treatment of severe heart valve disease; however, it subjects patient to lifelong warfarin therapy after MHVR with the attendant risk of bleeding and thrombosis. Whether internet-based warfarin management reduces complications and improves patient quality of life remains unknown. Objective: This study aimed to compare the effects of internet-based warfarin management and the conventional approach in patients who received MHVR in order to provide evidence regarding alternative strategies for long-term anticoagulation. Methods: This was a prospective, multicenter, randomized, open-label, controlled clinical trial with a 1-year follow-up. Patients who needed long-term warfarin anticoagulation after MHVR were enrolled and then randomly divided into conventional and internet-based management groups. The percentage of time in the therapeutic range (TTR) was used as the primary outcome, while bleeding, thrombosis, and other events were the secondary outcomes. Results: A total of 721 patients were enrolled. The baseline characteristics did not reach statistical differences between the 2 groups, suggesting the random assignment was successful. As a result, the internet-based group showed a significantly higher TTR (mean 0.53, SD 0.24 vs mean 0.46, SD 0.21; P<.001) and fraction of time in the therapeutic range (mean 0.48, SD 0.22 vs mean 0.42, SD 0.19; P<.001) than did those in the conventional group. Furthermore, as expected, the anticoagulation complications, including the bleeding and embolic events had a lower frequency in the internet-based group than in the conventional group (6.94% vs 12.74%; P=.01). Logistic regression showed that internet-based management increased the TTR by 7% (odds ratio [OR] 1.07, 95% CI 1.05-1.09; P<.001) and reduced the bleeding and embolic risk by 6% (OR 0.94, 95% CI 0.92-0.96; P=.01). Moreover, low TTR was found to be a risk factor for bleeding and embolic events (OR 0.87, 95% CI 0.83-0.91; P=.005). Conclusions: The internet-based warfarin management is superior to the conventional method, as it can reduce the anticoagulation complications in patients who receive long-term warfarin anticoagulation after MHVR. Trial Registration: Chinese Clinical Trial Registry ChiCTR1800016204; http://www.chictr.org.cn/showproj.aspx?proj=27518 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-032949 UR - https://www.jmir.org/2021/8/e29529 UR - http://dx.doi.org/10.2196/29529 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397393 ID - info:doi/10.2196/29529 ER - TY - JOUR AU - Zhang, Jing AU - Tucker, Joseph AU - Tang, Weiming AU - Wang, Hongyi AU - Chu, Zhenxing AU - Hu, Qinghai AU - Huang, Xiaojie AU - Chen, Yaokai AU - Wang, Hui AU - He, Xiaoqing AU - Li, Yao AU - Zhang, Lukun AU - Hu, Zhili AU - Bao, Rantong AU - Li, Shangcao AU - Li, Hang AU - Ding, Haibo AU - Jiang, Yongjun AU - Geng, Wenqing AU - Xu, Junjie AU - Shang, Hong PY - 2021/8/27 TI - Internet-Based HIV Self-Testing Among Men Who Have Sex With Men Through Pre-exposure Prophylaxis: 3-Month Prospective Cohort Analysis From China JO - J Med Internet Res SP - e23978 VL - 23 IS - 8 KW - HIV self-testing KW - men who have sex with men KW - pre-exposure prophylaxis KW - secondary distribution KW - usage N2 - Background: Routine HIV testing accompanied with pre-exposure prophylaxis (PrEP) requires innovative support in a real-world setting. Objective: This study aimed to determine the usage of HIV self-testing (HIVST) kits and their secondary distribution to partners among men who have sex with men (MSM) in China, who use PrEP, in an observational study between 2018 and 2019. Methods: In 4 major cities in China, we prospectively followed-up MSM from the China Real-world oral PrEP demonstration study, which provides daily or on-demand PrEP for 12 months, to assess the usage and secondary distribution of HIVST on quarterly follow-ups. Half of the PrEP users were randomized to receive 2 HIVSTs per month in addition to quarterly facility-based HIV testing. We evaluated the feasibility of providing HIVST to PrEP users. Results: We recruited 939 MSM and randomized 471 to receive HIVST, among whom 235 (49.9%) were daily and 236 (50.1%) were on-demand PrEP users. At baseline, the median age was 29 years, 390 (82.0%) men had at least college-level education, and 119 (25.3%) had never undergone facility-based HIV testing before. Three months after PrEP initiation, 341 (74.5%) men had used the HIVST provided to them and found it very easy to use. Among them, 180 of 341 (52.8%) men had distributed the HIVST kits it to other MSM, and 132 (51.6%) among the 256 men who returned HIVST results reported that used it with their sexual partners at the onset of intercourse. Participants on daily PrEP were more likely to use HIVST (adjusted hazard ratio=1.3, 95% CI 1.0-1.6) and distribute HIVST kits (adjusted hazard ratio=1.3, 95% CI 1.1-1.7) than those using on-demand PrEP. Conclusions: MSM who used PrEP had a high rate of usage and secondary distribution of HIVST kits, especially among those on daily PrEP, which suggested high feasibility and necessity for HIVST after PrEP initiation. Assuming that fourth-generation HIVST kits are available, HIVST may be able to replace facility-based HIV testing to a certain extent. Trial Registration: Chinese Clinical Trial Registry ChiCTR1800020374; https://www.chictr.org.cn/showprojen.aspx?proj=32481 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-036231 UR - https://www.jmir.org/2021/8/e23978 UR - http://dx.doi.org/10.2196/23978 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448709 ID - info:doi/10.2196/23978 ER - TY - JOUR AU - Schaub, P. Michael AU - Tiburcio, Marcela AU - Martínez-Vélez, Nora AU - Ambekar, Atul AU - Bhad, Roshan AU - Wenger, Andreas AU - Baumgartner, Christian AU - Padruchny, Dzianis AU - Osipchik, Sergey AU - Poznyak, Vladimir AU - Rekve, Dag AU - Landi Moraes, Fabricio AU - Monezi Andrade, Luiz André AU - Oliveira Souza-Formigoni, Lucia Maria AU - PY - 2021/8/27 TI - The Effectiveness of a Web-Based Self-Help Program to Reduce Alcohol Use Among Adults With Drinking Patterns Considered Harmful, Hazardous, or Suggestive of Dependence in Four Low- and Middle-Income Countries: Randomized Controlled Trial JO - J Med Internet Res SP - e21686 VL - 23 IS - 8 KW - alcohol KW - internet KW - public health KW - self-help KW - World Health Organization N2 - Background: Given the scarcity of alcohol prevention and use disorder treatments in many low- and middle-income countries (LMICs), the World Health Organization has launched an eHealth portal that includes the web-based self-help program ?Alcohol e-Health.? Objective: We aimed to test the effectiveness of the Alcohol e-Health program in a randomized controlled trial. Methods: This was a two-arm, individually randomized, and controlled trial across four LMICs comparing the self-help program and a psychoeducation and internet access as usual waiting list. Participants were broadly recruited from community samples in Belarus, Brazil, India, and Mexico from January 2016 through January 2019. The primary outcome measure was change in the Alcohol Use Disorders Identification Test (AUDIT) score with a time frame of 6 months between baseline and follow-up. Secondary outcomes included self-reported numbers of standard drinks over the previous week and cessation of harmful or hazardous drinking (AUDIT score <8). Results: For this study, we recruited 1400 predominantly male (n=982, 70.1%) at least harmful or hazardous alcohol drinkers. The mean age was 37.6 years (SD 10.5). The participants were recruited from Brazil (n=587), Mexico (n=509), India (n=212), and Belarus (n=92). Overall, complete case analysis identified higher AUDIT changes in the intervention group (B=?4.18, 95% CI ?5.42 to ?2.93, P<.001, d=0.56) that were mirrored by changes in weekly standard drinks (B=?9.34, 95% CI ?15.90 to ?2.77, P=.005, d=0.28) and cessation rates for harmful or hazardous drinking (?21=14.56, N=561, P<.001). The supplementary intention-to-treat analyses largely confirmed these initial results. Conclusions: The expansion of the Alcohol e-Health program to other LMICs with underdeveloped alcohol prevention and treatment systems for alcohol use disorders should be considered after successful replication of the present results. Trial Registration: ISRCTN ISRCTN14037475; https://www.isrctn.com/ISRCTN14037475 International Registered Report Identifier (IRRID): RR2-10.1111/add.14034 UR - https://www.jmir.org/2021/8/e21686 UR - http://dx.doi.org/10.2196/21686 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448710 ID - info:doi/10.2196/21686 ER - TY - JOUR AU - van de Water, F. Loïs AU - van den Boorn, G. Héctor AU - Hoxha, Florian AU - Henselmans, Inge AU - Calff, M. Mart AU - Sprangers, G. Mirjam A. AU - Abu-Hanna, Ameen AU - Smets, A. Ellen M. AU - van Laarhoven, M. Hanneke W. PY - 2021/8/27 TI - Informing Patients With Esophagogastric Cancer About Treatment Outcomes by Using a Web-Based Tool and Training: Development and Evaluation Study JO - J Med Internet Res SP - e27824 VL - 23 IS - 8 KW - prediction tool KW - communication skills training KW - shared decision-making KW - risk communication KW - treatment outcomes KW - esophageal cancer KW - gastric cancer KW - patient-physician communication N2 - Background: Due to the increasing use of shared decision-making, patients with esophagogastric cancer play an increasingly important role in the decision-making process. To be able to make well-informed decisions, patients need to be adequately informed about treatment options and their outcomes, namely survival, side effects or complications, and health-related quality of life. Web-based tools and training programs can aid physicians in this complex task. However, to date, none of these instruments are available for use in informing patients with esophagogastric cancer about treatment outcomes. Objective: This study aims to develop and evaluate the feasibility of using a web-based prediction tool and supporting communication skills training to improve how physicians inform patients with esophagogastric cancer about treatment outcomes. By improving the provision of treatment outcome information, we aim to stimulate the use of information that is evidence-based, precise, and personalized to patient and tumor characteristics and is communicated in a way that is tailored to individual information needs. Methods: We designed a web-based, physician-assisted prediction tool?Source?to be used during consultations by using an iterative, user-centered approach. The accompanying communication skills training was developed based on specific learning objectives, literature, and expert opinions. The Source tool was tested in several rounds?a face-to-face focus group with 6 patients and survivors, semistructured interviews with 5 patients, think-aloud sessions with 3 medical oncologists, and interviews with 6 field experts. In a final pilot study, the Source tool and training were tested as a combined intervention by 5 medical oncology fellows and 3 esophagogastric outpatients. Results: The Source tool contains personalized prediction models and data from meta-analyses regarding survival, treatment side effects and complications, and health-related quality of life. The treatment outcomes were visualized in a patient-friendly manner by using pictographs and bar and line graphs. The communication skills training consisted of blended learning for clinicians comprising e-learning and 2 face-to-face sessions. Adjustments to improve both training and the Source tool were made according to feedback from all testing rounds. Conclusions: The Source tool and training could play an important role in informing patients with esophagogastric cancer about treatment outcomes in an evidence-based, precise, personalized, and tailored manner. The preliminary evaluation results are promising and provide valuable input for the further development and testing of both elements. However, the remaining uncertainty about treatment outcomes in patients and established habits in doctors, in addition to the varying trust in the prediction models, might influence the effectiveness of the tool and training in daily practice. We are currently conducting a multicenter clinical trial to investigate the impact that the combined tool and training have on the provision of information in the context of treatment decision-making. UR - https://www.jmir.org/2021/8/e27824 UR - http://dx.doi.org/10.2196/27824 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448703 ID - info:doi/10.2196/27824 ER - TY - JOUR AU - Bruggmann, Christel AU - Adjedj, Julien AU - Sardy, Sylvain AU - Muller, Olivier AU - Voirol, Pierre AU - Sadeghipour, Farshid PY - 2021/8/30 TI - Effects of the Interactive Web-Based Video ?Mon Coeur, Mon BASIC? on Drug Adherence of Patients With Myocardial Infarction: Randomized Controlled Trial JO - J Med Internet Res SP - e21938 VL - 23 IS - 8 KW - acute coronary syndrome KW - eHealth KW - drug adherence KW - mHealth KW - mobile phone N2 - Background: Secondary prevention strategies after acute coronary syndrome (ACS) presentation with the use of drug combinations are essential to reduce the recurrence of cardiovascular events. However, lack of drug adherence is known to be common in this population and to be related to treatment failure. To improve drug adherence, we developed the ?Mon Coeur, Mon BASIC? video. This online video has been specifically designed to inform patients about their disease and their current medications. Interactivity has been used to increase patient attention, and the video can also be viewed on smartphones and tablets. Objective: The objective of this study was to assess the long-term impact of an informative web-based video on drug adherence in patients admitted for an ACS. Methods: This randomized study was conducted with consecutive patients admitted to University Hospital of Lausanne for ACS. We randomized patients to an intervention group, which had access to the web-based video and a short interview with the pharmacist, and a control group receiving usual care. The primary outcome was the difference in drug adherence, assessed with the Adherence to Refills and Medication Scale (ARMS; 9 multiple-choice questions, scores ranging from 12 for perfect adherence to 48 for lack of adherence), between groups at 1, 3, and 6 months. We assessed the difference in ARMS score between both groups with the Wilcoxon rank sum test. Secondary outcomes were differences in knowledge, readmissions, and emergency room visits between groups and patients? satisfaction with the video. Results: Sixty patients were included at baseline. The median age of the participants was 59 years (IQR 49-69), and 85% (51/60) were male. At 1 month, 51 patients participated in the follow-up, 50 patients participated at 3 months, and 47 patients participated at 6 months. The mean ARMS scores at 1 and 6 months did not differ between the intervention and control groups (13.24 vs 13.15, 13.52 vs 13.68, respectively). At 3 months, this score was significantly lower in the intervention group than in the control group (12.54 vs 13.75; P=.03). We observed significant increases in knowledge from baseline to 1 and 3 months, but not to 6 months, in the intervention group. Readmissions and emergency room visits have been very rare, and the proportion was not different among groups. Patients in the intervention group were highly satisfied with the video. Conclusions: Despite a lower sample size than we expected to reach, we observed that the ?Mon Coeur, Mon BASIC? web-based interactive video improved patients? knowledge and seemed to have an impact on drug adherence. These results are encouraging, and the video will be offered to all patients admitted to our hospital with ACS. Trial Registration: ClinicalTrials.gov NCT03949608; https://clinicaltrials.gov/ct2/show/NCT03949608 UR - https://www.jmir.org/2021/8/e21938 UR - http://dx.doi.org/10.2196/21938 UR - http://www.ncbi.nlm.nih.gov/pubmed/34459744 ID - info:doi/10.2196/21938 ER - TY - JOUR AU - Clark, Viktor AU - Kim, Jung Sunny PY - 2021/8/3 TI - Ecological Momentary Assessment and mHealth Interventions Among Men Who Have Sex With Men: Scoping Review JO - J Med Internet Res SP - e27751 VL - 23 IS - 8 KW - mHealth KW - men who have sex with men KW - mobile health KW - interventions KW - mental health KW - sexual health KW - ecological momentary assessment KW - behavior N2 - Background: Ecological momentary assessment (EMA) is a research design that allows for the measurement of nearly instantaneous experiences within the participant?s natural environment. Using EMA can help improve recall bias, ecological validity, and patient engagement while enhancing personalization and the ubiquity of interventions. People that can benefit from the use of EMA are men who have sex with men (MSM). Previous EMA studies have been successful in capturing patterns of depression, anxiety, substance use, and risky sexual behavior. These findings are directly relevant to MSM, who have high rates of each of these psychological and behavioral outcomes. Although there is a driving force behind the growing literature surrounding EMAs among MSM, no synthesizing reviews yet exist. Objective: The aims of this study were to (1) synthesize the literature across fields on how EMA methods have been used among MSM, (2) better understand the feasibility and acceptability of EMA interventions among MSM, and (3) inform designs for future research studies on best evidence-based practices for EMA interventions. Methods: Based on 4 library databases, we conducted a scoping review of EMAs used within interventions among MSM. The eligibility criteria included peer-reviewed studies conducted in the United States and the use of EMA methodology in an intervention for MSM. Modeling after the Centers for Disease Control and Prevention?s Compendium of Evidence-Based Interventions as the framework, we applied a typology that used 8 distinct review criteria, for example, sample size, design of the intervention, random assignment, design of the follow-up investigation, rate of retention, and rate of engagement. Results: Our results (k=15, N=952) indicated a range of sample sizes; the smallest sample size was 12, while the largest sample size was 120. Of the 15 studies, 7 (47%) focused on outcomes related to substance use or outcomes related to psychological experiences. Of the 15 studies, 5 (33%) implemented an EMA intervention across 30 days. Of the 15 studies, 2 studies (13%) used random assignment, and 2 studies (13%) had quasi-experimental designs. Of the 15 studies, 10 studies (67%) reported acceptable retention rates greater than 70%. The outcomes that had event-contingent prompts (ie, prompts after engaging in substance use) were not as effective in engaging participants, with overall engagement rates as low as 37%. Conclusions: Our systematic scoping review indicates strong evidence that the EMA methodology is both feasible and acceptable at high rates among MSM, especially, when examining psychological and behavioral outcomes such as negative or positive affect, risky sexual behavior, or substance use. Further research on optimal designs of EMA interventions for MSM is warranted. UR - https://www.jmir.org/2021/8/e27751 UR - http://dx.doi.org/10.2196/27751 UR - http://www.ncbi.nlm.nih.gov/pubmed/34342585 ID - info:doi/10.2196/27751 ER - TY - JOUR AU - Brunelli, Laura AU - De Vita, Chiara AU - Cenedese, Fabrizio AU - Cinello, Michela AU - Paris, Marta AU - Samogizio, Francesca AU - Starec, Anja AU - Bava, Michele AU - Dal Cin, Margherita AU - Zanchiello, Sara AU - Stampalija, Tamara PY - 2021/8/10 TI - Gaps and Future Challenges of Italian Apps for Pregnancy and Postnatal Care: Systematic Search on App Stores JO - J Med Internet Res SP - e29151 VL - 23 IS - 8 KW - pregnancy KW - postnatal care KW - app KW - mHealth KW - mobile health KW - newborn N2 - Background: Despite the availability of thousands of health apps worldwide, when considering those addressing children?s first 1000 days of life, most apps fail to consider the continuity between the prenatal and postnatal stages, and their joint impact on maternal and child health. The reliability, quality, and effectiveness of these apps are largely unknown, and the provided content seems questionable in terms of completeness, updating, and trustworthiness. Objective: This study evaluates available Italian pregnancy and postnatal care apps to highlight the main gaps to be overcome and the resulting future challenges to be met in this mobile health?related field. Methods: A systematic search was conducted on the Apple App Store and Google Play Store, and basic information was collected for all identified apps. After deduplication and further selection based on the exclusion criteria, an in-depth analysis of each app was performed by two researchers independently. A 71-item six-domain questionnaire about the desirable features of apps was used to assess information, functionalities, and technical features, while the Mobile Application Rating Scale (MARS) was employed for app quality evaluation. Results: From an initial sample of 684 apps, 22 were deeply analyzed. Most apps did not fulfill the expectations, as just one achieved 50% of all desirable aspects. Postnatal care and counselling for both the mother and child was the least accomplished domain. Moreover, the quality of app information was generally rated more negatively than the quality of their functionality and esthetic features. The lacking aspects were information about methods for postpartum family planning and birth spacing (1/22, 5%) and immunization (2/22, 9%). Conclusions: The identified gaps could serve as a basis for designing and implementing increasingly high-quality, targeted, and effective apps for pregnancy and postnatal health care, which provide comprehensive, reliable, and evidence-based information, as well as appropriate esthetic and functional characteristics, with relevant implications in terms of maternal and newborn health prevention and promotion. UR - https://www.jmir.org/2021/8/e29151 UR - http://dx.doi.org/10.2196/29151 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383668 ID - info:doi/10.2196/29151 ER - TY - JOUR AU - Yang, Kyungmi AU - Oh, Dongryul AU - Noh, Myoung Jae AU - Yoon, Gyul Han AU - Sun, Jong-Mu AU - Kim, Kwan Hong AU - Zo, Ill Jae AU - Shim, Mog Young AU - Ko, Hyunyoung AU - Lee, Jungeun AU - Kim, Youngin PY - 2021/8/27 TI - Feasibility of an Interactive Health Coaching Mobile App to Prevent Malnutrition and Muscle Loss in Esophageal Cancer Patients Receiving Neoadjuvant Concurrent Chemoradiotherapy: Prospective Pilot Study JO - J Med Internet Res SP - e28695 VL - 23 IS - 8 KW - esophageal cancer KW - malnutrition KW - muscle loss KW - sarcopenia KW - mobile app KW - mHealth N2 - Background: Excessive muscle loss is an important prognostic factor in esophageal cancer patients undergoing neoadjuvant chemoradiotherapy (NACRT), as reported in our previous research. Objective: In this pilot study, we prospectively tested the feasibility of a health coaching mobile app for preventing malnutrition and muscle loss in this patient population. Methods: Between July 2019 and May 2020, we enrolled 38 male patients with esophageal cancer scheduled for NACRT. For 8 weeks from the start of radiotherapy (RT), the patients used Noom, a health coaching mobile app that interactively provided online advice about food intake, exercise, and weight changes. The skeletal muscle index (SMI) measured based on computed tomography and nutrition-related laboratory markers were assessed before and after RT. We evaluated the changes in the SMI, nutrition, and inflammatory factors between the patient group that used the mobile app (mHealth group) and our previous study cohort (usual care group). Additionally, we analyzed the factors associated with walk steps recorded in the app. Results: Two patients dropped out of the study (no app usage; treatment changed to a definitive aim). The use (or activation) of the app was noted in approximately 70% (25/36) of the patients until the end of the trial. Compared to the 1:2 matched usual care group by propensity scores balanced with their age, primary tumor location, tumor stage, pre-RT BMI, and pre-RT SMI level, 30 operable patients showed less aggravation of the prognostic nutritional index (PNI) (?6.7 vs ?9.8; P=.04). However, there was no significant difference in the SMI change or the number of patients with excessive muscle loss (?SMI/50 days >10%). In patients with excessive muscle loss, the walk steps significantly decreased in the last 4 weeks compared to those in the first 4 weeks. Age affected the absolute number of walk steps (P=.01), whereas pre-RT sarcopenia was related to the recovery of the reduced walk steps (P=.03). Conclusions: For esophageal cancer patients receiving NACRT, a health care mobile app helped nutritional self-care with less decrease in the PNI, although it did not prevent excessive muscle loss. An individualized care model with proper exercise as well as nutritional support may be required to reduce muscle loss and malnutrition. UR - https://www.jmir.org/2021/8/e28695 UR - http://dx.doi.org/10.2196/28695 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448714 ID - info:doi/10.2196/28695 ER - TY - JOUR AU - Laestadius, I. Linnea AU - Craig, A. Katherine AU - Campos-Castillo, Celeste PY - 2021/8/10 TI - Perceptions of Alerts Issued by Social Media Platforms in Response to Self-injury Posts Among Latinx Adolescents: Qualitative Analysis JO - J Med Internet Res SP - e28931 VL - 23 IS - 8 KW - adolescents KW - social media KW - mental health KW - NSSI KW - race and ethnicity KW - mobile phone N2 - Background: There is growing interest in using social media data to detect and address nonsuicidal self-injury (NSSI) among adolescents. Adolescents often do not seek clinical help for NSSI and may adopt strategies to obscure detection; therefore, social media platforms may be able to facilitate early detection and treatment by using machine learning models to screen posts for harmful content and subsequently alert adults. However, such efforts have raised privacy and ethical concerns among health researchers. Little is currently known about how adolescents perceive these efforts. Objective: The aim of this study is to examine perceptions of automated alerts for NSSI posts on social media among Latinx adolescents, who are at risk for NSSI yet are underrepresented in both NSSI and health informatics research. In addition, we considered their perspectives on preferred recipients of automated alerts. Methods: We conducted semistructured, qualitative interviews with 42 Latinx adolescents between the ages of 13 and 17 years who were recruited from a nonprofit organization serving the Latinx community in Milwaukee, Wisconsin. The Latinx population in Milwaukee is largely of Mexican descent. All interviews were conducted between June and July 2019. Transcripts were analyzed using framework analysis to discern their perceptions of automated alerts sent by social media platforms and potential alert recipients. Results: Participants felt that automated alerts would make adolescents safer and expedite aid before the situation escalated. However, some worried that hyperbolic statements would generate false alerts and instigate conflicts. Interviews revealed strong opinions about ideal alert recipients. Parents were most commonly endorsed, but support was conditional on perceptions that the parent would respond appropriately. Emergency services were judged as safer but inappropriate for situations considered lower risk. Alerts sent to school staff generated the strongest privacy concerns. Altogether, the preferred alert recipients varied by individual adolescents and perceived risks in the situation. None raised ethical concerns about the collection, analysis, or storage of personal information regarding their mental health status. Conclusions: Overall, Latinx adolescents expressed broad support for automated alerts for NSSI on social media, which indicates opportunities to address NSSI. However, these efforts should be co-constructed with adolescents to ensure that preferences and needs are met, as well as embedded within broader approaches for addressing structural and cultural barriers to care. UR - https://www.jmir.org/2021/8/e28931 UR - http://dx.doi.org/10.2196/28931 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383683 ID - info:doi/10.2196/28931 ER - TY - JOUR AU - Omar Bali, Ahmed AU - Omer, Emad AU - Abdulridha, Kawa AU - Ahmad, Ramazan Araz PY - 2021/8/19 TI - Psychological Violence Against Arab Women in the Context of Social Media: Web-Based Questionnaire Study JO - J Med Internet Res SP - e27944 VL - 23 IS - 8 KW - psychological KW - violence KW - Arab women KW - social media KW - feminism KW - sociology KW - abuse KW - oppression KW - self-esteem N2 - Background: Social media provides women with varying platforms to express themselves, show their talents, communicate and expand their social relationships, and break the shackles imposed by their societies. Theoretically, social media can play a significant role in developing women?s freedom and decreasing social pressures; nonetheless, women continue to face violence during the social media era mainly in the form of psychological violence. Objective: This study aims to conduct an empirical in-depth analysis of how the digital space, particularly social media, provides men with new opportunities to surveil, restrict, harass, and intimidate feminists in Arab countries. Methods: This study includes an empirical survey to investigate what Arab women think are the causes and types of violence wielded against them and their perspectives on the impact of that violence. This study used a web-based questionnaire administered through Google Forms (n=1312) with responses from Arab women aged 15 years and above from all Arab countries. Results: We found that most Arab women feared posting an actual photograph of themselves on their social media accounts and only approximately one-third (490/1312, 37.3%) did so. Most women indicated that they encountered sexual harassment regardless of their age. Furthermore, most women were not aware of the legal aspects of this crime and even those who were aware indicated that they would not press charges for several reasons, including bringing dishonor upon their families, the time-consuming nature of litigation, and fear of revenge. Conclusions: This study shows that young and less educated women are more vulnerable to abuse from either social media users or being condemned by their families. This has several effects, including lower self-esteem and hesitancy in seeking a job, feelings of mistrust and fear, cynicism, anxiety, depression, and sleep disorders. These issues hold women back from using social media in positive ways and some consider leaving social media. UR - https://www.jmir.org/2021/8/e27944 UR - http://dx.doi.org/10.2196/27944 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420919 ID - info:doi/10.2196/27944 ER - TY - JOUR AU - Qin, Lei AU - Zhang, Xiaomei AU - Wu, Anlin AU - Miser, S. James AU - Liu, Yen-Lin AU - Hsu, C. Jason AU - Shia, Ben-Chang AU - Ye, Linglong PY - 2021/8/27 TI - Association Between Social Media Use and Cancer Screening Awareness and Behavior for People Without a Cancer Diagnosis: Matched Cohort Study JO - J Med Internet Res SP - e26395 VL - 23 IS - 8 KW - social media KW - cancer screening awareness KW - cancer screening behavior KW - gender-specific effects KW - propensity-score matching KW - general population N2 - Background: The use of social media in communications regarding cancer prevention is rapidly growing. However, less is known about the general population?s social media use related to cancer screening awareness and behavior for different cancers. Objective: We aimed to examine the relationship between social media use and cancer screening awareness and behavior among people without a cancer diagnosis. Methods: Data were collected from the Health Information National Trends Survey 5 Cycle 1 to 3 in the United States (n=12,227). Our study included 10,124 participants without a cancer diagnosis and 3 measures of screening awareness (those who had heard of hepatitis C virus [HCV], human papillomavirus [HPV], and the HPV vaccine) and 4 measures of behavior (those who had prostate-specific antigen tests, Papanicolaou tests for cervical cancer, as well as breast cancer and colon cancer tests). Propensity-score matching was conducted to adjust for the sociodemographic variables between the social media user and nonuser participants. Multivariable logistic regression was used to assess the association of social media use by gender. Jackknife replicate weights were incorporated into the analyses. Results: Of the 3794 matched participants, 1861 (57.6% weighted) were male, and the mean age was 55.5 (SD 0.42) years. Compared to social media nonusers, users were more likely to have heard of HCV (adjusted odds ratio [aOR]=2.27, 95% CI, 1.29-3.98 and aOR=2.86, 95% CI, 1.51-5.40, for male and female users, respectively) and HPV (aOR=1.82, 95% CI, 1.29-2.58 and aOR=2.35, 95% CI, 1.65-3.33, for male and female users, respectively). In addition, female users were more likely to have heard of the HPV vaccine (aOR=2.06, 95% CI, 1.41-3.00). No significant associations were found between social media use and prostate-specific antigen tests in males, Papanicolaou tests and breast cancer tests in females, or colon cancer tests in both male and female users. Conclusions: While social media services can potentially promote cancer screening awareness in the general population, but they did not improve screening behavior after adjusting for socioeconomic status. These findings strengthened our understanding of social media use in targeting health communications for different cancers. UR - https://www.jmir.org/2021/8/e26395 UR - http://dx.doi.org/10.2196/26395 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448708 ID - info:doi/10.2196/26395 ER - TY - JOUR AU - Fu, Guanghui AU - Song, Changwei AU - Li, Jianqiang AU - Ma, Yue AU - Chen, Pan AU - Wang, Ruiqian AU - Yang, Xiang Bing AU - Huang, Zhisheng PY - 2021/8/26 TI - Distant Supervision for Mental Health Management in Social Media: Suicide Risk Classification System Development Study JO - J Med Internet Res SP - e26119 VL - 23 IS - 8 KW - deep learning KW - distant supervision KW - mental health KW - crisis prevention N2 - Background: Web-based social media provides common people with a platform to express their emotions conveniently and anonymously. There have been nearly 2 million messages in a particular Chinese social media data source, and several thousands more are generated each day. Therefore, it has become impossible to analyze these messages manually. However, these messages have been identified as an important data source for the prevention of suicide related to depression disorder. Objective: We proposed in this paper a distant supervision approach to developing a system that can automatically identify textual comments that are indicative of a high suicide risk. Methods: To avoid expensive manual data annotations, we used a knowledge graph method to produce approximate annotations for distant supervision, which provided a basis for a deep learning architecture that was built and refined by interactions with psychology experts. There were three annotation levels, as follows: free annotations (zero cost), easy annotations (by psychology students), and hard annotations (by psychology experts). Results: Our system was evaluated accordingly and showed that its performance at each level was promising. By combining our system with several important psychology features from user blogs, we obtained a precision of 80.75%, a recall of 75.41%, and an F1 score of 77.98% for the hardest test data. Conclusions: In this paper, we proposed a distant supervision approach to develop an automatic system that can classify high and low suicide risk based on social media comments. The model can therefore provide volunteers with early warnings to prevent social media users from committing suicide. UR - https://www.jmir.org/2021/8/e26119 UR - http://dx.doi.org/10.2196/26119 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435964 ID - info:doi/10.2196/26119 ER - TY - JOUR AU - Beames, R. Joanne AU - Johnston, Lara AU - O'Dea, Bridianne AU - Torok, Michelle AU - Christensen, Helen AU - Boydell, M. Katherine AU - Werner-Seidler, Aliza PY - 2021/8/27 TI - Factors That Help and Hinder the Implementation of Digital Depression Prevention Programs: School-Based Cross-sectional Study JO - J Med Internet Res SP - e26223 VL - 23 IS - 8 KW - secondary school KW - depression KW - prevention KW - digital KW - barrier KW - facilitator KW - teacher KW - counselor KW - principal KW - student N2 - Background: Digital prevention programs that are delivered in a school environment can inoculate young people against depression. However, little is known about the school-based factors that help and hinder the implementation of these programs. Staff members are integral for supporting mental health programs in schools and are likely to have a wealth of expertise and knowledge about the factors that affect implementation. Objective: The primary objective of this study was to explore the barriers and facilitators to implementing a digital depression prevention program in Australian secondary schools with teachers, counselors, and principals. The secondary objective was to explore variations in these factors across different school contexts, including the school type (government or nongovernment), location (capital city, regional/or rural areas), and socioeconomic status (SES) (low, medium, high). Methods: This quantitative cross-sectional survey study assessed the barriers and facilitators to implementing a hypothetical digital prevention program in Australian schools. The survey was taken by 97 teachers (average age 38.3 years), 93 counselors (average age 39.5 years), and 11 principals (average age 50.9 years) across Australia between November 2017 and July 2018. Results: A range of barriers and facilitators relating to logistics and resources, staff support, and program factors were endorsed by the surveyed staff. Consistent with prior research, common barriers included a lack of time and resources (ie, staff and rooms). These barriers were particularly evident in government, rural/regional, and low socioeconomic schools. Other barriers were specific to digital delivery, including privacy issues and a lack of clarity around staff roles and responsibilities. Facilitators included upskilling staff through training, embedding the program into the curriculum, and other program factors including universal delivery, screening of students? mental health, and clear referral pathways. Knowledge about the program efficacy was also perceived as important by a large proportion of the respondents. Conclusions: The digital depression prevention program was perceived as suitable for use within different schools in Australia, although certain factors need to be considered to enable effective implementation. Logistics and resources, support, and program factors were identified as particularly important for school-based implementation. To maximize the effectiveness in delivering digital programs, implementation may need to be tailored to the staff roles and school types. UR - https://www.jmir.org/2021/8/e26223 UR - http://dx.doi.org/10.2196/26223 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448701 ID - info:doi/10.2196/26223 ER - TY - JOUR AU - Du, Jingcheng AU - Preston, Sharice AU - Sun, Hanxiao AU - Shegog, Ross AU - Cunningham, Rachel AU - Boom, Julie AU - Savas, Lara AU - Amith, Muhammad AU - Tao, Cui PY - 2021/8/5 TI - Using Machine Learning?Based Approaches for the Detection and Classification of Human Papillomavirus Vaccine Misinformation: Infodemiology Study of Reddit Discussions JO - J Med Internet Res SP - e26478 VL - 23 IS - 8 KW - HPV vaccine KW - social media KW - misinformation KW - infodemiology KW - infoveillance KW - deep learning KW - Reddit KW - machine learning N2 - Background: The rapid growth of social media as an information channel has made it possible to quickly spread inaccurate or false vaccine information, thus creating obstacles for vaccine promotion. Objective: The aim of this study is to develop and evaluate an intelligent automated protocol for identifying and classifying human papillomavirus (HPV) vaccine misinformation on social media using machine learning (ML)?based methods. Methods: Reddit posts (from 2007 to 2017, N=28,121) that contained keywords related to HPV vaccination were compiled. A random subset (2200/28,121, 7.82%) was manually labeled for misinformation and served as the gold standard corpus for evaluation. A total of 5 ML-based algorithms, including a support vector machine, logistic regression, extremely randomized trees, a convolutional neural network, and a recurrent neural network designed to identify vaccine misinformation, were evaluated for identification performance. Topic modeling was applied to identify the major categories associated with HPV vaccine misinformation. Results: A convolutional neural network model achieved the highest area under the receiver operating characteristic curve of 0.7943. Of the 28,121 Reddit posts, 7207 (25.63%) were classified as vaccine misinformation, with discussions about general safety issues identified as the leading type of misinformed posts (2666/7207, 36.99%). Conclusions: ML-based approaches are effective in the identification and classification of HPV vaccine misinformation on Reddit and may be generalizable to other social media platforms. ML-based methods may provide the capacity and utility to meet the challenge involved in intelligent automated monitoring and classification of public health misinformation on social media platforms. The timely identification of vaccine misinformation on the internet is the first step in misinformation correction and vaccine promotion. UR - https://www.jmir.org/2021/8/e26478 UR - http://dx.doi.org/10.2196/26478 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383667 ID - info:doi/10.2196/26478 ER - TY - JOUR AU - Tri Sakti, Muhammad Andi AU - Mohamad, Emma AU - Azlan, Anis Arina PY - 2021/8/9 TI - Mining of Opinions on COVID-19 Large-Scale Social Restrictions in Indonesia: Public Sentiment and Emotion Analysis on Online Media JO - J Med Internet Res SP - e28249 VL - 23 IS - 8 KW - large-scale social restrictions KW - social media KW - public sentiment KW - Twitter KW - COVID-19 KW - infodemiology KW - infoveillance N2 - Background: One of the successful measures to curb COVID-19 spread in large populations is the implementation of a movement restriction order. Globally, it was observed that countries implementing strict movement control were more successful in controlling the spread of the virus as compared with those with less stringent measures. Society?s adherence to the movement control order has helped expedite the process to flatten the pandemic curve as seen in countries such as China and Malaysia. At the same time, there are countries facing challenges with society?s nonconformity toward movement restriction orders due to various claims such as human rights violations as well as sociocultural and economic issues. In Indonesia, society?s adherence to its large-scale social restrictions (LSSRs) order is also a challenge to achieve. Indonesia is regarded as among the worst in Southeast Asian countries in terms of managing the spread of COVID-19. It is proven by the increased number of daily confirmed cases and the total number of deaths, which was more than 6.21% (1351/21,745) of total active cases as of May 2020. Objective: The aim of this study was to explore public sentiments and emotions toward the LSSR and identify issues, fear, and reluctance to observe this restriction among the Indonesian public. Methods: This study adopts a sentiment analysis method with a supervised machine learning approach on COVID-19-related posts on selected media platforms (Twitter, Facebook, Instagram, and YouTube). The analysis was also performed on COVID-19-related news contained in more than 500 online news platforms recognized by the Indonesian Press Council. Social media posts and news originating from Indonesian online media between March 31 and May 31, 2020, were analyzed. Emotion analysis on Twitter platform was also performed to identify collective public emotions toward the LSSR. Results: The study found that positive sentiment surpasses other sentiment categories by 51.84% (n=1,002,947) of the total data (N=1,934,596) collected via the search engine. Negative sentiment was recorded at 35.51% (686,892/1,934,596) and neutral sentiment at 12.65% (244,757/1,934,596). The analysis of Twitter posts also showed that the majority of public have the emotion of ?trust? toward the LSSR. Conclusions: Public sentiment toward the LSSR appeared to be positive despite doubts on government consistency in executing the LSSR. The emotion analysis also concluded that the majority of people believe in LSSR as the best method to break the chain of COVID-19 transmission. Overall, Indonesians showed trust and expressed hope toward the government?s ability to manage this current global health crisis and win against COVID-19. UR - https://www.jmir.org/2021/8/e28249 UR - http://dx.doi.org/10.2196/28249 UR - http://www.ncbi.nlm.nih.gov/pubmed/34280116 ID - info:doi/10.2196/28249 ER - TY - JOUR AU - Rabiolo, Alessandro AU - Alladio, Eugenio AU - Morales, Esteban AU - McNaught, Ian Andrew AU - Bandello, Francesco AU - Afifi, A. Abdelmonem AU - Marchese, Alessandro PY - 2021/8/11 TI - Forecasting the COVID-19 Epidemic by Integrating Symptom Search Behavior Into Predictive Models: Infoveillance Study JO - J Med Internet Res SP - e28876 VL - 23 IS - 8 KW - Google Trends KW - symptoms KW - coronavirus KW - SARS-CoV-2 KW - big data KW - time series KW - predictive models KW - Shiny web application KW - infodemiology KW - infoveillance KW - digital health KW - COVID-19 N2 - Background: Previous studies have suggested associations between trends of web searches and COVID-19 traditional metrics. It remains unclear whether models incorporating trends of digital searches lead to better predictions. Objective: The aim of this study is to investigate the relationship between Google Trends searches of symptoms associated with COVID-19 and confirmed COVID-19 cases and deaths. We aim to develop predictive models to forecast the COVID-19 epidemic based on a combination of Google Trends searches of symptoms and conventional COVID-19 metrics. Methods: An open-access web application was developed to evaluate Google Trends and traditional COVID-19 metrics via an interactive framework based on principal component analysis (PCA) and time series modeling. The application facilitates the analysis of symptom search behavior associated with COVID-19 disease in 188 countries. In this study, we selected the data of nine countries as case studies to represent all continents. PCA was used to perform data dimensionality reduction, and three different time series models (error, trend, seasonality; autoregressive integrated moving average; and feed-forward neural network autoregression) were used to predict COVID-19 metrics in the upcoming 14 days. The models were compared in terms of prediction ability using the root mean square error (RMSE) of the first principal component (PC1). The predictive abilities of models generated with both Google Trends data and conventional COVID-19 metrics were compared with those fitted with conventional COVID-19 metrics only. Results: The degree of correlation and the best time lag varied as a function of the selected country and topic searched; in general, the optimal time lag was within 15 days. Overall, predictions of PC1 based on both search terms and COVID-19 traditional metrics performed better than those not including Google searches (median 1.56, IQR 0.90-2.49 versus median 1.87, IQR 1.09-2.95, respectively), but the improvement in prediction varied as a function of the selected country and time frame. The best model varied as a function of country, time range, and period of time selected. Models based on a 7-day moving average led to considerably smaller RMSE values as opposed to those calculated with raw data (median 0.90, IQR 0.50-1.53 versus median 2.27, IQR 1.62-3.74, respectively). Conclusions: The inclusion of digital online searches in statistical models may improve the nowcasting and forecasting of the COVID-19 epidemic and could be used as one of the surveillance systems of COVID-19 disease. We provide a free web application operating with nearly real-time data that anyone can use to make predictions of outbreaks, improve estimates of the dynamics of ongoing epidemics, and predict future or rebound waves. UR - https://www.jmir.org/2021/8/e28876 UR - http://dx.doi.org/10.2196/28876 UR - http://www.ncbi.nlm.nih.gov/pubmed/34156966 ID - info:doi/10.2196/28876 ER - TY - JOUR AU - Effenberger, Maria AU - Kronbichler, Andreas AU - Bettac, Erica AU - Grabherr, Felix AU - Grander, Christoph AU - Adolph, Erik Timon AU - Mayer, Gert AU - Zoller, Heinz AU - Perco, Paul AU - Tilg, Herbert PY - 2021/8/17 TI - Using Infodemiology Metrics to Assess Public Interest in Liver Transplantation: Google Trends Analysis JO - J Med Internet Res SP - e21656 VL - 23 IS - 8 KW - digital medicine KW - search trends KW - public awareness KW - infodemiology KW - eHealth N2 - Background: Liver transplantation (LT) is the only curative treatment for end-stage liver disease. Less than 10% of global transplantation needs are met worldwide, and the need for LT is still increasing. The death rates on the waiting list remain too high. Objective: It is, therefore, critical to raise awareness among the public and health care providers and in turn increasingly acquire donors. Methods: We performed a Google Trends search using the search terms liver transplantation and liver transplant on October 15, 2020. On the basis of the resulting monthly data, the annual average Google Trends indices were calculated for the years 2004 to 2018. We not only investigated the trend worldwide but also used data from the United Network for Organ Sharing (UNOS), Spain, and Eurotransplant. Using pairwise Spearman correlations, Google Trends indices were examined over time and compared with the total number of liver transplants retrieved from the respective official websites of UNOS, the Organización Nacional de Trasplantes, and Eurotransplant. Results: From 2004 to 2018, there was a significant decrease in the worldwide Google Trends index from 78.2 in 2004 to 20.5 in 2018 (?71.2%). This trend was more evident in UNOS than in the Eurotransplant group. In the same period, the number of transplanted livers increased worldwide. The waiting list mortality rate was 31% for Eurotransplant and 29% for UNOS. However, in Spain, where there are excellent awareness programs, the Google Trends index remained stable over the years with comparable, increasing LT numbers but a significantly lower waiting list mortality (15%). Conclusions: Public awareness in LT has decreased significantly over the past two decades. Therefore, novel awareness programs should be initialized. UR - https://www.jmir.org/2021/8/e21656 UR - http://dx.doi.org/10.2196/21656 UR - http://www.ncbi.nlm.nih.gov/pubmed/34402801 ID - info:doi/10.2196/21656 ER - TY - JOUR AU - Zhu, Peng Yu AU - Park, Woo Han PY - 2021/8/26 TI - Development of a COVID-19 Web Information Transmission Structure Based on a Quadruple Helix Model: Webometric Network Approach Using Bing JO - J Med Internet Res SP - e27681 VL - 23 IS - 8 KW - quadruple helix model KW - COVID-19 KW - structural analysis KW - content analysis KW - network analysis KW - public health KW - webometrics KW - infodemiology KW - infoveillance KW - development KW - internet KW - online health information KW - structure KW - communication KW - big data N2 - Background: Developing an understanding of the social structure and phenomenon of pandemic information sources worldwide is immensely significant. Objective: Based on the quadruple helix model, the aim of this study was to construct and analyze the structure and content of the internet information sources regarding the COVID-19 pandemic, considering time and space. The broader goal was to determine the status and limitations of web information transmission and online communication structure during public health emergencies. Methods: By sorting the second top-level domain, we divided the structure of network information sources into four levels: government, educational organizations, companies, and nonprofit organizations. We analyzed the structure of information sources and the evolution of information content at each stage using quadruple helix and network analysis methods. Results: The results of the structural analysis indicated that the online sources of information in Asia were more diverse than those in other regions in February 2020. As the pandemic spread in April, the information sources in non-Asian regions began to diversify, and the information source structure diversified further in July. With the spread of the pandemic, for an increasing number of countries, not only the government authorities of high concern but also commercial and educational organizations began to produce and provide significant amounts of information and advice. Nonprofit organizations also produced information, but to a lesser extent. The impact of the virus spread from the initial public level of the government to many levels within society. After April, the government?s role in the COVID-19 network information was central. The results of the content analysis showed that there was an increased focus on discussion regarding public health?related campaign materials at all stages. The information content changed with the changing stages. In the early stages, the basic situation regarding the virus and its impact on health attracted most of the attention. Later, the content was more focused on prevention. The business and policy environment also changed from the beginning of the pandemic, and the social changes caused by the pandemic became a popular discussion topic. Conclusions: For public health emergencies, some online and offline information sources may not be sufficient. Diversified institutions must pay attention to public health emergencies and actively respond to multihelical information sources. In terms of published messages, the educational sector plays an important role in public health events. However, educational institutions release less information than governments and businesses. This study proposes that the quadruple helix not only has research significance in the field of scientific cooperation but could also be used to perform effective research regarding web information during crises. This is significant for further development of the quadruple helix model in the medical internet research area. UR - https://www.jmir.org/2021/8/e27681 UR - http://dx.doi.org/10.2196/27681 UR - http://www.ncbi.nlm.nih.gov/pubmed/34280119 ID - info:doi/10.2196/27681 ER - TY - JOUR AU - Wei, Shanzun AU - Ma, Ming AU - Wen, Xi AU - Wu, Changjing AU - Zhu, Guonian AU - Zhou, Xiangfu PY - 2021/8/26 TI - Online Public Attention Toward Premature Ejaculation in Mainland China: Infodemiology Study Using the Baidu Index JO - J Med Internet Res SP - e30271 VL - 23 IS - 8 KW - premature ejaculation KW - Baidu Index KW - infodemiology KW - public interest KW - patients? concern KW - sexuality KW - sexual dysfunction N2 - Background: Premature ejaculation (PE) is one of the most described psychosocial stress and sexual complaints worldwide. Previous investigations have focused predominantly on the prospective identification of cases that meet researchers? specific criteria. The genuine demand from patients with regard to information on PE and related issues may thus be neglected. Objective: This study aims to examine the online search trend and user demand related to PE on a national and regional scale using the dominant major search engine in mainland China. Methods: The Baidu Index was queried using the PE-related terms for the period of January 2011 to December 2020. The search volume for each term was recorded to analyze the search trend and demographic distributions. For user interest, the demand and trend data were collected and analyzed. Results: Of the 36 available PE search keywords, 4 PE searching topics were identified. The Baidu Search Index for each PE topic varied from 46.30% (86,840,487/187,558,154) to 6.40% (12,009,307/187,558,154). The annual percent change (APC) for the complaint topic was 48.80% (P<.001) for 2011 to 2014 and ?16.82% (P<.001) for 2014 to 2020. The APC for the inquiry topic was 16.21% (P=.41) for 2011 to 2014 and ?11.00% (P<.001) for 2014 to 2020. For the prognosis topic, the annual APC was 11.18% (P<.001) for 2011 to 2017 and ?19.86% (P<.001) for 2017 to 2020. For the treatment topic, the annual APC was 14.04% (P<.001) for 2011 to 2016 and ?38.83% (P<.001) for 2016 to 2020. The age distribution of those searching for topics related to PE showed that the population aged 20 to 40 years comprised nearly 70% of the total search inquiries (second was 17.95% in the age group younger than 19 years). People from East China made over 50% of the total search queries. Conclusions: The fluctuating online popularity of PE searches reflects the real-time population demands. It may help medical professionals better understand population interest, population concerns, regional variations, and gender differences on a nationwide scale and make disease-specific health care policies. The internet search data could be more reliable when the insufficient and lagging registry data are completed. UR - https://www.jmir.org/2021/8/e30271 UR - http://dx.doi.org/10.2196/30271 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435970 ID - info:doi/10.2196/30271 ER - TY - JOUR AU - Luo, Chen AU - Ji, Kaiyuan AU - Tang, Yulong AU - Du, Zhiyuan PY - 2021/8/27 TI - Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach JO - J Med Internet Res SP - e30715 VL - 23 IS - 8 KW - COVID-19 KW - vaccine KW - Zhihu KW - structural topic modeling KW - medical professional KW - laypeople KW - adverse reactions KW - vaccination KW - vaccine effectiveness KW - vaccine development N2 - Background: COVID-19 is still rampant all over the world. Until now, the COVID-19 vaccine is the most promising measure to subdue contagion and achieve herd immunity. However, public vaccination intention is suboptimal. A clear division lies between medical professionals and laypeople. While most professionals eagerly promote the vaccination campaign, some laypeople exude suspicion, hesitancy, and even opposition toward COVID-19 vaccines. Objective: This study aims to employ a text mining approach to examine expression differences and thematic disparities between the professionals and laypeople within the COVID-19 vaccine context. Methods: We collected 3196 answers under 65 filtered questions concerning the COVID-19 vaccine from the China-based question and answer forum Zhihu. The questions were classified into 5 categories depending on their contents and description: adverse reactions, vaccination, vaccine effectiveness, social implications of vaccine, and vaccine development. Respondents were also manually coded into two groups: professional and laypeople. Automated text analysis was performed to calculate fundamental expression characteristics of the 2 groups, including answer length, attitude distribution, and high-frequency words. Furthermore, structural topic modeling (STM), as a cutting-edge branch in the topic modeling family, was used to extract topics under each question category, and thematic disparities were evaluated between the 2 groups. Results: Laypeople are more prevailing in the COVID-19 vaccine?related discussion. Regarding differences in expression characteristics, the professionals posted longer answers and showed a conservative stance toward vaccine effectiveness than did laypeople. Laypeople mentioned countries more frequently, while professionals were inclined to raise medical jargon. STM discloses prominent topics under each question category. Statistical analysis revealed that laypeople preferred the ?safety of Chinese-made vaccine? topic and other vaccine-related issues in other countries. However, the professionals paid more attention to medical principles and professional standards underlying the COVID-19 vaccine. With respect to topics associated with the social implications of vaccines, the 2 groups showed no significant difference. Conclusions: Our findings indicate that laypeople and professionals share some common grounds but also hold divergent focuses toward the COVID-19 vaccine issue. These incongruities can be summarized as ?qualitatively different? in perspective rather than ?quantitatively different? in scientific knowledge. Among those questions closely associated with medical expertise, the ?qualitatively different? characteristic is quite conspicuous. This study boosts the current understanding of how the public perceives the COVID-19 vaccine, in a more nuanced way. Web-based question and answer forums are a bonanza for examining perception discrepancies among various identities. STM further exhibits unique strengths over the traditional topic modeling method in statistically testing the topic preference of diverse groups. Public health practitioners should be keenly aware of the cognitive differences between professionals and laypeople, and pay special attention to the topics with significant inconsistency across groups to build consensus and promote vaccination effectively. UR - https://www.jmir.org/2021/8/e30715 UR - http://dx.doi.org/10.2196/30715 UR - http://www.ncbi.nlm.nih.gov/pubmed/34346885 ID - info:doi/10.2196/30715 ER - TY - JOUR AU - Noser, Anne Elizabeth AU - Zhang, Jing AU - Rahbar, Hossein Mohammad AU - Sharrief, Zarinah Anjail AU - Barreto, David Andrew AU - Shaw, Sandi AU - Grotta, Charles James AU - Savitz, Isaac Sean AU - Ifejika, Lotea Nneka PY - 2021/8/13 TI - Leveraging Multimedia Patient Engagement to Address Minority Cerebrovascular Health Needs: Prospective Observational Study JO - J Med Internet Res SP - e28748 VL - 23 IS - 8 KW - environmental justice KW - urban flooding KW - stroke KW - community engagement KW - education KW - health disparities N2 - Background: Social inequities affecting minority populations after Hurricane Katrina led to an expansion of environmental justice literature. In August 2017, Hurricane Harvey rainfall was estimated as a 3000- to 20,000-year flood event, further affecting minority populations with disproportionate stroke prevalence. The Stomp Out Stroke initiative leveraged multimedia engagement, creating a patient-centered cerebrovascular health intervention. Objective: This study aims to address social inequities in cerebrovascular health through the identification of race- or ethnicity-specific health needs and the provision of in-person stroke prevention screening during two community events (May 2018 and May 2019). Methods: Stomp Out Stroke recruitment took place through internet-based channels (websites and social networking). Exclusively through web registration, Stomp Out Stroke participants (aged >18 years) detailed sociodemographic characteristics, family history of stroke, and stroke survivorship. Participant health interests were compared by race or ethnicity using Kruskal-Wallis or chi-square test at an ?=.05. A Bonferroni-corrected P value of .0083 was used for multiple comparisons. Results: Stomp Out Stroke registrants (N=1401) were 70% (973/1390) female (median age 45 years) and largely self-identified as members of minority groups: 32.05% (449/1401) Hispanic, 25.62% (359/1401) African American, 13.63% (191/1401) Asian compared with 23.63% (331/1401) non-Hispanic White. Stroke survivors comprised 11.55% (155/1401) of our population. A total of 124 stroke caregivers participated. Approximately 36.81% (493/1339) of participants had a family history of stroke. African American participants were most likely to have Medicare or Medicaid insurance (84/341, 24.6%), whereas Hispanic participants were most likely to be uninsured (127/435, 29.2%). Hispanic participants were more likely than non-Hispanic White participants to obtain health screenings (282/449, 62.8% vs 175/331, 52.9%; P=.03). Asian (105/191, 54.9%) and African American (201/359, 55.9%) participants were more likely to request stroke education than non-Hispanic White (138/331, 41.6%) or Hispanic participants (193/449, 42.9%). African American participants were more likely to seek overall health education than non-Hispanic White participants (166/359, 46.2% vs 108/331, 32.6%; P=.002). Non-Hispanic White participants (48/331, 14.5%) were less likely to speak to health care providers than African American (91/359, 25.3%) or Asian participants (54/191, 28.3%). During the 2018 and 2019 events, 2774 health screenings were completed across 12 hours, averaging four health screenings per minute. These included blood pressure (1031/2774, 37.16%), stroke risk assessment (496/2774, 17.88%), bone density (426/2774, 15.35%), carotid ultrasound (380/2774, 13.69%), BMI (182/2774, 6.56%), serum lipids (157/2774, 5.65%), and hemoglobin A1c (102/2774, 3.67%). Twenty multimedia placements using the Stomp Out Stroke webpage, social media, #stompoutstroke, television, iQ radio, and web-based news reached approximately 849,731 people in the Houston area. Conclusions: Using a combination of internet-based recruitment, registration, and in-person assessments, Stomp Out Stroke identified race- or ethnicity-specific health care needs and provided appropriate screenings to minority populations at increased risk of urban flooding and stroke. This protocol can be replicated in Southern US Stroke Belt cities with similar flood risks. UR - https://www.jmir.org/2021/8/e28748 UR - http://dx.doi.org/10.2196/28748 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397385 ID - info:doi/10.2196/28748 ER - TY - JOUR AU - Lange-Drenth, Lukas AU - Schulz, Holger AU - Endsin, Gero AU - Bleich, Christiane PY - 2021/8/16 TI - Patients With Cancer Searching for Cancer- or Health-Specific Web-Based Information: Performance Test Analysis JO - J Med Internet Res SP - e23367 VL - 23 IS - 8 KW - telemedicine KW - eHealth KW - eHealth literacy KW - digital literacy KW - internet KW - web-based KW - health information KW - health education KW - cancer KW - mobile phone N2 - Background: Searching the internet for cancer-related information helps patients with cancer satisfy their unmet information needs and empowers them to play a more active role in the management of their disease. However, to benefit from the search, patients need a sufficient level of skill to search, select, appraise, and apply web-based health information. Objective: We aim to study the operational, navigational, information, and evaluation skills and problems of patients with cancer performing cancer-related search tasks using the internet. Methods: A total of 21 patients with cancer were recruited during their stay at the rehabilitation clinic for oncological rehabilitation. Participants performed eight cancer-related search tasks using the internet. The participants were asked to think aloud while performing the tasks, and the screen activities were recorded. The types and frequencies of performance problems were identified and coded into categories following an inductive coding process. In addition, the performance and strategic characteristics of task execution were summarized descriptively. Results: All participants experienced problems or difficulties in executing the tasks, and a substantial percentage of tasks (57/142, 40.1%) could not be completed successfully. The participants? performance problems were coded into four categories, namely operating the computer and web browser, navigating and orientating, using search strategies, and evaluating the relevance and reliability of web-based information. The most frequent problems occurred in the third and fourth categories. A total of 90% (19/21) of participants used nontask-related search terms or nonspecific search terms. A total of 95% (20/21) of participants did not control for the source or topicality of the information found. In addition, none of the participants verified the information on 1 website with that on another website for each task. Conclusions: A substantial group of patients with cancer did not have the necessary skills to benefit from cancer-related internet searches. Future interventions are needed to support patients in the development of sufficient internet-searching skills, focusing particularly on information and evaluation skills. UR - https://www.jmir.org/2021/8/e23367 UR - http://dx.doi.org/10.2196/23367 UR - http://www.ncbi.nlm.nih.gov/pubmed/34398801 ID - info:doi/10.2196/23367 ER - TY - JOUR AU - Knop, Michael AU - Mueller, Marius AU - Niehaves, Bjoern PY - 2021/8/26 TI - Investigating the Use of Telemedicine for Digitally Mediated Delegation in Team-Based Primary Care: Mixed Methods Study JO - J Med Internet Res SP - e28151 VL - 23 IS - 8 KW - digital health KW - digital health care technologies KW - telemedicine KW - user perceptions KW - delegation KW - primary care KW - ambulant health care KW - medical assistants KW - general practitioners KW - COVID-19 KW - mixed method study KW - multidimensional scaling KW - mobile phone N2 - Background: Owing to the shortage of medical professionals, as well as demographic and structural challenges, new care models have emerged to find innovative solutions to counter medical undersupply. Team-based primary care using medical delegation appears to be a promising approach to address these challenges; however, it demands efficient communication structures and mechanisms to reinsure patients and caregivers receive a delegated, treatment-related task. Digital health care technologies hold the potential to render these novel processes effective and demand driven. Objective: The goal of this study is to recreate the daily work routines of general practitioners (GPs) and medical assistants (MAs) to explore promising approaches for the digital moderation of delegation processes and to deepen the understanding of subjective and perceptual factors that influence their technology assessment and use. Methods: We conducted a combination of 19 individual and group interviews with 12 GPs and 14 MAs, seeking to identify relevant technologies for delegation purposes as well as stakeholders? perceptions of their effectiveness. Furthermore, a web-based survey was conducted asking the interviewees to order identified technologies based on their assessed applicability in multi-actor patient care. Interview data were analyzed using a three-fold inductive coding procedure. Multidimensional scaling was applied to analyze and visualize the survey data, leading to a triangulation of the results. Results: Our results suggest that digital mediation of delegation underlies complex, reciprocal processes and biases that need to be identified and analyzed to improve the development and distribution of innovative technologies and to improve our understanding of technology use in team-based primary care. Nevertheless, medical delegation enhanced by digital technologies, such as video consultations, portable electrocardiograms, or telemedical stethoscopes, can counteract current challenges in primary care because of its unique ability to ensure both personal, patient-centered care for patients and create efficient and needs-based treatment processes. Conclusions: Technology-mediated delegation appears to be a promising approach to implement innovative, case-sensitive, and cost-effective ways to treat patients within the paradigm of primary care. The relevance of such innovative approaches increases with the tremendous need for differentiated and effective care, such as during the ongoing COVID-19 pandemic. For the successful and sustainable adoption of innovative technologies, MAs represent essential team members. In their role as mediators between GPs and patients, MAs are potentially able to counteract patients? resistance toward using innovative technology and compensate for patients? limited access to technology and care facilities. UR - https://www.jmir.org/2021/8/e28151 UR - http://dx.doi.org/10.2196/28151 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435959 ID - info:doi/10.2196/28151 ER - TY - JOUR AU - Butzner, Michael AU - Cuffee, Yendelela PY - 2021/8/26 TI - Telehealth Interventions and Outcomes Across Rural Communities in the United States: Narrative Review JO - J Med Internet Res SP - e29575 VL - 23 IS - 8 KW - telehealth KW - telemedicine KW - rural health KW - health outcomes KW - social determinants of health KW - eHealth KW - health care accessibility N2 - Background: In rural communities, there are gaps in describing the design and effectiveness of technology interventions for treating diseases and addressing determinants of health. Objective: The aim of this study is to evaluate literature on current applications, therapeutic areas, and outcomes of telehealth interventions in rural communities in the United States. Methods: A narrative review of studies published on PubMed from January 2017 to December 2020 was conducted. Key search terms included telehealth, telemedicine, rural, and outcomes. Results: Among 15 included studies, 9 studies analyzed telehealth interventions in patients, 3 in health care professionals, and 3 in both patients and health care professionals. The included studies reported positive outcomes and experiences of telehealth use in rural populations including acceptability and increased satisfaction; they also noted that technology is convenient and efficient. Other notable benefits included decreased direct and indirect costs to the patient (travel cost and time) and health care service provider (staffing), lower onsite health care resource utilization, improved physician recruitment and retention, improved access to care, and increased education and training of patients and health care professionals. Conclusions: Telehealth models were associated with positive outcomes for patients and health care professionals, suggesting these models are feasible and can be effective. Future telehealth interventions and studies examining these programs are warranted, especially in rural communities, and future research should evaluate the impact of increased telehealth use as a result of the COVID-19 pandemic. UR - https://www.jmir.org/2021/8/e29575 UR - http://dx.doi.org/10.2196/29575 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435965 ID - info:doi/10.2196/29575 ER - TY - JOUR AU - Komatsu, Teppei AU - Sakai, Kenichiro AU - Iguchi, Yasuyuki AU - Takao, Hiroyuki AU - Ishibashi, Toshihiro AU - Murayama, Yuichi PY - 2021/8/27 TI - Using a Smartphone Application for the Accurate and Rapid Diagnosis of Acute Anterior Intracranial Arterial Occlusion: Usability Study JO - J Med Internet Res SP - e28192 VL - 23 IS - 8 KW - stroke KW - infarction KW - teleradiology KW - smartphone KW - telehealth KW - reperfusion KW - neurology KW - mHealth KW - application KW - mobile health KW - mobile applications KW - diagnosis KW - diagnostics N2 - Background: Telestroke has developed rapidly as an assessment tool for patients eligible for reperfusion therapy. Objective: To investigate whether vascular neurologists can diagnose intracranial large vessel occlusion (LVO) as quickly and accurately using a smartphone application compared to a hospital-based desktop PC monitor. Methods: We retrospectively enrolled 108 consecutive patients with acute ischemic stroke in the middle cerebral artery territory who underwent magnetic resonance imaging (MRI) within 24 hours of their stroke onset. Two vascular neurologists, blinded to all clinical information, independently evaluated magnetic resonance angiography and fluid-attenuated inversion recovery images for the presence or absence of LVO in the internal carotid artery and middle cerebral artery (M1, M2, or M3) on both a smartphone application (Smartphone-LVO) and a hospital-based desktop PC monitor (PC-LVO). To evaluate the accuracy of an arterial occlusion diagnosis, interdevice variability between Smartphone-LVO and PC-LVO was analyzed using ? statistics, and image interpretation time was compared between Smartphone-LVO and PC-LVO. Results: There was broad agreement between Smartphone-LVO and PC-LVO evaluations regarding the presence or absence of arterial occlusion (Reader 1: ?=0.94; P<.001 vs Reader 2: ?=0.89; P<.001), and interpretation times were similar between Smartphone-LVO and PC-LVO. Conclusions: The results indicate the evaluation of neuroimages using a smartphone application can provide an accurate and timely diagnosis of anterior intracranial arterial occlusion that can be shared immediately with members of the stroke team to support the management of patients with hyperacute ischemic stroke. UR - https://www.jmir.org/2021/8/e28192 UR - http://dx.doi.org/10.2196/28192 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448716 ID - info:doi/10.2196/28192 ER - TY - JOUR AU - Gomes, Antunes Luís AU - Gregório, João Maria AU - Iakovleva, A. Tatiana AU - Sousa, de Rute Dinis AU - Bessant, John AU - Oliveira, Pedro AU - Branco, C. Jaime AU - Canhão, Helena AU - Rodrigues, Maria Ana PY - 2021/8/31 TI - A Home-Based eHealth Intervention for an Older Adult Population With Food Insecurity: Feasibility and Acceptability Study JO - J Med Internet Res SP - e26871 VL - 23 IS - 8 KW - food insecurity KW - eHealth KW - television app KW - elderly people KW - vulnerable population KW - cognitive behavioral strategy KW - health innovation KW - multidisciplinary program N2 - Background: Food insecurity is a global public health challenge, affecting predominately the most vulnerable people in society, including older adults. For this population, eHealth interventions represent an opportunity for promoting healthy lifestyle habits, thus mitigating the consequences of food insecurity. However, before their widespread dissemination, it is essential to evaluate the feasibility and acceptability of these interventions among end users. Objective: This study aims to explore the feasibility and acceptability of a home-based eHealth intervention focused on improving dietary and physical activity through an interactive television (TV) app among older adults with food insecurity. Methods: A pilot noncontrolled quasi-experimental study was designed with baseline and 3-month follow-up assessments. Older adult participants with food insecurity were recruited from 17 primary health care centers in Portugal. A home-based intervention program using an interactive TV app aimed at promoting healthy lifestyle behaviors was implemented over 12 weeks. Primary outcomes were feasibility (self-reported use and interest in eHealth) and acceptability (affective attitude, burden, ethicality, perceived effectiveness, and self-efficacy), which were evaluated using a structured questionnaire with a 7-point Likert scale. Secondary outcomes were changes in food insecurity (Household Food Insecurity Scale), quality of life (European Quality of Life Questionnaire with five dimensions and three levels and Functional Assessment of Chronic Illness Therapy-Fatigue), physical function (Health Assessment Questionnaire, Elderly Mobility Scale, grip strength, and regularity of exercise), and nutritional status (adherence to the Mediterranean diet). Results: A sample of 31 older adult individuals with food insecurity was enrolled in the 12-week intervention program with no dropouts. A total of 10 participants self-reported low use of the TV app. After the intervention, participants were significantly more interested in using eHealth to improve food insecurity (baseline median 1.0, IQR 3.0; 3-month median 5.0, IQR 5.0; P=.01) and for other purposes (baseline median 1.0, IQR 2.0; 3-month median 6.0, IQR 2.0; P=.03). High levels of acceptability were found both before and after (median range 7.0-7.0, IQR 2.0-0.0 and 5.0-7.0, IQR 2.0-2.0, respectively) the intervention, with no significant changes for most constructs. Clinically, there was a reduction of 40% in food insecurity (P=.001), decreased fatigue (mean ?3.82, SD 8.27; P=.02), and improved physical function (Health Assessment Questionnaire: mean ?0.22, SD 0.38; P=.01; Elderly Mobility Scale: mean ?1.50, SD 1.08; P=.01; regularity of exercise: baseline 10/31, 32%; 3 months 18/31, 58%; P=.02). No differences were found for the European Quality of Life Questionnaire with five dimensions and three levels, grip strength, or adherence to the Mediterranean diet. Conclusions: The home-based eHealth intervention was feasible and highly acceptable by participants, thus supporting a future full-scale trial. The intervention program not only reduced the proportion of older adults with food insecurity but also improved participants? fatigue and physical function. International Registered Report Identifier (IRRID): RR2-10.2196/resprot.6626 UR - https://www.jmir.org/2021/8/e26871 UR - http://dx.doi.org/10.2196/26871 UR - http://www.ncbi.nlm.nih.gov/pubmed/34463638 ID - info:doi/10.2196/26871 ER - TY - JOUR AU - Quinn, Marie Lauren AU - Olajide, Oluwafumbi AU - Green, Marsha AU - Sayed, Hazem AU - Ansar, Humera PY - 2021/8/31 TI - Patient and Professional Experiences With Virtual Antenatal Clinics During the COVID-19 Pandemic in a UK Tertiary Obstetric Hospital: Questionnaire Study JO - J Med Internet Res SP - e25549 VL - 23 IS - 8 KW - antenatal KW - virtual clinic KW - technology KW - COVID-19 KW - United Kingdom KW - pandemic KW - feasibility KW - effective KW - telehealth KW - virtual health N2 - Background: The COVID-19 pandemic required rapid implementation of virtual antenatal care to keep pregnant women safe. This transition from face-to-face usual care had to be embraced by patients and professionals alike. Objective: We evaluated patients? and professionals? experiences with virtual antenatal clinic appointments during the COVID-19 pandemic to determine satisfaction and inquire into the safety and quality of care received. Methods: A total of 148 women who attended a virtual antenatal clinic appointment at our UK tertiary obstetric care center over a 2-week period provided feedback (n=92, 62% response rate). A further 37 health care professionals (HCPs) delivering care in the virtual antenatal clinics participated in another questionnaire study (37/45, 82% response rate). Results: We showed that women were highly satisfied with the virtual clinics, with 86% (127/148) rating their experience as good or very good, and this was not associated with any statistically significant differences in age (P=.23), ethnicity (P=.95), number of previous births (P=.65), or pregnancy losses (P=.94). Even though 56% (83/148) preferred face-to-face appointments, 44% (65/148) either expressed no preference or preferred virtual, and these preferences were not associated with significant differences in patient demographics. For HCPs, 67% (18/27) rated their experience of virtual clinics as good or very good, 78% (21/27) described their experience as the same or better than face-to-face clinics, 15% (4/27) preferred virtual clinics, and 44% (12/27) had no preference. Importantly, 67% (18/27) found it easy or very easy to adapt to virtual clinics. Over 90% of HCPs agreed virtual clinics should be implemented long-term. Conclusions: Our study demonstrates high satisfaction with telephone antenatal clinics during the pandemic, which supports the transition toward widespread digitalization of antenatal care suited to 21st-century patients and professionals. UR - https://www.jmir.org/2021/8/e25549 UR - http://dx.doi.org/10.2196/25549 UR - http://www.ncbi.nlm.nih.gov/pubmed/34254940 ID - info:doi/10.2196/25549 ER - TY - JOUR AU - Fang, Heping AU - Xian, Ruoling AU - Ma, Zhuoying AU - Lu, Mingyue AU - Hu, Yan PY - 2021/8/26 TI - Comparison of the Differences Between Web-Based and Traditional Questionnaire Surveys in Pediatrics: Comparative Survey Study JO - J Med Internet Res SP - e30861 VL - 23 IS - 8 KW - pediatrics KW - survey KW - questionnaire KW - web survey KW - comparative study N2 - Background: A web-based survey is a novel method for data capture. Some studies have applied web-based surveys in pediatrics, but few of them have reported data on the differences between web-based and traditional questionnaire surveys. Objective: The objective of our study was to evaluate the internal consistency of a web-based survey and compare it with a traditional questionnaire survey in pediatrics. Methods: A convenience sample of caregivers was invited to participate in the survey on feeding patterns and their children?s eating behaviors if their children were aged 2 to 7 years. A web-based survey and a traditional questionnaire survey were carried out between October 2018 and July 2019. A total of 1085 caregivers were involved in this study, and they were divided into the following three groups based on methods and sources: (1) web-based survey from a web source, (2) web-based survey from a hospital source, and (3) traditional questionnaire survey from a hospital source. The data were then compared and analyzed. Results: A total of 735 caregivers participated in the web-based survey and 350 caregivers participated in the traditional questionnaire survey, and 816 cases were then included in the analyses after data processing. The effective rate of the web-based survey was 70.1% (515/735), and the completeness rate of the traditional questionnaire survey was 86.0% (301/350). There were no significant differences between web-based surveys from different sources. However, demographic characteristics were significantly different between the web-based and traditional questionnaire surveys, mainly in terms of age and caregivers (?²4=16.509, P=.002 and ?²4=111.464, P<.001, respectively). Caregivers of children aged 2 to 3 years and grandparents were more likely to respond to the web-based survey. Age-specific stratified analysis showed that the score of ?monitoring? and the reporting rate of ?poor appetite? in children aged 2 to 3 years were significantly higher in the web-based survey compared to the traditional questionnaire survey after adjusting for demographic characteristics. Conclusions: A web-based survey could be a feasible tool in pediatric studies. However, differences in demographic characteristics and their possible impacts on the results should be considered in the analyses. UR - https://www.jmir.org/2021/8/e30861 UR - http://dx.doi.org/10.2196/30861 UR - http://www.ncbi.nlm.nih.gov/pubmed/34319240 ID - info:doi/10.2196/30861 ER - TY - JOUR AU - Nwokeji, Uchenna AU - Spaulding, M. Erin AU - Shan, Rongzi AU - Turkson-Ocran, Ruth-Alma AU - Baptiste, Diana AU - Koirala, Binu AU - Plante, B. Timothy AU - Martin, S. Seth AU - Commodore-Mensah, Yvonne PY - 2021/8/13 TI - Health Information Technology Use Among Persons With Self-reported Atherosclerotic Cardiovascular Disease: Analysis of the 2011-2018 National Health Interview Survey JO - J Med Internet Res SP - e23765 VL - 23 IS - 8 KW - health information technology KW - cardiovascular disease KW - digital health KW - eHealth KW - mobile phone N2 - Background: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality in the United States. Health information technologies (HITs) have recently emerged as a viable intervention to mitigate the burden of ASCVD. Approximately 60% of US adults report searching the internet for health information; however, previous research has not examined the prevalence of general technology or HIT use among adults with and without ASCVD. In addition, social determinants in HIT use among adults with ASCVD are not well understood. Objective: The aim of this study was to evaluate the prevalence and social determinants of HIT use among US adults with versus without self-reported ASCVD. Methods: We pooled cross-sectional data from the 2011-2018 National Health Interview Survey (NHIS) to examine the general technology and HIT use among adults aged ?18 years with and without self-reported ASCVD (coronary heart disease, stroke, or both). General technology use was defined as mobile phone ownership, internet use, and computer use. HIT use was defined as looking up health information on the internet, filling a web-based prescription, scheduling a medical appointment on the internet, communicating with a health care provider by email, or using web-based group chats to learn about health topics. We evaluated sociodemographic differences in HIT use among respondents by using Poisson regression. Analyses were weighted according to NHIS standards. Results: A total sample of 256,117 individuals were included, of which 2194 (0.9%) reported prior ASCVD. Among adults with prior ASCVD, the mean age was 70.6 (SD 11.5) years, and 47.4% (1048/2194) of the adults were females. General technology use differed between participants with and without prior ASCVD, with 36.0% (614/1826) and 76.2% (157,642/213,816) indicating internet usage and 24.6% (374/1575) and 60.7% (107,742/184,557) indicating using a computer every day, respectively. Similarly, adults with ASCVD were less likely to use HIT than those without ASCVD (515/2194, 25.1% vs 123,966/253,923, 51.0%; P<.001). Among adults with prior ASCVD, social determinants that were associated with HIT use included younger age, higher education, higher income, being employed, and being married. Conclusions: HIT use was low among adults with a history of ASCVD, which may represent a barrier to delivering care via emerging HIT. Given the associations with social determinants such as income, education, and employment, targeted strategies and policies are needed to eliminate barriers to impact HIT usage. UR - https://www.jmir.org/2021/8/e23765 UR - http://dx.doi.org/10.2196/23765 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397391 ID - info:doi/10.2196/23765 ER - TY - JOUR AU - Liu, Natalie AU - Birstler, Jen AU - Venkatesh, Manasa AU - Hanrahan, Lawrence AU - Chen, Guanhua AU - Funk, Luke PY - 2021/8/9 TI - Obesity and BMI Cut Points for Associated Comorbidities: Electronic Health Record Study JO - J Med Internet Res SP - e24017 VL - 23 IS - 8 KW - obesity KW - body mass index (BMI) KW - risk factors KW - screening KW - health services KW - chronic disease N2 - Background: Studies have found associations between increasing BMIs and the development of various chronic health conditions. The BMI cut points, or thresholds beyond which comorbidity incidence can be accurately detected, are unknown. Objective: The aim of this study is to identify whether BMI cut points exist for 11 obesity-related comorbidities. Methods: US adults aged 18-75 years who had ?3 health care visits at an academic medical center from 2008 to 2016 were identified from eHealth records. Pregnant patients, patients with cancer, and patients who had undergone bariatric surgery were excluded. Quantile regression, with BMI as the outcome, was used to evaluate the associations between BMI and disease incidence. A comorbidity was determined to have a cut point if the area under the receiver operating curve was >0.6. The cut point was defined as the BMI value that maximized the Youden index. Results: We included 243,332 patients in the study cohort. The mean age and BMI were 46.8 (SD 15.3) years and 29.1 kg/m2, respectively. We found statistically significant associations between increasing BMIs and the incidence of all comorbidities except anxiety and cerebrovascular disease. Cut points were identified for hyperlipidemia (27.1 kg/m2), coronary artery disease (27.7 kg/m2), hypertension (28.4 kg/m2), osteoarthritis (28.7 kg/m2), obstructive sleep apnea (30.1 kg/m2), and type 2 diabetes (30.9 kg/m2). Conclusions: The BMI cut points that accurately predicted the risks of developing 6 obesity-related comorbidities occurred when patients were overweight or barely met the criteria for class 1 obesity. Further studies using national, longitudinal data are needed to determine whether screening guidelines for appropriate comorbidities may need to be revised. UR - https://www.jmir.org/2021/8/e24017 UR - http://dx.doi.org/10.2196/24017 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383661 ID - info:doi/10.2196/24017 ER - TY - JOUR AU - Stojanov, Riste AU - Popovski, Gorjan AU - Cenikj, Gjorgjina AU - Korou?i? Seljak, Barbara AU - Eftimov, Tome PY - 2021/8/9 TI - A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation JO - J Med Internet Res SP - e28229 VL - 23 IS - 8 KW - food information extraction KW - named-entity recognition KW - fine-tuning BERT KW - semantic annotation KW - information extraction KW - BERT KW - bidirectional encoder representations from transformers KW - natural language processing KW - machine learning N2 - Background: Recently, food science has been garnering a lot of attention. There are many open research questions on food interactions, as one of the main environmental factors, with other health-related entities such as diseases, treatments, and drugs. In the last 2 decades, a large amount of work has been done in natural language processing and machine learning to enable biomedical information extraction. However, machine learning in food science domains remains inadequately resourced, which brings to attention the problem of developing methods for food information extraction. There are only few food semantic resources and few rule-based methods for food information extraction, which often depend on some external resources. However, an annotated corpus with food entities along with their normalization was published in 2019 by using several food semantic resources. Objective: In this study, we investigated how the recently published bidirectional encoder representations from transformers (BERT) model, which provides state-of-the-art results in information extraction, can be fine-tuned for food information extraction. Methods: We introduce FoodNER, which is a collection of corpus-based food named-entity recognition methods. It consists of 15 different models obtained by fine-tuning 3 pretrained BERT models on 5 groups of semantic resources: food versus nonfood entity, 2 subsets of Hansard food semantic tags, FoodOn semantic tags, and Systematized Nomenclature of Medicine Clinical Terms food semantic tags. Results: All BERT models provided very promising results with 93.30% to 94.31% macro F1 scores in the task of distinguishing food versus nonfood entity, which represents the new state-of-the-art technology in food information extraction. Considering the tasks where semantic tags are predicted, all BERT models obtained very promising results once again, with their macro F1 scores ranging from 73.39% to 78.96%. Conclusions: FoodNER can be used to extract and annotate food entities in 5 different tasks: food versus nonfood entities and distinguishing food entities on the level of food groups by using the closest Hansard semantic tags, the parent Hansard semantic tags, the FoodOn semantic tags, or the Systematized Nomenclature of Medicine Clinical Terms semantic tags. UR - https://www.jmir.org/2021/8/e28229 UR - http://dx.doi.org/10.2196/28229 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383671 ID - info:doi/10.2196/28229 ER - TY - JOUR AU - Di Matteo, Daniel AU - Fotinos, Kathryn AU - Lokuge, Sachinthya AU - Mason, Geneva AU - Sternat, Tia AU - Katzman, A. Martin AU - Rose, Jonathan PY - 2021/8/13 TI - Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study JO - J Med Internet Res SP - e28918 VL - 23 IS - 8 KW - mobile sensing KW - passive EMA KW - passive sensing KW - psychiatric assessment KW - mood and anxiety disorders KW - mobile apps KW - mhealth KW - mobile phone KW - digital health KW - digital phenotyping N2 - Background: The lack of access to mental health care could be addressed, in part, through the development of automated screening technologies for detecting the most common mental health disorders without the direct involvement of clinicians. Objective smartphone-collected data may contain sufficient information about individuals? behaviors to infer their mental states and therefore screen for anxiety disorders and depression. Objective: The objective of this study is to compare how a single set of recognized and novel features, extracted from smartphone-collected data, can be used for predicting generalized anxiety disorder (GAD), social anxiety disorder (SAD), and depression. Methods: An Android app was designed, together with a centralized server system, to collect periodic measurements of objective smartphone data. The types of data included samples of ambient audio, GPS location, screen state, and light sensor data. Subjects were recruited into a 2-week observational study in which the app was run on their personal smartphones. The subjects also completed self-report severity measures of SAD, GAD, and depression. The participants were 112 Canadian adults from a nonclinical population. High-level features were extracted from the data of 84 participants, and predictive models of SAD, GAD, and depression were built and evaluated. Results: Models of SAD and depression achieved a significantly greater screening accuracy than uninformative models (area under the receiver operating characteristic means of 0.64, SD 0.13 and 0.72, SD 0.12, respectively), whereas models of GAD failed to be predictive. Investigation of the model coefficients revealed key features that were predictive of SAD and depression. Conclusions: We demonstrate the ability of a common set of features to act as predictors in the models of both SAD and depression. This suggests that the types of behaviors that can be inferred from smartphone-collected data are broad indicators of mental health, which can be used to study, assess, and track psychopathology simultaneously across multiple disorders and diagnostic boundaries. UR - https://www.jmir.org/2021/8/e28918 UR - http://dx.doi.org/10.2196/28918 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397386 ID - info:doi/10.2196/28918 ER - TY - JOUR AU - Brasier, Noe AU - Osthoff, Michael AU - De Ieso, Fiorangelo AU - Eckstein, Jens PY - 2021/8/19 TI - Next-Generation Digital Biomarkers for Tuberculosis and Antibiotic Stewardship: Perspective on Novel Molecular Digital Biomarkers in Sweat, Saliva, and Exhaled Breath JO - J Med Internet Res SP - e25907 VL - 23 IS - 8 KW - digital biomarkers KW - active tuberculosis KW - drug resistance KW - wearable KW - smart biosensors KW - iSudorology KW - infectious diseases UR - https://www.jmir.org/2021/8/e25907 UR - http://dx.doi.org/10.2196/25907 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420925 ID - info:doi/10.2196/25907 ER - TY - JOUR AU - Zhao, Zhong AU - Tang, Haiming AU - Zhang, Xiaobin AU - Qu, Xingda AU - Hu, Xinyao AU - Lu, Jianping PY - 2021/8/26 TI - Classification of Children With Autism and Typical Development Using Eye-Tracking Data From Face-to-Face Conversations: Machine Learning Model Development and Performance Evaluation JO - J Med Internet Res SP - e29328 VL - 23 IS - 8 KW - autism spectrum disorder KW - eye tracking KW - face-to-face interaction KW - machine learning KW - visual fixation N2 - Background: Previous studies have shown promising results in identifying individuals with autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data collected while participants viewed varying images (ie, pictures, videos, and web pages). Although gaze behavior is known to differ between face-to-face interaction and image-viewing tasks, no study has investigated whether eye-tracking data from face-to-face conversations can also accurately identify individuals with ASD. Objective: The objective of this study was to examine whether eye-tracking data from face-to-face conversations could classify children with ASD and typical development (TD). We further investigated whether combining features on visual fixation and length of conversation would achieve better classification performance. Methods: Eye tracking was performed on children with ASD and TD while they were engaged in face-to-face conversations (including 4 conversational sessions) with an interviewer. By implementing forward feature selection, four ML classifiers were used to determine the maximum classification accuracy and the corresponding features: support vector machine (SVM), linear discriminant analysis, decision tree, and random forest. Results: A maximum classification accuracy of 92.31% was achieved with the SVM classifier by combining features on both visual fixation and session length. The classification accuracy of combined features was higher than that obtained using visual fixation features (maximum classification accuracy 84.62%) or session length (maximum classification accuracy 84.62%) alone. Conclusions: Eye-tracking data from face-to-face conversations could accurately classify children with ASD and TD, suggesting that ASD might be objectively screened in everyday social interactions. However, these results will need to be validated with a larger sample of individuals with ASD (varying in severity and balanced sex ratio) using data collected from different modalities (eg, eye tracking, kinematic, electroencephalogram, and neuroimaging). In addition, individuals with other clinical conditions (eg, developmental delay and attention deficit hyperactivity disorder) should be included in similar ML studies for detecting ASD. UR - https://www.jmir.org/2021/8/e29328 UR - http://dx.doi.org/10.2196/29328 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435957 ID - info:doi/10.2196/29328 ER - TY - JOUR AU - Janssen, L. Sharon AU - Venema-Taat, Nynke AU - Medlock, Stephanie PY - 2021/8/11 TI - Anticipated Benefits and Concerns of Sharing Hospital Outpatient Visit Notes With Patients (Open Notes) in Dutch Hospitals: Mixed Methods Study JO - J Med Internet Res SP - e27764 VL - 23 IS - 8 KW - patient portal KW - access to information KW - barriers and facilitators KW - survey KW - qualitative KW - open notes KW - mixed methods KW - electronic health record N2 - Background: The past few years have seen an increase in interest in sharing visit notes with patients. Sharing visit notes with patients is also known as ?open notes.? Shared notes are seen as beneficial for patient empowerment and communication, but concerns have also been raised about potential negative effects. Understanding barriers is essential to successful organizational change, but most published studies on the topic come from countries where shared notes are incentivized or legally required. Objective: We aim to gather opinions about sharing outpatient clinic visit notes from patients and hospital physicians in the Netherlands, where there is currently no policy or incentive plan for shared visit notes. Methods: This multimethodological study was conducted in an academic and a nonacademic hospital in the Netherlands. We conducted a survey of patients and doctors in March-April 2019. In addition to the survey, we conducted think-aloud interviews to gather more insight into the reasons behind participants? answers. We surveyed 350 physicians and 99 patients, and think-aloud interviews were conducted with an additional 13 physicians and 6 patients. Results: Most patients (81/98, 77%) were interested in viewing their visit notes, whereas most physicians (262/345, 75.9%) were opposed to allowing patients to view their visit notes. Most patients (54/90, 60%) expected the notes to be written in layman?s terms, but most physicians (193/321, 60.1%) did not want to change their writing style to make it more understandable for patients. Doctors raised concerns that reading the note would make patients feel confused and anxious, that the patient would not understand the note, and that shared notes would result in more documentation time or losing a way to communicate with colleagues. Interviews also revealed concerns about documenting sensitive topics such as suspected abuse and unlikely but worrisome differential diagnoses. Physicians also raised concerns that documenting worrisome thoughts elsewhere in the record would result in fragmentation of the patient record. Patients were uncertain if they would understand the notes (46/90, 51%) and, in interviews, raised questions about security and privacy. Physicians did anticipate some benefits, such as the patients remembering the visit better, shared decision-making, and keeping patients informed, but 24% (84/350) indicated that they saw no benefit. Patients anticipated that they would remember the visit better, feel more in control, and better understand their health. Conclusions: Dutch patients are interested in shared visit notes, but physicians have many concerns that should be addressed if shared notes are pursued. Physicians? concerns should be addressed before shared notes are implemented. In hospitals where shared notes are implemented, the effects should be monitored (objectively, if possible) to determine whether the concerns raised by our participants have actualized into problems and whether the anticipated benefits are being realized. UR - https://www.jmir.org/2021/8/e27764 UR - http://dx.doi.org/10.2196/27764 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383660 ID - info:doi/10.2196/27764 ER - TY - JOUR AU - Kinney, P. Aaron AU - Sankaranarayanan, Balaji PY - 2021/8/27 TI - Effects of Patient Portal Use on Patient Satisfaction: Survey and Partial Least Squares Analysis JO - J Med Internet Res SP - e19820 VL - 23 IS - 8 KW - patient portal KW - patient satisfaction KW - gratification KW - health self-awareness KW - post-adoptive use KW - health perceptions N2 - Background: With digital delivery of health care services gaining prominence, patient portals have become a mainstay of many health care organizations. Despite the importance of patient portals, inconclusive data exist regarding the effect of patient portal use on patient satisfaction. Objective: The aim of this study is to understand the relationship between the postadoptive use of patient portals and patient satisfaction outcomes. Methods: Postadoptive use of patient portals has a positive relationship with the 3 dimensions of patient satisfaction, mediated by gratification, health self-awareness, and health perceptions. A total of 504 valid patient portal user responses were collected, and partial least squares analysis was performed to analyze the data. Results: Patient satisfaction was captured using three dimensions: care team interaction, atmosphere, and instruction effectiveness. The results show that postadoptive use of patient portals has a positive influence on all 3 dimensions of patient satisfaction through the mediating variables of gratification, health self-awareness, and health perceptions. Specifically, postadoptive use had significant positive influence on gratification, health self-awareness, and health perceptions. Each of the 3 patient perceptions had significant positive influence on all 3 dimensions of patient satisfaction: care team interaction, atmosphere, and instruction effectiveness. Specifically, our model explained 31.8% of the care team interaction, 40.6% of the atmosphere, and 39.1% of the instruction effectiveness. Conclusions: Our model shows that patient portal use can influence patient satisfaction through the mediating effects of gratification, health self-awareness, and health perception. Patient satisfaction is an important outcome for health care organizations. Therefore, by promoting effective patient portal use and fostering patient perceptions, health care organizations can improve patient satisfaction. UR - https://www.jmir.org/2021/8/e19820 UR - http://dx.doi.org/10.2196/19820 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448712 ID - info:doi/10.2196/19820 ER - TY - JOUR AU - van Rijt, Mattheus Antonius AU - Hulter, Pauline AU - Weggelaar-Jansen, Marie Anne AU - Ahaus, Kees AU - Pluut, Bettine PY - 2021/8/27 TI - Mental Health Care Professionals? Appraisal of Patients? Use of Web-Based Access to Their Electronic Health Record: Qualitative Study JO - J Med Internet Res SP - e28045 VL - 23 IS - 8 KW - patient portals KW - eHealth KW - mental health care professionals KW - mental health KW - eMental health KW - mental health care KW - patient-accessible KW - electronic health records KW - Open Notes KW - normalization process theory KW - NPT N2 - Background: Patients in a range of health care sectors can access their medical health records using a patient portal. In mental health care, the use of patient portals among mental health care professionals remains low. Mental health care professionals are concerned that patient access to electronic health records (EHRs) will negatively affect the patient?s well-being and privacy as well as the professional?s own workload. Objective: This study aims to provide insights into the appraisal work of mental health care professionals to assess and understand patient access to their EHRs through a patient portal. Methods: We conducted a qualitative study that included 10 semistructured interviews (n=11) and a focus group (n=10). Participants in both the interviews and the focus group were mental health care professionals from different professional backgrounds and staff employees (eg, team leaders and communication advisors). We collected data on their opinions and experiences with the recently implemented patient portal and their attempts to modify work practices. Results: Our study provides insights into mental health care professionals? appraisal work to assess and understand patient access to the EHR through a patient portal. A total of four topics emerged from our data analysis: appraising the effect on the patient-professional relationship, appraising the challenge of sharing and registering delicate information, appraising patient vulnerability, and redefining consultation routines and registration practices. Conclusions: Mental health care professionals struggle with the effects of web-based patient access and are searching for the best ways to modify their registration and consultation practices. Our participants seem to appraise the effects of web-based patient access individually. Our study signals the lack of systematization and communal appraisal. It also suggests various solutions to the challenges faced by mental health care professionals. To optimize the effects of web-based patient access to EHRs, mental health care professionals need to be involved in the process of developing, implementing, and embedding patient portals. UR - https://www.jmir.org/2021/8/e28045 UR - http://dx.doi.org/10.2196/28045 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448705 ID - info:doi/10.2196/28045 ER - TY - JOUR AU - Li, Li AU - Liu, Xiaobin AU - Chen, Zeyuan AU - Wang, Liyuan AU - Lian, Xiaoli AU - Zou, Huiru PY - 2021/8/13 TI - The Application of a Case-Based Social Media?Assisted Teaching Method in Cariology Education?Comparative Study JO - J Med Internet Res SP - e29372 VL - 23 IS - 8 KW - social media KW - case-based learning KW - cariology KW - dental cavity preparation KW - college students N2 - Background: Current cariology education based on the traditional teaching method faces a lot of challenges. Meanwhile, the COVID-19 pandemic caused an unprecedented disruption in medical education and health care systems worldwide. Innovation in the teaching mode of cariology education is required to change the situation. Objective: The goal of the research was to evaluate the application effects of a case-based social media?assisted teaching method in cariology education. Methods: Dental students of class 2019 were enrolled into the experimental group, while students of class 2018 served as control. A case-based social media?assisted teaching method was used in the experimental group, which included preclass activity via social media, additional discussion and practice process record in class, and questions and answers on the platform after class. The traditional teaching method, which consisted of conventional preparation before class, traditional lectures and demonstrations followed by students practice in class, and questions and answers step after class, was used in the control group. The teaching materials were the same in both groups. At the end of the program, students from both groups took cavity preparation skill evaluation tests. Questionnaires were tested on the case-based social media?assisted teaching group students anonymously. All data were analyzed using SPSS statistical software (version 22.0, IBM Corp). Results: The mean student cavity preparation skill evaluation scores was 82.51 (SD 6.82) in the experimental group and 77.19 (SD 5.98) in the control group (P<.05). The questionnaire response rate was 100%. Of those, 94.3% (100/106) of the students recommended the case-based social media?assisted teaching method in cariology education. The majority of the participants agreed that it helped them memorize the theoretical knowledge of cariology, facilitated in-depth discussion, improved their enthusiasm and initiative in learning, and enhanced the relationship between teachers and students (104/106, 98.1%). They also recognized that the classroom atmosphere was active (94/106, 88.7%). Conclusions: The case-based social media?assisted teaching method was beneficial in terms of learning, as demonstrated by the statistically significant improvement of the cavity preparation skill evaluation scores and satisfaction from attending students. This method could be used to supplement the teaching of cariology. UR - https://www.jmir.org/2021/8/e29372 UR - http://dx.doi.org/10.2196/29372 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397390 ID - info:doi/10.2196/29372 ER - TY - JOUR AU - Wang, Tong AU - Fan, Lingye AU - Zheng, Xu AU - Wang, Wei AU - Liang, Jun AU - An, Kai AU - Ju, Mei AU - Lei, Jianbo PY - 2021/8/12 TI - The Impact of Gamification-Induced Users' Feelings on the Continued Use of mHealth Apps: A Structural Equation Model With the Self-Determination Theory Approach JO - J Med Internet Res SP - e24546 VL - 23 IS - 8 KW - mHealth app KW - continued use KW - continuance intention KW - gamification KW - self-determination theory (SDT) KW - expectation confirmation model of information system continuance (ECM-ISC) KW - PLS-SEM N2 - Background: Continued use of mHealth apps can achieve better effects in health management. Gamification is an important factor in promoting users? intention to continue using mHealth apps. Past research has rarely explored the factors underlying the continued use of mobile health (mHealth) apps and gamification?s impact mechanism or path on continued use. Objective: This study aimed to explore the factors influencing mHealth app users? intention to continue using mHealth apps and the impact mechanism and path of users? feelings induced by gamification on continued mHealth app use. Methods: First, based on the expectation confirmation model of information system continuance, we built a theoretical model for continued use of mHealth apps based on users? feelings toward gamification. We used self-determination theory to analyze gamification?s impact on user perceptions and set the resulting feelings (competence, autonomy, and relatedness) as constructs in the model. Second, we used the survey method to validate the research model, and we used partial least squares to analyze the data. Results: A total of 2988 responses were collected from mHealth app users, and 307 responses were included in the structural equation model after passing the acceptance criteria. The intrinsic motivation for using mHealth apps is significantly affected by autonomy (?=.312; P<.001), competence (?=.346; P<.001), and relatedness (?=.165; P=.004) induced by gamification. The intrinsic motivation for using mHealth apps has a significant impact on satisfaction (?=.311, P<.001) and continuance intention (?=.142; P=.045); furthermore, satisfaction impacts continuance intention significantly (?=.415; P<.001). Confirmation has a significant impact on perceived usefulness (?=.859; P<.001) and satisfaction (?=.391; P<.001), and perceived usefulness has a significant impact on satisfaction (?=.269; P<.001) and continuance intention (?=.273; P=.001). The mediating effect analysis showed that in the impact path of the intrinsic motivation for using the mHealth apps on continuance intention, satisfaction plays a partial mediating role (?=.129; P<.001), with a variance accounted for of 0.466. Conclusions: This study explored the impact path of users? feelings induced by gamification on the intention of continued mHealth app use. We confirmed that perceived usefulness, confirmation, and satisfaction in the classical continued use theory for nonmedical information systems positively affect continuance intention. We also found that the path and mechanism of users' feelings regarding autonomy, competence, and relatedness generated during interactions with different gamification elements promote the continued use of mHealth apps. UR - https://www.jmir.org/2021/8/e24546 UR - http://dx.doi.org/10.2196/24546 UR - http://www.ncbi.nlm.nih.gov/pubmed/34387550 ID - info:doi/10.2196/24546 ER - TY - JOUR AU - Hutchinson, Claire AU - Brereton, Michelle AU - Adams, Julie AU - De La Salle, Barbara AU - Sims, Jon AU - Hyde, Keith AU - Chasty, Richard AU - Brown, Rachel AU - Rees-Unwin, Karen AU - Burthem, John PY - 2021/8/9 TI - The Use and Effectiveness of an Online Diagnostic Support System for Blood Film Interpretation: Comparative Observational Study JO - J Med Internet Res SP - e20815 VL - 23 IS - 8 KW - blood cell morphology KW - decision support KW - external quality assessment in hematology KW - diagnosis KW - digital morphology KW - morphology education N2 - Background: The recognition and interpretation of abnormal blood cell morphology is often the first step in diagnosing underlying serious systemic illness or leukemia. Supporting the staff who interpret blood film morphology is therefore essential for a safe laboratory service. This paper describes an open-access, web-based decision support tool, developed by the authors to support morphological diagnosis, arising from earlier studies identifying mechanisms of error in blood film reporting. The effectiveness of this intervention was assessed using the unique resource offered by the online digital morphology Continuing Professional Development scheme (DM scheme) offered by the UK National External Quality Assessment Service for Haematology, with more than 3000 registered users. This allowed the effectiveness of decision support to be tested within a defined user group, each of whom viewed and interpreted the morphology of identical digital blood films. Objective: The primary objective of the study was to test the effectiveness of the decision support system in supporting users to identify and interpret abnormal morphological features. The secondary objective was to determine the pattern and frequency of use of the system for different case types, and to determine how users perceived the support in terms of their confidence in decision-making. Methods: This was a comparative study of identical blood films evaluated either with or without decision support. Selected earlier cases from the DM scheme were rereleased as new cases but with decision support made available; this allowed a comparison of data sets for identical cases with or without decision support. To address the primary objectives, the study used quantitative evaluation and statistical comparisons of the identification and interpretation of morphological features between the two different case releases. To address the secondary objective, the use of decision support was assessed using web analytical tools, while a questionnaire was used to assess user perceptions of the system. Results: Cases evaluated with the aid of decision support had significantly improved accuracy of identification for relevant morphological features (mean improvement 9.8%) and the interpretation of those features (mean improvement 11%). The improvement was particularly significant for cases with higher complexity or for rarer diagnoses. Analysis of website usage demonstrated a high frequency of access for web pages relevant to each case (mean 9298 for each case, range 2661-24,276). Users reported that the decision support website increased their confidence for feature identification (4.8/5) and interpretation (4.3/5), both within the context of training (4.6/5) and also in their wider laboratory practice (4.4/5). Conclusions: The findings of this study demonstrate that directed online decision support for blood morphology evaluation improves accuracy and confidence in the context of educational evaluation of digital films, with effectiveness potentially extending to wider laboratory use. UR - https://www.jmir.org/2021/8/e20815 UR - http://dx.doi.org/10.2196/20815 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383663 ID - info:doi/10.2196/20815 ER - TY - JOUR AU - Hur, Sujeong AU - Min, Young Ji AU - Yoo, Junsang AU - Kim, Kyunga AU - Chung, Ryang Chi AU - Dykes, C. Patricia AU - Cha, Chul Won PY - 2021/8/11 TI - Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study JO - J Med Internet Res SP - e23508 VL - 23 IS - 8 KW - intensive care unit KW - machine learning KW - mechanical ventilator KW - patient safety KW - unplanned extubation N2 - Background: Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. Objective: This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. Methods: This study was conducted in an academic tertiary hospital in Seoul, Republic of Korea. The hospital had approximately 2000 inpatient beds and 120 ICU beds. As of January 2019, the hospital had approximately 9000 outpatients on a daily basis. The number of annual ICU admissions was approximately 10,000. We conducted a retrospective study between January 1, 2010, and December 31, 2018. A total of 6914 extubation cases were included. We developed a UE prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model?s performance, we used the area under the receiver operating characteristic curve (AUROC). The sensitivity, specificity, positive predictive value, negative predictive value, and F1 score were also determined for each model. For performance evaluation, we also used a calibration curve, the Brier score, and the integrated calibration index (ICI) to compare different models. The potential clinical usefulness of the best model at the best threshold was assessed through a net benefit approach using a decision curve. Results: Among the 6914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was higher during the night shift as compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality were higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.763, and for SVM was 0.740. Conclusions: We successfully developed and validated machine learning?based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787 and the sensitivity was 0.949, which was obtained using the RF algorithm. The RF model was well-calibrated, and the Brier score and ICI were 0.129 and 0.048, respectively. The proposed prediction model uses widely available variables to limit the additional workload on the clinician. Further, this evaluation suggests that the model holds potential for clinical usefulness. UR - https://www.jmir.org/2021/8/e23508 UR - http://dx.doi.org/10.2196/23508 UR - http://www.ncbi.nlm.nih.gov/pubmed/34382940 ID - info:doi/10.2196/23508 ER - TY - JOUR AU - Mishra, Ninad AU - Duke, Jon AU - Karki, Saugat AU - Choi, Myung AU - Riley, Michael AU - Ilatovskiy, V. Andrey AU - Gorges, Marla AU - Lenert, Leslie PY - 2021/8/11 TI - A Modified Public Health Automated Case Event Reporting Platform for Enhancing Electronic Laboratory Reports With Clinical Data: Design and Implementation Study JO - J Med Internet Res SP - e26388 VL - 23 IS - 8 KW - public health surveillance KW - sexually transmitted diseases KW - gonorrhea KW - chlamydia KW - electronic case reporting KW - electronic laboratory reporting KW - health information interoperability KW - fast healthcare interoperability resources KW - electronic health records KW - EHR N2 - Background: Public health reporting is the cornerstone of public health practices that inform prevention and control strategies. There is a need to leverage advances made in the past to implement an architecture that facilitates the timely and complete public health reporting of relevant case-related information that has previously not easily been available to the public health community. Electronic laboratory reporting (ELR) is a reliable method for reporting cases to public health authorities but contains very limited data. In an earlier pilot study, we designed the Public Health Automated Case Event Reporting (PACER) platform, which leverages existing ELR infrastructure as the trigger for creating an electronic case report. PACER is a FHIR (Fast Health Interoperability Resources)-based system that queries the electronic health record from where the laboratory test was requested to extract expanded additional information about a case. Objective: This study aims to analyze the pilot implementation of a modified PACER system for electronic case reporting and describe how this FHIR-based, open-source, and interoperable system allows health systems to conduct public health reporting while maintaining the appropriate governance of the clinical data. Methods: ELR to a simulated public health department was used as the trigger for a FHIR-based query. Predetermined queries were translated into Clinical Quality Language logics. Within the PACER environment, these Clinical Quality Language logical statements were managed and evaluated against the providers? FHIR servers. These predetermined logics were filtered, and only data relevant to that episode of the condition were extracted and sent to simulated public health agencies as an electronic case report. Design and testing were conducted at the Georgia Tech Research Institute, and the pilot was deployed at the Medical University of South Carolina. We evaluated this architecture by examining the completeness of additional information in the electronic case report, such as patient demographics, medications, symptoms, and diagnoses. This additional information is crucial for understanding disease epidemiology, but existing electronic case reporting and ELR architectures do not report them. Therefore, we used the completeness of these data fields as the metrics for enriching electronic case reports. Results: During the 8-week study period, we identified 117 positive test results for chlamydia. PACER successfully created an electronic case report for all 117 patients. PACER extracted demographics, medications, symptoms, and diagnoses from 99.1% (116/117), 72.6% (85/117), 70.9% (83/117), and 65% (76/117) of the cases, respectively. Conclusions: PACER deployed in conjunction with electronic laboratory reports can enhance public health case reporting with additional relevant data. The architecture is modular in design, thereby allowing it to be used for any reportable condition, including evolving outbreaks. PACER allows for the creation of an enhanced and more complete case report that contains relevant case information that helps us to better understand the epidemiology of a disease. UR - https://www.jmir.org/2021/8/e26388 UR - http://dx.doi.org/10.2196/26388 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383669 ID - info:doi/10.2196/26388 ER - TY - JOUR AU - Cresswell, Kathrin AU - Sheikh, Aziz AU - Franklin, Dean Bryony AU - Krasuska, Marta AU - The Nguyen, Hung AU - Hinder, Susan AU - Lane, Wendy AU - Mozaffar, Hajar AU - Mason, Kathy AU - Eason, Sally AU - Potts, Henry AU - Williams, Robin PY - 2021/8/19 TI - Interorganizational Knowledge Sharing to Establish Digital Health Learning Ecosystems: Qualitative Evaluation of a National Digital Health Transformation Program in England JO - J Med Internet Res SP - e23372 VL - 23 IS - 8 KW - digital transformation KW - health system KW - learning ecosystem N2 - Background: The English Global Digital Exemplar (GDE) program is one of the first concerted efforts to create a digital health learning ecosystem across a national health service. Objective: This study aims to explore mechanisms that support or inhibit the exchange of interorganizational digital transformation knowledge. Methods: We conducted a formative qualitative evaluation of the GDE program. We used semistructured interviews with clinical, technical, and managerial staff; national program managers and network leaders; nonparticipant observations of knowledge transfer activities through attending meetings, workshops, and conferences; and documentary analysis of policy documents. The data were thematically analyzed by drawing on a theory-informed sociotechnical coding framework. We used a mixture of deductive and inductive methods, supported by NVivo software, to facilitate coding. Results: We conducted 341 one-on-one and 116 group interviews, observed 86 meetings, and analyzed 245 documents from 36 participating provider organizations. We also conducted 51 high-level interviews with policy makers and vendors; performed 77 observations of national meetings, workshops, and conferences; and analyzed 80 national documents. Formal processes put in place by the GDE program to initiate and reinforce knowledge transfer and learning have accelerated the growth of informal knowledge networking and helped establish the foundations of a learning ecosystem. However, formal networks were most effective when supported by informal networking. The benefits of networking were enhanced (and costs reduced) by geographical proximity, shared culture and context, common technological functionality, regional and strategic alignments, and professional agendas. Conclusions: Knowledge exchange is most effective when sustained through informal networking driven by the mutual benefits of sharing knowledge and convergence between group members in their organizational and technological setting and goals. Policy interventions need to enhance incentives and reduce barriers to sharing across the ecosystem, be flexible in tailoring formal interventions to emerging needs, and promote informal knowledge sharing. UR - https://www.jmir.org/2021/8/e23372 UR - http://dx.doi.org/10.2196/23372 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420927 ID - info:doi/10.2196/23372 ER - TY - JOUR AU - Li, Jia AU - Yu, Kanghui AU - Bao, Xinyu AU - Liu, Xuan AU - Yao, Junping PY - 2021/8/13 TI - Patterns of eHealth Website User Engagement Based on Cross-site Clickstream Data: Correlational Study JO - J Med Internet Res SP - e29299 VL - 23 IS - 8 KW - engagement KW - clickstream data KW - cross-site visit KW - platform KW - channel KW - mobile phone N2 - Background: User engagement is a key performance variable for eHealth websites. However, most existing studies on user engagement either focus on a single website or depend on survey data. To date, we still lack an overview of user engagement on multiple eHealth websites derived from objective data. Therefore, it is relevant to provide a holistic view of user engagement on multiple eHealth websites based on cross-site clickstream data. Objective: This study aims to describe the patterns of user engagement on eHealth websites and investigate how platforms, channels, sex, and income influence user engagement on eHealth websites. Methods: The data used in this study were the clickstream data of 1095 mobile users, which were obtained from a large telecom company in Shanghai, China. The observation period covered 8 months (January 2017 to August 2017). Descriptive statistics, two-tailed t tests, and an analysis of variance were used for data analysis. Results: The medical category accounted for most of the market share of eHealth website visits (134,009/184,826, 72.51%), followed by the lifestyle category (46,870/184,826, 25.36%). The e-pharmacy category had the smallest market share, accounting for only 2.14% (3947/184,826) of the total visits. eHealth websites were characterized by very low visit penetration and relatively high user penetration. The distribution of engagement intensity followed a power law distribution. Visits to eHealth websites were highly concentrated. User engagement was generally high on weekdays but low on weekends. Furthermore, user engagement gradually increased from morning to noon. After noon, user engagement declined until it reached its lowest level at midnight. Lifestyle websites, followed by medical websites, had the highest customer loyalty. e-Pharmacy websites had the lowest customer loyalty. Popular eHealth websites, such as medical websites, can effectively provide referral traffic for lifestyle and e-pharmacy websites. However, the opposite is also true. Android users were more engaged in eHealth websites than iOS users. The engagement volume of app users was 4.85 times that of browser users, and the engagement intensity of app users was 4.22 times that of browser users. Male users had a higher engagement intensity than female users. Income negatively moderated the influence that platforms (Android vs iOS) had on user engagement. Low-income Android users were the most engaged in eHealth websites. Conversely, low-income iOS users were the least engaged in eHealth websites. Conclusions: Clickstream data provide a new way to derive an overview of user engagement patterns on eHealth websites and investigate the influence that various factors (eg, platform, channel, sex, and income) have on engagement behavior. Compared with self-reported data from a questionnaire, cross-site clickstream data are more objective, accurate, and appropriate for pattern discovery. Many user engagement patterns and findings regarding the influential factors revealed by cross-site clickstream data have not been previously reported. UR - https://www.jmir.org/2021/8/e29299 UR - http://dx.doi.org/10.2196/29299 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397392 ID - info:doi/10.2196/29299 ER - TY - JOUR AU - Ong, Wui Chee AU - Tan, Jin Marcus Chun AU - Lam, Michael AU - Koh, Chang Victor Teck PY - 2021/8/19 TI - Applications of Extended Reality in Ophthalmology: Systematic Review JO - J Med Internet Res SP - e24152 VL - 23 IS - 8 KW - extended reality KW - virtual reality KW - augmented reality KW - mixed reality KW - ophthalmology KW - ophthalmic N2 - Background: Virtual reality, augmented reality, and mixed reality make use of a variety of different software and hardware, but they share three main characteristics: immersion, presence, and interaction. The umbrella term for technologies with these characteristics is extended reality. The ability of extended reality to create environments that are otherwise impossible in the real world has practical implications in the medical discipline. In ophthalmology, virtual reality simulators have become increasingly popular as tools for surgical education. Recent developments have also explored diagnostic and therapeutic uses in ophthalmology. Objective: This systematic review aims to identify and investigate the utility of extended reality in ophthalmic education, diagnostics, and therapeutics. Methods: A literature search was conducted using PubMed, Embase, and Cochrane Register of Controlled Trials. Publications from January 1, 1956 to April 15, 2020 were included. Inclusion criteria were studies evaluating the use of extended reality in ophthalmic education, diagnostics, and therapeutics. Eligible studies were evaluated using the Oxford Centre for Evidence-Based Medicine levels of evidence. Relevant studies were also evaluated using a validity framework. Findings and relevant data from the studies were extracted, evaluated, and compared to determine the utility of extended reality in ophthalmology. Results: We identified 12,490 unique records in our literature search; 87 met final eligibility criteria, comprising studies that evaluated the use of extended reality in education (n=54), diagnostics (n=5), and therapeutics (n=28). Of these, 79 studies (91%) achieved evidence levels in the range 2b to 4, indicating poor quality. Only 2 (9%) out of 22 relevant studies addressed all 5 sources of validity evidence. In education, we found that ophthalmic surgical simulators demonstrated efficacy and validity in improving surgical performance and reducing complication rates. Ophthalmoscopy simulators demonstrated efficacy and validity evidence in improving ophthalmoscopy skills in the clinical setting. In diagnostics, studies demonstrated proof-of-concept in presenting ocular imaging data on extended reality platforms and validity in assessing the function of patients with ophthalmic diseases. In therapeutics, heads-up surgical systems had similar complication rates, procedural success rates, and outcomes in comparison with conventional ophthalmic surgery. Conclusions: Extended reality has promising areas of application in ophthalmology, but additional high-quality comparative studies are needed to assess their roles among incumbent methods of ophthalmic education, diagnostics, and therapeutics. UR - https://www.jmir.org/2021/8/e24152 UR - http://dx.doi.org/10.2196/24152 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420929 ID - info:doi/10.2196/24152 ER - TY - JOUR AU - Sharma, Narayan AU - Schwendimann, René AU - Endrich, Olga AU - Ausserhofer, Dietmar AU - Simon, Michael PY - 2021/8/19 TI - Variation of Daily Care Demand in Swiss General Hospitals: Longitudinal Study on Capacity Utilization, Patient Turnover and Clinical Complexity Levels JO - J Med Internet Res SP - e27163 VL - 23 IS - 8 KW - inpatient population KW - routine data KW - general hospitals KW - capacity utilization KW - clinical complexity KW - patient data KW - hospital system KW - complexity algorithm N2 - Background: Variations in hospitals? care demand relies not only on the patient volume but also on the disease severity. Understanding both daily severity and patient volume in hospitals could help to identify hospital pressure zones to improve hospital-capacity planning and policy-making. Objective: This longitudinal study explored daily care demand dynamics in Swiss general hospitals for 3 measures: (1) capacity utilization, (2) patient turnover, and (3) patient clinical complexity level. Methods: A retrospective population-based analysis was conducted with 1 year of routine data of 1.2 million inpatients from 102 Swiss general hospitals. Capacity utilization was measured as a percentage of the daily maximum number of inpatients. Patient turnover was measured as a percentage of the daily sum of admissions and discharges per hospital. Patient clinical complexity level was measured as the average daily patient disease severity per hospital from the clinical complexity algorithm. Results: There was a pronounced variability of care demand in Swiss general hospitals. Among hospitals, the average daily capacity utilization ranged from 57.8% (95% CI 57.3-58.4) to 87.7% (95% CI 87.3-88.0), patient turnover ranged from 22.5% (95% CI 22.1-22.8) to 34.5% (95% CI 34.3-34.7), and the mean patient clinical complexity level ranged from 1.26 (95% CI 1.25-1.27) to 2.06 (95% CI 2.05-2.07). Moreover, both within and between hospitals, all 3 measures varied distinctly between days of the year, between days of the week, between weekdays and weekends, and between seasons. Conclusions: While admissions and discharges drive capacity utilization and patient turnover variation, disease severity of each patient drives patient clinical complexity level. Monitoring?and, if possible, anticipating?daily care demand fluctuations is key to managing hospital pressure zones. This study provides a pathway for identifying patients? daily exposure to strained hospital systems for a time-varying causal model. UR - https://www.jmir.org/2021/8/e27163 UR - http://dx.doi.org/10.2196/27163 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420926 ID - info:doi/10.2196/27163 ER - TY - JOUR AU - Lyles, Rees Courtney AU - Adler-Milstein, Julia AU - Thao, Crishyashi AU - Lisker, Sarah AU - Nouri, Sarah AU - Sarkar, Urmimala PY - 2021/8/26 TI - Alignment of Key Stakeholders? Priorities for Patient-Facing Tools in Digital Health: Mixed Methods Study JO - J Med Internet Res SP - e24890 VL - 23 IS - 8 KW - medical informatics KW - medical informatics apps KW - information technology KW - implementation science KW - mixed methods N2 - Background: There is widespread agreement on the promise of patient-facing digital health tools to transform health care. Yet, few tools are in widespread use or have documented clinical effectiveness. Objective: The aim of this study was to gain insight into the gap between the potential of patient-facing digital health tools and real-world uptake. Methods: We interviewed and surveyed experts (in total, n=24) across key digital health stakeholder groups?venture capitalists, digital health companies, payers, and health care system providers or leaders?guided by the Consolidated Framework for Implementation Research. Results: Our findings revealed that external policy, regulatory demands, internal organizational workflow, and integration needs often take priority over patient needs and patient preferences for digital health tools, which lowers patient acceptance rates. We discovered alignment, across all 4 stakeholder groups, in the desire to engage both patients and frontline health care providers in broader dissemination and evaluation of digital health tools. However, major areas of misalignment between stakeholder groups have stymied the progress of digital health tool uptake?venture capitalists and companies focused on external policy and regulatory demands, while payers and providers focused on internal organizational workflow and integration needs. Conclusions: Misalignment of the priorities of digital health companies and their funders with those of providers and payers requires direct attention to improve uptake of patient-facing digital health tools and platforms. UR - https://www.jmir.org/2021/8/e24890 UR - http://dx.doi.org/10.2196/24890 UR - http://www.ncbi.nlm.nih.gov/pubmed/34435966 ID - info:doi/10.2196/24890 ER - TY - JOUR AU - Trojan, Andreas AU - Leuthold, Nicolas AU - Thomssen, Christoph AU - Rody, Achim AU - Winder, Thomas AU - Jakob, Andreas AU - Egger, Claudine AU - Held, Ulrike AU - Jackisch, Christian PY - 2021/8/5 TI - The Effect of Collaborative Reviews of Electronic Patient-Reported Outcomes on the Congruence of Patient- and Clinician-Reported Toxicity in Cancer Patients Receiving Systemic Therapy: Prospective, Multicenter, Observational Clinical Trial JO - J Med Internet Res SP - e29271 VL - 23 IS - 8 KW - cancer KW - consilium KW - app KW - eHealth KW - ePRO KW - CTCAE KW - congruency KW - patient-reported KW - symptoms N2 - Background: Electronic patient-reported outcomes (ePRO) are a relatively novel form of data and have the potential to improve clinical practice for cancer patients. In this prospective, multicenter, observational clinical trial, efforts were made to demonstrate the reliability of patient-reported symptoms. Objective: The primary objective of this study was to assess the level of agreement ? between symptom ratings by physicians and patients via a shared review process in order to determine the future reliability and utility of self-reported electronic symptom monitoring. Methods: Patients receiving systemic therapy in a (neo-)adjuvant or noncurative intention setting captured ePRO for 52 symptoms over an observational period of 90 days. At 3-week intervals, randomly selected symptoms were reviewed between the patient and physician for congruency on severity of the grading of adverse events according to the Common Terminology Criteria of Adverse Events (CTCAE). The patient-physician agreement for the symptom review was assessed via Cohen kappa (?), through which the interrater reliability was calculated. Chi-square tests were used to determine whether the patient-reported outcome was different among symptoms, types of cancer, demographics, and physicians? experience. Results: Among the 181 patients (158 women and 23 men; median age 54.4 years), there was a fair scoring agreement (?=0.24; 95% CI 0.16-0.33) for symptoms that were entered 2 to 4 weeks before the intended review (first rating) and a moderate agreement (?=0.41; 95% CI 0.34-0.48) for symptoms that were entered within 1 week of the intended review (second rating). However, the level of agreement increased from moderate (first rating, ?=0.43) to substantial (second rating, ?=0.68) for common symptoms of pain, fever, diarrhea, obstipation, nausea, vomiting, and stomatitis. Similar congruency levels of ratings were found for the most frequently entered symptoms (first rating: ?=0.42; second rating: ?=0.65). The symptom with the lowest agreement was hair loss (?=?0.05). With regard to the latency of symptom entry into the review, hardly any difference was demonstrated between symptoms that were entered from days 1 to 3 and from days 4 to 7 before the intended review (?=0.40 vs ?=0.39, respectively). In contrast, for symptoms that were entered 15 to 21 days before the intended review, no congruency was demonstrated (?=?0.15). Congruency levels seemed to be unrelated to the type of cancer, demographics, and physicians? review experience. Conclusions: The shared monitoring and review of symptoms between patients and clinicians has the potential to improve the understanding of patient self-reporting. Our data indicate that the integration of ePRO into oncological clinical research and continuous clinical practice provides reliable information for self-empowerment and the timely intervention of symptoms. Trial Registration: ClinicalTrials.gov NCT03578731; https://clinicaltrials.gov/ct2/show/NCT03578731 UR - https://www.jmir.org/2021/8/e29271 UR - http://dx.doi.org/10.2196/29271 UR - http://www.ncbi.nlm.nih.gov/pubmed/34383675 ID - info:doi/10.2196/29271 ER - TY - JOUR AU - Wee, Ling Priscilla Jia AU - Kwan, Heng Yu AU - Loh, Fang Dionne Hui AU - Phang, Kie Jie AU - Puar, H. Troy AU - Østbye, Truls AU - Thumboo, Julian AU - Yoon, Sungwon AU - Low, Leng Lian PY - 2021/8/13 TI - Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review JO - J Med Internet Res SP - e25002 VL - 23 IS - 8 KW - systematic review KW - measurement properties KW - patient-reported outcome measures KW - methodological quality KW - level of evidence KW - PROMs KW - patient reported outcome KW - diabetes N2 - Background: The management of diabetes is complex. There is growing recognition of the use of patient-reported outcome measures (PROMs) as a standardized method of obtaining an outlook on patients? functional status and well-being. However, no systematic reviews have summarized the studies that investigate the measurement properties of diabetes PROMs. Objective: Our aims were to conduct a systematic review of studies investigating the measurement properties of diabetes PROMs by evaluating the methodological quality and overall level of evidence of these PROMs and to categorize them based on the outcome measures assessed. Methods: This study was guided by the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Relevant articles were retrieved from the Embase, PubMed, and PsychINFO databases. The PROMs were evaluated with the COSMIN (COnsensus-based Standards for the selection of health Measurement Instruments) guidelines. Results: A total of 363 articles evaluating the measurement properties of PROMs for diabetes in the adult population were identified, of which 238 unique PROMs from 248 studies reported in 209 articles were validated in the type 2 diabetes population. PROMs with at least a moderate level of evidence for ?5 of 9 measurement properties include the Chinese version of the Personal Diabetes Questionnaire (C-PDQ), Diabetes Self-Management Instrument Short Form (DSMI-20), and Insulin Treatment Appraisal Scale in Hong Kong primary care patients (C-ITAS-HK), of which the C-PDQ has a ?sufficient (+)? rating for >4 measurement properties. A total of 43 PROMs meet the COSMIN guidelines for recommendation for use. Conclusions: This study identified and synthesized evidence for the measurement properties of 238 unique PROMs for patients with type 2 diabetes and categorized the PROMs according to their outcome measures. These findings may assist clinicians and researchers in selecting appropriate high-quality PROMs for clinical practice and research. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020180978; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020180978. UR - https://www.jmir.org/2021/8/e25002 UR - http://dx.doi.org/10.2196/25002 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397387 ID - info:doi/10.2196/25002 ER - TY - JOUR AU - Heisey-Grove, Dawn AU - Rathert, Cheryl AU - McClelland, E. Laura AU - Jackson, Kevin AU - DeShazo, P. Jonathan PY - 2021/8/19 TI - Patient and Clinician Characteristics Associated With Secure Message Content: Retrospective Cohort Study JO - J Med Internet Res SP - e26650 VL - 23 IS - 8 KW - patient-provider communication KW - electronic messaging KW - hypertension KW - diabetes N2 - Background: Good communication has been shown to affect patient outcomes; however, the effect varies according to patient and clinician characteristics. To date, no research has explored the differences in the content of secure messages based on these characteristics. Objective: This study aims to explore characteristics of patients and clinic staff associated with the content exchanged in secure messages. Methods: We coded 18,309 messages that were part of threads initiated by 1031 patients with hypertension, diabetes, or both conditions, in communication with 711 staff members. We conducted four sets of analyses to identify associations between patient characteristics and the types of messages they sent, staff characteristics and the types of messages they sent, staff characteristics and the types of messages patients sent to them, and patient characteristics and the types of messages they received from staff. Logistic regression was used to estimate the strength of the associations. Results: We found that younger patients had reduced odds of sharing clinical updates (odds ratio [OR] 0.77, 95% CI 0.65-0.91) and requesting prescription refills (OR 0.77, 95% CI 0.65-0.90). Women had reduced odds of self-reporting biometrics (OR 0.78, 95% CI 0.62-0.98) but greater odds of responding to a clinician (OR 1.20, 95% CI 1.02-1.42) and seeking medical guidance (OR 1.19, 95% CI 1.01-1.40). Compared with White patients, Black patients had greater odds of requesting preventive care (OR 2.68, 95% CI 1.30-5.51) but reduced odds of requesting a new or changed prescription (OR 0.72, 95% CI 0.53-0.98) or laboratory or other diagnostic procedures (OR 0.66, 95% CI 0.46-0.95). Staff had lower odds of sharing medical guidance with younger patients (OR 0.83, 95% CI 0.69-1.00) and uninsured patients (OR 0.21, 95% CI 0.06-0.73) but had greater odds of sharing medical guidance with patients with public payers (OR 2.03, 95% CI 1.26-3.25) compared with patients with private payers. Staff had reduced odds of confirming to women that their requests were fulfilled (OR 0.82, 95% CI 0.69-0.98). Compared with physicians, nurse practitioners had greater odds of sharing medical guidance with patients (OR 2.74, 95% CI 1.12-6.68) and receiving prescription refill requests (OR 3.39, 95% CI 1.49-7.71). Registered nurses had greater odds of deferred information sharing (OR 1.61, 95% CI 1.04-2.49) and receiving responses to messages (OR 3.93, 95% CI 2.18-7.11) than physicians. Conclusions: The differences we found in content use based on patient characteristics could lead to the exacerbation of health disparities when content is associated with health outcomes. Disparities in the content of secure messages could exacerbate disparities in patient outcomes, such as satisfaction, trust in the system, self-care, and health outcomes. Staff and administrators should evaluate how secure messaging is used to ensure that disparities in care are not perpetuated via this communication modality. UR - https://www.jmir.org/2021/8/e26650 UR - http://dx.doi.org/10.2196/26650 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420923 ID - info:doi/10.2196/26650 ER - TY - JOUR AU - Yeh, Chia-Han Marvin AU - Wang, Yu-Hsiang AU - Yang, Hsuan-Chia AU - Bai, Kuan-Jen AU - Wang, Hsiao-Han AU - Li, Jack Yu-Chuan PY - 2021/8/3 TI - Artificial Intelligence?Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach JO - J Med Internet Res SP - e26256 VL - 23 IS - 8 KW - artificial intelligence KW - lung cancer screening KW - electronic medical record N2 - Background: Artificial intelligence approaches can integrate complex features and can be used to predict a patient?s risk of developing lung cancer, thereby decreasing the need for unnecessary and expensive diagnostic interventions. Objective: The aim of this study was to use electronic medical records to prescreen patients who are at risk of developing lung cancer. Methods: We randomly selected 2 million participants from the Taiwan National Health Insurance Research Database who received care between 1999 and 2013. We built a predictive lung cancer screening model with neural networks that were trained and validated using pre-2012 data, and we tested the model prospectively on post-2012 data. An age- and gender-matched subgroup that was 10 times larger than the original lung cancer group was used to assess the predictive power of the electronic medical record. Discrimination (area under the receiver operating characteristic curve [AUC]) and calibration analyses were performed. Results: The analysis included 11,617 patients with lung cancer and 1,423,154 control patients. The model achieved AUCs of 0.90 for the overall population and 0.87 in patients ?55 years of age. The AUC in the matched subgroup was 0.82. The positive predictive value was highest (14.3%) among people aged ?55 years with a pre-existing history of lung disease. Conclusions: Our model achieved excellent performance in predicting lung cancer within 1 year and has potential to be deployed for digital patient screening. Convolution neural networks facilitate the effective use of EMRs to identify individuals at high risk for developing lung cancer. UR - https://www.jmir.org/2021/8/e26256 UR - http://dx.doi.org/10.2196/26256 UR - http://www.ncbi.nlm.nih.gov/pubmed/34342588 ID - info:doi/10.2196/26256 ER - TY - JOUR AU - He, Kai AU - Yao, Lixia AU - Zhang, JiaWei AU - Li, Yufei AU - Li, Chen PY - 2021/8/4 TI - Construction of Genealogical Knowledge Graphs From Obituaries: Multitask Neural Network Extraction System JO - J Med Internet Res SP - e25670 VL - 23 IS - 8 KW - genealogical knowledge graph KW - EHR KW - information extraction KW - genealogy KW - neural network N2 - Background: Genealogical information, such as that found in family trees, is imperative for biomedical research such as disease heritability and risk prediction. Researchers have used policyholder and their dependent information in medical claims data and emergency contacts in electronic health records (EHRs) to infer family relationships at a large scale. We have previously demonstrated that online obituaries can be a novel data source for building more complete and accurate family trees. Objective: Aiming at supplementing EHR data with family relationships for biomedical research, we built an end-to-end information extraction system using a multitask-based artificial neural network model to construct genealogical knowledge graphs (GKGs) from online obituaries. GKGs are enriched family trees with detailed information including age, gender, death and birth dates, and residence. Methods: Built on a predefined family relationship map consisting of 4 types of entities (eg, people?s name, residence, birth date, and death date) and 71 types of relationships, we curated a corpus containing 1700 online obituaries from the metropolitan area of Minneapolis and St Paul in Minnesota. We also adopted data augmentation technology to generate additional synthetic data to alleviate the issue of data scarcity for rare family relationships. A multitask-based artificial neural network model was then built to simultaneously detect names, extract relationships between them, and assign attributes (eg, birth dates and death dates, residence, age, and gender) to each individual. In the end, we assemble related GKGs into larger ones by identifying people appearing in multiple obituaries. Results: Our system achieved satisfying precision (94.79%), recall (91.45%), and F-1 measures (93.09%) on 10-fold cross-validation. We also constructed 12,407 GKGs, with the largest one made up of 4 generations and 30 people. Conclusions: In this work, we discussed the meaning of GKGs for biomedical research, presented a new version of a corpus with a predefined family relationship map and augmented training data, and proposed a multitask deep neural system to construct and assemble GKGs. The results show our system can extract and demonstrate the potential of enriching EHR data for more genetic research. We share the source codes and system with the entire scientific community on GitHub without the corpus for privacy protection. UR - https://www.jmir.org/2021/8/e25670 UR - http://dx.doi.org/10.2196/25670 UR - http://www.ncbi.nlm.nih.gov/pubmed/34346903 ID - info:doi/10.2196/25670 ER - TY - JOUR AU - Wang, Xueping AU - Zhong, Jie AU - Lei, Ting AU - Chen, Deng AU - Wang, Haijiao AU - Zhu, Lina AU - Chu, Shanshan AU - Liu, Ling PY - 2021/8/19 TI - An Artificial Neural Network Prediction Model for Posttraumatic Epilepsy: Retrospective Cohort Study JO - J Med Internet Res SP - e25090 VL - 23 IS - 8 KW - artificial neural network KW - posttraumatic epilepsy KW - traumatic brain injury N2 - Background: Posttraumatic epilepsy (PTE) is a common sequela after traumatic brain injury (TBI), and identifying high-risk patients with PTE is necessary for their better treatment. Although artificial neural network (ANN) prediction models have been reported and are superior to traditional models, the ANN prediction model for PTE is lacking. Objective: We aim to train and validate an ANN model to anticipate the risks of PTE. Methods: The training cohort was TBI patients registered at West China Hospital. We used a 5-fold cross-validation approach to train and test the ANN model to avoid overfitting; 21 independent variables were used as input neurons in the ANN models, using a back-propagation algorithm to minimize the loss function. Finally, we obtained sensitivity, specificity, and accuracy of each ANN model from the 5 rounds of cross-validation and compared the accuracy with a nomogram prediction model built in our previous work based on the same population. In addition, we evaluated the performance of the model using patients registered at Chengdu Shang Jin Nan Fu Hospital (testing cohort 1) and Sichuan Provincial People?s Hospital (testing cohort 2) between January 1, 2013, and March 1, 2015. Results: For the training cohort, we enrolled 1301 TBI patients from January 1, 2011, to December 31, 2017. The prevalence of PTE was 12.8% (166/1301, 95% CI 10.9%-14.6%). Of the TBI patients registered in testing cohort 1, PTE prevalence was 10.5% (44/421, 95% CI 7.5%-13.4%). Of the TBI patients registered in testing cohort 2, PTE prevalence was 6.1% (25/413, 95% CI 3.7%-8.4%). The results of the ANN model show that, the area under the receiver operating characteristic curve in the training cohort was 0.907 (95% CI 0.889-0.924), testing cohort 1 was 0.867 (95% CI 0.842-0.893), and testing cohort 2 was 0.859 (95% CI 0.826-0.890). Second, the average accuracy of the training cohort was 0.557 (95% CI 0.510-0.620), with 0.470 (95% CI 0.414-0.526) in testing cohort 1 and 0.344 (95% CI 0.287-0.401) in testing cohort 2. In addition, sensitivity, specificity, positive predictive values and negative predictors in the training cohort (testing cohort 1 and testing cohort 2) were 0.80 (0.83 and 0.80), 0.86 (0.80 and 0.84), 91% (85% and 78%), and 86% (80% and 83%), respectively. When calibrating this ANN model, Brier scored 0.121 in testing cohort 1 and 0.127 in testing cohort 2. Compared with the nomogram model, the ANN prediction model had a higher accuracy (P=.01). Conclusions: This study shows that the ANN model can predict the risk of PTE and is superior to the risk estimated based on traditional statistical methods. However, the calibration of the model is a bit poor, and we need to calibrate it on a large sample size set and further improve the model. UR - https://www.jmir.org/2021/8/e25090 UR - http://dx.doi.org/10.2196/25090 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420931 ID - info:doi/10.2196/25090 ER - TY - JOUR AU - Bang, Seok Chang AU - Lee, Jun Jae AU - Baik, Ho Gwang PY - 2021/8/25 TI - Computer-Aided Diagnosis of Diminutive Colorectal Polyps in Endoscopic Images: Systematic Review and Meta-analysis of Diagnostic Test Accuracy JO - J Med Internet Res SP - e29682 VL - 23 IS - 8 KW - artificial intelligence KW - deep learning KW - polyps KW - colon KW - colonoscopy KW - diminutive N2 - Background: Most colorectal polyps are diminutive and benign, especially those in the rectosigmoid colon, and the resection of these polyps is not cost-effective. Advancements in image-enhanced endoscopy have improved the optical prediction of colorectal polyp histology. However, subjective interpretability and inter- and intraobserver variability prohibits widespread implementation. The number of studies on computer-aided diagnosis (CAD) is increasing; however, their small sample sizes limit statistical significance. Objective: This review aims to evaluate the diagnostic test accuracy of CAD models in predicting the histology of diminutive colorectal polyps by using endoscopic images. Methods: Core databases were searched for studies that were based on endoscopic imaging, used CAD models for the histologic diagnosis of diminutive colorectal polyps, and presented data on diagnostic performance. A systematic review and diagnostic test accuracy meta-analysis were performed. Results: Overall, 13 studies were included. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of diminutive colorectal polyps (adenomatous or neoplastic vs nonadenomatous or nonneoplastic) were 0.96 (95% CI 0.93-0.97), 0.93 (95% CI 0.91-0.95), 0.87 (95% CI 0.76-0.93), and 87 (95% CI 38-201), respectively. The meta-regression analysis showed no heterogeneity, and no publication bias was detected. Subgroup analyses showed robust results. The negative predictive value of CAD models for the diagnosis of adenomatous polyps in the rectosigmoid colon was 0.96 (95% CI 0.95-0.97), and this value exceeded the threshold of the diagnosis and leave strategy. Conclusions: CAD models show potential for the optical histological diagnosis of diminutive colorectal polyps via the use of endoscopic images. Trial Registration: PROSPERO CRD42021232189; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=232189 UR - https://www.jmir.org/2021/8/e29682 UR - http://dx.doi.org/10.2196/29682 UR - http://www.ncbi.nlm.nih.gov/pubmed/34432643 ID - info:doi/10.2196/29682 ER - TY - JOUR AU - Aggarwal, Ravi AU - Farag, Soma AU - Martin, Guy AU - Ashrafian, Hutan AU - Darzi, Ara PY - 2021/8/26 TI - Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey JO - J Med Internet Res SP - e26162 VL - 23 IS - 8 KW - artificial intelligence KW - patient perception KW - data sharing KW - health data KW - privacy N2 - Background: Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to health care. However, for the successful implementation of AI, large amounts of health data are required for training and testing algorithms. As such, there is a need to understand the perspectives and viewpoints of patients regarding the use of their health data in AI research. Objective: We surveyed a large sample of patients for identifying current awareness regarding health data research, and for obtaining their opinions and views on data sharing for AI research purposes, and on the use of AI technology on health care data. Methods: A cross-sectional survey with patients was conducted at a large multisite teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data. Results: A total of 408 participants completed the survey. The respondents had generally low levels of prior knowledge about AI. Most were comfortable with sharing health data with the National Health Service (NHS) (318/408, 77.9%) or universities (268/408, 65.7%), but far fewer with commercial organizations such as technology companies (108/408, 26.4%). The majority endorsed AI research on health care data (357/408, 87.4%) and health care imaging (353/408, 86.4%) in a university setting, provided that concerns about privacy, reidentification of anonymized health care data, and consent processes were addressed. Conclusions: There were significant variations in the patient perceptions, levels of support, and understanding of health data research and AI. Greater public engagement levels and debates are necessary to ensure the acceptability of AI research and its successful integration into clinical practice in future. UR - https://www.jmir.org/2021/8/e26162 UR - http://dx.doi.org/10.2196/26162 UR - http://www.ncbi.nlm.nih.gov/pubmed/34236994 ID - info:doi/10.2196/26162 ER - TY - JOUR AU - Yu, Jessica AU - Chiu, Carter AU - Wang, Yajuan AU - Dzubur, Eldin AU - Lu, Wei AU - Hoffman, Julia PY - 2021/8/27 TI - A Machine Learning Approach to Passively Informed Prediction of Mental Health Risk in People with Diabetes: Retrospective Case-Control Analysis JO - J Med Internet Res SP - e27709 VL - 23 IS - 8 KW - diabetes mellitus KW - mental health KW - risk detection KW - passive sensing KW - ecological momentary assessment KW - machine learning N2 - Background: Proactive detection of mental health needs among people with diabetes mellitus could facilitate early intervention, improve overall health and quality of life, and reduce individual and societal health and economic burdens. Passive sensing and ecological momentary assessment are relatively newer methods that may be leveraged for such proactive detection. Objective: The primary aim of this study was to conceptualize, develop, and evaluate a novel machine learning approach for predicting mental health risk in people with diabetes mellitus. Methods: A retrospective study was designed to develop and evaluate a machine learning model, utilizing data collected from 142,432 individuals with diabetes enrolled in the Livongo for Diabetes program. First, participants? mental health statuses were verified using prescription and medical and pharmacy claims data. Next, four categories of passive sensing signals were extracted from the participants? behavior in the program, including demographics and glucometer, coaching, and event data. Data sets were then assembled to create participant-period instances, and descriptive analyses were conducted to understand the correlation between mental health status and passive sensing signals. Passive sensing signals were then entered into the model to train and test its performance. The model was evaluated based on seven measures: sensitivity, specificity, precision, area under the curve, F1 score, accuracy, and confusion matrix. SHapley Additive exPlanations (SHAP) values were computed to determine the importance of individual signals. Results: In the training (and validation) and three subsequent test sets, the model achieved a confidence score greater than 0.5 for sensitivity, specificity, area under the curve, and accuracy. Signals identified as important by SHAP values included demographics such as race and gender, participant?s emotional state during blood glucose checks, time of day of blood glucose checks, blood glucose values, and interaction with the Livongo mobile app and web platform. Conclusions: Results of this study demonstrate the utility of a passively informed mental health risk algorithm and invite further exploration to identify additional signals and determine when and where such algorithms should be deployed. UR - https://www.jmir.org/2021/8/e27709 UR - http://dx.doi.org/10.2196/27709 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448707 ID - info:doi/10.2196/27709 ER - TY - JOUR AU - English, Ned AU - Anesetti-Rothermel, Andrew AU - Zhao, Chang AU - Latterner, Andrew AU - Benson, F. Adam AU - Herman, Peter AU - Emery, Sherry AU - Schneider, Jordan AU - Rose, W. Shyanika AU - Patel, Minal AU - Schillo, A. Barbara PY - 2021/8/27 TI - Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning?Based Methodology JO - J Med Internet Res SP - e24408 VL - 23 IS - 8 KW - machine learning KW - image classification KW - convolutional neural network KW - object detection KW - crowdsourcing KW - tobacco point of sale KW - public health surveillance N2 - Background: With a rapidly evolving tobacco retail environment, it is increasingly necessary to understand the point-of-sale (POS) advertising environment as part of tobacco surveillance and control. Advances in machine learning and image processing suggest the ability for more efficient and nuanced data capture than previously available. Objective: The study aims to use machine learning algorithms to discover the presence of tobacco advertising in photographs of tobacco POS advertising and their location in the photograph. Methods: We first collected images of the interiors of tobacco retailers in West Virginia and the District of Columbia during 2016 and 2018. The clearest photographs were selected and used to create a training and test data set. We then used a pretrained image classification network model, Inception V3, to discover the presence of tobacco logos and a unified object detection system, You Only Look Once V3, to identify logo locations. Results: Our model was successful in identifying the presence of advertising within images, with a classification accuracy of over 75% for 8 of the 42 brands. Discovering the location of logos within a given photograph was more challenging because of the relatively small training data set, resulting in a mean average precision score of 0.72 and an intersection over union score of 0.62. Conclusions: Our research provides preliminary evidence for a novel methodological approach that tobacco researchers and other public health practitioners can apply in the collection and processing of data for tobacco or other POS surveillance efforts. The resulting surveillance information can inform policy adoption, implementation, and enforcement. Limitations notwithstanding, our analysis shows the promise of using machine learning as part of a suite of tools to understand the tobacco retail environment, make policy recommendations, and design public health interventions at the municipal or other jurisdictional scale. UR - https://www.jmir.org/2021/8/e24408 UR - http://dx.doi.org/10.2196/24408 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448700 ID - info:doi/10.2196/24408 ER - TY - JOUR AU - Naqvi, Ali Syed Asil AU - Tennankore, Karthik AU - Vinson, Amanda AU - Roy, C. Patrice AU - Abidi, Raza Syed Sibte PY - 2021/8/27 TI - Predicting Kidney Graft Survival Using Machine Learning Methods: Prediction Model Development and Feature Significance Analysis Study JO - J Med Internet Res SP - e26843 VL - 23 IS - 8 KW - kidney transplantation KW - machine learning KW - predictive modeling KW - survival prediction KW - dimensionality reduction KW - feature sensitivity analysis N2 - Background: Kidney transplantation is the optimal treatment for patients with end-stage renal disease. Short- and long-term kidney graft survival is influenced by a number of donor and recipient factors. Predicting the success of kidney transplantation is important for optimizing kidney allocation. Objective: The aim of this study was to predict the risk of kidney graft failure across three temporal cohorts (within 1 year, within 5 years, and after 5 years following a transplant) based on donor and recipient characteristics. We analyzed a large data set comprising over 50,000 kidney transplants covering an approximate 20-year period. Methods: We applied machine learning?based classification algorithms to develop prediction models for the risk of graft failure for three different temporal cohorts. Deep learning?based autoencoders were applied for data dimensionality reduction, which improved the prediction performance. The influence of features on graft survival for each cohort was studied by investigating a new nonoverlapping patient stratification approach. Results: Our models predicted graft survival with area under the curve scores of 82% within 1 year, 69% within 5 years, and 81% within 17 years. The feature importance analysis elucidated the varying influence of clinical features on graft survival across the three different temporal cohorts. Conclusions: In this study, we applied machine learning to develop risk prediction models for graft failure that demonstrated a high level of prediction performance. Acknowledging that these models performed better than those reported in the literature for existing risk prediction tools, future studies will focus on how best to incorporate these prediction models into clinical care algorithms to optimize the long-term health of kidney recipients. UR - https://www.jmir.org/2021/8/e26843 UR - http://dx.doi.org/10.2196/26843 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448704 ID - info:doi/10.2196/26843 ER - TY - JOUR AU - Chang, Panchun AU - Dang, Jun AU - Dai, Jianrong AU - Sun, Wenzheng PY - 2021/8/27 TI - Real-Time Respiratory Tumor Motion Prediction Based on a Temporal Convolutional Neural Network: Prediction Model Development Study JO - J Med Internet Res SP - e27235 VL - 23 IS - 8 KW - radiation therapy KW - temporal convolutional neural network KW - respiratory signal prediction KW - neural network KW - deep learning model KW - dynamic tracking N2 - Background: The dynamic tracking of tumors with radiation beams in radiation therapy requires the prediction of real-time target locations prior to beam delivery, as treatment involving radiation beams and gating tracking results in time latency. Objective: In this study, a deep learning model that was based on a temporal convolutional neural network was developed to predict internal target locations by using multiple external markers. Methods: Respiratory signals from 69 treatment fractions of 21 patients with cancer who were treated with the CyberKnife Synchrony device (Accuray Incorporated) were used to train and test the model. The reported model?s performance was evaluated by comparing the model to a long short-term memory model in terms of the root mean square errors (RMSEs) of real and predicted respiratory signals. The effect of the number of external markers was also investigated. Results: The average RMSEs of predicted (ahead time=400 ms) respiratory motion in the superior-inferior, anterior-posterior, and left-right directions and in 3D space were 0.49 mm, 0.28 mm, 0.25 mm, and 0.67 mm, respectively. Conclusions: The experiment results demonstrated that the temporal convolutional neural network?based respiratory prediction model could predict respiratory signals with submillimeter accuracy. UR - https://www.jmir.org/2021/8/e27235 UR - http://dx.doi.org/10.2196/27235 UR - http://www.ncbi.nlm.nih.gov/pubmed/34236336 ID - info:doi/10.2196/27235 ER - TY - JOUR AU - Hornsby, B. AU - Ensaff, H. PY - 2021/8/19 TI - Perspectives on Fruit and Vegetable Consumption and Government Dietary Guidelines: Content Analysis of Comments on News Websites JO - J Med Internet Res SP - e19917 VL - 23 IS - 8 KW - medical news KW - online news KW - user comments KW - public health KW - population health KW - qualitative analysis KW - perspectives KW - dietary guidelines KW - diet KW - fruit and vegetable consumption KW - mobile phone N2 - Background: News websites are an essential source of medical news for the public. Many websites offer users the opportunity to leave comments, which may provide rich insights into public perspectives on health issues. With an established role in public health, fruit and vegetable (FV) consumption is central to the government?s dietary guidelines. However, FV intake continues to fall short of government recommendations. Objective: Using comments from news websites, this study aims to explore public perspectives on FV intake and related government dietary guidelines. Methods: Data comprised 2696 web user comments generated in response to substantial media coverage for a meta-analysis examining FV consumption and the risk of all-cause mortality, cardiovascular disease, and total cancer. Using an inductive thematic approach, the data were analyzed and coded in an iterative process. Results: Four overarching themes emerged: personal factors, rejection, lack of knowledge, and food landscape, each with component subthemes. The lack of clarity around government dietary health guidelines was apparent, and this, along with emergent personal factors, may hinder better consumption. Rejection was also evident, as was a quality versus quantity of life debate. Conclusions: There are gaps in the public?s understanding of government guidelines, which may act as a constraint to better compliance. Further work should examine this issue and rejection and the possibility of public fatigue related to dietary health information and news. Similarly, future work should also explore targeted interventions with a specific emphasis on health literacy. UR - https://www.jmir.org/2021/8/e19917 UR - http://dx.doi.org/10.2196/19917 UR - http://www.ncbi.nlm.nih.gov/pubmed/34420913 ID - info:doi/10.2196/19917 ER - TY - JOUR AU - Koshechkin, Konstantin AU - Lebedev, Georgy AU - Radzievsky, George AU - Seepold, Ralf AU - Martinez, Madrid Natividad PY - 2021/8/18 TI - Blockchain Technology Projects to Provide Telemedical Services: Systematic Review JO - J Med Internet Res SP - e17475 VL - 23 IS - 8 KW - telemedicine KW - distributed ledger KW - health information exchange KW - blockchain N2 - Background: One of the most promising health care development areas is introducing telemedicine services and creating solutions based on blockchain technology. The study of systems combining both these domains indicates the ongoing expansion of digital technologies in this market segment. Objective: This paper aims to review the feasibility of blockchain technology for telemedicine. Methods: The authors identified relevant studies via systematic searches of databases including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar. The suitability of each for inclusion in this review was assessed independently. Owing to the lack of publications, available blockchain-based tokens were discovered via conventional web search engines (Google, Yahoo, and Yandex). Results: Of the 40 discovered projects, only 18 met the selection criteria. The 5 most prevalent features of the available solutions (N=18) were medical data access (14/18, 78%), medical service processing (14/18, 78%), diagnostic support (10/18, 56%), payment transactions (10/18, 56%), and fundraising for telemedical instrument development (5/18, 28%). Conclusions: These different features (eg, medical data access, medical service processing, epidemiology reporting, diagnostic support, and treatment support) allow us to discuss the possibilities for integration of blockchain technology into telemedicine and health care on different levels. In this area, a wide range of tasks can be identified that could be accomplished based on digital technologies using blockchains. UR - https://www.jmir.org/2021/8/e17475 UR - http://dx.doi.org/10.2196/17475 UR - http://www.ncbi.nlm.nih.gov/pubmed/34407924 ID - info:doi/10.2196/17475 ER - TY - JOUR AU - Liu, Liyun AU - Shi, Lizheng PY - 2021/8/13 TI - Chinese Patients? Intention to Use Different Types of Internet Hospitals: Cross-sectional Study on Virtual Visits JO - J Med Internet Res SP - e25978 VL - 23 IS - 8 KW - internet hospital KW - direct-to-consumer telemedicine KW - virtual visit KW - trust KW - intention to use KW - sponsorship type N2 - Background: The issuing of regulation schemes and the expanding health insurance coverage for virtual visits of internet hospitals would incentivize Chinese providers and patients to use virtual visits tremendously. China?s internet hospitals vary in sponsorship. However, little is known about patients? intention to use virtual visits delivered by different sponsorship types of internet hospitals. Objective: The goal of the research is to examine patients? intention to use virtual visits, as well as virtual visits delivered by different sponsorship types of internet hospitals. In addition, we will identify determinants of patients? intention to use virtual visits, as well as intention to use virtual visits delivered by different sponsorship types of internet hospitals. Methods: A cross-sectional survey of 1653 participants was conducted in 3-tier hospitals in 3 cities with different income levels in May and June 2019. Binary logistic regression analysis was used to identify the factors that affect patients? intention to use virtual visits. Multinomial logistic regression analysis was conducted to identify the determinants of the intention to use virtual visits delivered by different sponsorship types of internet hospitals (ie, enterprise-sponsored, hospital-sponsored, and government-sponsored). Results: A total of 76.64% (1145/1494) of adult participants were online medical information seekers, and 87.06% (969/1113) of online medical information seekers had intention to use virtual visits. Public hospital?sponsored internet hospitals were the most prevalent ones among Chinese patients (473/894, 52.9%), followed by the provincial government internet hospital platform (238/894, 26.6%), digital health companies (116/894, 13.0%), medical e-commerce companies (48/894, 5.4%), private hospitals (13/894, 1.5%), and other companies (6/894, 0.7%). Gender, education, monthly income, and consumer type were significantly associated with the intention to use virtual visits. Gender, age, education, city income level, consumer type, and trust in the sponsor of a health website were significantly associated with the patient?s intention to use virtual visits delivered by 3 different sponsorship types of internet hospitals. Conclusions: Chinese patients who were online medical information seekers had high intention to use virtual visits and had different intentions to use virtual visits delivered by different sponsorship types of internet hospitals. Public hospitals, the government, and digital health companies were the top 3 sponsorship types of internet hospitals that patients had intention to use. Trust in a health website sponsor significantly influenced the patient?s intention to use virtual visits delivered by different sponsorship types of internet hospitals. Gender, education, and consumer type were the factors significantly associated with both the intention to use virtual visits and the intention to use virtual visits delivered by different sponsorship types of internet hospitals. UR - https://www.jmir.org/2021/8/e25978 UR - http://dx.doi.org/10.2196/25978 UR - http://www.ncbi.nlm.nih.gov/pubmed/34397388 ID - info:doi/10.2196/25978 ER - TY - JOUR AU - Rostad, Marie Hanne AU - Stokke, Randi PY - 2021/8/16 TI - Integrating Welfare Technology in Long-term Care Services: Nationwide Cross-sectional Survey Study JO - J Med Internet Res SP - e22316 VL - 23 IS - 8 KW - ambient assisted living KW - cross-sectional survey KW - home care services KW - innovation KW - long-term care KW - nursing homes KW - telecare KW - welfare technology KW - mobile phone N2 - Background: Welfare technologies are often described as a solution to the increasing pressure on primary health care services. However, despite initiating welfare technology projects in the health care sector and different government incentives, research indicates that it is difficult to integrate welfare technology innovations in a complex and varying setting, such as long-term care. Objective: We aim to describe the types of welfare technology and the extent to which welfare technology is provided in long-term care (ie, nursing homes and home care services); examine whether the extent of welfare technology provision differs on the basis of municipal characteristics (ie, population size, centrality, the proportion of older inhabitants, and income); and identify how local governments (ie, municipalities) describe their efforts toward integrating welfare technologies in long-term care. Methods: Quantitative and qualitative data about welfare technology from a larger cross-sectional survey about the provision of long-term care services in Norwegian municipalities were combined with registry data. Representatives of 422 Norwegian municipalities were invited to participate in the survey. Frequencies were used to describe the distribution of the types and extent of welfare technologies, whereas the Fisher exact test and Kruskal-Wallis one-way analysis of variance were used to determine the association between the extent of welfare technology and municipal characteristics. Free-form text data were analyzed using thematic analysis. Results: A total of 277 municipalities were surveyed. Technology for safety was the most widespread type of welfare technology, whereas technology for social contact was the least prevalent. Two-thirds of the sample (183/277, 66.1%) in nursing home and (197/277, 71.1%) in home care services reported providing one or two different types of welfare technology. There was a statistically significant association between the extent of welfare technology and population size (in both nursing homes and home care services: P=.01), centrality (nursing homes: P=.01; home care services: P<.001), and municipal income (nursing homes: P=.02; home care services: P<.001). The extent of welfare technology was not associated with the proportion of older adults. The municipalities described being in a piloting phase and committing to future investment in welfare technology. Monetary resources were allocated, competency development among staff was initiated, and the municipalities were concerned about establishing collaborations within and between municipalities. Home care services seem to have a more person-centered approach in their efforts toward integrating welfare technologies, whereas nursing homes seem to have a more technology-centered approach. Conclusions: Many municipalities provide welfare technologies; however, their extent is limited and varies according to municipal characteristics. Municipal practices still seem dominated by piloting, and welfare technologies are not fully integrated into long-term care services. Innovation with welfare technology appears top-down and is influenced by national policy but also reflects creating a window of opportunity through the organization of municipal efforts toward integrating welfare technology through, for example, collaborations and committing personnel and financial resources. UR - https://www.jmir.org/2021/8/e22316 UR - http://dx.doi.org/10.2196/22316 UR - http://www.ncbi.nlm.nih.gov/pubmed/34398791 ID - info:doi/10.2196/22316 ER - TY - JOUR AU - Khuntia, Jiban AU - Ning, Xue AU - Stacey, Rulon PY - 2021/8/16 TI - Digital Orientation of Health Systems in the Post?COVID-19 ?New Normal? in the United States: Cross-sectional Survey JO - J Med Internet Res SP - e30453 VL - 23 IS - 8 KW - post?COVID-19 KW - digital orientation KW - health systems KW - digital transformation KW - digital health KW - telehealth KW - telemedicine KW - COVID-19 KW - impact KW - insight KW - cross-sectional KW - survey KW - United States KW - electronic health record KW - EHR N2 - Background: Almost all health systems have developed some form of customer-facing digital technologies and have worked to align these systems to their existing electronic health records to accommodate the surge in remote and virtual care deliveries during the COVID-19 pandemic. Others have developed analytics-driven decision-making capabilities. However, it is not clear how health systems in the United States are embracing digital technologies and there is a gap in health systems? abilities to integrate workflows with expanding technologies to spur innovation and futuristic growth. There is a lack of reliable and reported estimates of the current and futuristic digital orientations of health systems. Periodic assessments will provide imperatives to policy formulation and align efforts to yield the transformative power of emerging digital technologies. Objective: The aim of this study was to explore and examine differences in US health systems with respect to digital orientations in the post?COVID-19 ?new normal? in 2021. Differences were assessed in four dimensions: (1) analytics-oriented digital technologies (AODT), (2) customer-oriented digital technologies (CODT), (3) growth and innovation?oriented digital technologies (GODT), and (4) futuristic and experimental digital technologies (FEDT). The former two dimensions are foundational to health systems? digital orientation, whereas the latter two will prepare for future disruptions. Methods: We surveyed a robust group of health system chief executive officers (CEOs) across the United States from February to March 2021. Among the 625 CEOs, 135 (22%) responded to our survey. We considered the above four broad digital technology orientations, which were ratified with expert consensus. Secondary data were collected from the Agency for Healthcare Research and Quality Hospital Compendium, leading to a matched usable dataset of 124 health systems for analysis. We examined the relationship of adopting the four digital orientations to specific hospital characteristics and earlier reported factors as barriers or facilitators to technology adoption. Results: Health systems showed a lower level of CODT (mean 4.70) or GODT (mean 4.54) orientations compared with AODT (mean 5.03), and showed the lowest level of FEDT orientation (mean 4.31). The ordered logistic estimation results provided nuanced insights. Medium-sized (P<.001) health systems, major teaching health systems (P<.001), and systems with high-burden hospitals (P<.001) appear to be doing worse with respect to AODT orientations, raising some concerns. Health systems of medium (P<.001) and large (P=.02) sizes, major teaching health systems (P=.07), those with a high revenue (P=.05), and systems with high-burden hospitals (P<.001) have less CODT orientation. Health systems in the midwest (P=.05) and southern (P=.04) states are more likely to adopt GODT, whereas high-revenue (P=.004) and investor-ownership (P=.01) health systems are deterred from GODT. Health systems of a medium size, and those that are in the midwest (P<.001), south (P<.001), and west (P=.01) are more adept to FEDT, whereas medium (P<.001) and high-revenue (P<.001) health systems, and those with a high discharge rate (P=.04) or high burden (P=.003, P=.005) have subdued FEDT orientations. Conclusions: Almost all health systems have some current foundational digital technological orientations to glean intelligence or service delivery to customers, with some notable exceptions. Comparatively, fewer health systems have growth or futuristic digital orientations. The transformative power of digital technologies can only be leveraged by adopting futuristic digital technologies. Thus, the disparities across these orientations suggest that a holistic, consistent, and well-articulated direction across the United States remains elusive. Accordingly, we suggest that a policy strategy and financial incentives are necessary to spur a well-visioned and articulated digital orientation for all health systems across the United States. In the absence of such a policy to collectively leverage digital transformations, differences in care across the country will continue to be a concern. UR - https://www.jmir.org/2021/8/e30453 UR - http://dx.doi.org/10.2196/30453 UR - http://www.ncbi.nlm.nih.gov/pubmed/34254947 ID - info:doi/10.2196/30453 ER - TY - JOUR AU - Wang, Quan AU - Yang, Ke-Lu AU - Zhang, Zhen AU - Wang, Zhu AU - Li, Chen AU - Li, Lun AU - Tian, Jin-Hui AU - Ye, Ying-Jiang AU - Wang, Shan AU - Jiang, Ke-Wei PY - 2021/8/10 TI - Characterization of Global Research Trends and Prospects on Single-Cell Sequencing Technology: Bibliometric Analysis JO - J Med Internet Res SP - e25789 VL - 23 IS - 8 KW - single-cell sequencing KW - bibliometric analysis KW - cancer KW - cancer genomics KW - bioinformatics KW - cancer subtyping KW - tumor dissociation KW - tumor microenvironment KW - precision medicine KW - immunology KW - development trends KW - hotspots KW - research topics KW - Web of Science KW - CiteSpace KW - VOSviewer KW - network N2 - Background: As single-cell sequencing technology has been gradually introduced, it is essential to characterize global collaboration networks and map development trends over the past 20 years. Objective: The aim of this paper was to illustrate collaboration in the field of single-cell sequencing methods and explore key topics and future directions. Methods: Bibliometric analyses were conducted with CiteSpace and VOSviewer software on publications prior to November 2019 from the Web of Science Core Collection about single-cell sequencing methods. Results: Ultimately, we identified 2489 records, which were published in 495 journals by 14,202 authors from 1970 institutes in 61 countries. There was a noticeable increase in publications in 2014. The United States and high-income countries in Europe contributed to most of the records included. Harvard University, Stanford University, Karolinska Institutes, Peking University, and the University of Washington were the biggest nodes in every cluster of the collaboration network, and SA Teichmann, JC Marioni, A Regev, and FC Tang were the top-producing authors. Keywords co-occurrence analysis suggested applications in immunology as a developing research trend. Conclusions: We concluded that the global collaboration network was unformed and that high-income countries contributed more to the rapidly growth of publications of single-cell sequencing technology. Furthermore, the application in immunology might be the next research hotspot and developmental direction. UR - https://www.jmir.org/2021/8/e25789 UR - http://dx.doi.org/10.2196/25789 UR - http://www.ncbi.nlm.nih.gov/pubmed/34014832 ID - info:doi/10.2196/25789 ER - TY - JOUR AU - Antonio, G. Marcy AU - Petrovskaya, Olga AU - Lau, Francis PY - 2021/8/16 TI - Correction: The State of Evidence in Patient Portals: Umbrella Review JO - J Med Internet Res SP - e32421 VL - 23 IS - 8 UR - https://www.jmir.org/2021/8/e32421 UR - http://dx.doi.org/10.2196/32421 UR - http://www.ncbi.nlm.nih.gov/pubmed/34398799 ID - info:doi/10.2196/32421 ER - TY - JOUR AU - Piotto, Stefano AU - Di Biasi, Luigi AU - Marrafino, Francesco AU - Concilio, Simona PY - 2021/8/2 TI - Evaluating Epidemiological Risk by Using Open Contact Tracing Data: Correlational Study JO - J Med Internet Res SP - e28947 VL - 23 IS - 8 KW - SARS-CoV-2 KW - COVID-19 KW - contact tracing KW - Bluetooth Low Energy KW - transmission dynamics KW - infection spread KW - mobile apps KW - mHealth KW - digital apps KW - mobile phone N2 - Background: During the 2020s, there has been extensive debate about the possibility of using contact tracing (CT) to contain the SARS-CoV-2 pandemic, and concerns have been raised about data security and privacy. Little has been said about the effectiveness of CT. In this paper, we present a real data analysis of a CT experiment that was conducted in Italy for 8 months and involved more than 100,000 CT app users. Objective: We aimed to discuss the technical and health aspects of using a centralized approach. We also aimed to show the correlation between the acquired contact data and the number of SARS-CoV-2?positive cases. Finally, we aimed to analyze CT data to define population behaviors and show the potential applications of real CT data. Methods: We collected, analyzed, and evaluated CT data on the duration, persistence, and frequency of contacts over several months of observation. A statistical test was conducted to determine whether there was a correlation between indices of behavior that were calculated from the data and the number of new SARS-CoV-2 infections in the population (new SARS-CoV-2?positive cases). Results: We found evidence of a correlation between a weighted measure of contacts and the number of new SARS-CoV-2?positive cases (Pearson coefficient=0.86), thereby paving the road to better and more accurate data analyses and spread predictions. Conclusions: Our data have been used to determine the most relevant epidemiological parameters and can be used to develop an agent-based system for simulating the effects of restrictions and vaccinations. Further, we demonstrated our system's ability to identify the physical locations where the probability of infection is the highest. All the data we collected are available to the scientific community for further analysis. UR - https://www.jmir.org/2021/8/e28947 UR - http://dx.doi.org/10.2196/28947 UR - http://www.ncbi.nlm.nih.gov/pubmed/34227997 ID - info:doi/10.2196/28947 ER - TY - JOUR AU - Masngut, Nasaai AU - Mohamad, Emma PY - 2021/8/4 TI - Association Between Public Opinion and Malaysian Government Communication Strategies About the COVID-19 Crisis: Content Analysis of Image Repair Strategies in Social Media JO - J Med Internet Res SP - e28074 VL - 23 IS - 8 KW - COVID-19 KW - crisis KW - health communication KW - image repair KW - Malaysian government KW - sentiment KW - communication KW - content analysis KW - public opinion KW - social media KW - strategy N2 - Background: The COVID-19 health crisis has posed an unprecedented challenge for governments worldwide to manage and communicate about the pandemic effectively, while maintaining public trust. Good leadership image in times of a health emergency is paramount to ensure public confidence in governments? abilities to manage the crisis. Objective: The aim of this study was to identify types of image repair strategies utilized by the Malaysian government in their communication about COVID-19 in the media and analyze public responses to these messages on social media. Methods: Content analysis was employed to analyze 120 media statements and 382 comments retrieved from Facebook pages of 2 mainstream newspapers?Berita Harian and The Star. These media statements and comments were collected within a span of 6 weeks prior to and during the first implementation of Movement Control Order by the Malaysian Government. The media statements were analyzed according to Image Repair Theory to categorize strategies employed in government communications related to COVID-19 crisis. Public opinion responses were measured using modified lexicon-based sentiment analysis to categorize positive, negative, and neutral statements. Results: The Malaysian government employed all 5 Image Repair Theory strategies in their communications in both newspapers. The strategy most utilized was reducing offensiveness (75/120, 62.5%), followed by corrective action (30/120, 25.0%), evading responsibilities (10/120, 8.3%), denial (4/120, 3.3%), and mortification (1/120, 0.8%). This study also found multiple substrategies in government media statements including denial, shifting blame, provocation, defeasibility, accident, good intention, bolstering, minimization, differentiation, transcendence, attacking accuser, resolve problem, prevent recurrence, admit wrongdoing, and apologize. This study also found that 64.7% of public opinion was positive in response to media statements made by the Malaysian government and also revealed a significant positive association (P=.04) between image repair strategies utilized by the Malaysian government and public opinion. Conclusions: Communication in the media may assist the government in fostering positive support from the public. Suitable image repair strategies could garner positive public responses and help build trust in times of crisis. UR - https://www.jmir.org/2021/8/e28074 UR - http://dx.doi.org/10.2196/28074 UR - http://www.ncbi.nlm.nih.gov/pubmed/34156967 ID - info:doi/10.2196/28074 ER - TY - JOUR AU - Barbazza, Erica AU - Ivankovi?, Damir AU - Wang, Sophie AU - Gilmore, Jamieson Kendall AU - Poldrugovac, Mircha AU - Willmington, Claire AU - Larrain, Nicolas AU - Bos, Véronique AU - Allin, Sara AU - Klazinga, Niek AU - Kringos, Dionne PY - 2021/8/6 TI - Exploring Changes to the Actionability of COVID-19 Dashboards Over the Course of 2020 in the Canadian Context: Descriptive Assessment and Expert Appraisal Study JO - J Med Internet Res SP - e30200 VL - 23 IS - 8 KW - COVID-19 KW - performance measures KW - health information management KW - dashboards KW - public reporting of health care data KW - qualitative research KW - public health KW - medical informatics KW - surveillance KW - communication KW - assessment KW - Canada KW - decision-making KW - dynamic KW - development N2 - Background: Public web-based COVID-19 dashboards are in use worldwide to communicate pandemic-related information. Actionability of dashboards, as a predictor of their potential use for data-driven decision-making, was assessed in a global study during the early stages of the pandemic. It revealed a widespread lack of features needed to support actionability. In view of the inherently dynamic nature of dashboards and their unprecedented speed of creation, the evolution of dashboards and changes to their actionability merit exploration. Objective: We aimed to explore how COVID-19 dashboards evolved in the Canadian context during 2020 and whether the presence of actionability features changed over time. Methods: We conducted a descriptive assessment of a pan-Canadian sample of COVID-19 dashboards (N=26), followed by an appraisal of changes to their actionability by a panel of expert scorers (N=8). Scorers assessed the dashboards at two points in time, July and November 2020, using an assessment tool informed by communication theory and health care performance intelligence. Applying the nominal group technique, scorers were grouped in panels of three, and evaluated the presence of the seven defined features of highly actionable dashboards at each time point. Results: Improvements had been made to the dashboards over time. These predominantly involved data provision (specificity of geographic breakdowns, range of indicators reported, and explanations of data sources or calculations) and advancements enabled by the technologies employed (customization of time trends and interactive or visual chart elements). Further improvements in actionability were noted especially in features involving local-level data provision, time-trend reporting, and indicator management. No improvements were found in communicative elements (clarity of purpose and audience), while the use of storytelling techniques to narrate trends remained largely absent from the dashboards. Conclusions: Improvements to COVID-19 dashboards in the Canadian context during 2020 were seen mostly in data availability and dashboard technology. Further improving the actionability of dashboards for public reporting will require attention to both technical and organizational aspects of dashboard development. Such efforts would include better skill-mixing across disciplines, continued investment in data standards, and clearer mandates for their developers to ensure accountability and the development of purpose-driven dashboards. UR - https://www.jmir.org/2021/8/e30200 UR - http://dx.doi.org/10.2196/30200 UR - http://www.ncbi.nlm.nih.gov/pubmed/34280120 ID - info:doi/10.2196/30200 ER - TY - JOUR AU - große Deters, Fenne AU - Meier, Tabea AU - Milek, Anne AU - Horn, B. Andrea PY - 2021/8/10 TI - Self-Focused and Other-Focused Health Concerns as Predictors of the Uptake of Corona Contact Tracing Apps: Empirical Study JO - J Med Internet Res SP - e29268 VL - 23 IS - 8 KW - COVID-19 KW - corona contact tracing app KW - digital proximity tracing KW - preventive behavior KW - health concern KW - prosocial motivation KW - public health KW - risk perception, eHealth, Corona-Warn-App KW - SwissCovid KW - contact tracing app KW - contact tracing N2 - Background: Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial. Objective: This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one?s own health and concern to unknowingly infect others. Methods: A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables. Results: Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one?s own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that ?too much? concern leads to defensive reactions and reduces app uptake. Conclusions: As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed. UR - https://www.jmir.org/2021/8/e29268 UR - http://dx.doi.org/10.2196/29268 UR - http://www.ncbi.nlm.nih.gov/pubmed/34227995 ID - info:doi/10.2196/29268 ER - TY - JOUR AU - Liu, Siru AU - Li, Jili AU - Liu, Jialin PY - 2021/8/10 TI - Leveraging Transfer Learning to Analyze Opinions, Attitudes, and Behavioral Intentions Toward COVID-19 Vaccines: Social Media Content and Temporal Analysis JO - J Med Internet Res SP - e30251 VL - 23 IS - 8 KW - vaccine KW - COVID-19 KW - leveraging transfer learning KW - pandemic KW - infodemiology KW - infoveillance KW - public health KW - social media KW - content analysis KW - machine learning KW - online health N2 - Background: The COVID-19 vaccine is considered to be the most promising approach to alleviate the pandemic. However, in recent surveys, acceptance of the COVID-19 vaccine has been low. To design more effective outreach interventions, there is an urgent need to understand public perceptions of COVID-19 vaccines. Objective: Our objective was to analyze the potential of leveraging transfer learning to detect tweets containing opinions, attitudes, and behavioral intentions toward COVID-19 vaccines, and to explore temporal trends as well as automatically extract topics across a large number of tweets. Methods: We developed machine learning and transfer learning models to classify tweets, followed by temporal analysis and topic modeling on a dataset of COVID-19 vaccine?related tweets posted from November 1, 2020 to January 31, 2021. We used the F1 values as the primary outcome to compare the performance of machine learning and transfer learning models. The statistical values and P values from the Augmented Dickey-Fuller test were used to assess whether users? perceptions changed over time. The main topics in tweets were extracted by latent Dirichlet allocation analysis. Results: We collected 2,678,372 tweets related to COVID-19 vaccines from 841,978 unique users and annotated 5000 tweets. The F1 values of transfer learning models were 0.792 (95% CI 0.789-0.795), 0.578 (95% CI 0.572-0.584), and 0.614 (95% CI 0.606-0.622) for these three tasks, which significantly outperformed the machine learning models (logistic regression, random forest, and support vector machine). The prevalence of tweets containing attitudes and behavioral intentions varied significantly over time. Specifically, tweets containing positive behavioral intentions increased significantly in December 2020. In addition, we selected tweets in the following categories: positive attitudes, negative attitudes, positive behavioral intentions, and negative behavioral intentions. We then identified 10 main topics and relevant terms for each category. Conclusions: Overall, we provided a method to automatically analyze the public understanding of COVID-19 vaccines from real-time data in social media, which can be used to tailor educational programs and other interventions to effectively promote the public acceptance of COVID-19 vaccines. UR - https://www.jmir.org/2021/8/e30251 UR - http://dx.doi.org/10.2196/30251 UR - http://www.ncbi.nlm.nih.gov/pubmed/34254942 ID - info:doi/10.2196/30251 ER - TY - JOUR AU - Tan, Hao AU - Peng, Sheng-Lan AU - Zhu, Chun-Peng AU - You, Zuo AU - Miao, Ming-Cheng AU - Kuai, Shu-Guang PY - 2021/8/12 TI - Long-term Effects of the COVID-19 Pandemic on Public Sentiments in Mainland China: Sentiment Analysis of Social Media Posts JO - J Med Internet Res SP - e29150 VL - 23 IS - 8 KW - COVID-19 KW - emotional trauma KW - public sentiment on social media KW - long-term effect N2 - Background: The COVID-19 outbreak has induced negative emotions among people. These emotions are expressed by the public on social media and are rapidly spread across the internet, which could cause high levels of panic among the public. Understanding the changes in public sentiment on social media during the pandemic can provide valuable information for developing appropriate policies to reduce the negative impact of the pandemic on the public. Previous studies have consistently shown that the COVID-19 outbreak has had a devastating negative impact on public sentiment. However, it remains unclear whether there has been a variation in the public sentiment during the recovery phase of the pandemic. Objective: In this study, we aim to determine the impact of the COVID-19 pandemic in mainland China by continuously tracking public sentiment on social media throughout 2020. Methods: We collected 64,723,242 posts from Sina Weibo, China?s largest social media platform, and conducted a sentiment analysis based on natural language processing to analyze the emotions reflected in these posts. Results: We found that the COVID-19 pandemic not only affected public sentiment on social media during the initial outbreak but also induced long-term negative effects even in the recovery period. These long-term negative effects were no longer correlated with the number of new confirmed COVID-19 cases both locally and nationwide during the recovery period, and they were not attributed to the postpandemic economic recession. Conclusions: The COVID-19 pandemic induced long-term negative effects on public sentiment in mainland China even as the country recovered from the pandemic. Our study findings remind public health and government administrators of the need to pay attention to public mental health even once the pandemic has concluded. UR - https://www.jmir.org/2021/8/e29150 UR - http://dx.doi.org/10.2196/29150 UR - http://www.ncbi.nlm.nih.gov/pubmed/34280118 ID - info:doi/10.2196/29150 ER - TY - JOUR AU - Beaudoin, E. Christopher AU - Hong, Traci PY - 2021/8/12 TI - Predictors of COVID-19 Preventive Perceptions and Behaviors Among Millennials: Two Cross-sectional Survey Studies JO - J Med Internet Res SP - e30612 VL - 23 IS - 8 KW - COVID-19 KW - coronavirus KW - pandemic KW - preventive perceptions KW - preventive behaviors KW - health information seeking KW - political party identification KW - COVID-19 testing N2 - Background: COVID-19 preventive perceptions and behaviors, especially among US millennials, are an important means by which the pandemic can be slowed and negative health outcomes can be averted. Objective: This manuscript aims to advance knowledge on COVID-19 preventive perceptions and behaviors and their main predictors, including digital health information?seeking behavior (HISB), political party identification, and COVID-19 testing status. Methods: Two cross-sectional online surveys of US millennials were conducted from April 10 to 14, 2020 (N=274) (ie, Study 1), and from April 27 to May 7, 2020 (N=1037) (ie, Study 2). In the regression models, dependent variables included preventive behaviors (eg, wearing a face mask and social distancing) as well as four preventive perceptions: severity (ie, a person?s conception of the seriousness of COVID-19), susceptibility (ie, a person?s conception of the likelihood of being infected with COVID-19), self-efficacy (ie, a person?s perception that he or she can wear a face mask and perform social distancing to prevent COVID-19 infection), and response efficacy (ie, a person?s perception of whether wearing a face mask and social distancing can prevent COVID-19 infection). Key independent variables included digital HISB for self, digital HISB for another person, political party identification, and COVID-19 testing status. Results: Millennials reported lower levels of perceived susceptibility than the other three preventive perceptions (ie, severity, self-efficacy, and response efficacy), as well as fairly high levels of preventive behaviors. Unlike HISB for another person, digital HISB for self was positively associated with preventive perceptions and behaviors. In Study 1, respondents with higher levels of digital HISB for self had significantly higher perceptions of severity (?=.22, P<.001), self-efficacy (?=.15, P=.02), and response efficacy (?=.25, P<.001) as well as, at nearing significance, higher perceptions of susceptibility (?=.11, P=.07). In Study 2, respondents with higher levels of digital HISB for self had significantly higher perceptions of severity (?=.25, P<.001), susceptibility (?=.14, P<.001), and preventive behaviors (?=.24, P<.001). Preventive behaviors did not vary significantly according to political party identification, but preventive perceptions did. In Study 1, respondents who identified as being more Republican had significantly lower perceptions of self-efficacy (?=?.14, P=.02) and response efficacy (?=?.13, P=.03) and, at nearing significance, lower perceptions of severity (?=?.10, P=.08) and susceptibility (?=?.12, P=.06). In Study 2, respondents who identified as being more Republican had significantly lower perceptions of severity (?=?.08, P=.009). There were mixed effects of COVID-19 testing status on preventive perceptions, with respondents who had tested positive for COVID-19 having significantly higher perceptions of susceptibility in Study 1 (?=.17, P=.006) and significantly lower perceptions of severity in Study 2 (?=?.012, P<.001). Conclusions: As the largest and most digitally savvy generation, US millennials saw COVID-19 as a severe threat, but one that they were less susceptible to. For millennials, digital HISB for self, but not for another person, was critical to the development of preventive perceptions and behaviors. UR - https://www.jmir.org/2021/8/e30612 UR - http://dx.doi.org/10.2196/30612 UR - http://www.ncbi.nlm.nih.gov/pubmed/34182460 ID - info:doi/10.2196/30612 ER - TY - JOUR AU - Tozzi, Eugenio Alberto AU - Gesualdo, Francesco AU - Urbani, Emanuele AU - Sbenaglia, Alessandro AU - Ascione, Roberto AU - Procopio, Nicola AU - Croci, Ileana AU - Rizzo, Caterina PY - 2021/8/13 TI - Digital Surveillance Through an Online Decision Support Tool for COVID-19 Over One Year of the Pandemic in Italy: Observational Study JO - J Med Internet Res SP - e29556 VL - 23 IS - 8 KW - COVID-19 KW - public health KW - surveillance KW - digital surveillance KW - internet KW - online decision support system KW - decision support KW - support KW - online tool KW - Italy KW - observational N2 - Background: Italy has experienced severe consequences (ie, hospitalizations and deaths) during the COVID-19 pandemic. Online decision support systems (DSS) and self-triage applications have been used in several settings to supplement health authority recommendations to prevent and manage COVID-19. A digital Italian health tech startup, Paginemediche, developed a noncommercial, online DSS with a chat user interface to assist individuals in Italy manage their potential exposure to COVID-19 and interpret their symptoms since early in the pandemic. Objective: This study aimed to compare the trend in online DSS sessions with that of COVID-19 cases reported by the national health surveillance system in Italy, from February 2020 to March 2021. Methods: We compared the number of sessions by users with a COVID-19?positive contact and users with COVID-19?compatible symptoms with the number of cases reported by the national surveillance system. To calculate the distance between the time series, we used the dynamic time warping algorithm. We applied Symbolic Aggregate approXimation (SAX) encoding to the time series in 1-week periods. We calculated the Hamming distance between the SAX strings. We shifted time series of online DSS sessions 1 week ahead. We measured the improvement in Hamming distance to verify the hypothesis that online DSS sessions anticipate the trends in cases reported to the official surveillance system. Results: We analyzed 75,557 sessions in the online DSS; 65,207 were sessions by symptomatic users, while 19,062 were by contacts of individuals with COVID-19. The highest number of online DSS sessions was recorded early in the pandemic. Second and third peaks were observed in October 2020 and March 2021, respectively, preceding the surge in notified COVID-19 cases by approximately 1 week. The distance between sessions by users with COVID-19 contacts and reported cases calculated by dynamic time warping was 61.23; the distance between sessions by symptomatic users was 93.72. The time series of users with a COVID-19 contact was more consistent with the trend in confirmed cases. With the 1-week shift, the Hamming distance between the time series of sessions by users with a COVID-19 contact and reported cases improved from 0.49 to 0.46. We repeated the analysis, restricting the time window to between July 2020 and December 2020. The corresponding Hamming distance was 0.16 before and improved to 0.08 after the time shift. Conclusions: Temporal trends in the number of online COVID-19 DSS sessions may precede the trend in reported COVID-19 cases through traditional surveillance. The trends in sessions by users with a contact with COVID-19 may better predict reported cases of COVID-19 than sessions by symptomatic users. Data from online DSS may represent a useful supplement to traditional surveillance and support the identification of early warning signals in the COVID-19 pandemic. UR - https://www.jmir.org/2021/8/e29556 UR - http://dx.doi.org/10.2196/29556 UR - http://www.ncbi.nlm.nih.gov/pubmed/34292866 ID - info:doi/10.2196/29556 ER - TY - JOUR AU - Chum, Antony AU - Nielsen, Andrew AU - Bellows, Zachary AU - Farrell, Eddie AU - Durette, Pierre-Nicolas AU - Banda, M. Juan AU - Cupchik, Gerald PY - 2021/8/25 TI - Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data JO - J Med Internet Res SP - e28716 VL - 23 IS - 8 KW - COVID-19 KW - public opinion KW - social media KW - sentiment analysis KW - public health restrictions KW - infodemiology KW - infoveillance KW - coronavirus KW - evaluation N2 - Background: News media coverage of antimask protests, COVID-19 conspiracies, and pandemic politicization has overemphasized extreme views but has done little to represent views of the general public. Investigating the public?s response to various pandemic restrictions can provide a more balanced assessment of current views, allowing policy makers to craft better public health messages in anticipation of poor reactions to controversial restrictions. Objective: Using data from social media, this infoveillance study aims to understand the changes in public opinion associated with the implementation of COVID-19 restrictions (eg, business and school closures, regional lockdown differences, and additional public health restrictions, such as social distancing and masking). Methods: COVID-19?related tweets in Ontario (n=1,150,362) were collected based on keywords between March 12 and October 31, 2020. Sentiment scores were calculated using the VADER (Valence Aware Dictionary and Sentiment Reasoner) algorithm for each tweet to represent its negative to positive emotion. Public health restrictions were identified using government and news media websites. Dynamic regression models with autoregressive integrated moving average errors were used to examine the association between public health restrictions and changes in public opinion over time (ie, collective attention, aggregate positive sentiment, and level of disagreement), controlling for the effects of confounders (ie, daily COVID-19 case counts, holidays, and COVID-19?related official updates). Results: In addition to expected direct effects (eg, business closures led to decreased positive sentiment and increased disagreements), the impact of restrictions on public opinion was contextually driven. For example, the negative sentiment associated with business closures was reduced with higher COVID-19 case counts. While school closures and other restrictions (eg, masking, social distancing, and travel restrictions) generated increased collective attention, they did not have an effect on aggregate sentiment or the level of disagreement (ie, sentiment polarization). Partial (ie, region-targeted) lockdowns were associated with better public response (ie, higher number of tweets with net positive sentiment and lower levels of disagreement) compared to province-wide lockdowns. Conclusions: Our study demonstrates the feasibility of a rapid and flexible method of evaluating the public response to pandemic restrictions using near real-time social media data. This information can help public health practitioners and policy makers anticipate public response to future pandemic restrictions and ensure adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed, but controversial, restrictions. UR - https://www.jmir.org/2021/8/e28716 UR - http://dx.doi.org/10.2196/28716 UR - http://www.ncbi.nlm.nih.gov/pubmed/34227996 ID - info:doi/10.2196/28716 ER - TY - JOUR AU - Lapão, Velez Luís AU - Peyroteo, Mariana AU - Maia, Melanie AU - Seixas, Jorge AU - Gregório, João AU - Mira da Silva, Miguel AU - Heleno, Bruno AU - Correia, César Jorge PY - 2021/8/26 TI - Implementation of Digital Monitoring Services During the COVID-19 Pandemic for Patients With Chronic Diseases: Design Science Approach JO - J Med Internet Res SP - e24181 VL - 23 IS - 8 KW - primary healthcare KW - information systems KW - telemedicine KW - implementation KW - design science research KW - COVID-19 KW - monitoring KW - chronic disease KW - elderly KW - digital health N2 - Background: The COVID-19 pandemic is straining health systems and disrupting the delivery of health care services, in particular, for older adults and people with chronic conditions, who are particularly vulnerable to COVID-19 infection. Objective: The aim of this project was to support primary health care provision with a digital health platform that will allow primary care physicians and nurses to remotely manage the care of patients with chronic diseases or COVID-19 infections. Methods: For the rapid design and implementation of a digital platform to support primary health care services, we followed the Design Science implementation framework: (1) problem identification and motivation, (2) definition of the objectives aligned with goal-oriented care, (3) artefact design and development based on Scrum, (4) solution demonstration, (5) evaluation, and (6) communication. Results: The digital platform was developed for the specific objectives of the project and successfully piloted in 3 primary health care centers in the Lisbon Health Region. Health professionals (n=53) were able to remotely manage their first patients safely and thoroughly, with high degrees of satisfaction. Conclusions: Although still in the first steps of implementation, its positive uptake, by both health care providers and patients, is a promising result. There were several limitations including the low number of participating health care units. Further research is planned to deploy the platform to many more primary health care centers and evaluate the impact on patient?s health related outcomes. UR - https://www.jmir.org/2021/8/e24181 UR - http://dx.doi.org/10.2196/24181 UR - http://www.ncbi.nlm.nih.gov/pubmed/34313591 ID - info:doi/10.2196/24181 ER - TY - JOUR AU - Zola Matuvanga, Trésor AU - Johnson, Ginger AU - Larivière, Ynke AU - Esanga Longomo, Emmanuel AU - Matangila, Junior AU - Maketa, Vivi AU - Lapika, Bruno AU - Mitashi, Patrick AU - Mc Kenna, Paula AU - De Bie, Jessie AU - Van Geertruyden, Jean-Pierre AU - Van Damme, Pierre AU - Muhindo Mavoko, Hypolite PY - 2021/8/9 TI - Use of Iris Scanning for Biometric Recognition of Healthy Adults Participating in an Ebola Vaccine Trial in the Democratic Republic of the Congo: Mixed Methods Study JO - J Med Internet Res SP - e28573 VL - 23 IS - 8 KW - biometric identification KW - iris recognition KW - vaccine trial KW - participants' visits KW - acceptability KW - feasibility KW - Democratic Republic of the Congo KW - mixed methods KW - Ebola N2 - Background: A partnership between the University of Antwerp and the University of Kinshasa implemented the EBOVAC3 clinical trial with an Ebola vaccine regimen administered to health care provider participants in Tshuapa Province, Democratic Republic of the Congo. This randomized controlled trial was part of an Ebola outbreak preparedness initiative financed through Innovative Medicines Initiative-European Union. The EBOVAC3 clinical trial used iris scan technology to identify all health care provider participants enrolled in the vaccine trial, to ensure that the right participant received the right vaccine at the right visit. Objective: We aimed to assess the acceptability, accuracy, and feasibility of iris scan technology as an identification method within a population of health care provider participants in a vaccine trial in a remote setting. Methods: We used a mixed methods study. The acceptability was assessed prior to the trial through 12 focus group discussions (FGDs) and was assessed at enrollment. Feasibility and accuracy research was conducted using a longitudinal trial study design, where iris scanning was compared with the unique study ID card to identify health care provider participants at enrollment and at their follow-up visits. Results: During the FGDs, health care provider participants were mainly concerned about the iris scan technology causing physical problems to their eyes or exposing them to spiritual problems through sorcery. However, 99% (85/86; 95% CI 97.1-100.0) of health care provider participants in the FGDs agreed to be identified by the iris scan. Also, at enrollment, 99.0% (692/699; 95% CI 98.2-99.7) of health care provider participants accepted to be identified by iris scan. Iris scan technology correctly identified 93.1% (636/683; 95% CI 91.2-95.0) of the participants returning for scheduled follow-up visits. The iris scanning operation lasted 2 minutes or less for 96.0% (656/683; 95% CI 94.6-97.5), and 1 attempt was enough to identify the majority of study participants (475/683, 69.5%; 95% CI 66.1-73.0). Conclusions: Iris scans are highly acceptable as an identification tool in a clinical trial for health care provider participants in a remote setting. Its operationalization during the trial demonstrated a high level of accuracy that can reliably identify individuals. Iris scanning is found to be feasible in clinical trials but requires a trained operator to reduce the duration and the number of attempts to identify a participant. Trial Registration: ClinicalTrials.gov NCT04186000; https://clinicaltrials.gov/ct2/show/NCT04186000 UR - https://www.jmir.org/2021/8/e28573 UR - http://dx.doi.org/10.2196/28573 UR - http://www.ncbi.nlm.nih.gov/pubmed/34378545 ID - info:doi/10.2196/28573 ER - TY - JOUR AU - Shaballout, Nour AU - Aloumar, Anas AU - Manuel, Jorge AU - May, Marcus AU - Beissner, Florian PY - 2021/8/27 TI - Lateralization and Bodily Patterns of Segmental Signs and Spontaneous Pain in Acute Visceral Disease: Observational Study JO - J Med Internet Res SP - e27247 VL - 23 IS - 8 KW - digital pain drawings KW - visceral referred pain KW - referred pain KW - head zones KW - mydriasis KW - chest pain KW - clinical examination KW - differential diagnosis KW - digital health KW - digital drawings KW - pain KW - health technology KW - image analysis N2 - Background: The differential diagnosis of acute visceral diseases is a challenging clinical problem. Older literature suggests that patients with acute visceral problems show segmental signs such as hyperalgesia, skin resistance, or muscular defense as manifestations of referred visceral pain in somatic or visceral tissues with overlapping segmental innervation. According to these sources, the lateralization and segmental distribution of such signs may be used for differential diagnosis. Segmental signs and symptoms may be accompanied by spontaneous (visceral) pain, which, however, shows a nonsegmental distribution. Objective: This study aimed to investigate the lateralization (ie, localization on one side of the body, in preference to the other) and segmental distribution (ie, surface ratio of the affected segments) of spontaneous pain and (referred) segmental signs in acute visceral diseases using digital pain drawing technology. Methods: We recruited 208 emergency room patients that were presenting for acute medical problems considered by triage as related to internal organ disease. All patients underwent a structured 10-minute bodily examination to test for various segmental signs and spontaneous visceral pain. They were further asked their segmental symptoms such as nausea, meteorism, and urinary retention. We collected spontaneous pain and segmental signs as digital drawings and segmental symptoms as binary values on a tablet PC. After the final diagnosis, patients were divided into groups according to the organ affected. Using statistical image analysis, we calculated mean distributions of pain and segmental signs for the heart, lungs, stomach, liver/gallbladder, and kidneys/ureters, analyzing the segmental distribution of these signs and the lateralization. Results: Of the 208 recruited patients, 110 (52.9%) were later diagnosed with a single-organ problem. These recruited patients had a mean age of 57.3 (SD 17.2) years, and 40.9% (85/208) were female. Of these 110 patients, 85 (77.3%) reported spontaneous visceral pain. Of the 110, 81 (73.6%) had at least 1 segmental sign, and the most frequent signs were hyperalgesia (46/81, 57%), and muscle resistance (39/81, 48%). While pain was distributed along the body midline, segmental signs for the heart, stomach, and liver/gallbladder appeared mostly ipsilateral to the affected organ. An unexpectedly high number of patients (37/110, 33.6%) further showed ipsilateral mydriasis. Conclusions: This study underlines the usefulness of including digitally recorded segmental signs in bodily examinations of patients with acute medical problems. UR - https://www.jmir.org/2021/8/e27247 UR - http://dx.doi.org/10.2196/27247 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448718 ID - info:doi/10.2196/27247 ER -