TY - JOUR AU - McCabe, Catherine AU - Connolly, Leona AU - Quintana, Yuri AU - Weir, Arielle AU - Moen, Anne AU - Ingvar, Martin AU - McCann, Margaret AU - Doyle, Carmel AU - Hughes, Mary AU - Brenner, Maria PY - 2025/4/16 TI - How to Refine and Prioritize Key Performance Indicators for Digital Health Interventions: Tutorial on Using Consensus Methodology to Enable Meaningful Evaluation of Novel Digital Health Interventions JO - J Med Internet Res SP - e68757 VL - 27 KW - digital health interventions KW - key performance indicators KW - Delphi technique KW - consensus methodology KW - drug-related side effects and adverse reactions KW - referral KW - consultation UR - https://www.jmir.org/2025/1/e68757 UR - http://dx.doi.org/10.2196/68757 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/68757 ER - TY - JOUR AU - Nazar, Wojciech AU - Nazar, Grzegorz AU - Kami?ska, Aleksandra AU - Danilowicz-Szymanowicz, Ludmila PY - 2025/3/18 TI - How to Design, Create, and Evaluate an Instruction-Tuning Dataset for Large Language Model Training in Health Care: Tutorial From a Clinical Perspective JO - J Med Internet Res SP - e70481 VL - 27 KW - generative artificial intelligence KW - large language models KW - instruction-tuning datasets KW - tutorials KW - evaluation framework KW - health care UR - https://www.jmir.org/2025/1/e70481 UR - http://dx.doi.org/10.2196/70481 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/70481 ER - TY - JOUR AU - Vlake, H. Johan AU - Drop, Q. Denzel L. AU - Van Bommel, Jasper AU - Riva, Giuseppe AU - Wiederhold, K. Brenda AU - Cipresso, Pietro AU - Rizzo, S. Albert AU - Rothbaum, O. Barbara AU - Botella, Cristina AU - Hooft, Lotty AU - Bienvenu, J. Oscar AU - Jung, Christian AU - Geerts, Bart AU - Wils, Evert-Jan AU - Gommers, Diederik AU - van Genderen, E. Michel AU - PY - 2024/11/29 TI - Reporting Guidelines for the Early-Phase Clinical Evaluation of Applications Using Extended Reality: RATE-XR Qualitative Study Guideline JO - J Med Internet Res SP - e56790 VL - 26 KW - extended reality KW - XR KW - virtual reality KW - augmented reality KW - mixed reality KW - reporting guideline KW - Delphi process KW - consensus KW - computer-generated simulation KW - simulation KW - virtual world KW - simulation experience KW - clinical evaluation N2 - Background: Extended reality (XR), encompassing technologies such as virtual reality, augmented reality, and mixed reality, has rapidly gained prominence in health care. However, existing XR research often lacks rigor, proper controls, and standardization. Objective: To address this and to enhance the transparency and quality of reporting in early-phase clinical evaluations of XR applications, we present the ?Reporting for the early-phase clinical evaluation of applications using extended reality? (RATE-XR) guideline. Methods: We conducted a 2-round modified Delphi process involving experts from diverse stakeholder categories, and the RATE-XR is therefore the result of a consensus-based, multistakeholder effort. Results: The guideline comprises 17 XR-specific (composed of 18 subitems) and 14 generic reporting items, each with a complementary Explanation & Elaboration section. Conclusions: The items encompass critical aspects of XR research, from clinical utility and safety to human factors and ethics. By offering a comprehensive checklist for reporting, the RATE-XR guideline facilitates robust assessment and replication of early-stage clinical XR studies. It underscores the need for transparency, patient-centeredness, and balanced evaluation of the applications of XR in health care. By providing an actionable checklist of minimal reporting items, this guideline will facilitate the responsible development and integration of XR technologies into health care and related fields. UR - https://www.jmir.org/2024/1/e56790 UR - http://dx.doi.org/10.2196/56790 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/56790 ER - TY - JOUR AU - Harrison Ginsberg, Kristin AU - Babbott, Katie AU - Serlachius, Anna PY - 2024/11/28 TI - Exploring Participants? Experiences of Digital Health Interventions With Qualitative Methods: Guidance for Researchers JO - J Med Internet Res SP - e62761 VL - 26 KW - qualitative methods KW - content analysis KW - thematic analysis KW - digital health evaluation KW - user engagement KW - user experience KW - digital health intervention KW - innovation KW - patient experience KW - health care KW - researcher KW - technology KW - mobile health KW - mHealth KW - telemedicine KW - digital health KW - behavior change KW - usability KW - tutorial KW - research methods KW - qualitative research KW - study design UR - https://www.jmir.org/2024/1/e62761 UR - http://dx.doi.org/10.2196/62761 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/62761 ER - TY - JOUR AU - Pogrebnoy, Dina AU - Ashton, Lee AU - Beh, A. Brian AU - Burke, Meredith AU - Cullen, Richard AU - Czerenkowski, Jude AU - Davey, Julie AU - Dennett, M. Amy AU - English, Kevin AU - Godecke, Erin AU - Harper, Nicole AU - Lynch, Elizabeth AU - MacDonald-Wicks, Lesley AU - Patterson, Amanda AU - Ramage, Emily AU - Schelfhaut, Ben AU - Simpson, B. Dawn AU - Zacharia, Karly AU - English, Coralie PY - 2024/10/22 TI - Adapting a Telehealth Physical Activity and Diet Intervention to a Co-Designed Website for Self-Management After Stroke: Tutorial JO - J Med Internet Res SP - e58419 VL - 26 KW - stroke KW - secondary prevention KW - co-design KW - how-to guide, website development KW - accessibility KW - navigation KW - self-management UR - https://www.jmir.org/2024/1/e58419 UR - http://dx.doi.org/10.2196/58419 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/58419 ER - TY - JOUR AU - Burns, James AU - Chen, Kelly AU - Flathers, Matthew AU - Currey, Danielle AU - Macrynikola, Natalia AU - Vaidyam, Aditya AU - Langholm, Carsten AU - Barnett, Ian AU - Byun, Soo) Andrew (Jin AU - Lane, Erlend AU - Torous, John PY - 2024/8/23 TI - Transforming Digital Phenotyping Raw Data Into Actionable Biomarkers, Quality Metrics, and Data Visualizations Using Cortex Software Package: Tutorial JO - J Med Internet Res SP - e58502 VL - 26 KW - digital phenotyping KW - mental health KW - data visualization KW - data analysis KW - smartphones KW - smartphone KW - Cortex KW - open-source KW - data processing KW - mindLAMP KW - app KW - apps KW - data set KW - clinical KW - real world KW - methodology KW - mobile phone UR - https://www.jmir.org/2024/1/e58502 UR - http://dx.doi.org/10.2196/58502 UR - http://www.ncbi.nlm.nih.gov/pubmed/39178032 ID - info:doi/10.2196/58502 ER - TY - JOUR AU - Pretorius, Kelly PY - 2024/7/9 TI - A Simple and Systematic Approach to Qualitative Data Extraction From Social Media for Novice Health Care Researchers: Tutorial JO - JMIR Form Res SP - e54407 VL - 8 KW - social media analysis KW - data extraction KW - health care research KW - extraction tutorial KW - Facebook extraction KW - Facebook analysis KW - safe sleep KW - sudden unexpected infant death KW - social media KW - analysis KW - systematic approach KW - qualitative data KW - Facebook KW - health-related KW - maternal perspective KW - maternal perspectives KW - sudden infant death syndrome KW - mother KW - mothers KW - women KW - United States KW - SIDS KW - SUID KW - post KW - posts UR - https://formative.jmir.org/2024/1/e54407 UR - http://dx.doi.org/10.2196/54407 UR - http://www.ncbi.nlm.nih.gov/pubmed/38980712 ID - info:doi/10.2196/54407 ER - TY - JOUR AU - Singla, Ashwani AU - Khanna, Ritvik AU - Kaur, Manpreet AU - Kelm, Karen AU - Zaiane, Osmar AU - Rosenfelt, Scott Cory AU - Bui, An Truong AU - Rezaei, Navid AU - Nicholas, David AU - Reformat, Z. Marek AU - Majnemer, Annette AU - Ogourtsova, Tatiana AU - Bolduc, Francois PY - 2024/6/18 TI - Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial JO - J Med Internet Res SP - e50182 VL - 26 KW - chatbot KW - user interface KW - knowledge graph KW - neurodevelopmental disability KW - autism KW - intellectual disability KW - attention-deficit/hyperactivity disorder UR - https://www.jmir.org/2024/1/e50182 UR - http://dx.doi.org/10.2196/50182 UR - http://www.ncbi.nlm.nih.gov/pubmed/38888947 ID - info:doi/10.2196/50182 ER - TY - JOUR AU - Weng, Huiqin Janice AU - Hu, Yanyan AU - Heaukulani, Creighton AU - Tan, Clarence AU - Chang, Kuiyu Julian AU - Phang, Sheng Ye AU - Rajendram, Priyanka AU - Tan, Mooi Weng AU - Loke, Chiong Wai AU - Morris, T. Robert J. PY - 2024/6/4 TI - Mental Wellness Self-Care in Singapore With mindline.sg: A Tutorial on the Development of a Digital Mental Health Platform for Behavior Change JO - J Med Internet Res SP - e44443 VL - 26 KW - digital mental health KW - artificial intelligence KW - AI KW - AI chatbot KW - digital therapeutics KW - mental health KW - mental wellness KW - mobile phone N2 - Background: Singapore, like the rest of Asia, faces persistent challenges to mental health promotion, including stigma around unwellness and seeking treatment and a lack of trained mental health personnel. The COVID-19 pandemic, which created a surge in mental health care needs and simultaneously accelerated the adoption of digital health solutions, revealed a new opportunity to quickly scale innovative solutions in the region. Objective: In June 2020, the Singaporean government launched mindline.sg, an anonymous digital mental health resource website that has grown to include >500 curated local mental health resources, a clinically validated self-assessment tool for depression and anxiety, an artificial intelligence (AI) chatbot from Wysa designed to deliver digital therapeutic exercises, and a tailored version of the website for working adults called mindline at work. The goal of the platform is to empower Singapore residents to take charge of their own mental health and to be able to offer basic support to those around them through the ease and convenience of a barrier-free digital solution. Methods: Website use is measured through click-level data analytics captured via Google Analytics and custom application programming interfaces, which in turn drive a customized analytics infrastructure based on the open-source platforms Titanium Database and Metabase. Unique, nonbounced (users that do not immediately navigate away from the site), engaged, and return users are reported. Results: In the 2 years following launch (July 1, 2020, through June 30, 2022), the website received >447,000 visitors (approximately 15% of the target population of 3 million), 62.02% (277,727/447,783) of whom explored the site or engaged with resources (referred to as nonbounced visitors); 10.54% (29,271/277,727) of those nonbounced visitors returned. The most popular features on the platform were the dialogue-based therapeutic exercises delivered by the chatbot and the self-assessment tool, which were used by 25.54% (67,626/264,758) and 11.69% (32,469/277,727) of nonbounced visitors. On mindline at work, the rates of nonbounced visitors who engaged extensively (ie, spent ?40 seconds exploring resources) and who returned were 51.56% (22,474/43,588) and 13.43% (5,853/43,588) over a year, respectively, compared to 30.9% (42,829/138,626) and 9.97% (13,822/138,626), respectively, on the generic mindline.sg site in the same year. Conclusions: The site has achieved desired reach and has seen a strong growth rate in the number of visitors, which required substantial and sustained digital marketing campaigns and strategic outreach partnerships. The site was careful to preserve anonymity, limiting the detail of analytics. The good levels of overall adoption encourage us to believe that mild to moderate mental health conditions and the social factors that underly them are amenable to digital interventions. While mindline.sg was primarily used in Singapore, we believe that similar solutions with local customization are widely and globally applicable. UR - https://www.jmir.org/2024/1/e44443 UR - http://dx.doi.org/10.2196/44443 UR - http://www.ncbi.nlm.nih.gov/pubmed/38833294 ID - info:doi/10.2196/44443 ER - TY - JOUR AU - Cho, Hunyong AU - She, Jane AU - De Marchi, Daniel AU - El-Zaatari, Helal AU - Barnes, L. Edward AU - Kahkoska, R. Anna AU - Kosorok, R. Michael AU - Virkud, V. Arti PY - 2024/1/30 TI - Machine Learning and Health Science Research: Tutorial JO - J Med Internet Res SP - e50890 VL - 26 KW - health science researcher KW - machine learning pipeline KW - machine learning KW - medical machine learning KW - precision medicine KW - reproducibility KW - unsupervised learning UR - https://www.jmir.org/2024/1/e50890 UR - http://dx.doi.org/10.2196/50890 UR - http://www.ncbi.nlm.nih.gov/pubmed/38289657 ID - info:doi/10.2196/50890 ER - TY - JOUR AU - Henry, M. Lauren AU - Hansen, Eleanor AU - Chimoff, Justin AU - Pokstis, Kimberly AU - Kiderman, Miryam AU - Naim, Reut AU - Kossowsky, Joe AU - Byrne, E. Meghan AU - Lopez-Guzman, Silvia AU - Kircanski, Katharina AU - Pine, S. Daniel AU - Brotman, A. Melissa PY - 2024/1/4 TI - Selecting an Ecological Momentary Assessment Platform: Tutorial for Researchers JO - J Med Internet Res SP - e51125 VL - 26 KW - ecological momentary assessment KW - methodology KW - psychology and psychiatry KW - child and adolescent KW - in vivo and real time N2 - Background: Although ecological momentary assessment (EMA) has been applied in psychological research for decades, delivery methods have evolved with the proliferation of digital technology. Technological advances have engendered opportunities for enhanced accessibility, convenience, measurement precision, and integration with wearable sensors. Notwithstanding, researchers must navigate novel complexities in EMA research design and implementation. Objective: In this paper, we aimed to provide guidance on platform selection for clinical scientists launching EMA studies. Methods: Our team includes diverse specialties in child and adolescent behavioral and mental health with varying expertise on EMA platforms (eg, users and developers). We (2 research sites) evaluated EMA platforms with the goal of identifying the platform or platforms with the best fit for our research. We created a list of extant EMA platforms; conducted a web-based review; considered institutional security, privacy, and data management requirements; met with developers; and evaluated each of the candidate EMA platforms for 1 week. Results: We selected 2 different EMA platforms, rather than a single platform, for use at our 2 research sites. Our results underscore the importance of platform selection driven by individualized and prioritized laboratory needs; there is no single, ideal platform for EMA researchers. In addition, our project generated 11 considerations for researchers in selecting an EMA platform: (1) location; (2) developer involvement; (3) sample characteristics; (4) onboarding; (5) survey design features; (6) sampling scheme and scheduling; (7) viewing results; (8) dashboards; (9) security, privacy, and data management; (10) pricing and cost structure; and (11) future directions. Furthermore, our project yielded a suggested timeline for the EMA platform selection process. Conclusions: This study will guide scientists initiating studies using EMA, an in vivo, real-time research tool with tremendous promise for facilitating advances in psychological assessment and intervention. UR - https://www.jmir.org/2024/1/e51125 UR - http://dx.doi.org/10.2196/51125 UR - http://www.ncbi.nlm.nih.gov/pubmed/38175682 ID - info:doi/10.2196/51125 ER - TY - JOUR AU - Keogh, Alison AU - Mc Ardle, Ríona AU - Diaconu, Gabriela Mara AU - Ammour, Nadir AU - Arnera, Valdo AU - Balzani, Federica AU - Brittain, Gavin AU - Buckley, Ellen AU - Buttery, Sara AU - Cantu, Alma AU - Corriol-Rohou, Solange AU - Delgado-Ortiz, Laura AU - Duysens, Jacques AU - Forman-Hardy, Tom AU - Gur-Arieh, Tova AU - Hamerlijnck, Dominique AU - Linnell, John AU - Leocani, Letizia AU - McQuillan, Tom AU - Neatrour, Isabel AU - Polhemus, Ashley AU - Remmele, Werner AU - Saraiva, Isabel AU - Scott, Kirsty AU - Sutton, Norman AU - van den Brande, Koen AU - Vereijken, Beatrix AU - Wohlrab, Martin AU - Rochester, Lynn AU - PY - 2023/10/27 TI - Mobilizing Patient and Public Involvement in the Development of Real-World Digital Technology Solutions: Tutorial JO - J Med Internet Res SP - e44206 VL - 25 KW - patient involvement KW - patient engagement KW - public-private partnership KW - research consortium KW - digital mobility outcomes KW - real-world mobility KW - digital mobility measures UR - https://www.jmir.org/2023/1/e44206 UR - http://dx.doi.org/10.2196/44206 UR - http://www.ncbi.nlm.nih.gov/pubmed/37889531 ID - info:doi/10.2196/44206 ER - TY - JOUR AU - Thirunavukarasu, James Arun AU - Elangovan, Kabilan AU - Gutierrez, Laura AU - Li, Yong AU - Tan, Iris AU - Keane, A. Pearse AU - Korot, Edward AU - Ting, Wei Daniel Shu PY - 2023/10/12 TI - Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial JO - J Med Internet Res SP - e49949 VL - 25 KW - machine learning KW - automated machine learning KW - autoML KW - artificial intelligence KW - democratization KW - autonomous AI KW - imaging KW - image analysis KW - automation KW - AI engineering UR - https://www.jmir.org/2023/1/e49949 UR - http://dx.doi.org/10.2196/49949 UR - http://www.ncbi.nlm.nih.gov/pubmed/37824185 ID - info:doi/10.2196/49949 ER - TY - JOUR AU - Meskó, Bertalan PY - 2023/10/4 TI - Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial JO - J Med Internet Res SP - e50638 VL - 25 KW - artificial intelligence KW - AI KW - digital health KW - future KW - technology KW - ChatGPT KW - GPT-4 KW - large language models KW - language model KW - LLM KW - prompt KW - prompts KW - prompt engineering KW - AI tool KW - engineering KW - healthcare professional KW - decision-making KW - LLMs KW - chatbot KW - chatbots KW - conversational agent KW - conversational agents KW - NLP KW - natural language processing UR - https://www.jmir.org/2023/1/e50638 UR - http://dx.doi.org/10.2196/50638 UR - http://www.ncbi.nlm.nih.gov/pubmed/37792434 ID - info:doi/10.2196/50638 ER - TY - JOUR AU - Naef, C. Aileen AU - Jeitziner, Marie-Madlen AU - Jakob, M. Stephan AU - Müri, M. René AU - Nef, Tobias PY - 2023/9/14 TI - Creating Custom Immersive 360-Degree Videos for Use in Clinical and Nonclinical Settings: Tutorial JO - JMIR Med Educ SP - e42154 VL - 9 KW - 360-degree video KW - head-mounted display KW - healthcare KW - relaxing content KW - technology KW - video content KW - video production KW - virtual reality KW - VR UR - https://mededu.jmir.org/2023/1/e42154 UR - http://dx.doi.org/10.2196/42154 UR - http://www.ncbi.nlm.nih.gov/pubmed/37707883 ID - info:doi/10.2196/42154 ER - TY - JOUR AU - de Batlle, Jordi AU - Benítez, D. Ivan AU - Moncusí-Moix, Anna AU - Androutsos, Odysseas AU - Angles Barbastro, Rosana AU - Antonini, Alessio AU - Arana, Eunate AU - Cabrera-Umpierrez, Fernanda Maria AU - Cea, Gloria AU - Dafoulas, ?. George AU - Folkvord, Frans AU - Fullaondo, Ane AU - Giuliani, Francesco AU - Huang, Hsiao-Ling AU - Innominato, F. Pasquale AU - Kardas, Przemyslaw AU - Lou, Q. Vivian W. AU - Manios, Yannis AU - Matsangidou, Maria AU - Mercalli, Franco AU - Mokhtari, Mounir AU - Pagliara, Silvio AU - Schellong, Julia AU - Stieler, Lisa AU - Votis, Konstantinos AU - Currás, Paula AU - Arredondo, Teresa Maria AU - Posada, Jorge AU - Guillén, Sergio AU - Pecchia, Leandro AU - Barbé, Ferran AU - Torres, Gerard AU - Fico, Giuseppe AU - PY - 2023/6/28 TI - GATEKEEPER?s Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases JO - J Med Internet Res SP - e42187 VL - 25 KW - big data KW - chronic diseases KW - eHealth KW - healthy aging KW - integrated care KW - large-scale pilots N2 - Background: The World Health Organization?s strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. Objective: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. Methods: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. Results: Seven European countries were selected, covering Europe?s geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence?based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. Conclusions: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space. UR - https://www.jmir.org/2023/1/e42187 UR - http://dx.doi.org/10.2196/42187 UR - http://www.ncbi.nlm.nih.gov/pubmed/37379060 ID - info:doi/10.2196/42187 ER - TY - JOUR AU - Hou, Jue AU - Zhao, Rachel AU - Gronsbell, Jessica AU - Lin, Yucong AU - Bonzel, Clara-Lea AU - Zeng, Qingyi AU - Zhang, Sinian AU - Beaulieu-Jones, K. Brett AU - Weber, M. Griffin AU - Jemielita, Thomas AU - Wan, Sabrina Shuyan AU - Hong, Chuan AU - Cai, Tianrun AU - Wen, Jun AU - Ayakulangara Panickan, Vidul AU - Liaw, Kai-Li AU - Liao, Katherine AU - Cai, Tianxi PY - 2023/5/25 TI - Generate Analysis-Ready Data for Real-world Evidence: Tutorial for Harnessing Electronic Health Records With Advanced Informatic Technologies JO - J Med Internet Res SP - e45662 VL - 25 KW - electronic health records KW - real-world evidence KW - data curation KW - medical informatics KW - randomized controlled trials KW - reproducibility UR - https://www.jmir.org/2023/1/e45662 UR - http://dx.doi.org/10.2196/45662 UR - http://www.ncbi.nlm.nih.gov/pubmed/37227772 ID - info:doi/10.2196/45662 ER - TY - JOUR AU - Sudre, Gustavo AU - Bagi?, I. Anto AU - Becker, T. James AU - Ford, P. John PY - 2023/4/27 TI - An Emerging Screening Method for Interrogating Human Brain Function: Tutorial JO - JMIR Form Res SP - e37269 VL - 7 KW - screening KW - brain function KW - cognition KW - magnetoencephalography KW - MEG KW - neuroimaging KW - tutorial KW - tool KW - cognitive test KW - signal KW - cognitive function UR - https://formative.jmir.org/2023/1/e37269 UR - http://dx.doi.org/10.2196/37269 UR - http://www.ncbi.nlm.nih.gov/pubmed/37103988 ID - info:doi/10.2196/37269 ER - TY - JOUR AU - Bendtsen, Marcus PY - 2022/12/16 TI - Avoiding Under- and Overrecruitment in Behavioral Intervention Trials Using Bayesian Sequential Designs: Tutorial JO - J Med Internet Res SP - e40730 VL - 24 IS - 12 KW - digital alcohol intervention KW - Bayesian sequential design KW - sample size KW - randomized controlled trial KW - trial recruitment KW - behavioural intervention KW - participant recruitment KW - research participants KW - research methods KW - effect size KW - trial procedure UR - https://www.jmir.org/2022/12/e40730 UR - http://dx.doi.org/10.2196/40730 UR - http://www.ncbi.nlm.nih.gov/pubmed/36525297 ID - info:doi/10.2196/40730 ER - TY - JOUR AU - Etling, Ann Mary AU - Musili, Michael AU - Eastes, Kaytlin AU - Oyungu, Eren AU - McHenry, S. Megan PY - 2022/12/8 TI - Creating the Map of Interactive Services Aiding and Assisting Persons With Disabilities (MSAADA) Project: Tutorial for the Novel Use of a Store Locator App JO - Interact J Med Res SP - e37036 VL - 11 IS - 2 KW - map KW - virtual KW - interactive KW - disability KW - resources KW - inclusion KW - mHealth KW - Kenya KW - global health KW - public health N2 - Background: An estimated 15% of the global population is living with a disability. In Kenya, children with disabilities remain among the most vulnerable populations, experiencing substantial barriers to wellness and inclusion. Smartphone ownership and internet access have been increasing across sub-Saharan Africa, including in Kenya. Despite these advances, online or mobile resources remain limited and difficult to find and navigate. Objective: This paper aims to describe the novel use of a store locator app to develop an interactive map of organizations that provide medical, educational, and socioeconomic resources to individuals with disabilities in Kenya. The target audience is individuals with disabilities, medical professionals, and organization leaders. Methods: A comprehensive list of organizations, government county offices, educational assessment and resource centers, and institutions was compiled. Organizations were contacted via email, WhatsApp, or in person for semistructured interviews. Based on the services offered, each organization was assigned categorical search tags. The data were entered into a third-party store locator app. The resulting map was inserted into a page on the Academic Model Providing Access to Healthcare (AMPATH) website. Results: The Map of Interactive Services Aiding and Assisting Persons With Disabilities (MSAADA; this abbreviation is also Swahili for ?help?) was launched in July 2020 in both English and Swahili. The map included 89 organizations across Kenya. Of these, 51 were reached for an interview (for a 57% response rate). Interviewees cited limited paid staff and dependence on grant-based funding as primary challenges to growth and sustainability. Conclusions: MSAADA is an interactive, virtual map that aims to connect individuals with disabilities, medical professionals, and organization leaders to resources in Kenya. The novel use of a store locator app to compile resources in remote settings has the potential to improve access to health care for a wide variety of specialties and patient populations. Innovators in global health should consider the use of store locator apps to connect individuals to resources in regions with limited mapping. UR - https://www.i-jmr.org/2022/2/e37036 UR - http://dx.doi.org/10.2196/37036 UR - http://www.ncbi.nlm.nih.gov/pubmed/36480245 ID - info:doi/10.2196/37036 ER - TY - JOUR AU - Olson, Jenny AU - Hadjiconstantinou, Michelle AU - Luff, Carly AU - Watts, Karen AU - Watson, Natasha AU - Miller, Venus AU - Schofield, Deborah AU - Khunti, Kamlesh AU - Davies, J. Melanie AU - Calginari, Sara PY - 2022/4/20 TI - From the United Kingdom to Australia?Adapting a Web-Based Self-management Education Program to Support the Management of Type 2 Diabetes: Tutorial JO - J Med Internet Res SP - e26339 VL - 24 IS - 4 KW - diabetes mellitus KW - type 2 KW - technology KW - self-management UR - https://www.jmir.org/2022/4/e26339 UR - http://dx.doi.org/10.2196/26339 UR - http://www.ncbi.nlm.nih.gov/pubmed/35442198 ID - info:doi/10.2196/26339 ER - TY - JOUR AU - Fundingsland Jr, Lauritz Edwin AU - Fike, Joseph AU - Calvano, Joshua AU - Beach, Jeffrey AU - Lai, Deborah AU - He, Shuhan PY - 2022/4/15 TI - Methodological Guidelines for Systematic Assessments of Health Care Websites Using Web Analytics: Tutorial JO - J Med Internet Res SP - e28291 VL - 24 IS - 4 KW - Google Analytics KW - website usability KW - conversion rate KW - website engagement KW - user demographics KW - website traffic KW - website content KW - internet browsers KW - healthcare websites KW - web analytics KW - healthcare industry KW - usability UR - https://www.jmir.org/2022/4/e28291 UR - http://dx.doi.org/10.2196/28291 UR - http://www.ncbi.nlm.nih.gov/pubmed/35436216 ID - info:doi/10.2196/28291 ER - TY - JOUR AU - Szinay, Dorothy AU - Cameron, Rory AU - Naughton, Felix AU - Whitty, A. Jennifer AU - Brown, Jamie AU - Jones, Andy PY - 2021/10/11 TI - Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design JO - J Med Internet Res SP - e32365 VL - 23 IS - 10 KW - discrete choice experiment KW - stated preference methods KW - mHealth KW - digital health KW - quantitative methodology KW - uptake KW - engagement KW - methodology KW - preference KW - Bayesian KW - design KW - tutorial KW - qualitative KW - user preference UR - https://www.jmir.org/2021/10/e32365 UR - http://dx.doi.org/10.2196/32365 UR - http://www.ncbi.nlm.nih.gov/pubmed/34633290 ID - info:doi/10.2196/32365 ER - TY - JOUR AU - Milligan, John Kevin AU - Daulton, Scott Robert AU - St Clair, Taylor Zachary AU - Epperson, Veronica Madison AU - Holloway, Mackenzie Rachel AU - Schlaudecker, David Jeffrey PY - 2021/7/8 TI - Creation of a Student-Run Medical Education Podcast: Tutorial JO - JMIR Med Educ SP - e29157 VL - 7 IS - 3 KW - podcast KW - medical student KW - near-peer KW - medical education N2 - Background: Podcasting has become a popular medium for medical education content. Educators and trainees of all levels are turning to podcasts for high-quality, asynchronous content. Although numerous medical education podcasts have emerged in recent years, few student-run podcasts exist. Student-run podcasts are a novel approach to supporting medical students. Near-peer mentoring has been shown to promote medical students? personal and professional identity formation. Student-run podcasts offer a new medium for delivering near-peer advice to medical students in an enduring and accessible manner. Objective: This paper describes the creation of the UnsCripted Medicine Podcast?a student-run medical education podcast produced at the University of Cincinnati College of Medicine. Methods: The planning and preparatory phases spanned 6 months. Defining a target audience and establishing a podcast mission were key first steps. Efforts were directed toward securing funding; obtaining necessary equipment; and navigating the technical considerations of recording, editing, and publishing a podcast. In order to ensure that high professionalism standards were met, key partnerships were created with faculty from the College of Medicine. Results: The UnsCripted Medicine Podcast published 53 episodes in its first 2 years. The number of episodes released per month ranges from 0 to 5, with a mean of 2.0 episodes. The podcast has a Twitter account with 217 followers. The number of listeners who subscribed to the podcast via Apple Podcasts grew to 86 in the first year and then to 218 in the second year. The show has an average rating of 4.8 (out of 5) on Apple Podcasts, which is based on 24 ratings. The podcast has hosted 70 unique guests, including medical students, resident physicians, attending physicians, nurses, physicians? family members, graduate medical education leadership, and educators. Conclusions: Medical student?run podcasts are a novel approach to supporting medical students and fostering professional identity formation. Podcasts are widely available and convenient for listeners. Additionally, podcast creators can publish content with lower barriers of entry compared to those of other forms of published content. Medical schools should consider supporting student podcast initiatives to allow for near-peer mentoring, augment the community, facilitate professional identity formation, and prepare the rising physician workforce for the technological frontier of medical education and practice. UR - https://mededu.jmir.org/2021/3/e29157 UR - http://dx.doi.org/10.2196/29157 UR - http://www.ncbi.nlm.nih.gov/pubmed/34255694 ID - info:doi/10.2196/29157 ER - TY - JOUR AU - Acquaviva, D. Kimberly PY - 2021/5/17 TI - Establishing and Facilitating Large-Scale Manuscript Collaborations via Social Media: Novel Method and Tools for Replication JO - J Med Internet Res SP - e25077 VL - 23 IS - 5 KW - social media KW - crowdsourcing KW - collaboration KW - health professions KW - medicine KW - scholarship KW - literature KW - research N2 - Background: Authorship teams in the health professions are typically composed of scholars who are acquainted with one another before a manuscript is written. Even if a scholar has identified a diverse group of collaborators outside their usual network, writing an article with a large number of co-authors poses significant logistical challenges. Objective: This paper describes a novel method for establishing and facilitating large-scale manuscript collaborations via social media. Methods: On September 11, 2020, I used the social media platform Twitter to invite people to collaborate on an article I had drafted. Anyone who wanted to collaborate was welcome, regardless of discipline, specialty, title, country of residence, or degree completion. During the 25 days that followed, I used Google Docs, Google Sheets, and Google Forms to manage all aspects of the collaboration. Results: The collaboration resulted in the completion of 2 manuscripts in a 25-day period. The International Council of Medical Journal Editors authorship criteria were met by 40 collaborators for the first article (?Documenting Social Media Engagement as Scholarship: A New Model for Assessing Academic Accomplishment for the Health Professions?) and 35 collaborators for the second article (?The Benefits of Using Social Media as a Health Professional in Academia?). The authorship teams for both articles were notably diverse, with 17%-18% (7/40 and 6/35, respectively) of authors identifying as a person of color and/or underrepresented minority, 37%-38% (15/40 and 13/35, respectively) identifying as LGBTQ+ (lesbian, gay, bisexual, transgender, gender non-conforming, queer and/or questioning), 73%-74% (29/40 and 26/35, respectively) using she/her pronouns, and 20%-23% (9/40 and 7/35, respectively) identifying as a person with a disability. Conclusions: Scholars in the health professions can use this paper in conjunction with the tools provided to replicate this process in carrying out their own large-scale manuscript collaborations. UR - https://www.jmir.org/2021/5/e25077 UR - http://dx.doi.org/10.2196/25077 UR - http://www.ncbi.nlm.nih.gov/pubmed/33999002 ID - info:doi/10.2196/25077 ER - TY - JOUR AU - Nguyen, Xuan-Lan Anne AU - Trinh, Xuan-Vi AU - Wang, Y. Sophia AU - Wu, Y. Albert PY - 2021/5/17 TI - Determination of Patient Sentiment and Emotion in Ophthalmology: Infoveillance Tutorial on Web-Based Health Forum Discussions JO - J Med Internet Res SP - e20803 VL - 23 IS - 5 KW - sentiment analysis KW - emotions analysis KW - natural language processing KW - online forums KW - social media KW - patient attitudes KW - medicine KW - infodemiology KW - infoveillance KW - digital health N2 - Background: Clinical data in social media are an underused source of information with great potential to allow for a deeper understanding of patient values, attitudes, and preferences. Objective: This tutorial aims to describe a novel, robust, and modular method for the sentiment analysis and emotion detection of free text from web-based forums and the factors to consider during its application. Methods: We mined the discussion and user information of all posts containing search terms related to a medical subspecialty (oculoplastics) from MedHelp, the largest web-based platform for patient health forums. We used data cleaning and processing tools to define the relevant subset of results and prepare them for sentiment analysis. We executed sentiment and emotion analyses by using IBM Watson Natural Language Understanding to generate sentiment and emotion scores for the posts and their associated keywords. The keywords were aggregated using natural language processing tools. Results: Overall, 39 oculoplastic-related search terms resulted in 46,381 eligible posts within 14,329 threads. Posts were written by 18,319 users (117 doctors; 18,202 patients) and included 201,611 associated keywords. Keywords that occurred ?500 times in the corpus were used to identify the most prominent topics, including specific symptoms, medication, and complications. The sentiment and emotion scores of these keywords and eligible posts were analyzed to provide concrete examples of the potential of this methodology to allow for a better understanding of patients? attitudes. The overall sentiment score reflects a positive, neutral, or negative sentiment, whereas the emotion scores (anger, disgust, fear, joy, and sadness) represent the likelihood of the presence of the emotion. In keyword grouping analyses, medical signs, symptoms, and diseases had the lowest overall sentiment scores (?0.598). Complications were highly associated with sadness (0.485). Forum posts mentioning body parts were related to sadness (0.416) and fear (0.321). Administration was the category with the highest anger score (0.146). The top 6 forum subgroups had an overall negative sentiment score; the most negative one was the Neurology forum, with a score of ?0.438. The Undiagnosed Symptoms forum had the highest sadness score (0.448). The least likely fearful posts were those from the Eye Care forum, with a score of 0.260. The overall sentiment score was much more negative before the doctor replied. The anger, disgust, fear, and sadness emotion scores decreased in likelihood, whereas joy was slightly more likely to be expressed after doctors replied. Conclusions: This report allows physicians and researchers to efficiently mine and perform sentiment analysis on social media to better understand patients? perspectives and promote patient-centric care. Important factors to be considered during its application include evaluating the scope of the search; selecting search terms and understanding their linguistic usages; and establishing selection, filtering, and processing criteria for posts and keywords tailored to the desired results. UR - https://www.jmir.org/2021/5/e20803 UR - http://dx.doi.org/10.2196/20803 UR - http://www.ncbi.nlm.nih.gov/pubmed/33999001 ID - info:doi/10.2196/20803 ER - TY - JOUR AU - Lalande, Kathleen AU - Greenman, S. Paul AU - Bouchard, Karen AU - Johnson, M. Susan AU - Tulloch, Heather PY - 2021/4/6 TI - The Healing Hearts Together Randomized Controlled Trial and the COVID-19 Pandemic: A Tutorial for Transitioning From an In-Person to a Web-Based Intervention JO - J Med Internet Res SP - e25502 VL - 23 IS - 4 KW - web-based intervention KW - internet-based intervention KW - randomized controlled trial KW - COVID-19 KW - research KW - tutorial KW - digital medicine KW - behavioral medicine KW - telehealth KW - telemedicine KW - cardiovascular rehabilitation UR - https://www.jmir.org/2021/4/e25502 UR - http://dx.doi.org/10.2196/25502 UR - http://www.ncbi.nlm.nih.gov/pubmed/33729984 ID - info:doi/10.2196/25502 ER - TY - JOUR AU - Shepperd, A. James AU - Pogge, Gabrielle AU - Hunleth, M. Jean AU - Ruiz, Sienna AU - Waters, A. Erika PY - 2021/3/11 TI - Guidelines for Conducting Virtual Cognitive Interviews During a Pandemic JO - J Med Internet Res SP - e25173 VL - 23 IS - 3 KW - cognitive interview KW - COVID-19 KW - guidelines KW - teleresearch KW - pandemic KW - tablet computer KW - telehealth KW - training UR - https://www.jmir.org/2021/3/e25173 UR - http://dx.doi.org/10.2196/25173 UR - http://www.ncbi.nlm.nih.gov/pubmed/33577464 ID - info:doi/10.2196/25173 ER - TY - JOUR AU - Do, Quan AU - Marc, David AU - Plotkin, Marat AU - Pickering, Brian AU - Herasevich, Vitaly PY - 2020/12/24 TI - Starter Kit for Geotagging and Geovisualization in Health Care: Resource Paper JO - JMIR Form Res SP - e23379 VL - 4 IS - 12 KW - geographic mapping KW - medicalGIS guidelines KW - information storage and retrieval KW - mapping KW - geotagging KW - data visualization KW - population KW - public health N2 - Background: Geotagging is the process of attaching geospatial tags to various media data types. In health care, the goal of geotagging is to gain a better understanding of health-related questions applied to populations. Although there has been a prevalence of geographic information in public health, in order to effectively use and expand geotagging across health care there is a requirement to understand other factors such as the disposition, standardization, data sources, technologies, and limitations. Objective: The objective of this document is to serve as a resource for new researchers in the field. This report aims to be comprehensive but easy for beginners to understand and adopt in practice. The optimal geocodes, their sources, and a rationale for use are suggested. Geotagging?s issues and limitations are also discussed. Methods: A comprehensive review of technical instructions and articles was conducted to evaluate guidelines for geotagging, and online resources were curated to support the implementation of geotagging practices. Summary tables were developed to describe the available geotagging resources (free and for fee) that can be leveraged by researchers and quality improvement personnel to effectively perform geospatial analyses primarily targeting US health care. Results: This paper demonstrated steps to develop an initial geotagging and geovisualization project with clear structure and instructions. The geotagging resources were summarized. These resources are essential for geotagging health care projects. The discussion section provides better understanding of geotagging?s limitations and suggests suitable way to approach it. Conclusions: We explain how geotagging can be leveraged in health care and offer the necessary initial resources to obtain geocodes, adjustment data, and health-related measures. The resources outlined in this paper can support an individual and/or organization in initiating a geotagging health care project. UR - http://formative.jmir.org/2020/12/e23379/ UR - http://dx.doi.org/10.2196/23379 UR - http://www.ncbi.nlm.nih.gov/pubmed/33361054 ID - info:doi/10.2196/23379 ER - TY - JOUR AU - Patel, Devika AU - Hawkins, Jessica AU - Chehab, Zena Lara AU - Martin-Tuite, Patrick AU - Feler, Joshua AU - Tan, Amy AU - Alpers, S. Benjamin AU - Pink, Sophia AU - Wang, Jerome AU - Freise, Jonathan AU - Kim, Phillip AU - Peabody, Christopher AU - Bowditch, John AU - Williams, R. Eric AU - Sammann, Amanda PY - 2020/12/16 TI - Developing Virtual Reality Trauma Training Experiences Using 360-Degree Video: Tutorial JO - J Med Internet Res SP - e22420 VL - 22 IS - 12 KW - virtual reality KW - cineVR KW - 360-degree video KW - trauma training KW - medical education UR - http://www.jmir.org/2020/12/e22420/ UR - http://dx.doi.org/10.2196/22420 UR - http://www.ncbi.nlm.nih.gov/pubmed/33325836 ID - info:doi/10.2196/22420 ER - TY - JOUR AU - Martin, L. Christie AU - Kramer-Kostecka, N. Eydie AU - Linde, A. Jennifer AU - Friend, Sarah AU - Zuroski, R. Vanessa AU - Fulkerson, A. Jayne PY - 2020/9/23 TI - Leveraging Interdisciplinary Teams to Develop and Implement Secure Websites for Behavioral Research: Applied Tutorial JO - J Med Internet Res SP - e19217 VL - 22 IS - 9 KW - research ethics and compliance KW - website development KW - behavioral research KW - digital interventions KW - website authentication KW - website security UR - http://www.jmir.org/2020/9/e19217/ UR - http://dx.doi.org/10.2196/19217 UR - http://www.ncbi.nlm.nih.gov/pubmed/32965234 ID - info:doi/10.2196/19217 ER - TY - JOUR AU - Robinson, Heather AU - Appelbe, Duncan AU - Dodd, Susanna AU - Flowers, Susan AU - Johnson, Sonia AU - Jones, H. Steven AU - Mateus, Céu AU - Mezes, Barbara AU - Murray, Elizabeth AU - Rainford, Naomi AU - Rosala-Hallas, Anna AU - Walker, Andrew AU - Williamson, Paula AU - Lobban, Fiona PY - 2020/7/17 TI - Methodological Challenges in Web-Based Trials: Update and Insights From the Relatives Education and Coping Toolkit Trial JO - JMIR Ment Health SP - e15878 VL - 7 IS - 7 KW - randomized controlled trial KW - research design KW - methods KW - internet KW - web KW - mental health KW - relatives KW - carers N2 - International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2017-016965 UR - https://mental.jmir.org/2020/7/e15878 UR - http://dx.doi.org/10.2196/15878 UR - http://www.ncbi.nlm.nih.gov/pubmed/32497018 ID - info:doi/10.2196/15878 ER - TY - JOUR AU - Hadjiconstantinou, Michelle AU - Schreder, Sally AU - Brough, Christopher AU - Northern, Alison AU - Stribling, Bernie AU - Khunti, Kamlesh AU - Davies, J. Melanie PY - 2020/5/11 TI - Using Intervention Mapping to Develop a Digital Self-Management Program for People With Type 2 Diabetes: Tutorial on MyDESMOND JO - J Med Internet Res SP - e17316 VL - 22 IS - 5 KW - diabetes mellitus, type 2 KW - technology KW - self-management UR - https://www.jmir.org/2020/5/e17316 UR - http://dx.doi.org/10.2196/17316 UR - http://www.ncbi.nlm.nih.gov/pubmed/32391797 ID - info:doi/10.2196/17316 ER - TY - JOUR AU - Chow, I. Philip PY - 2020/4/20 TI - Developing Mental or Behavioral Health Mobile Apps for Pilot Studies by Leveraging Survey Platforms: A Do-it-Yourself Process JO - JMIR Mhealth Uhealth SP - e15561 VL - 8 IS - 4 KW - app KW - mental health KW - mHealth N2 - Background: Behavioral health researchers are increasingly recognizing the potential of mobile phone apps to deliver empirically supported treatments. However, current options for developing apps typically require large amounts of expertise or money. Objective: This paper aims to describe a pragmatic do-it-yourself approach for researchers to create and pilot an Android mobile phone app using existing survey software (eg, Qualtrics survey platform). Methods: This study was conducted at an academic research center in the United States focused on developing and evaluating behavioral health technologies. The process outlined in this paper was derived and condensed from the steps to building an existing app intervention, iCanThrive, which was developed to enhance mental well-being in women cancer survivors. Results: This paper describes an inexpensive, practical process that uses a widely available survey software, such as Qualtrics, to create and pilot a mobile phone intervention that is presented to participants as a Web viewer app that is downloaded from the Google Play store. Health researchers who are interested in using this process to pilot apps are encouraged to inquire about the survey platforms available to them, the level of security those survey platforms provide, and the regulatory guidelines set forth by their institution. Conclusions: As app interventions continue to gain interest among researchers and consumers alike, it is important to find new ways to efficiently develop and pilot app interventions before committing a large amount of resources. Mobile phone app interventions are an important component to discovering new ways to reach and support individuals with behavioral or mental health disorders. UR - https://mhealth.jmir.org/2020/4/e15561 UR - http://dx.doi.org/10.2196/15561 UR - http://www.ncbi.nlm.nih.gov/pubmed/32310143 ID - info:doi/10.2196/15561 ER - TY - JOUR AU - Parga-Belinkie, Joanna AU - Merchant, M. Raina PY - 2019/12/20 TI - Voices in Evidence-Based Newborn Care: A How-to-Guide on Developing a Parent-Facing Podcast JO - JMIR Pediatr Parent SP - e16335 VL - 2 IS - 2 KW - neonatology KW - social media KW - medical education KW - patient education UR - http://pediatrics.jmir.org/2019/2/e16335/ UR - http://dx.doi.org/10.2196/16335 UR - http://www.ncbi.nlm.nih.gov/pubmed/31859674 ID - info:doi/10.2196/16335 ER - TY - JOUR AU - Tobore, Igbe AU - Li, Jingzhen AU - Yuhang, Liu AU - Al-Handarish, Yousef AU - Kandwal, Abhishek AU - Nie, Zedong AU - Wang, Lei PY - 2019/08/02 TI - Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations JO - JMIR Mhealth Uhealth SP - e11966 VL - 7 IS - 8 KW - machine learning KW - deep learning KW - big data KW - mHealth KW - medical imaging KW - electronic health record KW - biologicals KW - biomedical KW - ECG KW - EEG KW - artificial intelligence UR - https://mhealth.jmir.org/2019/8/e11966/ UR - http://dx.doi.org/10.2196/11966 UR - http://www.ncbi.nlm.nih.gov/pubmed/31376272 ID - info:doi/10.2196/11966 ER - TY - JOUR AU - Mavragani, Amaryllis AU - Ochoa, Gabriela PY - 2019/05/29 TI - Google Trends in Infodemiology and Infoveillance: Methodology Framework JO - JMIR Public Health Surveill SP - e13439 VL - 5 IS - 2 KW - big data KW - health KW - infodemiology KW - infoveillance KW - internet behavior KW - Google Trends UR - http://publichealth.jmir.org/2019/2/e13439/ UR - http://dx.doi.org/10.2196/13439 UR - http://www.ncbi.nlm.nih.gov/pubmed/31144671 ID - info:doi/10.2196/13439 ER - TY - JOUR AU - Adam, Maya AU - McMahon, A. Shannon AU - Prober, Charles AU - Bärnighausen, Till PY - 2019/01/30 TI - Human-Centered Design of Video-Based Health Education: An Iterative, Collaborative, Community-Based Approach JO - J Med Internet Res SP - e12128 VL - 21 IS - 1 KW - human-centered design KW - health promotion KW - health behavior KW - health knowledge, attitudes, practice KW - community health workers KW - telemedicine KW - eHealth KW - mHealth UR - http://www.jmir.org/2019/1/e12128/ UR - http://dx.doi.org/10.2196/12128 UR - http://www.ncbi.nlm.nih.gov/pubmed/30698531 ID - info:doi/10.2196/12128 ER - TY - JOUR AU - Akers, Laura AU - Gordon, S. Judith PY - 2018/11/08 TI - Using Facebook for Large-Scale Online Randomized Clinical Trial Recruitment: Effective Advertising Strategies JO - J Med Internet Res SP - e290 VL - 20 IS - 11 KW - research subject recruitment KW - advertisements KW - social media UR - http://www.jmir.org/2018/11/e290/ UR - http://dx.doi.org/10.2196/jmir.9372 UR - http://www.ncbi.nlm.nih.gov/pubmed/30409765 ID - info:doi/10.2196/jmir.9372 ER - TY - JOUR AU - Zafar, Sidra AU - Habboush, Yacob AU - Beidas, Sary PY - 2018/11/07 TI - Use of Grading of Recommendations, Assessment, Development, and Evaluation to Combat Fake News: A Case Study of Influenza Vaccination in Pregnancy JO - JMIR Med Educ SP - e10347 VL - 4 IS - 2 KW - GRADE KW - influenza KW - vaccination KW - spontaneous abortion KW - miscarriage N2 - Background: The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework is a validated evaluation tool used to assess the quality of scientific publications. It helps in enhancing clinicians? decision-making process and supports production of informed healthy policy. Objective: The purpose of this report was two-fold. First, we reviewed the interpretation of observational studies. The second purpose was to share or provide an example using the GRADE criteria. Methods: To illustrate the use of the GRADE framework to assess publications, we selected a study evaluating the risk of spontaneous abortion (SAB) after influenza vaccine administration. Results: Since 2004, the Centers for Disease Control and Prevention and the Advisory Committee on Immunization Practice have recommended influenza vaccination of pregnant women. Previous studies have not found an association between influenza vaccination and SAB. However, in a recent case-control study by Donahue et al, a correlation with SAB in women who received the H1N1 influenza vaccine was identified. For women who received H1N1?containing vaccine in the previous and current influenza season, the adjusted odds ratio (aOR) for SAB was 7.7 (95% CI, 2.2-27.3), while the aOR for women not vaccinated in the previous season but vaccinated in the current season was 1.3 (95% CI, 0.7-2.7). Conclusions: Our goal is to enable the readers to critique published literature using appropriate evaluation tools such as GRADE. UR - http://mededu.jmir.org/2018/2/e10347/ UR - http://dx.doi.org/10.2196/10347 UR - http://www.ncbi.nlm.nih.gov/pubmed/30404772 ID - info:doi/10.2196/10347 ER - TY - JOUR AU - Bendtsen, Marcus PY - 2018/10/24 TI - A Gentle Introduction to the Comparison Between Null Hypothesis Testing and Bayesian Analysis: Reanalysis of Two Randomized Controlled Trials JO - J Med Internet Res SP - e10873 VL - 20 IS - 10 KW - null hypothesis testing KW - Bayesian analysis KW - randomized controlled trials KW - Bayes theorem KW - randomized controlled trials as topic UR - http://www.jmir.org/2018/10/e10873/ UR - http://dx.doi.org/10.2196/10873 UR - http://www.ncbi.nlm.nih.gov/pubmed/30148453 ID - info:doi/10.2196/10873 ER - TY - JOUR AU - O?Sullivan, Benjamin AU - Alam, Fahad AU - Matava, Clyde PY - 2018/07/16 TI - Creating Low-Cost 360-Degree Virtual Reality Videos for Hospitals: A Technical Paper on the Dos and Don?ts JO - J Med Internet Res SP - e239 VL - 20 IS - 7 KW - 360-degree video KW - VR KW - virtual reality KW - video production KW - anesthetic preparation KW - preoperative anxiety KW - preoperative preparation UR - http://www.jmir.org/2018/7/e239/ UR - http://dx.doi.org/10.2196/jmir.9596 UR - http://www.ncbi.nlm.nih.gov/pubmed/30012545 ID - info:doi/10.2196/jmir.9596 ER - TY - JOUR AU - Hekler, B. Eric AU - Rivera, E. Daniel AU - Martin, A. Cesar AU - Phatak, S. Sayali AU - Freigoun, T. Mohammad AU - Korinek, Elizabeth AU - Klasnja, Predrag AU - Adams, A. Marc AU - Buman, P. Matthew PY - 2018/06/28 TI - Tutorial for Using Control Systems Engineering to Optimize Adaptive Mobile Health Interventions JO - J Med Internet Res SP - e214 VL - 20 IS - 6 KW - adaptive interventions KW - mHealth KW - eHealth KW - digital health KW - control systems engineering KW - behavior change KW - optimization KW - multiphase optimization strategy KW - physical activity KW - behavioral maintenance N2 - Background: Adaptive behavioral interventions are individualized interventions that vary support based on a person's evolving needs. Digital technologies enable these adaptive interventions to function at scale. Adaptive interventions show great promise for producing better results compared with static interventions related to health outcomes. Our central thesis is that adaptive interventions are more likely to succeed at helping individuals meet and maintain behavioral targets if its elements can be iteratively improved via data-driven testing (ie, optimization). Control systems engineering is a discipline focused on decision making in systems that change over time and has a wealth of methods that could be useful for optimizing adaptive interventions. Objective: The purpose of this paper was to provide an introductory tutorial on when and what to do when using control systems engineering for designing and optimizing adaptive mobile health (mHealth) behavioral interventions. Overview: We start with a review of the need for optimization, building on the multiphase optimization strategy (MOST). We then provide an overview of control systems engineering, followed by attributes of problems that are well matched to control engineering. Key steps in the development and optimization of an adaptive intervention from a control engineering perspective are then summarized, with a focus on why, what, and when to do subtasks in each step. Implications: Control engineering offers exciting opportunities for optimizing individualization and adaptation elements of adaptive interventions. Arguably, the time is now for control systems engineers and behavioral and health scientists to partner to advance interventions that can be individualized, adaptive, and scalable. This tutorial should aid in creating the bridge between these communities. UR - http://www.jmir.org/2018/6/e214/ UR - http://dx.doi.org/10.2196/jmir.8622 UR - http://www.ncbi.nlm.nih.gov/pubmed/29954725 ID - info:doi/10.2196/jmir.8622 ER - TY - JOUR AU - Sieverink, Floor AU - Kelders, Saskia AU - Poel, Mannes AU - van Gemert-Pijnen, Lisette PY - 2017/08/07 TI - Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data JO - JMIR Res Protoc SP - e156 VL - 6 IS - 8 KW - eHealth KW - black box KW - evaluation KW - log data analysis UR - http://www.researchprotocols.org/2017/8/e156/ UR - http://dx.doi.org/10.2196/resprot.6452 UR - http://www.ncbi.nlm.nih.gov/pubmed/28784592 ID - info:doi/10.2196/resprot.6452 ER - TY - JOUR AU - Heffernan, Joanne Kayla AU - Chang, Shanton AU - Maclean, Tamara Skye AU - Callegari, Teresa Emma AU - Garland, Marie Suzanne AU - Reavley, Jane Nicola AU - Varigos, Andrew George AU - Wark, Dennis John PY - 2016/02/09 TI - Guidelines and Recommendations for Developing Interactive eHealth Apps for Complex Messaging in Health Promotion JO - JMIR mHealth uHealth SP - e14 VL - 4 IS - 1 KW - mhealth KW - complex messaging KW - vitamin D KW - eHealth smartphone apps KW - interactive N2 - Background: The now ubiquitous catchphrase, ?There?s an app for that,? rings true owing to the growing number of mobile phone apps. In excess of 97,000 eHealth apps are available in major app stores. Yet the effectiveness of these apps varies greatly. While a minority of apps are developed grounded in theory and in conjunction with health care experts, the vast majority are not. This is concerning given the Hippocratic notion of ?do no harm.? There is currently no unified formal theory for developing interactive eHealth apps, and development is especially difficult when complex messaging is required, such as in health promotion and prevention. Objective: This paper aims to provide insight into the creation of interactive eHealth apps for complex messaging, by leveraging the Safe-D case study, which involved complex messaging required to guide safe but sufficient UV exposure for vitamin D synthesis in users. We aim to create recommendations for developing interactive eHealth apps for complex messages based on the lessons learned during Safe-D app development. Methods: For this case study we developed an Apple and Android app, both named Safe-D, to safely improve vitamin D status in young women through encouraging safe ultraviolet radiation exposure. The app was developed through participatory action research involving medical and human computer interaction researchers, subject matter expert clinicians, external developers, and target users. The recommendations for development were created from analysis of the development process. Results: By working with clinicians and implementing disparate design examples from the literature, we developed the Safe-D app. From this development process, recommendations for developing interactive eHealth apps for complex messaging were created: (1) involve a multidisciplinary team in the development process, (2) manage complex messages to engage users, and (3) design for interactivity (tailor recommendations, remove barriers to use, design for simplicity). Conclusions: This research has provided principles for developing interactive eHealth apps for complex messaging as guidelines by aggregating existing design concepts and expanding these concepts and new learnings from our development process. A set of guidelines to develop interactive eHealth apps generally, and specifically those for complex messaging, was previously missing from the literature; this research has contributed these principles. Safe-D delivers complex messaging simply, to aid education, and explicitly, considering user safety. UR - http://mhealth.jmir.org/2016/1/e14/ UR - http://dx.doi.org/10.2196/mhealth.4423 UR - http://www.ncbi.nlm.nih.gov/pubmed/26860623 ID - info:doi/10.2196/mhealth.4423 ER - TY - JOUR AU - Pagoto, Sherry AU - Waring, E. Molly AU - May, N. Christine AU - Ding, Y. Eric AU - Kunz, H. Werner AU - Hayes, Rashelle AU - Oleski, L. Jessica PY - 2016/01/29 TI - Adapting Behavioral Interventions for Social Media Delivery JO - J Med Internet Res SP - e24 VL - 18 IS - 1 KW - social media KW - behavioral interventions KW - health behavior KW - online social networks UR - http://www.jmir.org/2016/1/e24/ UR - http://dx.doi.org/10.2196/jmir.5086 UR - http://www.ncbi.nlm.nih.gov/pubmed/26825969 ID - info:doi/10.2196/jmir.5086 ER - TY - JOUR AU - Abroms, C. Lorien AU - Whittaker, Robyn AU - Free, Caroline AU - Mendel Van Alstyne, Judith AU - Schindler-Ruwisch, M. Jennifer PY - 2015/12/21 TI - Developing and Pretesting a Text Messaging Program for Health Behavior Change: Recommended Steps JO - JMIR mHealth uHealth SP - e107 VL - 3 IS - 4 KW - mHealth KW - telemedicine KW - SMS KW - text messaging KW - behavior change KW - behavior modification N2 - Background: A growing body of evidence demonstrates that text messaging-based programs (short message service [SMS]) on mobile phones can help people modify health behaviors. Most of these programs have consisted of automated and sometimes interactive text messages that guide a person through the process of behavior change. Objective: This paper provides guidance on how to develop text messaging programs aimed at changing health behaviors. Methods: Based on their collective experience in designing, developing, and evaluating text messaging programs and a review of the literature, the authors drafted the guide. One author initially drafted the guide and the others provided input and review. Results: Steps for developing a text messaging program include conducting formative research for insights into the target audience and health behavior, designing the text messaging program, pretesting the text messaging program concept and messages, and revising the text messaging program. Conclusions: The steps outlined in this guide may help in the development of SMS-based behavior change programs. UR - http://mhealth.jmir.org/2015/4/e107/ UR - http://dx.doi.org/10.2196/mhealth.4917 UR - http://www.ncbi.nlm.nih.gov/pubmed/26690917 ID - info:doi/10.2196/mhealth.4917 ER - TY - JOUR AU - Bergmo, Strand Trine PY - 2015/11/09 TI - How to Measure Costs and Benefits of eHealth Interventions: An Overview of Methods and Frameworks JO - J Med Internet Res SP - e254 VL - 17 IS - 11 KW - eHealth KW - telemedicine KW - telehealth KW - telemonitoring KW - health economics KW - economic evaluation KW - cost-benefit analysis KW - cost-effectiveness analysis KW - cost-utility analysis KW - quality-adjusted life years (QALYs) UR - http://www.jmir.org/2015/11/e254/ UR - http://dx.doi.org/10.2196/jmir.4521 UR - http://www.ncbi.nlm.nih.gov/pubmed/26552360 ID - info:doi/10.2196/jmir.4521 ER - TY - JOUR AU - Bock, C. Beth AU - Rosen, K. Rochelle AU - Barnett, P. Nancy AU - Thind, Herpreet AU - Walaska, Kristen AU - Foster, Robert AU - Deutsch, Christopher AU - Traficante, Regina PY - 2015/02/24 TI - Translating Behavioral Interventions Onto mHealth Platforms: Developing Text Message Interventions for Smoking and Alcohol JO - JMIR mHealth uHealth SP - e22 VL - 3 IS - 1 KW - mHealth KW - text message KW - smoking cessation KW - alcohol KW - qualitative methods UR - http://mhealth.jmir.org/2015/1/e22/ UR - http://dx.doi.org/10.2196/mhealth.3779 UR - http://www.ncbi.nlm.nih.gov/pubmed/25714907 ID - info:doi/10.2196/mhealth.3779 ER - TY - JOUR AU - Yardley, Lucy AU - Morrison, Leanne AU - Bradbury, Katherine AU - Muller, Ingrid PY - 2015/01/30 TI - The Person-Based Approach to Intervention Development: Application to Digital Health-Related Behavior Change Interventions JO - J Med Internet Res SP - e30 VL - 17 IS - 1 KW - person-based approach KW - Internet KW - qualitative research KW - evaluation studies KW - feasibility studies KW - health promotion KW - patient education KW - professional education KW - behavior change. UR - http://www.jmir.org/2015/1/e30/ UR - http://dx.doi.org/10.2196/jmir.4055 UR - http://www.ncbi.nlm.nih.gov/pubmed/25639757 ID - info:doi/10.2196/jmir.4055 ER - TY - JOUR AU - Horvath, J. Keith AU - Ecklund, M. Alexandra AU - Hunt, L. Shanda AU - Nelson, F. Toben AU - Toomey, L. Traci PY - 2015/01/23 TI - Developing Internet-Based Health Interventions: A Guide for Public Health Researchers and Practitioners JO - J Med Internet Res SP - e28 VL - 17 IS - 1 KW - Internet KW - public health KW - intervention KW - development N2 - Background: Researchers and practitioners interested in developing online health interventions most often rely on Web-based and print resources to guide them through the process of online intervention development. Although useful for understanding many aspects of best practices for website development, missing from these resources are concrete examples of experiences in online intervention development for health apps from the perspective of those conducting online health interventions. Objective: This study aims to serve as a series of case studies in the development of online health interventions to provide insights for researchers and practitioners who are considering technology-based interventional or programmatic approaches. Methods: A convenience sample of six study coordinators and five principal investigators at a large, US-based land grant university were interviewed about the process of developing online interventions in the areas of alcohol policy, adolescent health, medication adherence, and human immunodeficiency virus prevention in transgender persons and in men who have sex with men. Participants were asked questions that broadly addressed each of the four phases of the User-Centered Design Process Map from the US Department of Health and Human Services' Research-Based Web Design & Usability Guidelines. Interviews were audio recorded and transcribed. Qualitative codes were developed using line-by-line open coding for all transcripts, and all transcripts were coded independently by at least 2 authors. Differences among coders were resolved with discussion. Results: We identified the following seven themes: (1) hire a strong (or at least the right) research team, (2) take time to plan before beginning the design process, (3) recognize that vendors and researchers have differing values, objectives, and language, (4) develop a detailed contract, (5) document all decisions and development activities, (6) use a content management system, and (7) allow extra time for testing and debugging your intervention. Each of these areas is discussed in detail, with supporting quotations from principal investigators and study coordinators. Conclusions: The values held by members of each participating organization involved in the development of the online intervention or program, as well as the objectives that are trying to be met with the website, must be considered. These defined values and objectives should prompt an open and explicit discussion about the scope of work, budget, and other needs from the perspectives of each organization. Because of the complexity of developing online interventions, researchers and practitioners should become familiar with the process and how it may differ from the development and implementation of in-person interventions or programs. To assist with this, the intervention team should consider expanding the team to include experts in computer science or learning technologies, as well as taking advantage of institutional resources that will be needed for successful completion of the project. Finally, we describe the tradeoff between funds available for online intervention or program development and the complexity of the project. UR - http://www.jmir.org/2015/1/e28/ UR - http://dx.doi.org/10.2196/jmir.3770 UR - http://www.ncbi.nlm.nih.gov/pubmed/25650702 ID - info:doi/10.2196/jmir.3770 ER - TY - JOUR AU - Agboola, Stephen AU - Hale, M. Timothy AU - Masters, Caitlin AU - Kvedar, Joseph AU - Jethwani, Kamal PY - 2014/12/17 TI - ?Real-World? Practical Evaluation Strategies: A Review of Telehealth Evaluation JO - JMIR Res Protoc SP - e75 VL - 3 IS - 4 KW - telehealth KW - eHealth KW - evaluation KW - evaluation framework KW - diabetes mellitus KW - technology N2 - Background: Currently, the increasing interest in telehealth and significant technological breakthroughs of the past decade create favorable conditions for the widespread adoption of telehealth services. Therefore, expectations are high that telehealth can help alleviate prevailing challenges in health care delivery. However, in order to translate current research to policy and facilitate adoption by patients and health care providers, there is need for compelling evidence of the effectiveness of telehealth interventions. Such evidence is gathered from rigorously designed research studies, which may not always be practical in many real-world settings. Objective: Our aim was to summarize current telehealth evaluation strategies and challenges and to outline practical approaches to conduct evaluation in real-world settings using one of our previously reported telehealth initiatives, the Diabetes Connect program, as a case study. Methods: We reviewed commonly used current evaluation frameworks and strategies, as well as best practices based on successful evaluative efforts to date to address commonly encountered challenges in telehealth evaluation. These challenges in telehealth evaluation and commonly used frameworks are described relevant to the evaluation of Diabetes Connect, a 12-month Web-based blood glucose monitoring program. Results: Designers of telehealth evaluation frameworks must give careful consideration to the elements of planning, implementation, and impact assessment of interventions. Evaluating performance at each of these phases is critical to the overall success of an intervention. Although impact assessment occurs at the end of a program, our review shows that it should begin at the point of problem definition. Critical to the success of an evaluative strategy is early planning that involves all stakeholders to identify the overall goals of the program and key measures of success at each phase of the program life cycle. This strategy should enable selection of an appropriate evaluation strategy and measures to aid in the ongoing development and implementation of telehealth and provide better evidence of program impact. Conclusions: We recommend a pragmatic, multi-method, multi-phase approach to telehealth evaluation that is flexible and can be adapted to the characteristics and challenges unique to each telehealth program. UR - http://www.researchprotocols.org/2014/4/e75/ UR - http://dx.doi.org/10.2196/resprot.3459 UR - http://www.ncbi.nlm.nih.gov/pubmed/25524892 ID - info:doi/10.2196/resprot.3459 ER - TY - JOUR AU - Zhang, WB Melvyn AU - Tsang, Tammy AU - Cheow, Enquan AU - Ho, SH Cyrus AU - Yeong, Beng Ng AU - Ho, CM Roger PY - 2014/11/11 TI - Enabling Psychiatrists to be Mobile Phone App Developers: Insights Into App Development Methodologies JO - JMIR mHealth uHealth SP - e53 VL - 2 IS - 4 KW - smartphone application KW - mobile application KW - creation N2 - Background: The use of mobile phones, and specifically smartphones, in the last decade has become more and more prevalent. The latest mobile phones are equipped with comprehensive features that can be used in health care, such as providing rapid access to up-to-date evidence-based information, provision of instant communications, and improvements in organization. The estimated number of health care apps for mobile phones is increasing tremendously, but previous research has highlighted the lack of critical appraisal of new apps. This lack of appraisal of apps has largely been due to the lack of clinicians with technical knowledge of how to create an evidence-based app. Objective: We discuss two freely available methodologies for developing Web-based mobile phone apps: a website builder and an app builder. With these, users can program not just a Web-based app, but also integrate multimedia features within their app, without needing to know any programming language. Methods: We present techniques for creating a mobile Web-based app using two well-established online mobile app websites. We illustrate how to integrate text-based content within the app, as well as integration of interactive videos and rich site summary (RSS) feed information. We will also briefly discuss how to integrate a simple questionnaire survey into the mobile-based app. A questionnaire survey was administered to students to collate their perceptions towards the app. Results: These two methodologies for developing apps have been used to convert an online electronic psychiatry textbook into two Web-based mobile phone apps for medical students rotating through psychiatry in Singapore. Since the inception of our mobile Web-based app, a total of 21,991 unique users have used the mobile app and online portal provided by WordPress, and another 717 users have accessed the app via a Web-based link. The user perspective survey results (n=185) showed that a high proportion of students valued the textbook and objective structured clinical examination videos featured in the app. A high proportion of students concurred that a self-designed mobile phone app would be helpful for psychiatry education. Conclusions: These methodologies can enable busy clinicians to develop simple mobile Web-based apps for academic, educational, and research purposes, without any prior knowledge of programming. This will be beneficial for both clinicians and users at large, as there will then be more evidence-based mobile phone apps, or at least apps that have been appraised by a clinician. UR - http://mhealth.jmir.org/2014/4/e53/ UR - http://dx.doi.org/10.2196/mhealth.3425 UR - http://www.ncbi.nlm.nih.gov/pubmed/25486985 ID - info:doi/10.2196/mhealth.3425 ER - TY - JOUR AU - Regola, Nathan AU - Chawla, V. Nitesh PY - 2013/03/13 TI - Storing and Using Health Data in a Virtual Private Cloud JO - J Med Internet Res SP - e63 VL - 15 IS - 3 KW - medical informatics KW - HIPAA UR - http://www.jmir.org/2013/3/e63/ UR - http://dx.doi.org/10.2196/jmir.2076 UR - http://www.ncbi.nlm.nih.gov/pubmed/23485880 ID - info:doi/10.2196/jmir.2076 ER -