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Prevalence of Multiple Chronic Conditions Among Adults in the All of Us Research Program: Exploratory Analysis

Prevalence of Multiple Chronic Conditions Among Adults in the All of Us Research Program: Exploratory Analysis

Moreover, research suggests that more contemporary generations of adults have a greater MCC burden and are diagnosed with MCC at earlier ages than previous generations [6]. Estimation of the prevalence of MCC throughout all stages of adulthood is a critical reflection of the MCC burden; it is important to examine the prevalence of MCC broadly using regularly updated data sources to inform targeted prevention and management strategies and resource prioritization.

Xintong Li, Caitlin Dreisbach, Carolina M Gustafson, Komal Patel Murali, Theresa A Koleck

JMIR Form Res 2025;9:e69138

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population–Based Study

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population–Based Study

Predictors were measured at baseline and processed according to a standardized protocol. A comprehensive and prospective data collection process was implemented, encompassing various aspects such as demographics, medical history, medical imaging, laboratory data, lifestyle habits, and outcomes. Blood pressure was measured in each participant using a mercury column sphygmomanometer, an appropriately sized cuff, and a standardized protocol to ensure accuracy and precision [17].

Thien Vu, Yoshihiro Kokubo, Mai Inoue, Masaki Yamamoto, Attayeb Mohsen, Agustin Martin-Morales, Research Dawadi, Takao Inoue, Jie Ting Tay, Mari Yoshizaki, Naoki Watanabe, Yuki Kuriya, Chisa Matsumoto, Ahmed Arafa, Yoko M Nakao, Yuka Kato, Masayuki Teramoto, Michihiro Araki

JMIR Cardio 2025;9:e68066

Digital Mental Health Interventions for Young People Aged 16-25 Years: Scoping Review

Digital Mental Health Interventions for Young People Aged 16-25 Years: Scoping Review

Reimbursement typically included monetary incentives, such as a voucher or money for completing the baseline, postintervention, and follow-up measures (47/145, 32.4%); some form of course credit for those who were studying (11/145, 7.6%); a voucher, money/gift card, or course credit (11/145, 7.6%); entry into a prize draw (4/145, 2.8%); and a voucher or money and entry into a prize draw (4/145, 2.8%).

Courtney Potts, Carmen Kealy, Jamie M McNulty, Alba Madrid-Cagigal, Thomas Wilson, Maurice D Mulvenna, Siobhan O'Neill, Gary Donohoe, Margaret M Barry

J Med Internet Res 2025;27:e72892

Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients

Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients

A Delphi methodology was decided upon as it allows us to reach a consensus of patient preferences with an iterative, anonymous, multistage approach with controlled feedback of comments and scores on a 5-point Likert scale [30,31]. The Delphi methodology recommends 3 rounds of feedback; the first round is to generate qualitative data on a topic and the remaining rounds are to gain a consensus through Likert scales [31].

Jack Lumsdon, Cameron Wilson, Lisa Alcock, Clemens Becker, Francesco Benvenuti, Tecla Bonci, Koen van den Brande, Gavin Brittain, Philip Brown, Ellen Buckley, Marco Caruso, Brian Caulfield, Andrea Cereatti, Laura Delgado-Ortiz, Silvia Del Din, Jordi Evers, Judith Garcia-Aymerich, Heiko Gaßner, Tova Gur Arieh, Clint Hansen, Jeffrey M Hausdorff, Hugo Hiden, Emily Hume, Cameron Kirk, Walter Maetzler, Dimitrios Megaritis, Lynn Rochester, Kirsty Scott, Basil Sharrack, Norman Sutton, Beatrix Vereijken, Ioannis Vogiatzis, Alison Yarnall, Alison Keogh, Alma Cantu

JMIR Form Res 2025;9:e68782

Digital Integrated Interventions for Comorbid Depression and Substance Use Disorder: Narrative Review and Content Analysis

Digital Integrated Interventions for Comorbid Depression and Substance Use Disorder: Narrative Review and Content Analysis

(computer, smartphone, internet, and text message) outside of the traditional F2 F therapy setting; and (4) the article was written in English as a peer-reviewed journal article.

Geneva K Jonathan, Qiuzuo Guo, Heyli Arcese, A Eden Evins, Sabine Wilhelm

JMIR Ment Health 2025;12:e67670

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Based on this rating of the complexity of pain symptoms, the majority (64.7%) were assessed as WPN 3 chronic pain syndrome and 35.3% as WPN 4 (maximal score), consistently showing a clear indication of psychosocial factors underlying chronic pain and disability. Most participants lived with a partner, were employed, and used pain medication.

Fredrick Zmudzki, Rob J E M Smeets, Jan S Groenewegen, Erik van der Graaff

JMIR Rehabil Assist Technol 2025;12:e65890

Evaluating the Use of a Note-Taking App by Japanese Resident Physicians: Nationwide Cross-Sectional Study

Evaluating the Use of a Note-Taking App by Japanese Resident Physicians: Nationwide Cross-Sectional Study

Note-taking during learning has long been a mainstay of educational practice and data over the last 60 years, demonstrating its contribution to improved learning and test scores [1,2]. In 1995, a study on effective note-taking among students reported that free note-taking by learners was a particularly effective process [3]. A 2002 report noted that the most effective way for medical students to perform well was to take written notes on materials prepared in advance by the teachers [4].

Taiju Miyagami, Yuji Nishizaki, Taro Shimizu, Yu Yamamoto, Kiyoshi Shikino, Koshi Kataoka, Masanori Nojima, Gautam A Deshpande, Toshio Naito, Yasuharu Tokuda

JMIR Form Res 2025;9:e55087

Mono-Professional Simulation-Based Obstetric Training in a Low-Resource Setting: Stepped-Wedge Cluster Randomized Trial

Mono-Professional Simulation-Based Obstetric Training in a Low-Resource Setting: Stepped-Wedge Cluster Randomized Trial

This led to the creation of 2 different scenarios for postpartum hemorrhage, a scenario for eclampsia, a scenario involving fetal distress with a ventouse delivery, and a breech delivery scenario. Both medical-technical and teamwork skills were included in the training, with the difficulty level increasing throughout the day. Every SHO participated in at least 2 scenarios during the 1-day training, while having an observer role in the nonparticipating scenarios.

Anne A C van Tetering, Ella L de Vries, Peter Ntuyo, E R van den Heuvel, Annemarie F Fransen, M Beatrijs van der Hout-van der Jagt, Imelda Namagembe, Josaphat Byamugisha, S Guid Oei

JMIR Med Educ 2025;11:e54911

Telenursing Health Education and Lifestyle Modification Among Patients With Diabetes in Bangladesh: Protocol for a Pilot Study With a Quasi-experimental Pre- and Postintervention Design

Telenursing Health Education and Lifestyle Modification Among Patients With Diabetes in Bangladesh: Protocol for a Pilot Study With a Quasi-experimental Pre- and Postintervention Design

A pilot study with a quasi-experimental pre- and postintervention design will be implemented. As we will try to explore the participants’ characteristics, we want to conduct a pilot study to see the feasibility of this project among these participants. We plan to conduct quasi-experimental pre- and postintervention design, as we found in this setting randomization; case-control is rather difficult.

Michiko Moriyama, K A T M Ehsanul Huq, Lucy Mondol, Akhi Roy Mita, Niru Shamsun Nahar

JMIR Res Protoc 2025;14:e71849

Use and Acceptance of Innovative Digital Health Solutions Among Patients and Professionals: Survey Study

Use and Acceptance of Innovative Digital Health Solutions Among Patients and Professionals: Survey Study

In turn, digital health can be subcategorized into a variety of dimensions. e Health (and its subset m Health) serves as a foundational category, in which health information technology plays a critical role, focusing on the management and exchange of health information through electronic health records and interoperability systems [2,3]. In the following, these definitions will be assumed for this study.

Fritz Seidl, Florian Hinterwimmer, Ferdinand Vogt, Günther M Edenharter, Karl F Braun, Rüdiger von Eisenhart-Rothe, AG Digitalisierung der DGOU, Peter Biberthaler, Dominik Pförringer

JMIR Hum Factors 2025;12:e60779