JMIR Formative Research

Although these models demonstrate high diagnostic performance, they do not differentiate between clinical subtypes, which limits their guidance on personalized treatment strategies. Additionally, ML models remain difficult to interpret directly, presenting what is known as the “black box” problem, which limits their application by clinicians. The study by Jiang et al [27] used an ML method to build a predictive model, but they did not target patients with sepsis, and the model was not externally validated.

Wei Jiang, Yaosheng Zhang, Jiayi Weng, Lin Song, Siqi Liu, Xianghui Li, Shiqi Xu, Keran Shi, Luanluan Li, Chuanqing Zhang, Jing Wang, Quan Yuan, Yongwei Zhang, Jun Shao, Jiangquan Yu, Ruiqiang Zheng

J Med Internet Res 2025;27:e62932

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Wearable Activity Tracker–Based Interventions for Physical Activity, Body Composition, and Physical Function Among Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials

Ran Li, Yangan Li, Lu Wang, Lijuan Li, Chenying Fu, Danrong Hu, Quan Wei

J Med Internet Res 2025;27:e59507

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Effect of a Telemedicine Model on Patients With Heart Failure With Reduced Ejection Fraction in a Resource-Limited Setting in Vietnam: Cohort Study

Hoai Thi Thu Nguyen, Hieu Ba Tran, Phuong Minh Tran, Hung Manh Pham, Co Xuan Dao, Thanh Ngoc Le, Loi Doan Do, Ha Quoc Nguyen, Thom Thi Vu, James Kirkpatrick, Christopher Reid, Dung Viet Nguyen

J Med Internet Res 2025;27:e67228

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Measuring Mental Health in 2 Brazilian University Centers: Protocol for a Cohort Survey

The platform provides a convenient “survey queue” for participants to access the survey questionnaires and a “to-do list” so they can keep track of their progress. This allows for the tracking of initial participation, completeness status, and longitudinal data collection for all participants. The REDCap feature best suited to address automation of the communication process and is, furthermore, better at data collection is the automated invitations.

Talita Di Santi, Ariana Gomes Nascimento, Pedro Fukuti, Vinnie Marchisio, Gian Carlo Araujo do Amaral, Camille Figueiredo Peternella Vaz, Luiz David Finotti Carrijo, Lilian Cristie de Oliveira, Luiz Octávio da Costa, Elisângela Mancini Marion Konieczniak, Luana Aparecida Zuppi Garcia, Vanessa Cristina Cabrelon Jusevicius, Eduardo de Castro Humes, Paulo Rossi Menezes, Euripedes Miguel, Arthur Caye

JMIR Res Protoc 2025;14:e63636

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Therapeutic Guidelines for the Self-Management of Major Depressive Disorder: Scoping Review

It should be noted that, regardless of the physical activity chosen, people with major depressive disorder need to make it part of their routine and do it [47] according to their tolerance and state of health [54]. An important concern in relation to physical activity for people with major depressive disorder is the fact that some of the common symptoms of depression (fatigue, lack of energy, psychomotor retardation, despair, and feelings of worthlessness) interfere with the motivation to exercise [57].

Priscila de Campos Tibúrcio, Priscila Maria Marcheti, Daniela Miori Pascon, Marco Antônio Montebello Junior, Maria Alzete de Lima, Carla Sílvia Fernandes, Célia Samarina Vilaça de Brito Santos, Maria do Perpétuo Socorro de Sousa Nóbrega

Interact J Med Res 2025;14:e63959

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Codevelopment of an mHealth App With Health Care Providers, Digital Health Experts, Community Partners, and Families for Childhood Obesity Management: Protocol for a Co-Design Process

Despite research showing that parents are an integral part of pediatric obesity prevention and treatment, the currently available apps do not target parents or families but focus solely on the child. A review of m Health apps for pediatric obesity prevention and treatment also found that most apps lacked any expert recommendations. m Health apps have also been found to lack a theoretical basis for their development, thereby limiting their efficacy [19].

Siao Hui Toh, Courtney Davis, Khairunisa Bte Khaider, Zhi Quan Ong, Ethel Jie Kai Lim, Chu Shan Elaine Chew

JMIR Res Protoc 2025;14:e59238

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Current Status and Future Directions of Ferroptosis Research in Breast Cancer: Bibliometric Analysis

Jia-Yuan Luo, Yu-Long Deng, Shang-Yi Lu, Si-Yan Chen, Rong-Quan He, Di-Yuan Qin, Bang-Teng Chi, Gang Chen, Xia Yang, Wei Peng

Interact J Med Res 2025;14:e66286

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Use of Digital Health Technologies for Dementia Care: Bibliometric Analysis and Report

First, narrative reviews are highly prone to selection bias, as they typically do not systematically cover all relevant studies. Similarly, integrative reviews often lack the rigorous, standardized search and inclusion criteria that are fundamental to systematic and scoping reviews [16,17]. Therefore, we excluded these types of publications to minimize potential inconsistencies and biases that could compromise the validity of our bibliometric analysis. [16,17].

Hebatullah Abdulazeem, Israel Júnior Borges do Nascimento, Ishanka Weerasekara, Amin Sharifan, Victor Grandi Bianco, Ciara Cunningham, Indunil Kularathne, Genevieve Deeken, Jerome de Barros, Brijesh Sathian, Lasse Østengaard, Frederique Lamontagne-Godwin, Joost van Hoof, Ledia Lazeri, Cassie Redlich, Hannah R Marston, Ryan Alistair Dos Santos, Natasha Azzopardi-Muscat, Yongjie Yon, David Novillo-Ortiz