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The Digital Library of Health Care Consultations and Simulated Health Care Student Teaching: Protocol for a Repository of Recordings to Support Communication Research

The Digital Library of Health Care Consultations and Simulated Health Care Student Teaching: Protocol for a Repository of Recordings to Support Communication Research

Participants are invited via an online consumer platform at the National Centre for Healthy Ageing as well as public announcements at National Centre for Healthy Ageing events. There are no exclusion criteria for health care narrative participants.

Elizabeth Ann Sturgiss, Kimberley Norman, Terry Haines, Katrina Long, Suzanne Nielsen, Jenny Sim, Aron Shlonsky, Brendan Shannon, Cylie Williams

JMIR Res Protoc 2025;14:e67910

Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study

Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study

In 2019, the revised version of this tool Ro B2 was released to address limitations of the previous version, such as inconsistent domain use and the lack of an overall judgment domain. Ro B2 evaluates potential biases from the randomization process, deviations from intended interventions, missing data, measurement of the outcomes, selection of the reported results, and overall bias.

Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

J Med Internet Res 2025;27:e70450

Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis

Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis

Simulating an outcome given an observed baseline state is performed by setting each baseline node with the values of the observed baseline state and then simulating the follow-up state. This corresponds to doing “nothing” below, which is shorthand for simulating a follow-up state given no intervention. The interventional do-operation is used to simulate outcomes given idealized interventions.

Mathew Varidel, Victor An, Ian B Hickie, Sally Cripps, Roman Marchant, Jan Scott, Jacob J Crouse, Adam Poulsen, Bridianne O'Dea, Sarah McKenna, Frank Iorfino

J Med Internet Res 2025;27:e71305

Association Between the Parenting Competence and Quality of Life of Family Caregivers of Children Aged 0-3 Years: Cross-Sectional Study

Association Between the Parenting Competence and Quality of Life of Family Caregivers of Children Aged 0-3 Years: Cross-Sectional Study

Consequently, an initial sample size of 70 to 140 participants is suggested. To accommodate a potential 10% loss of samples and the presence of invalid questionnaires, the minimum sample size should be adjusted to range from 77 to 154 participants. In this study, a total of 300 questionnaires were disseminated; 9 of them were excluded due to incomplete questionnaires.

Wei He, Le-shan Zhou, Long-yi Hu

JMIR Pediatr Parent 2025;8:e67872

Artificial Intelligence–Based Mobile Phone Apps for Child Mental Health: Comprehensive Review and Content Analysis

Artificial Intelligence–Based Mobile Phone Apps for Child Mental Health: Comprehensive Review and Content Analysis

This allows for a tailored intervention, optimizing the support offered based on an objective analysis of user data. Growing up in the digital era, children are inherently familiar with digital devices such as smartphones and tablets [12,13]. These tools offer an intuitive and user-friendly interface, eliminating complexities or abstract concepts and reducing potential barriers for younger users [13].

Fan Yang, Jianan Wei, Xuejun Zhao, Ruopeng An

JMIR Mhealth Uhealth 2025;13:e58597

Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models

Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models

Despite the diminishing immediate threat of COVID-19, the ongoing risks associated with long COVID and reinfection make it important to retain public attention on COVID-19–related policies and information. The challenges of fake news and misinformation persist as the world transitions into a postpandemic era coexisting with the virus. Specifically, issues related to long COVID and reinfection continue to be crucial points for misinformation.

Jian-An Chen, Wu-Chun Chung, Che-Lun Hung, Chun-Ying Wu

J Med Internet Res 2025;27:e73601

Effects of Digital Sleep Interventions on Sleep Among College Students and Young Adults: Systematic Review and Meta-Analysis

Effects of Digital Sleep Interventions on Sleep Among College Students and Young Adults: Systematic Review and Meta-Analysis

These include poor dietary habits, obesity [9], and an increased risk of mental health problems (eg, depression, suicidal behavior, and substance abuse) [10-13]. Furthermore, insufficient sleep adversely affects academic performance and may lead to a need for prolonged years of study [14]. Poor sleep in college students and young adults can also contribute to long-term sleep disturbances that may persist into adulthood [15].

Yi-An Lu, Hui-Chen Lin, Pei-Shan Tsai

J Med Internet Res 2025;27:e69657

Co-Designing, Developing, and Testing a Mental Health Platform for Young People Using a Participatory Design Methodology in Colombia: Mixed Methods Study

Co-Designing, Developing, and Testing a Mental Health Platform for Young People Using a Participatory Design Methodology in Colombia: Mixed Methods Study

This user-driven methodology not only enhances usability but also fosters long-term engagement, ensuring that the technology remains relevant and effectively integrated into everyday practice [17]. Colombia is an upper–middle-income country [18] that faces many societal and economic challenges, further exacerbated by the COVID-19 pandemic [18]. The latest MH survey indicates that 26.5% of adolescents and 26.2% of adults aged 18 to 44 years are likely to experience >2 MH problems [19].

Laura Ospina-Pinillos, Débora L Shambo-Rodríguez, Mónica Natalí Sánchez-Nítola, Alexandra Morales, Laura C Gallego-Sanchez, María Isabel Riaño-Fonseca, Andrea Carolina Bello-Tocancipá, Alvaro Navarro-Mancilla, Jaime A Pavlich-Mariscal, Alexandra Pomares-Quimbaya, Carlos Gómez-Restrepo, Ian B Hickie, Jo-An Occhipinti

JMIR Hum Factors 2025;12:e66558