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Competency of Large Language Models in Evaluating Appropriate Responses to Suicidal Ideation: Comparative Study

Competency of Large Language Models in Evaluating Appropriate Responses to Suicidal Ideation: Comparative Study

While such referrals may be beneficial, they also artificially circumscribed interactions in a way that could be taken as a missed opportunity. There are several important study limitations to note. First, LLM technologies are constantly evolving. This study offers a snapshot of LLM performance in July 2024. Second, we selected the SIRI-2 as an evaluative tool because it is widely used; however, alternative instruments could result in different findings.

Ryan K McBain, Jonathan H Cantor, Li Ang Zhang, Olesya Baker, Fang Zhang, Alyssa Halbisen, Aaron Kofner, Joshua Breslau, Bradley Stein, Ateev Mehrotra, Hao Yu

J Med Internet Res 2025;27:e67891

Unraveling Online Mental Health Through the Lens of Early Maladaptive Schemas: AI-Enabled Content Analysis of Online Mental Health Communities

Unraveling Online Mental Health Through the Lens of Early Maladaptive Schemas: AI-Enabled Content Analysis of Online Mental Health Communities

These models can capture subtle meanings in textual discourse, such as recognizing that the phrase “dark tunnel” in “I just feel like I’m stuck in a dark tunnel, and there’s no way out” metaphorically conveys despair, isolation, and hopelessness [33]. LLMs have also been used to predict mental health problems, such as depression, from online conversations [34-38] and have recently been applied to predict EMSs in OMHC posts [16].

Beng Heng Ang, Sujatha Das Gollapalli, Mingzhe Du, See-Kiong Ng

J Med Internet Res 2025;27:e59524

Spaced Digital Education for Health Professionals: Systematic Review and Meta-Analysis

Spaced Digital Education for Health Professionals: Systematic Review and Meta-Analysis

An important strategy to increase recruitment and retention of health care workers is providing high-quality education in an affordable, effective, and sustainable way [5]. Digital education is “the act of teaching and learning by means of digital technologies” [6]. Digital education may promote continuous professional development and improve health care workers’ competencies by offering convenient and adaptable learning tools that can be accessed at any place and time [6-10].

Laura Martinengo, Matthew Song Peng Ng, Tony De Rong Ng, Yi-Ian Ang, Ahmad Ishqi Jabir, Bhone Myint Kyaw, Lorainne Tudor Car

J Med Internet Res 2024;26:e57760

A Nationwide Physical Activity Intervention for 654,500 Adults in Singapore: Cost-Utility Analysis

A Nationwide Physical Activity Intervention for 654,500 Adults in Singapore: Cost-Utility Analysis

Scenario analysis, one-way deterministic sensitivity analysis, deterministic threshold sensitivity analysis, and probabilistic sensitivity analysis were done to assess the robustness of our model results in the base case to changes in key parameters over plausible ranges. All analyses were conducted in R version 4.1.2 (R Foundation for Statistical Computing). We examined the differentiation of cost among different physical activity levels within each health state.

Gregory Ang, Chuen Seng Tan, Yot Teerawattananon, Falk Müller-Riemenschneider, Cynthia Chen

JMIR Public Health Surveill 2024;10:e46178

Comparing Human-Smartphone Interactions and Actigraphy Measurements for Circadian Rhythm Stability and Adiposity: Algorithm Development and Validation Study

Comparing Human-Smartphone Interactions and Actigraphy Measurements for Circadian Rhythm Stability and Adiposity: Algorithm Development and Validation Study

In recent years, digital footprints, such as human-smartphone interactions, have emerged as a new way to observe human circadian rhythms [11,12]. Real-time, passively collected data from these interactions can provide long-term recordings of circadian rhythms in a natural setting, potentially offering an alternative to actigraphy.

Hai-Hua Chuang, Chen Lin, Li-Ang Lee, Hsiang-Chih Chang, Guan-Jie She, Yu-Hsuan Lin

J Med Internet Res 2024;26:e50149

Risk Perception, Acceptance, and Trust of Using AI in Gastroenterology Practice in the Asia-Pacific Region: Web-Based Survey Study

Risk Perception, Acceptance, and Trust of Using AI in Gastroenterology Practice in the Asia-Pacific Region: Web-Based Survey Study

One such recent example is the survey on gastrointestinal (GI) health care in 2022, which covered clinicians’ perspectives in a general way [13]. However, such surveys lack granularity. It is impossible to know under what circumstances do clinicians become less trusting or accepting or become more concerned about the deployments of AI. Moreover, there is a lack of explicit modeling from collected data to relate patterns of risk perception, acceptance, and trust among practitioners.

Wilson WB Goh, Kendrick YA Chia, Max FK Cheung, Kalya M Kee, May O Lwin, Peter J Schulz, Minhu Chen, Kaichun Wu, Simon SM Ng, Rashid Lui, Tiing Leong Ang, Khay Guan Yeoh, Han-mo Chiu, Deng-chyang Wu, Joseph JY Sung

JMIR AI 2024;3:e50525