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Longitudinal Associations Between Adolescents’ mHealth App Use, Body Dissatisfaction, and Physical Self-Worth: Random Intercept Cross-Lagged Panel Study

Longitudinal Associations Between Adolescents’ mHealth App Use, Body Dissatisfaction, and Physical Self-Worth: Random Intercept Cross-Lagged Panel Study

We examined whether changes in the m Health app use of an adolescent resulted in changes in body dissatisfaction and physical self-worth of the same adolescent 6 months later. We also examined the reciprocal effects and determined whether individual changes in body dissatisfaction and physical self-worth influenced the m Health app use of the same adolescent 6 months later.

Hayriye Gulec, Michal Muzik, David Smahel, Lenka Dedkova

JMIR Ment Health 2025;12:e60844

Health Information Scanning and Seeking in Diverse Language, Cultural and Technological Media Among Latinx Adolescents: Cross-Sectional Study

Health Information Scanning and Seeking in Diverse Language, Cultural and Technological Media Among Latinx Adolescents: Cross-Sectional Study

Current reports depict an adolescent mental health crisis in the United States. About 1 in 5 adolescents experience poor mental health, especially race and ethnic minoritized adolescents [1-6]. In 2021, the US Surgeon General stated that the COVID-19 pandemic further altered adolescents’ experiences at home, school, and the community, which generated devastating effects on their mental health [7].

Melissa J DuPont-Reyes, Alice P Villatoro, Lu Tang

J Med Internet Res 2025;27:e64672

Current Landscape and Future Directions for Mental Health Conversational Agents for Youth: Scoping Review

Current Landscape and Future Directions for Mental Health Conversational Agents for Youth: Scoping Review

Our final search string consisted of the following keywords: (“conversational agent” OR “chatbot” OR “virtual agent” OR “virtual assistant” OR “AI assistant” OR “AI bot” OR “social bot”) AND (teen OR adolescent OR youth OR young) AND (mental). Then, we identified 4 relevant and cross-disciplinary databases that included research on CAs in the health care domain, including Pro Quest, Scopus, Web of Science, and Pub Med. The same search string was used to retrieve articles across the 4 databases.

Jinkyung Katie Park, Vivek K Singh, Pamela Wisniewski

JMIR Med Inform 2025;13:e62758

Provider Perspectives on the Use of Mental Health Apps, and the BritePath App in Particular, With Adolescents at Risk for Suicidal Behavior: Qualitative Study

Provider Perspectives on the Use of Mental Health Apps, and the BritePath App in Particular, With Adolescents at Risk for Suicidal Behavior: Qualitative Study

Adolescent suicidal behavior, suicide ideation, and depression are major public health problems that have increased significantly over the past 20 years [1-3] and have been exacerbated by the COVID-19 pandemic and its sequelae [4-8]. For example, between 2019 and 2021, the number of female high school students reporting that they had seriously considered attempting suicide increased by 6% [3].

Frances Lynch, Julie Cavese, Lucy Fulton, Nancy Vuckovic, David Brent

JMIR Hum Factors 2025;12:e64867

Comparing Digital Versus Face-to-Face Delivery of Systemic Psychotherapy Interventions: Systematic Review and Meta-Analysis of Randomized Controlled Trials

Comparing Digital Versus Face-to-Face Delivery of Systemic Psychotherapy Interventions: Systematic Review and Meta-Analysis of Randomized Controlled Trials

Includes family members and other important persons (eg, teachers, friends, professional helpers) directly or indirectly through systemic questioning, hypothesizing, and specific interventions All CPPs are delivered to the caregiver-adolescent dyad. Appreciates and uses clients’ perspectives on problems, resources, and preferred solutions: 2 of 4 CPPs are as follows: CPP1 and CPP3: cognitive restructuring (addressing beliefs, attitudes, and attributions that could negatively affect effective interactions).

Pieter Erasmus, Moritz Borrmann, Jule Becker, Lars Kuchinke, Gunther Meinlschmidt

Interact J Med Res 2025;14:e46441

Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study

Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study

Conventional statistical methods have long been used to examine the predictors and outcomes of adolescent substance use [4]. However, these approaches often fall short in capturing complex, nonlinear relationships between variables. Therefore, with recent advancements, machine learning (ML) has introduced powerful tools capable of identifying complex patterns and relationships, offering a deeper understanding of adolescent substance use [5].

Soeun Kim, Hyejun Kim, Seokjun Kim, Hojae Lee, Ahmed Hammoodi, Yujin Choi, Hyeon Jin Kim, Lee Smith, Min Seo Kim, Guillaume Fond, Laurent Boyer, Sung Wook Baik, Hayeon Lee, Jaeyu Park, Rosie Kwon, Selin Woo, Dong Keon Yon

J Med Internet Res 2025;27:e62805

Association Among BMI, Self-Esteem, and Nonsuicidal Self-Injury in Young Adults to Understand the Influence of Socioenvironmental Factors: Longitudinal Study

Association Among BMI, Self-Esteem, and Nonsuicidal Self-Injury in Young Adults to Understand the Influence of Socioenvironmental Factors: Longitudinal Study

With the change in social living environment, adolescents are facing increasing pressure and challenges, and adolescent NSSI has become a problem that cannot be ignored. NSSI is a common mental health problem among adolescents [32]. In a college student–related survey, approximately 1 in 5 (20.4%) students reported lifelong NSSI, and the frequency of persistent NSSI was estimated at 56.4%, with 15.6% of students reporting high-frequency repeat patterns (≥5 times per year) [33].

Yi Zhang, Ruixue Ying, Wan Lu, Xuemeng Liu, Keyan Hu, Qing Feng, Zixiang Yu, Zhen Wang, Fangting Lu, Yahu Miao, Nanzhen Ma, Fangbiao Tao, Tian Jiang, Qiu Zhang

JMIR Public Health Surveill 2025;11:e52928