Objective: Peer victimization is linked to psychological distress, but some youth are less affected than others. Identifying protective factors can inform prevention programs. Using longitudinal data from 7 graders we tested the role of social intelligence as a protective factor in the relation between peer victimization and depressive symptoms.
Method: Students ( = 986; 54% female; 43% non-white) from three schools provided self-report data via computer-assisted survey interviews in the fall (Time 1, T1) and spring (Time 2, T2) of 7 grade.
Results: Females reported more depressive symptoms and less physical victimization than males but did not differ from males on social intelligence or relational victimization. Regression analyses controlling for T1 depressive symptoms and other potential confounds revealed that both physical and relational victimization were positively and significantly associated with T2 depressive symptoms, but the strength of the relation varied by gender and by social intelligence. Specifically, the associations between victimization and depressive symptoms were stronger among females than males and among those with low or moderate rather than high social intelligence.
Conclusions: Social intelligence may protect youth from the psychological harms of peer victimization and could be an effective target of prevention programming.
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http://dx.doi.org/10.1037/vio0000234 | DOI Listing |
J Med Internet Res
January 2025
Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.
View Article and Find Full Text PDFInteract J Med Res
January 2025
Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background: Incorporating artificial intelligence (AI) into medical education has gained significant attention for its potential to enhance teaching and learning outcomes. However, it lacks a comprehensive study depicting the academic performance and status of AI in the medical education domain.
Objective: This study aims to analyze the social patterns, productive contributors, knowledge structure, and clusters since the 21st century.
JMIR Infodemiology
January 2025
Salzburg University of Applied Sciences, Puch/Salzburg, Austria.
Background: The novel coronavirus disease (COVID-19) sparked significant health concerns worldwide, prompting policy makers and health care experts to implement nonpharmaceutical public health interventions, such as stay-at-home orders and mask mandates, to slow the spread of the virus. While these interventions proved essential in controlling transmission, they also caused substantial economic and societal costs and should therefore be used strategically, particularly when disease activity is on the rise. In this context, geosocial media posts (posts with an explicit georeference) have been shown to provide a promising tool for anticipating moments of potential health care crises.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Engineering Management and Systems Engineering, George Washington University, Washington, DC, United States.
Background: Large language model (LLM) artificial intelligence chatbots using generative language can offer smoking cessation information and advice. However, little is known about the reliability of the information provided to users.
Objective: This study aims to examine whether 3 ChatGPT chatbots-the World Health Organization's Sarah, BeFreeGPT, and BasicGPT-provide reliable information on how to quit smoking.
JMIR Med Educ
January 2025
College of Medicine, Alfaisal University, Takhasussi street, Riyadh, 11533, Saudi Arabia, 966 559441589.
Background: There has been a rise in the popularity of ChatGPT and other chat-based artificial intelligence (AI) apps in medical education. Despite data being available from other parts of the world, there is a significant lack of information on this topic in medical education and research, particularly in Saudi Arabia.
Objective: The primary objective of the study was to examine the familiarity, usage patterns, and attitudes of Alfaisal University medical students toward ChatGPT and other chat-based AI apps in medical education.
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