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Increasing Access to Mental Health Supports for 18- to 25-Year-Old Indigenous Youth With the JoyPop Mobile Mental Health App: Study Protocol for a Randomized Controlled Trial.
JMIR Res Protoc
January 2025
Department of Psychology, Lakehead University, Thunder Bay, ON, Canada.
Background: Transitional-aged youth have a high burden of mental health difficulties in Canada, with Indigenous youth, in particular, experiencing additional circumstances that challenge their well-being. Mobile health (mHealth) approaches hold promise for supporting individuals in areas with less access to services such as Northern Ontario.
Objective: The primary objective of this study is to evaluate the effectiveness of the JoyPop app in increasing emotion regulation skills for Indigenous transitional-aged youth (aged 18-25 years) on a waitlist for mental health services when compared with usual practice (UP).
At least four groups of kratom consumers in the United States: latent-class analysis of motivations for kratom use.
Am J Drug Alcohol Abuse
January 2025
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Kratom is a plant with alkaloids acting at opioid, serotonergic, adrenergic, and other receptors. Consumers report numerous use motivations. To distinguish subgroups of kratom consumers by kratom-use motivations using latent-class analysis.
View Article and Find Full Text PDFUser-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.
JMIR Res Protoc
January 2025
Institute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.
View Article and Find Full Text PDFGeosocial Media's Early Warning Capabilities Across US County-Level Political Clusters: Observational Study.
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 PDFAssessing the Adherence of ChatGPT Chatbots to Public Health Guidelines for Smoking Cessation: Content Analysis.
J 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.
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