Negative Effects of Fitness Apps on Users
Fitness apps may have negative effects on users, leading to feelings of shame and disengagement. πββοΈπ
November 12, 2025
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Discover the newest research about AI innovations in π§ Mental Health.
A Prompt Engineering Framework for Large Language Model-Based Mental Health Chatbots: Conceptual Framework.
Exploring MIND-SAFE: A Framework for Ethical AI in Mental Health Chatbots π€π§
November 8, 2025
Challenges and opportunities of psychological aging research.
Exploring psychological aging: challenges, interdisciplinary approaches, and tech advancements for better understanding. ππ§
November 5, 2025
Multidisciplinary perspectives on personalised prevention in youth mental health.
Exploring AI’s Role in Youth Mental Health: Multidisciplinary Insights on Personalized Prevention Strategies π€π§
November 4, 2025
[Psychiatry in the digital age: technological revolution and ethical challenges].
Digital psychiatry evolves with AI, enhancing care access but raising ethical concerns. Balance is crucial for effective treatment. π€π§
November 2, 2025
Evaluation of Alignment Between Large Language Models and Expert Clinicians in Suicide Risk Assessment.
Chatbots’ responses to suicide risk queries show alignment with expert clinicians at extremes but inconsistencies in intermediate risks. ππ€
November 1, 2025
Uncovering predictors of bipolar II conversion to bipolar I: A machine learning analysis of national health records in Taiwan.
Predicting bipolar II to I conversion: 14% risk identified using machine learning with 86% accuracy. ππ§
October 26, 2025
Performance of Automatic Speech Analysis in Detecting Depression: Systematic Review and Meta-Analysis.
Automatic Speech Analysis shows 81% accuracy in detecting depression, highlighting its potential as a complementary diagnostic tool. ππ£οΈ
October 23, 2025
A Window Into Vulnerability and Support: At-Risk Mothers’ Perinatal Experiences and Perspectives on mHealth-Based Care.
Exploring mHealth’s Role in Supporting At-Risk Mothers’ Perinatal Experiences π±π€±
October 20, 2025
Prediction of suicidal ideation and depression in the general population with subthreshold insomnia using machine learning models.
Machine learning models effectively predict suicidal ideation and depression in insomnia patients. Study shows AUROC scores of 0.78-0.82. ππ§
October 19, 2025