AIMC Topic: Mental Health

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Safety and User Experience of a Generative Artificial Intelligence Digital Mental Health Intervention: Exploratory Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: General awareness and exposure to generative artificial intelligence (AI) have increased recently. This transformative technology has the potential to create a more dynamic and engaging user experience in digital mental health interventio...

Utilising Machine Learning for Better Mental Health and Decision Making: A Case Study of Timebanking UK.

Studies in health technology and informatics
This study explores how the integration of predictive models with machine learning and natural language processing can optimise community-based service operations, using Timebanking UK as a case study. The research evaluated these models in terms of ...

Evaluating Generative AI in Mental Health: Systematic Review of Capabilities and Limitations.

JMIR mental health
BACKGROUND: The global shortage of mental health professionals, exacerbated by increasing mental health needs post COVID-19, has stimulated growing interest in leveraging large language models to address these challenges.

Effectiveness of AI-Driven Conversational Agents in Improving Mental Health Among Young People: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: The increasing prevalence of mental health issues among adolescents and young adults, coupled with barriers to accessing traditional therapy, has led to growing interest in artificial intelligence (AI)-driven conversational agents (CAs) a...

Combining Artificial Intelligence and Human Support in Mental Health: Digital Intervention With Comparable Effectiveness to Human-Delivered Care.

Journal of medical Internet research
BACKGROUND: Escalating mental health demand exceeds existing clinical capacity, necessitating scalable digital solutions. However, engagement remains challenging. Conversational agents can enhance engagement by making digital programs more interactiv...

Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies.

JMIR public health and surveillance
BACKGROUND: Converging evidence indicates an adolescent mental health crisis in Western societies that has developed and exacerbated over the past decade. The proposed driving factors of this trend include more screen time, physical inactivity, and s...

Machine learning-based predictive modelling of mental health in Rwandan Youth.

Scientific reports
Globally, mental disorders are a significant burden, particularly in low- and middle-income countries, with high prevalence in Rwanda, especially among survivors of the 1994 genocide against Tutsi. Machine learning offers promise in predicting mental...

Key Predictors of Generativity in Adulthood: A Machine Learning Analysis.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: This study aimed to explore a broad range of predictors of generativity in older adults. The study included over 60 predictors across multiple domains, including personality, daily functioning, socioeconomic factors, health status, and me...

Virtual reality and artificial intelligence: the future of mental health. A narrative review.

Recenti progressi in medicina
In recent years, the use of artificial intelligence (AI) and virtual reality (VR) in the psychiatric field has been rapidly developing. This narrative review seeks to provide insight into how these technologies may be used in psychiatric disorders. V...

Effects of artificial intelligence and virtual reality interventions in art therapy among older people with mild cognitive impairment.

Australasian journal on ageing
OBJECTIVES: Integrating artificial intelligence and virtual reality into an art health program, this study aimed to compare the effects of artificial intelligence (AI) intervention in art therapy, virtual reality (VR) intervention in art therapy and ...