AIMC Topic: Mental Health

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Physical and mental health management for the older adult using XGBoost algorithm supported by new media technology: developing personalized health intervention plans using healthcare data from the CLHLS database.

Frontiers in public health
INTRODUCTION: With the increasing aging population, there is a growing need for precise and intelligent health management solutions tailored to older adult individuals. This study proposes a comprehensive digital health management platform that integ...

Needs and Preferences of Swedish Young Adults for a Digital App Promoting Mental Health Literacy, Occupational Balance, and Peer Support: Qualitative Interview Study.

JMIR formative research
BACKGROUND: Young adults experience stressors in their transition to adulthood and are at increased risk of mental ill-health. This risk is compounded by young adults' low levels of mental health literacy and limited competencies in implementing stra...

The Applications of Large Language Models in Mental Health: Scoping Review.

Journal of medical Internet research
BACKGROUND: Mental health is emerging as an increasingly prevalent public issue globally. There is an urgent need in mental health for efficient detection methods, effective treatments, affordable privacy-focused health care solutions, and increased ...

Game Design, Effectiveness, and Implementation of Serious Games Promoting Aspects of Mental Health Literacy Among Children and Adolescents: Systematic Review.

JMIR mental health
BACKGROUND: The effects of traditional health-promoting and preventive interventions in mental health and mental health literacy are often attenuated by low adherence and user engagement. Gamified approaches such as serious games (SGs) may be useful ...

Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach.

Journal of medical Internet research
BACKGROUND: Perinatal depression and anxiety significantly impact maternal and infant health, potentially leading to severe outcomes like preterm birth and suicide. Aboriginal women, despite their resilience, face elevated risks due to the long-term ...

Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study.

JMIR mHealth and uHealth
BACKGROUND: Considering the high prevalence of mental health conditions among young people and the technological advancements of artificial intelligence (AI)-based approaches in health services, mobile health (mHealth) apps for mental health are a pr...

Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: Recent years have seen an immense surge in the creation and use of chatbots as social and mental health companions. Aiming to provide empathic responses in support of the delivery of personalized support, these tools are often presented a...

Exploring mental health literacy on twitter: A machine learning approach.

Journal of affective disorders
OBJECTIVES: This study investigates whether reducing mental illness stigma, enhancing help-seeking efficacy, and maintaining positive mental health mediate the relationship between the recognition of mental disorders and help-seeking attitudes.

Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic.

Scientific reports
Suicide causes over 700,000 deaths annually worldwide. Mental disorders are closely linked to suicidal ideation, but predicting suicide remains complex due to the multifaceted nature of contributing factors. Traditional assessment tools often fail to...

Extreme Weather, Vulnerable Populations, and Mental Health: The Timely Role of AI Interventions.

International journal of environmental research and public health
Environmental disasters are becoming increasingly frequent and severe, disproportionately impacting vulnerable populations who face compounded risks due to intersectional factors such as gender, socioeconomic status, rural residence, and cultural ide...