Artificial Intelligence in Mental Health Support: Opportunities, Applications, and Ethical Challenges

Mental health conditions have become one of the most urgent public health challenges worldwide, affecting nearly one billion people and creating substantial social and economic burdens. Despite increasing demand for psychological services, barriers such as financial costs, shortages of mental health professionals, geographical inequalities, and social stigma prevent many individuals from receiving timely support. This paper examines the biological, psychological, and environmental factors contributing to mental disorders and evaluates the potential role of artificial intelligence (AI) conversational models in mental health support. It argues that AI cannot replace licensed clinicians but can serve as a complementary tool by improving accessibility, providing continuous communication, offering privacy, and delivering personalized psychoeducation. Particular attention is given to autism spectrum disorder (ASD), where AI's predictable communication style may support communication practice and reduce social pressure. The paper also discusses AI-assisted interventions based on cognitive behavioral therapy (CBT) and examines ethical challenges, including privacy, algorithmic bias, and clinical responsibility. Overall, responsible cooperation between AI technologies and healthcare professionals may improve the accessibility and effectiveness of future mental healthcare.

Authors

Publication Details

Journal
Lecture Notes in Education Psychology and Public Media
Published
2026-10-27
DOI
https://doi.org/10.54254/2753-7048/2026.pe38327
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence in Mental Health Support: Opportunities, Applications, and Ethical Challenges

Zengchen Wang
2 links
Lecture Notes in Education Psychology and Public Media
Digital Mental Health Interventions
article

Artificial Intelligence in Mental Health Support: Opportunities, Applications, and Ethical Challenges

Zengchen Wang
article en

Abstract

Mental health conditions have become one of the most urgent public health challenges worldwide, affecting nearly one billion people and creating substantial social and economic burdens. Despite increasing demand for psychological services, barriers such as financial costs, shortages of mental health professionals, geographical inequalities, and social stigma prevent many individuals from receiving timely support. This paper examines the biological, psychological, and environmental factors contributing to mental disorders and evaluates the potential role of artificial intelligence (AI) conversational models in mental health support. It argues that AI cannot replace licensed clinicians but can serve as a complementary tool by improving accessibility, providing continuous communication, offering privacy, and delivering personalized psychoeducation. Particular attention is given to autism spectrum disorder (ASD), where AI's predictable communication style may support communication practice and reduce social pressure. The paper also discusses AI-assisted interventions based on cognitive behavioral therapy (CBT) and examines ethical challenges, including privacy, algorithmic bias, and clinical responsibility. Overall, responsible cooperation between AI technologies and healthcare professionals may improve the accessibility and effectiveness of future mental healthcare.

Lecture Notes in Education Psychology and Public MediaVol. 155(1)
Good health and well-being, Reduced inequalities
Openalex Percentile: Top 9%
Digital Mental Health Interventions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon