When machine meets mind: A two-stage literature review on AI applications in mental health research

Mental health problems have brought a serious impact on people’s quality of life and health. With the development of technology, the emerging technologies such as artificial intelligence (AI) (combined with Big Data) has the potential to become new means of intervening in mental illness. This study analyzes the abstracts of the relevant literature involving the applications of AI in the field of mental health through dynamic topic modelling. Nine main research topics are extracted and analyzed. Then we identify current research hotspots and possible future directions by analyzing the evolutionary trends of these topics over time. In the future, the representative literature will be searched and reviewed based on the extracted topics to comprehensively and deeply explore the applications status and potential of these technologies in the field of mental health.

Publication Details

Journal
Journal of the Association for Information Systems
Published
2024-12-01
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

When machine meets mind: A two-stage literature review on AI applications in mental health research

Journal of the Association for Information Systems
Mental Health via Writing
article

When machine meets mind: A two-stage literature review on AI applications in mental health research

article en

Abstract

Mental health problems have brought a serious impact on people’s quality of life and health. With the development of technology, the emerging technologies such as artificial intelligence (AI) (combined with Big Data) has the potential to become new means of intervening in mental illness. This study analyzes the abstracts of the relevant literature involving the applications of AI in the field of mental health through dynamic topic modelling. Nine main research topics are extracted and analyzed. Then we identify current research hotspots and possible future directions by analyzing the evolutionary trends of these topics over time. In the future, the representative literature will be searched and reviewed based on the extracted topics to comprehensively and deeply explore the applications status and potential of these technologies in the field of mental health.

Journal of the Association for Information Systems
Openalex Percentile: Top 42%
Mental Health via Writing
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.