AI Use for Mental Health Information and Professional Psychological Help-Seeking Intentions Among Saudi Women: A Cross-Sectional Study

Mental health concerns remain a major public health challenge, while artificial intelligence (AI)-based tools are increasingly used to obtain mental health-related information. However, little is known about the relationship between AI use and professional psychological help-seeking intentions, particularly among Saudi women. This cross-sectional study examined this association among 134 Saudi women aged 18 years and older recruited through social media platforms. An online questionnaire assessed AI use for mental health information, confidence in AI-provided information, perceived barriers to professional help-seeking, and professional psychological help-seeking intentions. Data were analyzed using descriptive statistics, Pearson correlation, and multiple regression. AI use was negatively correlated with professional psychological help-seeking intentions (r = −0.45, p < 0.001). Multiple regression analysis showed that greater AI use and higher perceived barriers were associated with lower professional psychological help-seeking intentions, whereas confidence in AI-provided information was not significantly associated with help-seeking intentions. These findings provide preliminary evidence of an association between AI use and professional psychological help-seeking intentions but do not establish causality. Given the cross-sectional design and smaller-than-planned sample, the findings should be interpreted cautiously. Larger longitudinal studies are needed to clarify this relationship and examine actual help-seeking behavior.

Authors

Institutions

Publication Details

Journal
Behavioral Sciences
Published
2026-09-14
DOI
https://doi.org/10.3390/bs16091642
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
article

AI Use for Mental Health Information and Professional Psychological Help-Seeking Intentions Among Saudi Women: A Cross-Sectional Study

Nawal Alissa
Behavioral Sciences
Digital Mental Health Interventions
article

AI Use for Mental Health Information and Professional Psychological Help-Seeking Intentions Among Saudi Women: A Cross-Sectional Study

Nawal Alissa
article en

Abstract

Mental health concerns remain a major public health challenge, while artificial intelligence (AI)-based tools are increasingly used to obtain mental health-related information. However, little is known about the relationship between AI use and professional psychological help-seeking intentions, particularly among Saudi women. This cross-sectional study examined this association among 134 Saudi women aged 18 years and older recruited through social media platforms. An online questionnaire assessed AI use for mental health information, confidence in AI-provided information, perceived barriers to professional help-seeking, and professional psychological help-seeking intentions. Data were analyzed using descriptive statistics, Pearson correlation, and multiple regression. AI use was negatively correlated with professional psychological help-seeking intentions (r = −0.45, p < 0.001). Multiple regression analysis showed that greater AI use and higher perceived barriers were associated with lower professional psychological help-seeking intentions, whereas confidence in AI-provided information was not significantly associated with help-seeking intentions. These findings provide preliminary evidence of an association between AI use and professional psychological help-seeking intentions but do not establish causality. Given the cross-sectional design and smaller-than-planned sample, the findings should be interpreted cautiously. Larger longitudinal studies are needed to clarify this relationship and examine actual help-seeking behavior.

Behavioral SciencesVol. 16(9)
King Saud University (SA)
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.

AI Use for Mental Health Information and Professional Psychological Help-Seeking Intentions Among Saudi Women: A Cross-Sectional Study — Nawal Alissa · Behavioral Sciences (2026) | TGRS Research Map | TGRS