Association between Conversational AI Usage and Depressive Symptoms among Young Adults in West Bengal: A Cross-sectional Study

Abstract

Background: Conversational artificial intelligence (AI) tools have become increasingly integrated into the daily lives of young adults for educational, emotional, and productivity-related purposes. Despite growing reliance on these technologies, their psychological impact on youth mental health remains insufficiently understood. Objective: This study aimed to examine the association between conversational AI usage and depressive symptom severity among young adults in West Bengal, India. Methods: A cross-sectional online survey was conducted among 231 young adults aged 18–25 years using convenience and snowball sampling methods. Depressive symptoms were assessed using the validated Patient Health Questionnaire-9 (PHQ-9). Data regarding conversational AI usage frequency and usage purposes were also collected. Pearson correlation, simple linear regression, one-way ANOVA, and chi-square analyses were performed to evaluate associations between AI usage and depression severity. Results: The mean PHQ-9 score was 11.0 ± 5.78, indicating an overall moderate level of depressive symptoms among participants. ChatGPT was the most frequently used AI platform (71.86%). Pearson correlation analysis demonstrated a weak negative association between AI usage frequency and PHQ-9 scores (r = −0.113, p = 0.086), which was not statistically significant. Regression analysis similarly showed that conversational AI usage did not significantly predict depression severity (R² = 0.013). No significant differences in depression scores were observed across AI usage groups in ANOVA or chi-square analyses. Conclusion: The findings suggest that conversational AI usage is not significantly associated with depressive symptom severity among young adults in West Bengal. While AI tools may support productivity and emotional engagement, they should not be considered substitutes for professional mental health care. Further longitudinal and qualitative research is needed to better understand the long-term psychological implications of AI-mediated interactions.