Evaluating the Effectiveness of AI-Driven Chatbots in Early Detection of Mental Health Disorders and Psychological Counseling

Abstract

The rapid growth of Artificial Intelligence (AI) and the development of natural-language-processing and conversational-technology systems, such as chatbots, has opened up new avenues for providing mental health support in an easily accessible manner. Chatbots driven by AI allow users to communicate in a natural way with the technology, receive psychoeducational information from it, and enable the chatbot to detect potential signs of psychological distress. The technology is able to generate basic supportive responses to users, and assist them in seeking professional help. This research investigates the potential effectiveness of AI-powered chatbots in assisting in the early identification of mental health issues and in providing initial counseling. The research will evaluate how well these four variables influence a user’s perception of the effectiveness of the provided counseling: Early Detection of Symptoms; Emotional Responsiveness; Customization/Personalization; Accessibility. Descriptive and analytical data collection methods were employed via a cross-sectional study design. An additional focus point included within this research project was a survey of 229 participants who were either experienced with conversational-AI based systems or had some familiarity with them. The structured questionnaire used a five-point Likert scale to collect the participant's perceptions of their experiences with AI-assisted counseling. Frequency analysis, descriptive statistics, Cronbach's alpha reliability assessment, Pearson correlation, multiple regression analysis, independent samples t-tests, and One-Way ANOVA statistical analyses were performed to analyze the participant's ratings. As indicated by the results, there appears to be a relationship between each dimension and perceived counseling effectiveness. Specifically, customization/personalization and emotional responsiveness appear to have a stronger relationship to perceived counseling effectiveness than does early symptom detection. Multiple regression analysis demonstrated that when considered collectively, the dimensions identified above are significant predictors of perceived counseling effectiveness. The researcher found that AI-driven chatbots may be effective supplemental tools for raising awareness about mental health issues, performing preliminary screenings, educating consumers regarding mental health, and providing counseling support. However, chatbots cannot replace the role of licensed professionals including psychologists, psychiatrists etc. Therefore, researchers conclude that any use of AI-based mental health systems requires human oversight, safeguards against misuse of personal identifiable information, valid clinical applications, clear communication of risks/benefits, and reasonable mechanisms for escalating critical care situations.