Effectiveness of Topic-Based Chatbots on Mental Health Self-Care and Mental Well-Being: Randomized Controlled Trial.

backgroundThe global surge in mental health challenges has placed unprecedented strain on health care systems, highlighting the need for scalable interventions to promote mental health self-care. Chatbots have emerged as promising tools by providing accessible, evidence-based support. While chatbots have shown promise in delivering mental health interventions, most studies have only focused on clinical populations and symptom reduction, leaving a critical gap in understanding their preventive potential for self-care and mental health literacy in the general population.

objectiveThis study evaluated the effectiveness of a rule-based, topic-specific chatbot intervention in improving self-care efficacy, mental health literacy, self-care intention, self-care behaviors, and mental well-being immediately after 10 days and 1 month of its use.

methodsA 2-arm, assessor-blinded randomized controlled trial was conducted. A total of 285 participants were randomly assigned to the chatbot intervention group (n=140) and a waitlist control group (n=145). The chatbot intervention consisted of 10 topic-specific sessions targeting stress management, emotion regulation, and value clarification, delivered over 10 days with a 7-day free-access period. Primary outcomes included self-care self-efficacy, behavioral intentions, self-care behaviors, and mental health literacy. Secondary outcomes included depressive symptoms, anxiety symptoms, and mental well-being. Assessments were self-administered on the web at baseline, 10 days after the intervention, and at a 1-month follow-up. All outcomes were analyzed using linear mixed models with an intention-to-treat approach, and effect sizes were calculated using Cohen d.

resultsParticipants in the chatbot group demonstrated significantly greater improvements in behavioral intentions (F

conclusionsThis study highlights the potential of rule-based chatbots in promoting mental health literacy and fostering short-term self-care intentions. However, the lack of sustained effects points to the necessary improvements required in chatbot design, including greater personalization and interactive features to enhance self-efficacy and long-term mental health outcomes. Future research should explore hybrid approaches that combine rule-based and generative artificial intelligence systems to optimize intervention effectiveness.

trial registrationClinicalTrials.gov NCT05694507; https://clinicaltrials.gov/ct2/show/NCT05694507.