Challenges in Implementing a Mobile AI Chatbot Intervention for Depression Among Youth on Psychiatric Waiting Lists:...

Area of Science:

• Pediatric Mental Health
• Digital Health Interventions
• Artificial Intelligence in Healthcare

Background:

• Child and adolescent mental health is a growing concern, with limited access to psychiatric care in Japan causing long wait times.
• Artificial intelligence (AI)-driven chatbots offer potential digital solutions to support youth during these extended waiting periods.
• The AI chatbot 'emol,' integrating acceptance and commitment therapy, was chosen after a review of Japanese mental health technology.

Purpose of the Study:

• To examine the feasibility of utilizing an AI chatbot ('emol') for pediatric and adolescent individuals awaiting psychiatric services.
• This exploratory trial aimed to assess engagement and potential benefits of digital mental health support.

Main Methods:

• A parallel-group randomized controlled trial involved participants aged 12-18 years on psychiatric waiting lists.
• Participants were randomized to receive 8 weekly AI chatbot sessions or standard mental health information.
• Outcomes included changes in depression/anxiety scores and secondary engagement metrics via voice and writing analysis.

Main Results:

• Despite 96 eligible individuals, only 3 provided initial consent, and all subsequently withdrew or were excluded.
• No evaluable data was collected due to zero participants completing the study.
• Low engagement was potentially linked to perceived irrelevance of digital tools, complex protocols, and privacy concerns.

Conclusions:

• Significant barriers to engagement indicate a need for simpler digital intervention protocols and secure, trusted environments.
• Future research should explore delivering these interventions in supportive settings like schools or community centers to improve accessibility and participation.