JMIR Publications

ABSTRACT

Background:

Depression is a severe and prevalent mental disorder among youth that requires professional care, but various barriers hinder access to effective treatments. Chatbots, the latest innovation in the research on digital mental health interventions (DMHIs), have shown potential in addressing these barriers. However, most studies on how to design chatbots to treat depression have focused on adult populations or on prevention among the general population.

Objective:

The current study aims to investigate the problems faced by youth with depression and their coping strategies as well as attitudes, expectations, and design preferences for chatbots designed to treat depression in youths.

Methods:

We conducted a mixed-methods study, compromising a questionnaire, a semi-structured interview, and a concurrent think-aloud session with a chatbot prototype with 14 youth with a current or remitted depressive episode.

Results:

Participants reported a wide range of problems beyond core depressive symptoms, such as interpersonal challenges, concerns about school and the future and problems with human therapists. Coping strategies varied, with most seeking social support or engaging in pleasant activities. Attitudes towards chatbots for depression treatment were predominantly positive, with participants expressing less anxiety about using a chatbot than seeing a human therapist. Participants showed diverse and partially contradictory design preferences. Design preferences included diverse dialogue topics, such as discussing daily life, acute problems and therapeutic exercises, as well as various preferences for the personality, language use and personalization of the chatbot.

Conclusions:

Our study provides a comprehensive foundation for designing chatbots that meet the unique needs and design preferences of youth with depression. The findings can inform the design of engaging and effective chatbots tailored to this vulnerable population.