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Designing Chatbots to Treat Depression in Youth: Qualitative Study
Thus, there is a critical need for research on how to design chatbots that focus on specific problems of youth with depressive symptoms to achieve sufficient engagement and optimal treatment outcomes.
Our study aims to address this research gap by investigating the following research questions: (1) What problems do youth with depressive symptoms face? (2) What adaptive coping strategies do they apply? (3) What attitudes and expectations do they have for chatbots designed to treat depression among youth?
JMIR Hum Factors 2025;12:e66632
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Structured, evidence-based approaches in face-to-face (F2 F) settings have proven beneficial for treating major depressive disorder (MDD) and substance use disorder (SUD) [1,2], which frequently co-occur. Researchers are increasingly leveraging digital platforms to enhance the reach and accessibility of these treatments.
JMIR Ment Health 2025;12:e67670
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Consequently, cognitive bias modification (CBM) interventions that target this negative bias may reduce depressive symptoms [4].
A CBM intervention was developed to aim at changing negative biases in the perception of emotional facial expressions [4]. This CBM technique shifts participants’ responses toward more positive interpretations of ambiguous facial expressions [4].
JMIR Serious Games 2025;13:e65103
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Celebrities and influencers on social media platforms have contributed to rising negative body image perceptions [13], which have been associated with higher depressive symptoms, loss of confidence, loneliness, and risk of developing eating disorders [13,14].
JMIR Form Res 2025;9:e58916
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However, Grünzig et al [17] conducted a systematic review of low-intensity interventions to reduce depressive symptoms before outpatient psychotherapy and found limited evidence of their effectiveness in reducing depressive symptoms. Among the reviewed studies, the interventions were a mix of face-to-face sessions, web-based training for self-help strategies, and supervised bibliotherapy with feedback via email or telephone [17].
JMIR Ment Health 2024;11:e56650
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However, recent studies examining the impact of the COVID-19 pandemic on internalizing disorders suggest substantial increases in rates of depressive disorders [10-12].
JMIR Ment Health 2024;11:e54252
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The scale asks the frequency of experiencing mental distress (0=not at all to 3=nearly every day) during the 2 weeks prior to the survey, with 2 items referring to anxiety symptoms (α=.90) and 2 to depressive symptoms (α=.82). Items are summed to create 2 indexes, each ranging between 0 and 6 with higher numbers indicating higher levels of mental distress. Each score is then dichotomized, with respondents scoring 3 or greater coded as likely experiencing the condition represented by the subscale [34].
JMIR Form Res 2024;8:e55759
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Descriptive data for the total sample and scales mean comparisons between different age groups.
a P
b SCS: Self-Compassion Scale.
c DEQ-A: self-criticism subscale of the Depressive Experiences Questionnaire.
d DEQ-D: dependency subscale of the Depressive Experiences Questionnaire.
e BSQ: Body Shape Questionnaire.
Mean scores and SDs of the scales as a result of time spent using Instagram, as well as the P value after performing ANOVA analysis are presented in Table 4.
J Med Internet Res 2024;26:e51957
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