Exploring Socio-Cultural Challenges and Opportunities in Designing Mental Health Chatbots for Adolescents in India

TL;DR

The paper examines socio-cultural barriers and opportunities for mental health chatbots tailored to Indian adolescents, addressing stigma, accessibility, and cultural relevance. Using a mixed-methods design with a survey of 278 adolescents and 12 in-depth interviews plus a prototype chatbot, it identifies critical gaps in current digital tools and the potential for anonymous, personalized, locally contextualized support. Key findings show low formal help-seeking, strong social stigma, high smartphone access, a strong preference for text-based interactions, and dissatisfaction with non-localized resources, while highlighting the receptivity of chatbots when privacy and personalization are prioritized. The authors propose design recommendations—encompassing anonymity, localization, memory/history, multi-modal interactions, measured response length, personalization, emotional support, and adaptable personas—to guide culturally sensitive chatbot development and improve accessibility for India’s diverse adolescent population.

Abstract

Mental health challenges among Indian adolescents are shaped by unique cultural and systemic barriers, including high social stigma and limited professional support. Through a mixed-methods study involving a survey of 278 adolescents and follow-up interviews with 12 participants, we explore how adolescents perceive mental health challenges and interact with digital tools. Quantitative results highlight low self-stigma but significant social stigma, a preference for text over voice interactions, and low utilization of mental health apps but high smartphone access. Our qualitative findings reveal that while adolescents value privacy, emotional support, and localized content in mental health tools, existing chatbots lack personalization and cultural relevance. These findings inform recommendations for culturally sensitive chatbot design that prioritizes anonymity, tailored support, and localized resources to better meet the needs of adolescents in India. This work advances culturally sensitive chatbot design by centering underrepresented populations, addressing critical gaps in accessibility and support for adolescents in India.

Figures (1)

• Figure 1: The chatbot interface. Interviewees could access the chatbot on their phone, tablet, or laptop and interacted via text. The chatbot was programmed to always give short responses and ask one question per turn.