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

2025-03-11

AI Summary

This study addresses the severe shortage of adolescent mental health support in India, driven by pervasive social stigma, scarce professional resources, and culturally insensitive or non-personalized chatbots. Through a mixed-methods approach—comprising 278 surveys and 12 in-depth interviews—the research systematically identifies critical cultural constraints: strong demand for anonymity, marked preference for native languages, high mobile phone usage yet low adoption of mental health apps, and, notably, the paradoxical coexistence of low self-stigma and high perceived social stigma—a previously unreported pattern. Building on these insights, the study proposes a culturally grounded chatbot design framework centered on four pillars: linguistic localization, affective interaction, enhanced privacy safeguards, and anti-internalized-stigma mechanisms. It further delivers actionable, implementation-ready design guidelines. This work advances both theoretical understanding and practical deployment of digital mental health interventions in Global South contexts.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

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.

Problem

• Addressing cultural and systemic barriers in mental health for Indian adolescents.
• Exploring adolescent preferences for digital mental health tools and chatbot interactions.
• Designing culturally sensitive chatbots with privacy, personalization, and localized content.

Innovation

• Culturally sensitive chatbot design for adolescents
• Prioritizes anonymity and tailored emotional support
• Incorporates localized content and resources