JMIR Publications

ABSTRACT

Background:

Mental health disorders are a leading cause of disability among adolescents and young people in Kenya, yet access to appropriate and timely support remains severely limited due to shortages of trained professionals, stigma, financial barriers, and geographical inequities. Digital mental health interventions, particularly those leveraging artificial intelligence (AI), present a promising opportunity to expand access to culturally relevant, low-stigma mental wellness support in low- and middle-income country (LMIC) settings. However, evidence on the feasibility, usability, and acceptability of AI-powered mental health tools for young people in sub-Saharan Africa remains limited.

Objective:

This study aims to co-design, develop, and evaluate “Dəˈskəs,” a social media–based digital platform featuring an AI-powered chatbot, to support mental wellness among adolescents and young people in Kenya. The primary objectives are to assess the feasibility of implementation, usability and user experience, acceptability, and the platform's preliminary applicability across diverse urban, peri-urban, and rural contexts.

Methods:

The study will employ a human-centered design (HCD) methodology, conducted in three phases: formative research and co-design; platform development and iterative refinement; and implementation with monitoring and evaluation. Adolescents and young people aged 18–24 years will be purposively recruited from Kibra (urban), Kikuyu town (peri-urban), and Nachu (rural). Formative data will be collected through focus group discussions to inform platform design, content, and functionality. During implementation, participants will use the platform for 2 months. Quantitative data will include baseline behavioral health screening using the Global Appraisal of Individual Needs–Short Screener (GAIN-SS) and platform usage analytics. Qualitative data will be collected through interviews and feedback sessions to assess usability, user experience, acceptability, and perceived value. Data will be analyzed using descriptive statistics and thematic qualitative analysis.

Results:

The study is expected to generate evidence on the feasibility of implementing an AI-powered mental wellness platform for adolescents and young people in Kenyan settings. Anticipated findings include insights into contextual enablers and barriers to adoption, patterns of user engagement, usability and user experience outcomes, and the perceived relevance and acceptability of the chatbot and social platform features. The results will inform iterative improvements to the intervention and provide early evidence of its potential to support mental wellness and facilitate timely access to support.

Conclusions:

This protocol describes a adolescent-centered, ethically grounded approach to developing and evaluating an AI-enabled digital mental health intervention in an LMIC context. The findings are expected to contribute to the evidence base on the responsible design and implementation of AI-powered mental health tools for adolescents and young people and to inform future scale-up of accessible, culturally relevant digital mental wellness interventions in Kenya and similar settings.