A scoping review of culturally sensitive large language models-based cognitive behavioural therapy for anxiety and depression: Global lessons for African implementation - Kevin Igwe; Kevin Durrhiem (Interdisciplinary Journal of Sociality Studies)
Anxiety and depression are significant global mental health challenges. In Africa, these conditions are critical social issues deeply connected to factors such as socio-economic disparities, cultural stigma, and limited healthcare resources. These factors create substantial barriers to effective care, highlighting the need for innovative approaches to mental health treatment. Large Language Model-based (LLM-based) Cognitive Behavioural Therapy (CBT) addresses this need by leveraging CBT’s structured and effective interventions while allowing for innovative approaches to scale the intervention for these conditions. However, existing research predominantly explores LLM integration in Western contexts, with minimal focus on African cultural dynamics. This scoping review investigates the integration of culturally sensitive elements in LLM-based CBT interventions for anxiety and depression, focusing on addressing the unique considerations for African implementation. Scopus, Web of Science (WOS), EBSCO, and Google Scholar were searched to identify studies published between 2019 and 2024. The review examines global practices of integrating cultural elements into LLM-based CBT and specific considerations for implementing these interventions in Africa. Findings reveal key challenges, including limited culturally representative datasets, diverse norms, traditional beliefs, and ethical concerns. Collaboration with African researchers and communities is crucial for addressing these gaps and ensuring culturally appropriate solutions. LLM-based CBT can address Africa’s mental health needs if culturally sensitive practices are prioritised. This review offers guidance for ethical, accessible, and effective interventions, combining global best practices with local insights.