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Keywords: Conversational AI [1], elder mental health [2], psychological well-being [5].
The global surge in aging populations and digital mental health interventions underscores the urgency to understand how cultural preferences shape the adoption and efficacy of conversational AI tools for supporting older adults’ mental well-being. This systematic review aims to (1) examine how cultural factors influence the perception, usability, and acceptance of conversational AI tools among older adults for mental health support; (2) identify design features and implementation strategies that enhance or hinder user engagement across cultural contexts; and (3) highlight gaps in current research and propose culturally adaptive recommendations for AI-based mental health interventions. Guided by the PRISMA 2020 framework. This review will synthesize evidence from 2015 to 2025 from Scopus, PubMed, and Google Scholar. The search strategy includes terms such as “conversational AI,” “chatbots,” “virtual assistants,” “mental health,” “older adults,” “cross-cultural,” “user acceptance,” and “psychological well-being.” Inclusion criteria encompass peer-reviewed articles, empirical studies, pilot trials, and qualitative evaluations involving adults aged 60+ using AI-driven conversational agents for mental health outcomes. Data extraction & quality assessment will follow standardized protocols, with findings narratively synthesized to identify cultural divergences and design gaps. A key contribution is the identification of cultural blind spots in existing AI solutions, which are predominantly designed around Western cultural norms, potentially limiting trust, engagement, and effectiveness among non-Western or culturally diverse older populations. Through this study we propose culturally adaptive design recommendations to foster equitable, effective conversational AI solutions supporting the well-being of aging communities worldwide.
