To examine the current evidence of AI-driven conversational tools in mental health, focusing on their application, acceptance, and limitations within the MENA region.
Approach:
Literature Review: A structured search of MEDLINE and Embase (2000–2026) identified studies on conversational AI in mental health, prioritizing evidence from the MENA region and supplemented by relevant global literature.
Key Findings:
Mental health disorders affect up to 40% of adults in the MENA region, with treatment gaps of 80-95% due to provider shortages, financial strain, and cultural barriers.
AI tools, including large language models and psychotherapy chatbots, offer high accessibility and user engagement for low-intensity support, but their effectiveness is limited by linguistic and cultural mismatches, including Arabic diglossia.
User acceptance reflects a paradox; stigma and privacy concerns drive reliance on anonymous AI tools while simultaneously limiting trust in their clinical reliability.
Current AI systems are insufficiently adapted to the MENA context, underscoring the need for culturally grounded, dialect-sensitive, and clinically supervised approaches.
Interpretation:
AI has potential as a scalable adjunct in mental health care but requires adaptation to local cultural contexts and oversight to ensure effectiveness and safety.
Limitations:
AI tools may produce inaccurate or misleading information, particularly in emotionally complex situations.
Concerns about psychological effects from extensive engagement with AI tools have been reported, highlighting the need for careful implementation.
Conclusion:
AI is best viewed as a complementary tool that enhances access and support while emphasizing the essential role of human clinicians.
