Discover Artificial Intelligence • Article in Press
Expert perspectives on AI-based counseling for anxiety and depression in Iran: cultural, ethical, and clinical insights
Authors: Mahdi Naeim & Mohammad Narimani
Publication: Discover Artificial Intelligence (Published online: 12 May 2026, Received: 8 October 2025, Accepted: 22 April 2026)
DOI: 10.1007/s44163-026-01345-6
This study investigated how Iranian experts in mental health, information technology, and public health perceive the potential role of artificial intelligence (AI) in counseling for anxiety and depression, focusing on effectiveness, cultural adaptation, and ethical considerations for AI integration into clinical practice.
Key Insights at a Glance
Leveraging expert consensus for strategic AI implementation in mental health. The findings highlight critical factors for successful AI integration in culturally specific contexts.
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Experts perceiving AI usefulness for mild-moderate cases
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Experts highlighting accessibility opportunities
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Experts raising privacy/data concerns
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Experts noting lack of genuine empathy
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Conditional Effectiveness for Mild-Moderate Symptoms
Experts noted AI's utility is conditional, dependent on symptom severity and clinical context. It is suitable for mild to moderate cases (21/25 experts), offering timely support like breathing exercises and psychoeducation. AI also shows promise for early screening and triage (17/25 experts), identifying risks and directing individuals to professional services sooner. However, it is not appropriate for crises or severe pathology (16/25 experts), with experts uniformly warning against its inadequacy for high-risk or complex clinical presentations.
Enhancing Access and Reducing Inequity
AI is seen as a powerful tool to bridge gaps in mental health support, especially in underserved areas. A significant majority of experts (23/25) emphasized its role in addressing workforce shortages, providing basic guidance where specialists are scarce. Additionally, 15 experts noted AI's potential in reducing stigma associated with help-seeking by offering a more private and less judgmental entry point for individuals.
Navigating Cultural & Ethical Imperatives
A major theme was the necessity for AI tools to align with local cultural and ethical standards. Privacy and data security were a primary concern for 20 experts, stressing that mistrust in data policies could hinder honest disclosure. The need for cultural/religious adaptation was highlighted by 18 experts, who stressed that advice must be calibrated to Iranian social norms, family roles, and religious beliefs to be accepted. There was also a perceived risk of over-reliance (14 experts) on AI, potentially leading individuals to neglect necessary clinical care.
Dynamics of Human-AI Therapeutic Interaction
The nature of the interaction between humans and AI was a key discussion point. A significant 22 experts pointed to the lack of genuine empathy as a central limitation of AI in therapeutic work, stating that human connection is irreplaceable. Conversely, 13 experts noted that AI could serve as a non-judgmental space, allowing users, particularly adolescents, to disclose sensitive issues more freely without fear of societal judgment.
Overcoming Implementation Hurdles
Successful integration of AI requires addressing several practical barriers. The need for regulation and standards was emphasized by 19 experts to ensure safe and responsible deployment. Clinician AI-literacy was deemed important by 17 experts, advocating for training to appropriately interpret AI recommendations. Infrastructure limitations (15 experts), such as unreliable internet and low digital literacy in certain regions, were also cited as challenges. Finally, the need for culturally reflective datasets (18 experts) was crucial, with warnings that Western-trained models might misinterpret Persian communication patterns.
Enterprise Process Flow: Thematic Structure of AI-Assisted Counseling in Iran
Conditional Effectiveness
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Access & Equity
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Cultural & Ethical Concerns
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Human-AI Interaction
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Implementation Barriers
| Feature | Iranian Context (Study Findings) | Broader Global Context (General Literature) |
|---|---|---|
| Cultural Adaptation | Crucial for acceptance; alignment with local norms, family structures, and religious beliefs is paramount. | Often less explicit emphasis; focus on universal effectiveness, but cultural nuances increasingly recognized. |
| Ethical & Data Governance | High concern for privacy, data security, and local control; potential misuse in surveillance is a significant risk. | Standardized regulations developing; focus on data privacy, transparency, and accountability, but specific cultural contexts sometimes overlooked. |
| Role of Empathy | Human empathy is irreplaceable; AI lacks genuine emotional resonance, limiting therapeutic depth. | AI often seen as a supplementary tool; limitations in expressing genuine empathy are acknowledged, leading to a focus on structured support. |
| Accessibility Impact | Significant potential to bridge mental health service gaps, especially in underserved rural areas with workforce shortages. | Improves access to care; particularly useful for those facing geographical or stigma-related barriers, though rural shortages might be less acute than in Iran. |
| Implementation Readiness | Requires robust regulatory frameworks, clinician training, improved infrastructure (internet, digital literacy), and culturally reflective datasets. | Focus on integration with existing clinical workflows, scalability, and continuous model refinement; infrastructure generally more robust. |
Cultural Nuances in AI Mental Health: An Iranian Perspective
The integration of AI into mental health counseling in Iran presents unique challenges, particularly concerning cultural and religious alignment. Experts in this study highlighted that for AI tools to be effective and accepted, their content must deeply resonate with local Iranian social norms, family structures, and religious beliefs. As one expert, P15_Sanandaj_Coun, plainly stated: 'Advice about family roles, emotional expression, or relationships must be aligned with local norms, otherwise users will ignore it.' This emphasizes that a direct transfer of AI models from Western contexts without careful adaptation could lead to their rejection or ineffectiveness. Successful deployment will require localized content development, ensuring that AI interventions are not just technologically advanced but also culturally sensitive and ethically congruent with the Iranian societal framework.
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