Evidence map›Paper›PMID 42676617›Full record

ArticleDigital health

Barriers to artificial intelligence chatbot utilization among patients near the Iran-Afghanistan border: A qualitative interview study.

Mohsen Khosravi, Fatemezahra Zahrayi, Fatemeh Beiky, Ali Miri, Motahareh Nakhaei, Djavad Ghoddoosi-Nejad, Saeede Saadatjoo

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mohsen KhosraviSocial Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran.ORCID https://orcid.org/0000-0002-0576-7660
Fatemezahra ZahrayiStudent research committee, Birjand University of Medical Sciences, Birjand, Iran.
Fatemeh BeikyStudent research committee, Birjand University of Medical Sciences, Birjand, Iran.
Ali MiriStudent research committee, Birjand University of Medical Sciences, Birjand, Iran.
Motahareh NakhaeiClinical Research Development Unit, Razi Hospital, Birjand University of Medical Sciences, Birjand, Iran.
Djavad Ghoddoosi-NejadSocial Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran.
Saeede SaadatjooSocial Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Artificial Intelligence (AI) presents significant advantages in healthcare. The Iran-Afghanistan border region, marked by low socioeconomic status, experiences poor health outcomes, especially among women and children. The presence of armed conflict in the region has further exacerbated the situation. This study examined barriers to patient adoption of AI chatbots in this region. Methods: This was a qualitative exploratory study conducted in June and July 2025 in Birjand, eastern Iran, near the Iran-Afghanistan border. Forty-two unstructured interviews were held with patients at a group of clinics and primary healthcare centers. The interviews were conducted during and immediately following the onset of the armed conflict between Iran and Israel. Data were analyzed using the Boyatzis framework. Results: The findings revealed that barriers to AI chatbot usage among patients could be categorized into four main areas: lack of awareness, knowledge, and training; user barriers; technological barriers; and financial barriers. User barriers encompassed the greatest number of sub-themes, whereas financial barriers were represented by only a single sub-theme, indicating less representation by the study participants. Conclusion: The study provided novel data on wartime conditions, offering valuable insights for stakeholders in conflict-affected or at-risk regions. The findings can support effective AI chatbot adoption by local populations during war or crises and inform efforts to improve usage in low-resource and conflict settings.

Indexed as

artificial intelligencegenerative artificial intelligencelarge language modelspatient-centered carepatients

Identifiers

PMID42676617
PMCPMC13527368

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