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Peer-reviewedCC BY 4.0Frontiers in Public Health

Generative AI, cyberchondria, and digital health inequality: a public health challenge for Somalia and other fragile health systems

  • Abdisamad Abdihakim Aadam1,2
  • Maida Ali Daahiye1,2
  • Abdirizak Ahmed Mohamed1,2
  • Abdimalik Dahir Ali1,2
  • Ilyas Abdullahi Khalif1,3,4
4 affiliations
  1. 1Faculty of Health Sciences and Tropical Medicine, Somali National University
  2. 2Benaadir Research, Consultancy and Evaluation Center
  3. 3Center for Health Research and Innovation, Somali National University
  4. 4Faculty of Health Sciences, Salaam University
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Abstract

Generative artificial intelligence (GenAI) is transforming access to health information through rapid, personalized, and conversational responses. While this may improve health education and reduce information barriers, it may also increase exposure to misinformation, uncertainty, misplaced trust, and health anxiety. This Perspective examines the potential relationship between GenAI-mediated health-information seeking, cyberchondria, digital health inequality, and health-system vulnerability, using Somalia as an important context for examining how these dynamics may unfold in a fragile health system. We argue that conversational AI may reinforce existing patterns of repeated symptom searching and reassurance seeking, although direct evidence linking GenAI to cyberchondria remains limited. Somalia-specific evidence on GenAI-mediated health-information seeking is currently unavailable; therefore, the Somali context is considered through structural conditions, including unequal digital access, constrained healthcare access, and limited local health-information infrastructure. Safe and equitable adoption requires Somali-language validation, digital-health literacy, human oversight, data protection, and local research capacity.

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Cite

BibTeXRIS
BibTeX
@article{aadam2026generative,
  title = {{Generative AI, cyberchondria, and digital health inequality: a public health challenge for Somalia and other fragile health systems}},
  author = {Abdisamad Abdihakim Aadam and Maida Ali Daahiye and Abdirizak Ahmed Mohamed and Abdimalik Dahir Ali and Ilyas Abdullahi Khalif},
  journal = {Frontiers in Public Health},
  year = {2026},
  month = oct,
  doi = {10.3389/fpubh.2026.1942140},
  url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1942140/full},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Generative AI, cyberchondria, and digital health inequality: a public health challenge for Somalia and other fragile health systems
AU  - Abdisamad Abdihakim Aadam
AU  - Maida Ali Daahiye
AU  - Abdirizak Ahmed Mohamed
AU  - Abdimalik Dahir Ali
AU  - Ilyas Abdullahi Khalif
PY  - 2026
DA  - 2026/10/27
JO  - Frontiers in Public Health
DO  - 10.3389/fpubh.2026.1942140
UR  - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1942140/full
AB  - Generative artificial intelligence (GenAI) is transforming access to health information through rapid, personalized, and conversational responses. While this may improve health education and reduce information barriers, it may also increase exposure to misinformation, uncertainty, misplaced trust, and health anxiety. This Perspective examines the potential relationship between GenAI-mediated health-information seeking, cyberchondria, digital health inequality, and health-system vulnerability, using Somalia as an important context for examining how these dynamics may unfold in a fragile health system. We argue that conversational AI may reinforce existing patterns of repeated symptom searching and reassurance seeking, although direct evidence linking GenAI to cyberchondria remains limited. Somalia-specific evidence on GenAI-mediated health-information seeking is currently unavailable; therefore, the Somali context is considered through structural conditions, including unequal digital access, constrained healthcare access, and limited local health-information infrastructure. Safe and equitable adoption requires Somali-language validation, digital-health literacy, human oversight, data protection, and local research capacity.
SN  - 2296-2565
ER  -