Trust in AI-Assisted Medical Expertise Among Patients with Diabetes: A Qualitative Focus Group Study
Abstract
Background: The use of artificial intelligence (AI) is increasingly implemented in the Danish healthcare system, including in the prevention and treatment of diabetes in medical consultations. AI has primarily been studied from medical and technical perspectives, whereas patients’ perceptions of and trust in AI-assisted medical expertise remain limited. This pilot study aimed to explore patients’ attitudes and experiences with AI in diabetes care.
Methods: Three focus groups were conducted, each consisting of 3–5 adults (>50 years) with diabetes: two groups with type 1 diabetes and one group with type 2 diabetes. Data were analysed using an inductive thematic approach, resulting in the development of four theoretically informed themes related to trust and the relationship with healthcare professionals.
Results: Patients with both type 1 and type 2 diabetes were generally optimistic about AI and already used it in their everyday lives for optimization and self-management. They increasingly viewed themselves as 1) experts in managing their own condition. Some patients were more skeptical, expressing concerns that excessive focus on AI and technology could overshadow quality of life. Despite this, they emphasized 2) the importance of relationships with healthcare professionals. Patients expressed a need to ask questions and engage in dialogue to receive support in interpreting health data and discussing decisions, particularly when data were unfavorable. Trust in AI was strengthened when 3) healthcare professionals were involved in AI-assisted consultations. Patients preferred that 4) overall responsibility remained with healthcare professionals and trusted their judgment.
Conclusions: Overall, patients with diabetes tended to trust AI in medical consultations. This trust was reinforced by face-to-face relationships with healthcare professionals. However, it remained essential that healthcare professionals were available for guidance and assumed overall responsibility.
Key messages: • Patients with both type 1 and type 2 diabetes increasingly used AI and viewed themselves as experts in managing their own condition.
• Trust in AI in medical consultations among patients with both type 1 and type 2 diabetes was reinforced through face-to-face interactions with healthcare professionals.
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BibTeX
@article{ledderer2026trust,
title = {{Trust in AI-Assisted Medical Expertise Among Patients with Diabetes: A Qualitative Focus Group Study}},
author = {L Ledderer and A Fage-Butler and KH Nielsen and A Irwin and R Nyrup and TE Agergard and AL Jensen and T Ravn},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.1227},
url = {https://doi.org/10.1093/eurpub/ckag169.1227},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Trust in AI-Assisted Medical Expertise Among Patients with Diabetes: A Qualitative Focus Group Study
AU - L Ledderer
AU - A Fage-Butler
AU - KH Nielsen
AU - A Irwin
AU - R Nyrup
AU - TE Agergard
AU - AL Jensen
AU - T Ravn
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.1227
UR - https://doi.org/10.1093/eurpub/ckag169.1227
AB - Background: The use of artificial intelligence (AI) is increasingly implemented in the Danish healthcare system, including in the prevention and treatment of diabetes in medical consultations. AI has primarily been studied from medical and technical perspectives, whereas patients’ perceptions of and trust in AI-assisted medical expertise remain limited. This pilot study aimed to explore patients’ attitudes and experiences with AI in diabetes care. Methods: Three focus groups were conducted, each consisting of 3–5 adults (>50 years) with diabetes: two groups with type 1 diabetes and one group with type 2 diabetes. Data were analysed using an inductive thematic approach, resulting in the development of four theoretically informed themes related to trust and the relationship with healthcare professionals. Results: Patients with both type 1 and type 2 diabetes were generally optimistic about AI and already used it in their everyday lives for optimization and self-management. They increasingly viewed themselves as 1) experts in managing their own condition. Some patients were more skeptical, expressing concerns that excessive focus on AI and technology could overshadow quality of life. Despite this, they emphasized 2) the importance of relationships with healthcare professionals. Patients expressed a need to ask questions and engage in dialogue to receive support in interpreting health data and discussing decisions, particularly when data were unfavorable. Trust in AI was strengthened when 3) healthcare professionals were involved in AI-assisted consultations. Patients preferred that 4) overall responsibility remained with healthcare professionals and trusted their judgment. Conclusions: Overall, patients with diabetes tended to trust AI in medical consultations. This trust was reinforced by face-to-face relationships with healthcare professionals. However, it remained essential that healthcare professionals were available for guidance and assumed overall responsibility. Key messages: • Patients with both type 1 and type 2 diabetes increasingly used AI and viewed themselves as experts in managing their own condition. • Trust in AI in medical consultations among patients with both type 1 and type 2 diabetes was reinforced through face-to-face interactions with healthcare professionals.
SN - 1101-1262
SN - 1464-360X
ER -