Older adults' attitudes toward knowing their risk of Alzheimer's disease and preclinical diagnostic communication: A nationwide study.

Authors

Marie Bruun, T Rune Nielsen, Gunhild Waldemar, Kristian Steen Frederiksen

Published in

Journal of Alzheimer's disease : JAD. Pages 13872877261489585. Sep 28, 2026. Epub Sep 28, 2026.

Abstract

BackgroundCommunication about biomarkers and disclosure of Alzheimer's disease pathology is challenging. Earlier diagnosis has intensified this challenge, but evidence regarding communication of positive biomarker results for Alzheimer's disease to individuals with subjective cognitive decline remains limited.ObjectiveThe study aimed to investigate older adults' attitude toward knowing their risk of Alzheimer's disease, preferences regarding pre-biomarker counseling and diagnostic disclosure, and their views on the use of artificial intelligence in the diagnostic process when presented with a hypothetical scenario of subjective cognitive decline.MethodsWe conducted a cross-sectional nationwide questionnaire survey among an age-selected, sex- and residence-balanced sample from the Danish Civil Registration System where individuals with dementia, nursing home residency, or dementia medication use were excluded. An online questionnaire was sent to 30,000 participants.ResultsA total of 12,939 participants (aged 55-84 years, 53.3% female) answered at least one questionnaire item (response rate: 43.1%). More than two-thirds of the participants were interested in knowing their Alzheimer's disease risk status (76.4%). Information on treatment options, test reliability and risk prediction, along with written material, personal interaction and follow-up consultation, were rated as the most important topics. Simple graphical figures were preferred to accompany risk communication. Finally, 56.4% were positive toward use of artificial intelligence in diagnostics by physicians.ConclusionsOlder adults are interested in knowing their risk of developing Alzheimer's disease and trust physicians' use of artificial intelligence in the diagnostic process. Moreover, their preferences regarding information and methodology may help improve the current guidelines.

PMID:
42803724
Bibliographic data and abstract were imported from PubMed on 28 Sep 2026.

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