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34/100

✓ Peer-reviewed alzhub usefulness score 34 out of 100. Digital health tools

Topic: Risk, prevention and care in population studies

Digital health innovations hold diagnostic and therapeutic promise but may be subject to biases for underrepresented groups. We explored perceptions of using artificial intelligence (AI) diagnostics for dementia through a focus group as part of the Automated Brain Image Analysis for Timely and Equitable Dementia Diagnosis (ABATED) study. Qualitative feedback from a diverse public engagement group indicated that cultural variations in trust and acceptability of AI diagnostics may be an unrecognised source of real-world inequity. Efforts focused on the adoption of AI diagnostics in memory clinic pathways should aim to recognise and account for this issue.

Key findings

Qualitative feedback from a diverse public engagement group indicated that cultural variations in trust and acceptability of AI diagnostics may be an unrecognised source of real-world inequity.

Why it matters

This focus-group study found that cultural differences in trust and acceptability of AI dementia diagnostics may be an unrecognized source of inequity. It concerns how people view diagnostic tools, not any treatment, cure, or prevention for Alzheimer's disease.

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Study details

Evidence strengthLow

How this study scored 34/100

Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on impact for its field and year, so that was left out: it earned 32 of the 94 points we could judge it on, which is 34 out of 100.

Component	Points	Why
Journal tier	7 / 10	Tier 3 — peer-reviewed journal (Journal of Alzheimer s Disease)
Journal's citation record	2 / 4	Journal of Alzheimer s Disease: journal h-index 218 (OpenAlex, 2026-10-29)
Study design	0 / 12	No study design recorded — scores zero, not guessed (not stated in the record — scored 0)
Strength of evidence	1 / 5	Rated “low” in our summary
Peer-review validation	10 / 10	Peer-reviewed. Published as an article in a named peer-reviewed journal.
How recent	4 / 5	2025 — within 3 year(s) of the newest study here
Sample size	0 / 4	Participant count not stated — scores zero (not stated in the record — scored 0)
Effect reported	0 / 3	No effect size reported — scores zero (not stated in the record — scored 0)
Studied in people	0 / 3	Not stated whether this was studied in people — scores zero (not stated in the record — scored 0)
Randomised / blinded	0 / 2	No randomisation or blinding stated — scores zero (not stated in the record — scored 0)
Times cited	1 / 7	Cited 1 times (OpenAlex, 2026-10-10)
Citations per year	0 / 5	0.3 citations a year over 3 year(s) since 2025
Impact for its field and year	— / 6	No field-weighted citation impact (OpenAlex has none yet) — left out of this score
Cited by studies here	0 / 6	No other study in this library cites it
Still being cited	0 / 4	Cited 1 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record	2 / 4	Last-listed author Charles R. Marshall: h-index 31 (OpenAlex, whole career)
Institution's track record	1 / 3	Queen Mary University of London: institution h-index 1,058 (OpenAlex)
Multi-centre collaboration	0 / 3	OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete)
Indexed in PubMed	2 / 2	Indexed in PubMed (PMID 39956979)
Free to read	2 / 2	Free to read
Points	32 / 94	Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 32 of the 94 points we could judge it on is 34 out of 100.
Total	34 / 100	—

What each of these 20 components measures, and what this score is not →

Read the original

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.

APA 7th

Chandra, A., Senthilvel, K., Anjum, R., Uchegbu, I., Smith, L. J., Beaumont, H., et al. (2025). Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia. Journal of Alzheimer s Disease. https://doi.org/10.1177/13872877251319353

Vancouver

Chandra A, Senthilvel K, Anjum R, Uchegbu I, Smith LJ, Beaumont H, et al. Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia. Journal of Alzheimer s Disease. 2025. doi:10.1177/13872877251319353. PMID: 39956979.

BibTeX

@article{chandra2025-39956979,
  author  = {Chandra, Avinash and Senthilvel, Kaviya and Anjum, Rifah and Uchegbu, Ijeoma and Smith, Laura Jennie and Beaumont, Helen and Punjabi, Reshma and Begum, S. Hussna and others},
  title   = {{Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia}},
  journal = {Journal of Alzheimer s Disease},
  year    = {2025},
  doi     = {10.1177/13872877251319353},
  pmid    = {39956979},
  url     = {https://doi.org/10.1177/13872877251319353}
}

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