Evidence map›Paper›PMID 41491050›Full record

ArticleBJGP open2026

Using artificial intelligence (CognoSpeak™) in memory assessments: a GP interview study.

Caitlin H Illingworth, Florence Mutlow, Lewis Roberts, Theocharis Stavroulakis, Daniel J Blackburn, Jon M Dickson

Abstract read
In one paragraph

Article in BJGP open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Caitlin H IllingworthDivision of Neuroscience, School of Medicine and Population Health, Sheffield Institute for Translational Neuroscience (SITRaN), The University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0009-0002-3800-7999
Florence MutlowSheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
Lewis RobertsSheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
Theocharis StavroulakisDivision of Neuroscience, School of Medicine and Population Health, Sheffield Institute for Translational Neuroscience (SITRaN), The University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0000-0002-3535-7822
Daniel J BlackburnDivision of Neuroscience, School of Medicine and Population Health, Sheffield Institute for Translational Neuroscience (SITRaN), The University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0000-0001-8886-1283
Jon M DicksonSheffield Centre for Health and Related Research (SCHARR), School of Medicine and Population Health, Sheffield, UK j.m.dickson@sheffield.ac.uk.ORCID https://orcid.org/0000-0002-1361-2714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe memory assessment pathway (MAP) for people with subjective memory deficits (dementia, mild cognitive impairment, and other diagnoses) is under huge strain and new diagnostic technologies have been identified as a high priority for research.

aimTo investigate the views of GPs on the MAP, and on how an artificial intelligence tool (CognoSpeak™) could be implemented. DESIGN &

settingQualitative interview study in a large region of the NHS (South Yorkshire) in England.

methodEighteen GPs were recruited using convenience sampling to undertake semi-structured interviews, which were analysed using reflexive thematic analysis (demographic data were monitored to ensure diversity).

resultsGPs think that the MAP has system-wide problems, and that GPs are overworked yet underutilised. They highlighted assessment and referral dilemmas, and the perspectives of patients and families. When asked about implementation of CognoSpeak™, they gave their thoughts on the optimal sites of implementation. The GPs also highlighted barriers and difficulties, as well as the opportunities and benefits, and they made proposals for the future development of CognoSpeak™.

conclusionGPs thought effective implementation of CognoSpeak™ could save time, expedite diagnosis, free-up much needed capacity, and improve the longitudinal assessment of people with mild cognitive impairment. A major concern among GPs was the potential for unintended consequences such as creating additional unfunded work. They also felt it could exacerbate difficulties at the intersections between subjective memory deficits and other factors such as low mood, excess alcohol consumption, learning difficulties, or language and culture. They were concerned about poor access to technology among older and more economically deprived people.

Indexed as

artificial intelligencedementiafamily medicineinformation technology

Identifiers

PMID41491050
PMCPMC13540348

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.