Evidence map›Paper›PMID 42013397›Full record

ArticleJMIR aging2026

Exploring Information Access in Aging Populations and Those With Dementia and Mild Cognitive Impairment in the United Kingdom: Survey and Focus Group Study.

Claire Rogers, William J McGeown, Yashar Moshfeghi

Abstract read
In one paragraph

Article in JMIR aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Claire RogersNeuraSearch Laboratory, Department of Computer and Information Sciences, University of Strathclyde, 26 Richmond Street, Glasgow, United Kingdom, 44 1415483256.ORCID http://orcid.org/0009-0007-8855-4743
William J McGeownDepartment of Psychological Sciences and Health, University of Strathclyde, Glasgow, United Kingdom.ORCID http://orcid.org/0000-0001-7943-5901
Yashar MoshfeghiNeuraSearch Laboratory, Department of Computer and Information Sciences, University of Strathclyde, 26 Richmond Street, Glasgow, United Kingdom, 44 1415483256.ORCID http://orcid.org/0000-0003-4186-1088

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the growing aging population, technology that supports independent living is increasingly important. Web search systems are well established, whereas generative artificial intelligence (Gen-AI; eg, ChatGPT) represents a newer, adaptive tool that could offer personalized information access. However, little is known about how older adults, particularly those with mild cognitive impairment (MCI) or mild dementia, perceive and engage with these systems. Objective: This study explored the use of and perspectives on web search and Gen-AI in older adults with and without cognitive impairment (including MCI and early-stage dementia). Methods: A UK-wide mixed methods study was conducted with older adults, including those with MCI or mild dementia. An online survey captured technology use, Likert-scale ratings of web search and Gen-AI, and reasons for nonuse. Follow-up focus groups provided in-depth qualitative perspectives. Quantitative data were analyzed using descriptive and comparative statistics, while qualitative data were thematically analyzed. Results: Survey findings showed higher use of web search (275/280, 98.2%) compared to Gen-AI (40/286, 14%) within these groups. Web search was rated positively across participants, although challenges were raised regarding the phrasing of queries and commercialization. Gen-AI use was less common, but more than half of nonusers expressed willingness to adopt it in the future. Combined with focus group responses, themes exploring keyword searching, mistrust, lack of knowledge, and willingness to learn were established. Participants also suggested potential applications of Gen-AI, such as supporting independent living through monitoring and simplifying complex searches. Conclusions: Web search remains the primary method, and participants highlighted both advantages and frustrations with current systems. Gen-AI was underused but seen as promising, with its adoption mainly limited by mistrust and knowledge gaps. Our findings indicate that structured training, early introduction, and user-centered design could encourage adoption, enhance accessibility, and support independent living among older adults with and without MCI.

Indexed as

Access to InformationAgingCognitive DysfunctionDementiaAgedAged, 80 and overFemaleFocus GroupsGenerative Artificial IntelligenceHumansMaleSurveys and QuestionnairesUnited Kingdomaccessibilityagingartificial intelligenceChatGPTdementiagenerative AIinformation retrievalmild cognitive impairmentolder adultsearch

Identifiers

PMID42013397
PMCPMC13099020

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.