Evidence map›Paper›PMID 42062924›Full record

ArticleBMC geriatrics2026

Educating older adults to use technologies for health management in social settings: perspectives of older adults and community workers.

Ting Liu, Yiming Luo, Patrick Pang, Ying Lau

Abstract read
In one paragraph

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

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0cells of the map it votes in
0citing papers in PubMed
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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

4 authors.

Ting LiuFaculty of Applied Sciences, Macao Polytechnic University, Macao, Macao, Special Administrative Region of China.ORCID 0009-0001-0331-262X
Yiming LuoFaculty of Applied Sciences, Macao Polytechnic University, Macao, Macao, Special Administrative Region of China.ORCID 0009-0002-6117-738X
Patrick PangFaculty of Applied Sciences, Macao Polytechnic University, Macao, Macao, Special Administrative Region of China. mail@patrickpang.net.ORCID 0000-0002-8820-5443
Ying LauThe Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong S.A.R.ORCID 0000-0002-8289-3441

Funding

Macao Polytechnic University RP/FCA-10/2022
6 · The paper itself

Abstract

backgroundWith the acceleration of global aging, the potential of digital technologies for self-care management among older adults has surged. Older adults often face numerous difficulties and challenges when seeking health information, including issues related to technology adaptability and the complexity of the social learning environment. In addressing these challenges, Bandura's Social Learning Theory framework offers a robust theoretical foundation for resolving these dilemmas.

methodsThis research employs focus groups and semi-structured interviews with 20 older adults and 6 community workers on four occasions. Qualitative data were analyzed using Braun and Clarke's six-phase reflexive thematic analysis to identify key themes.

resultsOlder adults learn to utilize technology for health management through peer imitation and community workers. Community workers' lack of systematic training results in a limited range of technologies. The complexity of technology and the absence of family support were found to weaken older adults' self-efficacy, while community workers struggled to provide in-depth guidance due to resource constraints. While encouraging short-term participation, over-reliance on incentives can lead to instrumental motivation. Both older adults and workers called for an age-friendly design, highlighting inadequate community equipment and weak promotional activities as critical issues that need to be addressed.

conclusionThe needs of older adults and community workers in utilizing technology for health exhibit a multi-layered interaction. Older adults require simplified technologies and social support, and community workers demand technical training and policy backing. The study's findings support a reframing of immediate recommendations towards age-friendly design, structured training for community workers, and policy support for resources. Developing artificial intelligence-assisted tools is a potential long-term direction inferred from the broader need for scalable and personalized support, thereby narrowing the technology gaps for older adults.

Indexed as

Community Health WorkersSelf CareSocial EnvironmentAgedAged, 80 and overDigital HealthFemaleFocus GroupsHumansMaleMiddle AgedCommunity workersDigital technologiesHealth educationOlder adultsSocial learning theory

Identifiers

PMID42062924
PMCPMC13281290

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.