Evidence map›Paper›PMID 39723998›Full record

ArticleJMIR formative research2024

Engagement With Digital Health Technologies Among Older People Living in Socially Deprived Areas: Qualitative Study of Influencing Factors.

Helen Chadwick, Louise Laverty, Robert Finnigan, Robert Elias, Ken Farrington, Fergus J Caskey, Sabine N van der Veer

Abstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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  5. Review
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

7 authors.

Helen ChadwickDivision of Informatics, Imaging and Data Sciences, Manchester Academic Health Science Centre, The University of Manchester, Vaughan House, Portsmouth Street, Manchester, M13 9GB, United Kingdom, 44 1613067767.ORCID 0000-0001-6465-8002
Louise LavertyDivision of Informatics, Imaging and Data Sciences, Manchester Academic Health Science Centre, The University of Manchester, Vaughan House, Portsmouth Street, Manchester, M13 9GB, United Kingdom, 44 1613067767.ORCID 0000-0002-8491-8171
Robert FinniganNHS England North West Kidney Network, Manchester, United Kingdom.ORCID 0009-0004-0697-6757
Robert EliasKing's Kidney Care, Kings College Hospital NHS Foundation Trust, London, United Kingdom.ORCID 0000-0002-3703-906X
Ken FarringtonCentre for Health Services and Clinical Research, The University of Hertfordshire, Hatfield, United Kingdom.ORCID 0000-0001-8862-6056
Fergus J CaskeyBristol Medical School, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-5199-3925
Sabine N van der VeerDivision of Informatics, Imaging and Data Sciences, Manchester Academic Health Science Centre, The University of Manchester, Vaughan House, Portsmouth Street, Manchester, M13 9GB, United Kingdom, 44 1613067767.ORCID 0000-0003-0929-436X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The potential benefits of incorporating digital technologies into health care are well documented. For example, they can improve access for patients living in remote or underresourced locations. However, despite often having the greatest health needs, people who are older or living in more socially deprived areas may be less likely to have access to these technologies and often lack the skills to use them. This puts them at risk of experiencing further health inequities. In addition, we know that digital health inequities associated with older age may be compounded by lower socioeconomic status. Yet, there is limited research on the intersectional barriers and facilitators for engagement with digital health technology by older people who are particularly marginalized. Objective: This study aimed to explore factors influencing engagement with digital health technologies among people at the intersection of being older and socially deprived. Methods: We conducted semistructured interviews with people who were 70 years or older, living in a socially deprived area, or both. Chronic kidney disease was our clinical context. We thematically analyzed interview transcripts using the Unified Theory of Acceptance and Use of Technology as a theoretical framework. Results: We interviewed 26 people. The majority were White British (n=20) and had moderate health and digital literacy levels (n=10 and n=11, respectively). A total of 13 participants were 70 years of age or older and living in a socially deprived area. Across participants, we identified 2 main themes from the interview data. The first showed that some individuals did not use digital health technologies due to a lack of engagement with digital technology in general. The second theme indicated that people felt that digital health technologies were "not for them." We identified the following key engagement factors, with the first 2 particularly impacting participants who were both older and socially deprived: lack of opportunities in the workplace to become digitally proficient; lack of appropriate support from family and friends; negative perceptions of age-related social norms about technology use; and reduced intrinsic motivation to engage with digital health technology because of a perceived lack of relevant benefits. Participants on the intersection of older age and social deprivation also felt significant anxiety around using digital technology and reported a sense of distrust toward digital health care. Conclusions: We identified factors that may have a more pronounced negative impact on the health equity of older people living in socially deprived areas compared with their counterparts who only have one of these characteristics. Successful implementation of digital health interventions therefore warrants dedicated strategies for managing the digital health equity impact on this group. Future studies should further develop these strategies and investigate their effectiveness, as well as explore the influence of related characteristics, such as educational attainment and ethnicity.

Indexed as

Digital TechnologyQualitative ResearchAgedAged, 80 and overDigital HealthFemaleHumansInterviews as TopicMalePoverty Areasageddigital healthhealth equityintersectionality, qualitative researchsocial deprivation

Identifiers

PMID39723998
PMCPMC11694154

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Registered trials

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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.