Evidence map›Paper›PMID 42190266›Full record

ArticleJMIR human factors2026

Perspectives and Needs Regarding Remote Monitoring Technologies Among South Asian Individuals Living With Long-Term Conditions in the United Kingdom: Semistructured Interview and Focus Group Study.

Syed Mustafa Ali, Yumna Masood, Karen Staniland, William G Dixon, Sabine N van der Veer, Caroline Sanders

Abstract read
In one paragraph

Article in JMIR human factors, 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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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

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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

6 authors.

Syed Mustafa Ali *Division of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, The University of Manchester, Portsmouth St, Manchester, M13 9GB, United Kingdom, +44 161 306 7876.ORCID 0000-0001-9393-9049
Yumna Masood *Division of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, The University of Manchester, Portsmouth St, Manchester, M13 9GB, United Kingdom, +44 161 306 7876.ORCID 0000-0002-0903-6945
Karen StanilandDivision of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, The University of Manchester, Portsmouth St, Manchester, M13 9GB, United Kingdom, +44 161 306 7876.ORCID 0000-0002-4175-8649
William G DixonDivision of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, The University of Manchester, Portsmouth St, Manchester, M13 9GB, United Kingdom, +44 161 306 7876.ORCID 0000-0001-5881-4857
Sabine N van der VeerDivision of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, The University of Manchester, Portsmouth St, Manchester, M13 9GB, United Kingdom, +44 161 306 7876.ORCID 0000-0003-0929-436X
Caroline SandersNational Institute for Health and Care Research (NIHR) Applied Research Collaboration - Greater Manchester (ARC-GM), Manchester, United Kingdom.ORCID 0000-0002-0539-928X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: South Asian individuals face a higher burden of long-term conditions while also experiencing more inequities in health care access and outcomes. Despite the potential of remote monitoring technologies to improve management of long-term conditions, South Asian individuals are less likely to engage with digital health interventions and are underrepresented in health research, partly due to language barriers. Objective: This study explored the perspectives and needs regarding remote monitoring technologies of South Asian individuals living with a long-term condition in the United Kingdom who did not have English as their first language. We used Pakistanis as an example subgroup of South Asian individuals and rheumatoid arthritis and early inflammatory arthritis as example long-term conditions. Methods: We conducted semistructured interviews and a focus group discussion with Pakistani adults diagnosed with rheumatoid or early inflammatory arthritis who did not have English as their first language. Audio-recordings were transcribed verbatim, deidentified, and analyzed thematically. Results: Seventeen adults participated in this study (n=9, 53% in an individual interview and n=8, 47% in the focus group); none of them had previous experience of remote monitoring technologies. We identified three themes: (1) the perceived value and challenges of using remote monitoring technologies for disease self-management, (2) differences in perceived needs and capacity for using remote monitoring technologies between first- and later-generation immigrants related to social determinants, and (3) the role of community and family support in using remote monitoring technologies. Participants perceived remote monitoring technologies as useful, particularly where they were dissatisfied with current health care services. Language and the role of family and community members in supporting technology use were considered important factors, but needs in these areas varied between first-generation (migrated to the United Kingdom) and second- or third-generation immigrants (born in the United Kingdom to parents or grandparents who migrated to the United Kingdom). For first-generation immigrants, these factors intersected with other social and digital determinants, such as gender and literacy, resulting in additional requirements. Conclusions: Addressing language and literacy barriers, alongside leveraging family and community support, will contribute to equitable remote monitoring technologies to facilitate self-managing long-term conditions among South Asian ethnic minority groups. Future efforts should focus on developing tailored, culturally responsive approaches, particularly for first-generation immigrants, to ensure remote monitoring technologies decrease rather than exacerbate existing ethnic health inequities.

Indexed as

AdultAgedChronic DiseaseDigital HealthFemaleFocus GroupsHumansInterviews as TopicMaleMiddle AgedPakistanQualitative ResearchRemote Patient MonitoringSouth Asian PeopleUnited Kingdomdigital inclusionethnic health inequalitieslanguage barrierspatient-generated health dataremote monitoringSouth Asian individuals

Identifiers

PMID42190266
PMCPMC13211867

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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.