Evidence map›Paper›PMID 35969455›Full record

ArticleJMIR cardio2022

Frameworks for Implementation, Uptake, and Use of Cardiometabolic Disease-Related Digital Health Interventions in Ethnic Minority Populations: Scoping Review.

Mel Ramasawmy, Lydia Poole, Zareen Thorlu-Bangura, Aneesha Chauhan, Mayur Murali, Parbir Jagpal, Mehar Bijral, Jai Prashar, Abigail G-Medhin, Elizabeth Murray and 16 more

Open access · goldAbstract readScoping Review
In one paragraph

Article in JMIR cardio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 5% of its field
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Strategies to promote the dissemination of psychosocial digital health resources for those affected by cancer: scoping review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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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

26 authors at 13 institutions in 1 country.

Mel RamasawmyInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-4864-8565
Lydia PooleInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-1325-7107
Zareen Thorlu-BanguraInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-8727-9718
Aneesha ChauhanCharing Cross Hospital, Imperial College Healthcare NHS Trust, London, United Kingdom.ORCID https://orcid.org/0000-0002-0686-5713
Mayur MuraliDivision of Anaesthetics, Pain Medicine, and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-2340-7810
Parbir JagpalSchool of Pharmacy, University of Birmingham, Birmingham, United Kingdom.ORCID https://orcid.org/0000-0002-0294-1571
Mehar BijralUniversity College London Medical School, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-1283-426X
Jai PrasharUniversity College London Medical School, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-1500-7427
Abigail G-MedhinDepartment of Population Health Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-6928-8493
Elizabeth MurrayeHealth Unit, Research Department of Primary Care and Population Health, University College London Medical School, London, United Kingdom.ORCID https://orcid.org/0000-0002-8932-3695
Fiona StevensoneHealth Unit, Research Department of Primary Care and Population Health, University College London Medical School, London, United Kingdom.ORCID https://orcid.org/0000-0003-2139-2309
Ann BlandfordUniversity College London Interaction Centre, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-3198-7122
Henry W W PottsInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-6200-8804
Kamlesh KhuntiDiabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, United Kingdom.ORCID https://orcid.org/0000-0003-2343-7099
Wasim HanifDepartment of Diabetes and Institute of Translational Medicine, University Hospital Birmingham, Birmingham, United Kingdom.ORCID https://orcid.org/0000-0003-2133-7465
Paramjit GillDivision of Health Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom.ORCID https://orcid.org/0000-0001-8756-6813
Madiha SajidPatient and Public Involvement Representative, DISC Study (UK), United Kingdom.ORCID https://orcid.org/0000-0001-6294-2595
Kiran PatelDivision of Health Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom.ORCID https://orcid.org/0000-0002-4355-8114
Harpreet SoodHealth Education England, London, United Kingdom.ORCID https://orcid.org/0000-0002-2280-7345
Neeraj BhalaQueen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.ORCID https://orcid.org/0000-0003-2502-1177
Shivali ModhaPatient and Public Involvement Representative, DISC Study (UK), United Kingdom.ORCID https://orcid.org/0000-0001-5588-3603
Manoj MistryPatient and Public Involvement Representative, DISC Study (UK), United Kingdom.ORCID https://orcid.org/0000-0002-8174-636X
Vinod PatelWarwick Medical School, University of Warwick, Coventry, United Kingdom.ORCID https://orcid.org/0000-0001-7336-9341
Sarah N AliDepartment of Diabetes and Endocrinology, Royal Free London NHS Foundation Trust, London, United Kingdom.ORCID https://orcid.org/0000-0002-3948-4917
Aftab AlaDepartment of Access and Medicine, Royal Surrey NHS Foundation Trust, Guildford, United Kingdom.ORCID https://orcid.org/0000-0001-6257-3160
Amitava BanerjeeInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-8741-3411
University College London · GBUniversity of Warwick · GBHealth Education England · GBImperial College Healthcare NHS Trust · GBImperial College London · GBKing's College London · GBLondon Centre for Nanotechnology · GBRoyal Free London NHS Foundation Trust · GBUniversity Hospitals Birmingham NHS Foundation Trust · GBUniversity Hospitals Coventry and Warwickshire NHS Trust · GBUniversity of Birmingham · GBUniversity of Leicester · GBUniversity of Surrey · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital health interventions have become increasingly common across health care, both before and during the COVID-19 pandemic. Health inequalities, particularly with respect to ethnicity, may not be considered in frameworks that address the implementation of digital health interventions. We considered frameworks to include any models, theories, or taxonomies that describe or predict implementation, uptake, and use of digital health interventions.

objectiveWe aimed to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake, and use of digital health interventions; health and ethnic inequalities; and interventions for cardiometabolic disease.

methodsSCOPUS, PubMed, EMBASE, Google Scholar, and gray literature were searched to identify papers on frameworks relevant to the implementation, uptake, and use of digital health interventions; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which frameworks address health inequalities, specifically ethnic inequalities; explored how they were addressed; and developed recommendations for good practice.

resultsOf 58 relevant papers, 22 (38%) included frameworks that referred to health inequalities. Inequalities were conceptualized as society-level, system-level, intervention-level, and individual. Only 5 frameworks considered all levels. Three frameworks considered how digital health interventions might interact with or exacerbate existing health inequalities, and 3 considered the process of health technology implementation, uptake, and use and suggested opportunities to improve equity in digital health. When ethnicity was considered, it was often within the broader concepts of social determinants of health. Only 3 frameworks explicitly addressed ethnicity: one focused on culturally tailoring digital health interventions, and 2 were applied to management of cardiometabolic disease.

conclusionsExisting frameworks evaluate implementation, uptake, and use of digital health interventions, but to consider factors related to ethnicity, it is necessary to look across frameworks. We have developed a visual guide of the key constructs across the 4 potential levels of action for digital health inequalities, which can be used to support future research and inform digital health policies.

Indexed as

cardiologycardiometabolicculturaldigital healthdiversediversityeHealthethnicityframeworkhealth inequalitieshealth inequalityhealth technologymetabolicmetabolismminorityreview

Identifiers

PMID35969455
PMCPMC9412726
OpenAlexW4226307367

What OpenQuestion 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 OpenQuestion graph.