Evidence map›Paper›PMID 38315515›Full record

ArticleJournal of medical Internet research2024

Mapping Theories, Models, and Frameworks to Evaluate Digital Health Interventions: Scoping Review.

Geneviève Rouleau, Kelly Wu, Karishini Ramamoorthi, Cherish Boxall, Rebecca H Liu, Shelagh Maloney, Jennifer Zelmer, Ted Scott, Darren Larsen, Harindra C Wijeysundera and 5 more

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 3 pooled it
–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

29 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

15 authors.

Geneviève RouleauNursing department, Université du Québec en Outaouais, Saint-Jérôme, QC, Canada.ORCID 0000-0003-1093-6577
Kelly WuInstitute for Health System Solutions and Virtual Care Toronto, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0002-9805-5514
Karishini RamamoorthiInstitute for Health System Solutions and Virtual Care Toronto, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0002-7066-0560
Cherish BoxallSouthampton Clinical Trials Unit, University of Southampton, Southampton, United Kingdom.ORCID 0000-0002-7850-233X
Rebecca H LiuInstitute for Health System Solutions and Virtual Care Toronto, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0002-3946-4035
Shelagh MaloneyCanada Infoway, Toronto, ON, Canada.ORCID 0009-0001-7298-6900
Jennifer ZelmerHealthcare Excellence Canada, Ottawa, ON, Canada.ORCID 0000-0002-1556-6686
Ted ScottSchool of Nursing, Hamilton Health Sciences, McMaster University, Hamilton, ON, Canada.ORCID 0000-0002-6190-050X
Darren LarsenTelus Healthcare Delivery, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0003-0614-4251
Harindra C WijeysunderaSchulich Heart Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.ORCID 0000-0001-8464-1080
Daniela ZieglerCentre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.ORCID 0000-0002-7210-5296
Sacha BhatiaOntario Health, Toronto, ON, Canada.ORCID 0000-0001-6206-5318
Vanessa KishimotoInstitute for Health System Solutions and Virtual Care Toronto, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0002-4516-1225
Carolyn Steele GrayLunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada.ORCID 0000-0002-2146-0001
Laura DesveauxInstitute for Health System Solutions and Virtual Care Toronto, Women's College Hospital, Toronto, ON, Canada.ORCID 0000-0003-3429-1865

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital health interventions (DHIs) are a central focus of health care transformation efforts, yet their uptake in practice continues to fall short of their potential. In order to achieve their desired outcomes and impact, DHIs need to reach their target population and need to be used. Many factors can rapidly intersect between this dynamic of users and interventions. The application of theories, models, and frameworks (TMFs) can facilitate the systematic understanding and explanation of the complex interactions between users, practices, technology, and health system factors that underpin research questions. There remains a gap in our understanding of how TMFs have been applied to guide the evaluation of DHIs with real-world health system operations.

objectiveThis study aims to map TMFs used in studies to guide the evaluation of DHIs. The objectives are to (1) describe the TMFs and the constructs they target, (2) identify how TMFs have been prospectively used (ie, their roles) in primary studies to evaluate DHIs, and (3) to reflect on the relevance and utility of our findings for knowledge users.

methodsThis scoping review was conducted in partnership with knowledge users using an integrated knowledge translation approach. We included papers (eg, reports; empirical quantitative, qualitative, and mixed methods studies; conference proceedings; and dissertations) if primary insights resulting from the application of TMFs were presented. Any type of DHI was eligible. Papers published from 2000 and onward were mainly identified from the following databases: MEDLINE (Ovid), CINAHL Complete (EBSCOhost), PsycINFO (Ovid), EBM Reviews (Ovid), and Embase (Ovid).

resultsA total of 156 studies published between 2000 and 2022 were included. A total of 68 distinct TMFs were identified across 85 individual studies. In more than half (85/156, 55%) of the included studies, 1 of following 6 prevailing TMFs were reported: Consolidated Framework for Implementation Research (n=39); the Reach, Effectiveness, Adoption, Implementation, and Maintenance Framework (n=17); the Technology of Acceptance Model (n=16); the Unified Theory on Acceptance and Use of Technology (n=12); the Diffusion of Innovation Theory (n=10); and Normalization Process Theory (n=9). The most common intended roles of the 6 TMFs were to inform data collection (n=86), to inform data analysis (n=69), and to identify key constructs that may serve as barriers and facilitators (n=52).

conclusionsAs TMFs are most often reported to be applied to support data collection and analysis, researchers should consider more clearly synthesizing key insights as practical use cases to both increase the relevance and digestibility of their findings. There is also a need to adapt or develop guidelines for better reporting DHIs and the use of TMFs to guide evaluation. Hence, it would contribute to ensuring ongoing technology transformation efforts are evidence and theory informed rather than anecdotally driven.

Indexed as

Digital HealthTelemedicineHumansdigital health interventionsevaluationframeworksimplementationintegrated knowledge translation, theoriesmodelsscoping review

Identifiers

PMID38315515
PMCPMC10877497

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.