Evidence map›Paper›PMID 35675111›Full record

ArticleJournal of medical Internet research2022

Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework.

Yang Yang, Elisabeth Boulton, Chris Todd

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 4 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, 4 syntheses or guidelines pooled it.

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  13. Effectiveness of mobile health interventions on physical activity management in frail older adults: a systematic review and meta-analysis.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2026
    Review
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  18. Staying engaged: a scoping review of psychological and motivational drivers of adherence to technology-supported physical activity in older adults.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2025
    Review
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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

3 authors.

Yang YangSchool of Health Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-2283-5266
Elisabeth BoultonSchool of Health Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0003-2791-8295
Chris ToddSchool of Health Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0001-6645-4505

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.

objectiveOur primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.

methodsMEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.

resultsIn total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.

conclusionsThis study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

Indexed as

Mobile ApplicationsTelemedicineAdolescentAdultExerciseHealth BehaviorHumansTechnologyadherenceframeworkmHealthmobile healthmobile phonephysical activityscoping review

Identifiers

PMID35675111
PMCPMC9218881

What Socratic 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 Socratic graph.