Evidence map›Paper›PMID 32729839›Full record

ArticleJMIR mHealth and uHealth2020

Barriers to and Facilitators of the Prescription of mHealth Apps in Australian General Practice: Qualitative Study.

Oyungerel Byambasuren, Elaine Beller, Tammy Hoffmann, Paul Glasziou

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 5 pooled it
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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

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

54 citing papers in PubMed, 5 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

4 authors.

Oyungerel Byambasuren *Institute for Evidence-Based Healthcare, Bond University, Robina, Australia.ORCID 0000-0002-8641-1286
Elaine BellerInstitute for Evidence-Based Healthcare, Bond University, Robina, Australia.ORCID 0000-0002-3241-2611
Tammy HoffmannInstitute for Evidence-Based Healthcare, Bond University, Robina, Australia.ORCID 0000-0001-5210-8548
Paul GlasziouInstitute for Evidence-Based Healthcare, Bond University, Robina, Australia.ORCID 0000-0001-7564-073X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ubiquity of smartphones and health apps make them a potential self-management tool for patients that could be prescribed by medical professionals. However, little is known about how Australian general practitioners and their patients view the possibility of prescribing mobile health (mHealth) apps as a nondrug intervention.

objectiveThis study aimed to determine barriers and facilitators to prescribing mHealth apps in Australian general practice from the perspective of general practitioners and their patients.

methodsWe conducted semistructured interviews in Australian general practice settings with purposively sampled general practitioners and patients. The audio-recorded interviews were transcribed, coded, and thematically analyzed by two researchers.

resultsInterview participants included 20 general practitioners and 15 adult patients. General practitioners' perceived barriers to prescribing apps included a generational difference in the digital propensity for providers and patients; lack of knowledge of prescribable apps and trustworthy sources to access them; the time commitment required of providers and patients to learn and use the apps; and concerns about privacy, safety, and trustworthiness of health apps. General practitioners perceived facilitators as trustworthy sources to access prescribable apps and information, and younger generation and widespread smartphone ownership. For patients, the main barriers were older age and usability of mHealth apps. Patients were not concerned about privacy and data safety issues regarding health app use. Facilitators for patients included the ubiquity of smartphones and apps, especially for the younger generation and recommendation of apps by doctors. We identified evidence of effectiveness as an independent theme from both the provider and patient perspectives.

conclusionsmHealth app prescription appears to be feasible in general practice. The barriers and facilitators identified by the providers and patients overlapped, though privacy was of less concern to patients. The involvement of health professionals and patients is vital for the successful integration of effective, evidence-based mHealth apps with clinical practice.

Indexed as

General PracticeMobile ApplicationsTelemedicineAdultAustraliaFemaleHumansMaleMiddle AgedPrescriptionsapp prescriptionappsgeneral practicemHealthmobile apps

Identifiers

PMID32729839
PMCPMC7426799

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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.