Evidence map›Paper›PMID 33777705›Full record

ArticleInternet interventions2021

Evaluating the quality and safety of health-related apps and e-tools: Adapting the Mobile App Rating Scale and developing a quality assurance protocol.

Anna E Roberts, Tracey A Davenport, Toby Wong, Hyei-Won Moon, Ian B Hickie, Haley M LaMonica

Abstract read
In one paragraph

Article in Internet interventions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  8. Frameworks for assessing digital health technologies: a scoping review.International journal of technology assessment in health care · 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

6 authors.

Anna E RobertsBrain and Mind Centre, The University of Sydney. Sydney, NSW, Australia.
Tracey A DavenportBrain and Mind Centre, The University of Sydney. Sydney, NSW, Australia.
Toby WongBrain and Mind Centre, The University of Sydney. Sydney, NSW, Australia.
Hyei-Won MoonBrain and Mind Centre, The University of Sydney. Sydney, NSW, Australia.
Ian B HickieBrain and Mind Centre, The University of Sydney. Sydney, NSW, Australia.
Haley M LaMonicaBrain and Mind Centre, The University of Sydney. Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhilst apps and e-tools have tremendous potential as low-cost, scalable mental health intervention and prevention tools, it is essential that consumers and health professionals have a means by which to evaluate their quality and safety.

objectiveThis study aimed to: 1) adapt the original Mobile App Rating Scale (MARS) in order to be appropriate for the evaluation of both mobile phone applications as well as e-tools; 2) test the reliability of the revised scale; and 3) develop a quality assurance protocol for identifying and rating new apps and e-tools to determine appropriateness for use in clinical practice.

methodsThe MARS was adapted to include items specific to health-related apps and e-tools, such as the availability of resources, strategies for self-management, and quality information. The 41 apps and e-tools in the standard youth configuration of the InnoWell Platform, a digital tool designed to support or enhance mental health service delivery, were independently rated by two expert raters using the A-MARS. Cronbach's alpha was used to calculate the internal consistency and interclass correlation coefficients were used to calculate interrater reliability.

resultsThe A-MARS was shown to be a reliable scale with acceptable to excellent internal consistency and moderate to excellent interrater reliability across the subscales. Given the ever-increasing number of health information technologies on the market, a protocol to identify and rate new apps and e-tools for potential clinical use is presented.

conclusionsWhilst the A-MARS is a useful tool to guide health professionals as they explore available apps and e-tools for potential clinical use, the training, time, and skill required to use it effectively may be prohibitive. As such, health professionals and services are likely to benefit from including a digital navigator as part of the care team to assist in selecting and rating apps and e-tools, increasing the usability of the data, and technology troubleshooting. When selecting, evaluating and/or recommending apps and e-tools to consumers, it is important to consider: 1) the availability of explicit strategies to set, monitor and review SMART goals; 2) the accessibility of credible, user friendly information and resources from reputable sources; 3) evidence of effectiveness; and 4) interoperability with other health information technologies.

Indexed as

AppsDigital toolsMental healthMobile healthQuality assuranceTechnology

Identifiers

PMID33777705
PMCPMC7985461

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.