Evidence map›Paper›PMID 34855618›Full record

SynthesisJMIR mHealth and uHealth2021

Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review.

Antonio Muro-Culebras, Adrian Escriche-Escuder, Jaime Martin-Martin, Cristina Roldán-Jiménez, Irene De-Torres, Maria Ruiz-Muñoz, Manuel Gonzalez-Sanchez, Fermin Mayoral-Cleries, Attila Biró, Wen Tang and 3 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 6 pooled it
9.4field-weighted citation impact, top 2% 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

44 citing papers in PubMed, 6 syntheses or guidelines pooled it, 86 citations in OpenAlex.

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  4. Quality Assessment of Digital Health Apps: Umbrella Review.Journal of medical Internet research · 2024
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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

13 authors at 5 institutions in 4 countries.

Antonio Muro-Culebras *Grupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0003-2117-1813
Adrian Escriche-Escuder *Grupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0003-4402-6483
Jaime Martin-MartinGrupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0001-6143-6703
Cristina Roldán-JiménezGrupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0002-7355-9740
Irene De-TorresPhysical Medicine and Rehabilitation Unit, Regional University Hospital of Malaga, Málaga, Spain.ORCID 0000-0001-8590-4057
Maria Ruiz-MuñozGrupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0003-0454-2758
Manuel Gonzalez-SanchezGrupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0003-3993-5092
Fermin Mayoral-CleriesMental Health Unit, Regional University Hospital of Malaga, Málaga, Spain.ORCID 0000-0002-9710-9672
Attila BiróITWare, Budapest, Hungary.ORCID 0000-0002-0430-9932
Wen TangFaculty of Science and Technology, Bournemouth University, Bournemouth, United Kingdom.ORCID 0000-0001-6220-2423
Borjanka NikolovaArthaus, Skopje, Republic of North Macedonia.ORCID 0000-0002-7231-6886
Alfredo SalvatoreSensorID Snc, Boiano, Italy.ORCID 0000-0001-8256-3517
Antonio Ignacio Cuesta-VargasGrupo Clinimetría (F-14), University of Málaga, Málaga, Spain.ORCID 0000-0002-8880-4315
Instituto de Investigación Biomédica de Málaga · ESHospital Regional Universitario de Málaga · ESArtHaus (Macedonia) · MKBournemouth University · GBQueensland University of Technology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are several mobile health (mHealth) apps in mobile app stores. These apps enter the business-to-customer market with limited controls. Both, apps that users use autonomously and those designed to be recommended by practitioners require an end-user validation to minimize the risk of using apps that are ineffective or harmful. Prior studies have reviewed the most relevant aspects in a tool designed for assessing mHealth app quality, and different options have been developed for this purpose. However, the psychometric properties of the mHealth quality measurement tools, that is, the validity and reliability of the tools for their purpose, also need to be studied. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) initiative has developed tools for selecting the most suitable measurement instrument for health outcomes, and one of the main fields of study was their psychometric properties.

objectiveThis study aims to address and psychometrically analyze, following the COSMIN guideline, the quality of the tools that are used to measure the quality of mHealth apps.

methodsFrom February 1, 2019, to December 31, 2019, 2 reviewers searched PubMed and Embase databases, identifying mHealth app quality measurement tools and all the validation studies associated with each of them. For inclusion, the studies had to be meant to validate a tool designed to assess mHealth apps. Studies that used these tools for the assessment of mHealth apps but did not include any psychometric validation were excluded. The measurement tools were analyzed according to the 10 psychometric properties described in the COSMIN guideline. The dimensions and items analyzed in each tool were also analyzed.

resultsThe initial search showed 3372 articles. Only 10 finally met the inclusion criteria and were chosen for analysis in this review, analyzing 8 measurement tools. Of these tools, 4 validated ≥5 psychometric properties defined in the COSMIN guideline. Although some of the tools only measure the usability dimension, other tools provide information such as engagement, esthetics, or functionality. Furthermore, 2 measurement tools, Mobile App Rating Scale and mHealth Apps Usability Questionnaire, have a user version, as well as a professional version.

conclusionsThe Health Information Technology Usability Evaluation Scale and the Measurement Scales for Perceived Usefulness and Perceived Ease of Use were the most validated tools, but they were very focused on usability. The Mobile App Rating Scale showed a moderate number of validated psychometric properties, measures a significant number of quality dimensions, and has been validated in a large number of mHealth apps, and its use is widespread. It is suggested that the continuation of the validation of this tool in other psychometric properties could provide an appropriate option for evaluating the quality of mHealth apps.

Indexed as

Mobile ApplicationsTelemedicineConsensusHumansPsychometricsReproducibility of ResultsassessmenteHealthmHealthmobile appsmobile healthmobile phonequestionnaire designratingsmartphone

Identifiers

PMID34855618
PMCPMC8686474
OpenAlexW3118167776

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.