Evidence map›Paper›PMID 34463623›Full record

ArticleJMIR mHealth and uHealth2021

Promoting Health via mHealth Applications Using a French Version of the Mobile App Rating Scale: Adaptation and Validation Study.

Ina Saliasi, Prescilla Martinon, Emily Darlington, Colette Smentek, Delphine Tardivo, Denis Bourgeois, Claude Dussart, Florence Carrouel, Laurie Fraticelli

Abstract read
In one paragraph

Article 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 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 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

9 authors.

Ina Saliasi *Health, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0003-1151-2653
Prescilla Martinon *Health, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0002-2958-9256
Emily DarlingtonHealth, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0001-8671-2022
Colette SmentekHealth, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0002-7266-3351
Delphine TardivoLaboratory Anthropology, Health Law, and Medical Ethics, UMR 7268, Aix-Marseille University 2, Marseille, France.ORCID 0000-0003-2952-4425
Denis BourgeoisHealth, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0003-4754-2512
Claude DussartHealth, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0002-1091-9139
Florence Carrouel *Health, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0002-6823-1636
Laurie Fraticelli *Health, Systemic, Process, Research Unit 4129, University Claude Bernard Lyon 1, University of Lyon, Lyon, France.ORCID 0000-0002-2647-658X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the recent decades, the number of apps promoting health behaviors and health-related strategies and interventions has increased alongside the number of smartphone users. Nevertheless, the validity process for measuring and reporting app quality remains unsatisfactory for health professionals and end users and represents a public health concern. The Mobile Application Rating Scale (MARS) is a tool validated and widely used in the scientific literature to evaluate and compare mHealth app functionalities. However, MARS is not adapted to the French culture nor to the language.

objectiveThis study aims to translate, adapt, and validate the equivalent French version of MARS (ie, MARS-F).

methodsThe original MARS was first translated to French by two independent bilingual scientists, and their common version was blind back-translated twice by two native English speakers, culminating in a final well-established MARS-F. Its comprehensibility was then evaluated by 6 individuals (3 researchers and 3 nonacademics), and the final MARS-F version was created. Two bilingual raters independently completed the evaluation of 63 apps using MARS and MARS-F. Interrater reliability was assessed using intraclass correlation coefficients. In addition, internal consistency and validity of both scales were assessed. Mokken scale analysis was used to investigate the scalability of both MARS and MARS-F.

resultsMARS-F had a good alignment with the original MARS, with properties comparable between the two scales. The correlation coefficients (r) between the corresponding dimensions of MARS and MARS-F ranged from 0.97 to 0.99. The internal consistencies of the MARS-F dimensions engagement (ω=0.79), functionality (ω=0.79), esthetics (ω=0.78), and information quality (ω=0.61) were acceptable and that for the overall MARS score (ω=0.86) was good. Mokken scale analysis revealed a strong scalability for MARS (Loevinger H=0.37) and a good scalability for MARS-F (H=0.35).

conclusionsMARS-F is a valid tool, and it would serve as a crucial aid for researchers, health care professionals, public health authorities, and interested third parties, to assess the quality of mHealth apps in French-speaking countries.

Indexed as

Mobile ApplicationsTelemedicineHealth BehaviorHumansLanguageReproducibility of Resultsapplication validationdigital healthdigital health toolseHealthhealth applicationsMARSmHealthmHealth applicationsMobile App Rating Scalemobile healthmobile health appsquality assessment toolrating scale evolutionvalidation

Identifiers

PMID34463623
PMCPMC8441605

What OpenQuestion holds

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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.