Evidence map›Paper›PMID 40093705›Full record

ReviewDigital health

Quality evaluation and functional classification of Arabic health apps: A systematic review.

Asma Am Abahussin, Ahmed Aa Alnakhibi, Bandar Ma Alfulaij

Abstract readReview
In one paragraph

Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Asma Am AbahussinDepartment of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.ORCID https://orcid.org/0000-0002-7831-1445
Ahmed Aa AlnakhibiDepartment of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Bandar Ma AlfulaijDepartment of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The study aimed to systematically review mHealth apps available for Arabic speakers regarding quality and functional classification. Methods: A systematic search was conducted on the Apple App Store. Eligible apps were downloaded and tested thoroughly and rated independently by two reviewers using the Mobile App Rating Scale (MARS). The National Institute for Health and Care Excellence (NICE) evidence standards framework for evaluating Digital Health Technologies (DHTs) was used to perform the functional classification for the included apps. Results: Sixty-one health-related apps met the eligibility criteria and were included in the study. The average overall MARS score across all apps was 4.03 ( Conclusion: This work summarises the current state of available free-of-charge mHealth apps for Arabic speakers on the Apple App Store by highlighting their quality and coverage of functionalities and areas of health. In general, most of the apps were considered to be of decent quality but with partially limited functions and coverage of health conditions. Developers of future Arabic health apps should focus on engagement and aesthetic features, employing more advanced functions and supporting a wide range of health interventions.

Indexed as

appsArabicclassificationfunctionsMARSmHealthMobile applicationsmobile healthNICEquality

Identifiers

PMID40093705
PMCPMC11907622

What OpenQuestion holds

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LicenceCC BY-NC
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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.