Evidence map›Paper›PMID 33787894›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2021

Scoping review: Development and assessment of evaluation frameworks of mobile health apps for recommendations to consumers.

Martin Hensher, Paul Cooper, Sithara Wanni Arachchige Dona, Mary Rose Angeles, Dieu Nguyen, Natalie Heynsbergh, Mary Lou Chatterton, Anna Peeters

Abstract readScoping Review
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Quality Assessment of Digital Health Apps: Umbrella Review.Journal of medical Internet research · 2024
    Pooled it
  3. Pooled it
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  19. Current challenges for evaluating mobile health applications.Journal of the American Medical Informatics Association : JAMIA · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Martin HensherInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Paul CooperInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Sithara Wanni Arachchige DonaInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Mary Rose AngelesInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.ORCID 0000-0001-5660-9198
Dieu NguyenInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Natalie HeynsberghInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Mary Lou ChattertonInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Anna PeetersInstitute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe study sought to review the different assessment items that have been used within existing health app evaluation frameworks aimed at individual, clinician, or organizational users, and to analyze the scoring and evaluation methods used in these frameworks. MATERIALS AND

methodsWe searched multiple bibliographic databases and conducted backward searches of reference lists, using search terms that were synonyms of "health apps," "evaluation," and "frameworks." The review covered publications from 2011 to April 2020. Studies on health app evaluation frameworks and studies that elaborated on the scaling and scoring mechanisms applied in such frameworks were included.

resultsTen common domains were identified across general health app evaluation frameworks. A list of 430 assessment criteria was compiled across 97 identified studies. The most frequently used scaling mechanism was a 5-point Likert scale. Most studies have adopted summary statistics to generate the total scoring of each app, and the most popular approach taken was the calculation of mean or average scores. Other frameworks did not use any scaling or scoring mechanism and adopted criteria-based, pictorial, or descriptive approaches, or "threshold" filter. DISCUSSION: There is wide variance in the approaches to evaluating health apps within published frameworks, and this variance leads to ongoing uncertainty in how to evaluate health apps.

conclusionsA new evaluation framework is needed that can integrate the full range of evaluative criteria within one structure, and provide summative guidance on health app rating, to support individual app users, clinicians, and health organizations in choosing or recommending the best health app.

Indexed as

Mobile ApplicationsTelemedicinePublicationsResearch Designassessment criteriaevaluation frameworkhealth appsscoring and scaling

Identifiers

PMID33787894
PMCPMC8263081

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.