Evidence map›Paper›PMID 36246848›Full record

ArticleFrontiers in digital health2022

Systematic assessment of the quality and integrity of popular mental health smartphone apps using the American Psychiatric Association's app evaluation model.

Nikki S Rickard, Perin Kurt, Tanya Meade

Open access · goldAbstract read
In one paragraph

Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Nikki S RickardSchool of Psychology, Western Sydney University, Sydney, NSW, Australia.
Perin KurtSchool of Psychology, Western Sydney University, Sydney, NSW, Australia.
Tanya MeadeSchool of Psychology, Western Sydney University, Sydney, NSW, Australia.
Western Sydney University · AUMonash University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile phones are playing an increasingly important role in supporting mental health, by providing confidential, accessible and scalable support for individuals who may not seek or have means of accessing professional help. There are concerns, however, that many apps claiming to support mental health do not meet professional, ethical or evidence-based standards. App store search algorithms favour popularity (reviews and downloads) and commercial factors (in-app purchases), with what appears to be low prioritisation of safety or effectiveness features. In this paper, the most visible 100 apps for "depression", "anxiety" and/or "mood" on the Google Play and Apple App stores were selected for assessment using the American Psychiatric Association App Evaluation model. This model systematically assesses apps across five broad steps: accessibility, integrity, clinical and research evidence base, user engagement and interoperability. Assessment is hierarchical, with the most fundamental requirements of apps assessed first, with apps excluded at each step if they do not meet the criteria. The relationship between app quality and app store visibility was first analysed. App quality was also compared across four different app function types: mental health promotion or psychoeducation; monitoring or tracking; assessment or prevention; and intervention or treatment. Of the 92 apps assessed (after eight failed to meet inclusion criteria), half failed to meet the first criterion step of accessibility, and a further 20% of the remaining apps failed to meet the second criterion step of security and privacy. Only three of the 10 apps most visible on app stores met the criteria for research/clinical base and engagement/ease of use, and only one app fulfilled all five criterion steps of the evaluation model. Quality did not differ significantly across app function type. There was no significant correlation between app quality and app store visibility, which presents a potential risk to vulnerable consumers. The findings of this review highlight the need for greater accountability of app developers to meet, and report, at least minimum quality and integrity standards for their apps. Recommendations are also provided to assist users and clinicians to make informed choices in their selection of reputable and effective mental health apps.

Indexed as

anxietyapp evaluationdepressiondigital mental healthmobile application (app)moodself-helpsmartphone

Identifiers

PMID36246848
PMCPMC9561256
OpenAlexW4298145393

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.