Evidence map›Paper›PMID 34982717›Full record

ArticleJMIR mHealth and uHealth2022

Multipurpose Mobile Apps for Mental Health in Chinese App Stores: Content Analysis and Quality Evaluation.

Xiaoqian Wu, Lin Xu, PengFei Li, TingTing Tang, Cheng Huang

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

12 citing papers in PubMed, 20 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Xiaoqian WuCollege of Medical Informatics, Chongqing Medical University, Chongqing, China.ORCID 0000-0001-6416-2445
Lin XuCollege of Medical Informatics, Chongqing Medical University, Chongqing, China.ORCID 0000-0002-2678-0493
PengFei LiSchool of Public Health, Weifang Medical University, Weifang, China.ORCID 0000-0001-9935-616X
TingTing TangThe Children's Hospital of Chongqing Medical University, Chongqing, China.ORCID 0000-0002-1353-906X
Cheng HuangCollege of Medical Informatics, Chongqing Medical University, Chongqing, China.ORCID 0000-0001-7937-7166
Chongqing Medical University · CNChildren's Hospital of Chongqing Medical University · CNWeifang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental disorders impose varying degrees of burden on patients and their surroundings. However, people are reluctant to take the initiative to seek mental health services because of the uneven distribution of resources and stigmatization. Thus, mobile apps are considered an effective way to eliminate these obstacles and improve mental health awareness.

objectiveThis study aims to evaluate the quality, function, privacy measures, and evidence-based and professional background of multipurpose mental health apps in Chinese commercial app stores.

methodsA systematic search was conducted on iOS and Android platforms in China to identify multipurpose mental health apps. Two independent reviewers evaluated the identified mobile apps using the Mobile App Rating Scale (MARS). Each app was downloaded, and the general characteristics, privacy and security measures, development background, and functional characteristics of each app were evaluated.

resultsA total of 40 apps were analyzed, of which 35 (87.5%) were developed by companies and 33 (82.5%) provided links to access the privacy policy; 21 (52.5%) apps did not mention the involvement of relevant professionals or the guidance of a scientific basis in the app development process. The main built-in functions of these apps include psychological education (38/40, 95%), self-assessment (34/40, 85%), and counseling (33/40, 82.5%). The overall quality average MARS score of the 40 apps was 3.54 (SD 0.39), and the total score was between 2.96 and 4.30. The total MARS score was significantly positively correlated with the scores of each subscale (r=0.62-0.88, P<.001). However, the user score of the app market was not significantly correlated with the total MARS score (r=0.17, P=.33).

conclusionsThe quality of multipurpose mental health apps in China's main app market is generally good. However, health professionals are less involved in the development of these apps, and the privacy protection policy of the apps also needs to be described in more detail. This study provides a reference for the development of multipurpose mental health apps.

Indexed as

Mobile ApplicationsChinaDelivery of Health CareHumansMental HealthPrivacyappcontent analysismental healthmHealthmobile apps

Identifiers

PMID34982717
PMCPMC8767465
OpenAlexW3215623818

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.