Evidence map›Paper›PMID 37999950›Full record

ArticleJMIR mHealth and uHealth2023

The Most Popular Commercial Weight Management Apps in the Chinese App Store: Analysis of Quality, Features, and Behavior Change Techniques.

Lan Geng, Genyan Jiang, Lingling Yu, Yueming Xu, Wei Huang, Zhiqi Chen, Xiaoyan Qi, Ting Zhang, Mei Zhao

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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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.

Lan Geng *School of Nursing, Anhui Medical University, Hefei, China.ORCID 0009-0004-0956-6446
Genyan Jiang *School of Nursing, Anhui Medical University, Hefei, China.ORCID 0009-0007-6139-0574
Lingling YuSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0009-0000-7911-3208
Yueming XuSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0009-0003-7296-9144
Wei HuangSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0000-0002-2814-3471
Zhiqi ChenSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0009-0003-4469-2758
Xiaoyan QiSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0000-0001-9588-6278
Ting ZhangSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0000-0001-7942-8971
Mei ZhaoSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0000-0003-3530-0233

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany smartphone apps designed to assist individuals in managing their weight are accessible, but the assessment of app quality and features has predominantly taken place in Western countries. Nevertheless, there is a scarcity of research evaluating weight management apps in China, which highlights the need for further investigation in this area.

objectiveThis study aims to conduct a comprehensive search for the most popular commercial Chinese smartphone apps focused on weight management and assess their quality, behavior change techniques (BCTs), and content-related features using appropriate evaluation scales. Additionally, the study sought to investigate the associations between the quality of various domains within weight management apps and the number of incorporated BCTs and app features.

methodsIn April 2023, data on weight management apps from the iOS and Android app stores were downloaded from the Qimai Data platform. Subsequently, a total of 35 weight management apps were subjected to screening and analysis by 2 researchers. The features and quality of the apps were independently assessed by 6 professionals specializing in nutrition management and health behavioral change using the Mobile Application Rating Scale (MARS). Two registered dietitians, who had experience in app development and coding BCTs, applied the established 26-item BCT taxonomy to verify the presence of BCTs. Mean (SD) scores and their distributions were calculated for each section and item. Spearman correlations were used to assess the relationship between an app's quality and its technical features, as well as the number of incorporated BCTs.

resultsThe data set included a total of 35 apps, with 8 available in the Android Store, 10 in the Apple Store, and 17 in both. The overall quality, with a mean MARS score of 3.44 (SD 0.44), showed that functionality was the highest scoring domain (mean 4.18, SD 0.37), followed by aesthetics (mean 3.43, SD 0.42), engagement (mean 3.26, SD 0.64), and information (mean 2.91, SD 0.52), which had the lowest score. The mean number of BCTs in the analyzed apps was 9.17 (range 2-18 BCTs/app). The most common BCTs were "prompt review of behavioral goals" and "provide instruction," present in 31 apps (89%). This was followed by "prompt self-monitoring of behavior" in 30 apps (86%), "prompt specific goal setting" in 29 apps (83%), and "provide feedback on performance" in 27 apps (77%). The most prevalent features in the analyzed apps were the need for web access (35/35, 100%), monitoring/tracking (30/35, 86%), goal setting (29/35, 83%), and sending alerts (28/35, 80%). The study also revealed strong positive correlations among the number of BCTs incorporated, app quality, and app features. This suggests that apps with a higher number of BCTs tend to have better overall quality and more features.

conclusionsThe study found that the overall quality of weight management apps in China is moderate, with a particular weakness in the quality of information provided. The most prevalent BCTs in these apps were reviewing behavioral goals, providing guidance, self-monitoring of behavior, goal setting, and offering performance feedback. The most common features were the need for web access, monitoring and tracking, goal setting, and sending alerts. Notably, higher-quality weight management apps in China tended to incorporate more BCTs and features. These findings can be valuable for developers looking to improve weight management apps and enhance their potential to drive behavioral change in weight management.

Indexed as

Health PromotionMobile ApplicationsBehavior TherapyChinaEast Asian PeopleHumansappsChinaMARSmobile appsmobile healthqualityweight lossweight management

Identifiers

PMID37999950
PMCPMC10709793

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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.