Evidence map›Paper›PMID 41917972›Full record

ArticleNutrition journal2026

Evaluating function availability and user satisfaction with nutrition apps: user-generated content analysis and text mining study.

Songping Li, Qinghua Yao, Feihe Shao, Kejun Yang, Xiao Yu, Lixue Zhou, Junyi Xin

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Article in Nutrition journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Songping LiInformation Center, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Qinghua YaoDepartment of Clinical Nutrition, The Second Affiliated Hospital of Zhejiang, Chinese Medical University, Hangzhou, Zhejiang, China.
Feihe ShaoInformation Center, Hangzhou Linan First People's Hospital, Hangzhou, Zhejiang, China.
Kejun YangDepartment of Radiology, Cixi People's Hospital Affiliated to Wenzhou Medical University, Ningbo, Zhejiang, China.
Xiao YuDepartment of Clinical Nutrition, The Second Affiliated Hospital of Zhejiang, Chinese Medical University, Hangzhou, Zhejiang, China.
Lixue ZhouDepartment of Medical Records and Health Statistics, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Junyi XinSchool of Information Engineering, Hangzhou Medical College, 8 Yikang Street, Linan District, Hangzhou, 310000, Zhejiang, China. xinjunyi@hmc.edu.cn.

Funding

Joint TCM Science & Technology Projects of National Demonstration Zones for Comprehensive TCM Reform GZY-KJS-ZJ-2026-051Soft Science Research Planning Project of Zhejiang Province 2024C35064
6 · The paper itself

Abstract

backgroundNutrition apps are increasingly used to support dietary self-management and health promotion. However, how app functions align with nutrition-related tasks and user satisfaction with these apps remain unclear. Evidence from cross-country comparisons is limited.

objectiveThis study aimed to compare function availability and user satisfaction of nutrition apps in China and the US and to examine key factors associated with nutrition app satisfaction in different market contexts.

methodsA large-scale review-based analysis was conducted using nutrition app data from major app stores in China and the US. Task–Technology Fit, Latent Dirichlet Allocation, the Two-Factor Theory, the KANO model, DeepSeek-R1, and the Analytic Hierarchy Process were combined to assess function coverage and satisfaction patterns. A total of 269,300 reviews from China and 455,245 reviews from the US were included.

resultsChinese nutrition apps showed broader coverage in target monitoring (n = 111, 84.73%) and nutrition education (n = 101, 77.10%), while US apps focused more on dietary behavior intervention (n = 364, 89.66%). Both countries showed clear gaps in personalized nutrition services. KANO analysis showed that all identified factors in China were classified as charm attributes, whereas in the US both charm and essential attributes were identified. AHP-based results indicated that overall user satisfaction was higher in China (0.8901/1) than in the US (0.8372/1). In the US market, dissatisfaction was primarily associated with issues related to the food database (0.7217/1) and fee (0.6795/1), whereas Chinese users more frequently reported concerns regarding reliability (0.7725/1).

conclusionsUser satisfaction with nutrition apps differs between China and the US in functional focus and expectation structures. Improving system reliability in China and optimizing core functions and pricing in the US, alongside strengthening personalized services in both contexts, are key to enhancing user satisfaction and intervention effectiveness.

Indexed as

Consumer BehaviorData MiningHealth PromotionMobile ApplicationsChinaHumansUnited StatesAppsComparative studyEvaluationMobile healthNutrition managementUser satisfaction

Identifiers

PMID41917972
PMCPMC13188609

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