Evidence map›Paper›PMID 40839869›Full record

ArticleJournal of medical Internet research2025

User Satisfaction With Pregnancy Management Apps in Mainland China: User-Generated Content Analysis and Text Mining Study.

Xiaoyi Jiao, Lu Jiang, Min Zhao, Junhao Ma, Yanwei Li, Tian Shen, Yongcheng Liu, Yue Hu, Zhengyang Lu, Mengyao Xing and 3 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
  2. Review
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

13 authors.

Xiaoyi JiaoSchool of Public Health, Zhejiang University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0004-1357-1352
Lu JiangDepartment of Obstetrics, Second Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0000-0002-5449-4363
Min ZhaoDepartment of Obstetrics, Xinglin Hospital of Xiamen, Xiamen, Fujian Province, China.ORCID https://orcid.org/0009-0002-4787-5835
Junhao MaSchool of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0006-3308-5284
Yanwei LiSchool of Nursing, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0001-3523-3483
Tian ShenSchool of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0000-2038-6180
Yongcheng LiuNetEase ThunderFire UX User Experience Center, Netease Group, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0006-7663-6322
Yue HuSchool of Nursing, Southwest Medical University, Luzhou, Sichuan Province, China.ORCID https://orcid.org/0009-0009-3962-5175
Zhengyang LuSchool of Public Health, Zhejiang University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0009-5881-5628
Mengyao XingSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0009-0002-9889-1229
Jun LiangSchool of Public Health, Zhejiang University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0000-0002-0551-6706
Peng XiangDepartment of AI and IT, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China.ORCID https://orcid.org/0000-0001-9617-597X
Jianbo LeiClinical Research Center, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, China.ORCID https://orcid.org/0000-0002-1744-0235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChina's 3-child policy has increased the demand for scientific and personalized pregnancy health management. The convenience of mobile health has promoted the use of pregnancy management apps among pregnant women. User satisfaction has a significant impact on continued use intention. Systematically evaluating user satisfaction with pregnancy management apps is of great significance in promoting the digital transformation of maternal-infant health care.

objectiveThis study aimed to explore user satisfaction with pregnancy management apps by mining user-generated content and analyzing the differences in user satisfaction among different operating systems. Under the guidance of Herzberg two-factor theory, this study explored the demand structure in user experience and investigated the influencing factors on satisfaction from 2 aspects: user satisfaction and dissatisfaction, providing reference for the development of mobile health apps for pregnancy management.

methodsWe screened pregnancy management apps from the app stores of 5 mobile phone manufacturers in mainland China and collected the app-based reviews and ratings posted by users. We performed topic clustering and semantic parsing using the latent Dirichlet allocation and DeepSeek-R1 models. Influencing factors for satisfaction and dissatisfaction were identified using the Tobit regression model. The Kano model was used to classify the factors as basic or attractive. The Wald test was applied to analyze the differences in the effects across various factors.

resultsWe examined 86 pregnancy management apps, amounting to 180,107 reviews in total. The overall satisfaction rate with pregnancy apps was relatively high (72.34%). Android users had higher satisfaction rates than iOS users (89.32% vs 60.75%). User reviews were clustered into 12 themes, categorized into 3 types: technical security support, basic service experience, and maternal-infant scenarios. The basic factors causing dissatisfaction included system login (β=2.829; P<.001) and privacy disclosure (β=1.955; P<.001). Attractive factors boosting satisfaction included storage optimization (β=0.220; P<.001), page design (β=0.223; P<.001), function provision (β=0.023; P=.001), platform feedback (β=0.222; P<.001), physicians' inquiries (β=0.356; P<.001), menstrual management (β=0.209; P<.001), pregnancy guidelines (β=0.306; P<.001), parenting science popularization (β=0.238; P<.001), growth record (β=0.401; P<.001), and maternal-infant community (β=0.307; P<.001).

conclusionsThere were significant differences in user satisfaction between the iOS and Android platforms, reflecting the heterogeneity of responses to user demands in different technological ecosystems. Twelve themes showed the multilevel needs of pregnant women for pregnancy management apps, forming a progressive service chain: security guarantee to demand satisfaction to experience improvement. Twelve factors had asymmetric correlations with user satisfaction and dissatisfaction with pregnancy management apps. Two factors were related to basic attributes of the apps and 10 factors to attractive attributes. By distinguishing between basic and attractive factors, the use of pregnancy management apps may be improved.

Indexed as

Data MiningMobile ApplicationsPatient SatisfactionAdultChinaFemaleHumansPregnancyTelemedicinelatent Dirichlet allocationLDApregnancy management apptopic modeltwo-factor theoryuser-generated contentuser satisfaction

Identifiers

PMID40839869
PMCPMC12411797

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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.