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

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Abstract
BACKGROUND China’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. OBJECTIVE This 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. METHODS We 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. RESULTS We 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). CONCLUSIONS There 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.
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