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. 2025 Jul 16;25(1):351.
doi: 10.1186/s12905-025-03907-9.

Empowering postpartum women: the role of mHealth apps in promoting mental health and obesity prevention

Huang Xiaocui  1 , Ye Shengyao  2 , Nadia Samsudin  3 , Li Kuan  4 , Lin Xuefen  4
Affiliations

Empowering postpartum women: the role of mHealth apps in promoting mental health and obesity prevention

Huang Xiaocui et al. BMC Womens Health. .

Abstract

Background: The proliferation of mobile health (mHealth) applications has markedly influenced self-management practices related to obesity and mental well-being. However, the effectiveness of fitness apps in enhancing health outcomes is closely tied to their frequency of usage, a factor that has been insufficiently explored, especially among postpartum populations.

Objective: This study aimed to propose and empirically test a structural equation modeling (SEM) framework to examine the moderating effects of fitness app usage frequency on the relationships among obesity, lifestyle behaviors, dietary habits, and mental health outcomes among postpartum women.

Methods: A cross-sectional self-reported online survey was administered to postpartum women in Malaysia within one year after childbirth, collecting 468 valid responses. Participants were categorized into four distinct groups based on their frequency of fitness app usage: daily, weekly, rarely, and never.

Results: The SEM analyses highlighted significant variations among the four user groups. The daily-user model exhibited the strongest explanatory power (R² = 0.82), followed by weekly (R² = 0.79), rarely (R² = 0.66), and never-user groups (R² = 0.59). Specifically, in the daily-user group, demographic factors, lifestyle behaviors, dietary intake, and Body Mass Index (BMI) explained 82% of the variance in mental health outcomes. Across all usage categories, BMI consistently demonstrated a significant negative relationship with mental health symptoms, suggesting better mental health among participants with lower BMI. Further, factor loading analyses identified screen time (0.89) and physical activity (0.81) as dominant indicators of lifestyle behaviors. Frequent app users (daily and weekly) displayed healthier dietary choices and lower BMI scores compared to infrequent users.

Conclusions: Regular engagement with fitness mHealth applications is associated with better mental health and may support obesity management among postpartum women. This study underscores the critical moderating role of app usage frequency in optimizing health outcomes, providing practical implications for public health strategies and interventions targeting postpartum populations.

Keywords: Health risk; Non-communicable disease; Obesity; Psychological well-being; Public health.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of UCSI University (protocol code IEC-2023-FOSSLA-0202 on 9 April 2024). Informed consent was obtained from all subjects involved in the study. The research methods were performed in accordance with the relevant guidelines and regulations. Participants of the study were informed about the purpose, objectives, and their right to participate, decline participation, or withdraw their participation in the research activities by verbal. Respondents have been notified that the information given was private and confidential which only going to use for academic purposes only. Written informed consent was obtained from all respondents. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

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Research framework
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Healthy and Unhealthy food consumption
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Daily fitness app use model
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Weekly fitness app use model
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Rarely fitness app use model
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Never use fitness app model
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Impact significance in all models
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References

    1. Varma DS, Mualem M, Goodin A, Gurka KK, Wen TS, Gurka MJ, et al. Acceptability of an mHealth app for monitoring perinatal and postpartum mental health: qualitative study with women and providers. JMIR Form Res. 2023;7:e44500. - PMC - PubMed
    1. El Ayadi AM, Diamond-Smith NG, Duggal M, Singh P, Sharma P, Kaur J, et al. Preliminary impact of an mHealth education and social support intervention on maternal health knowledge and outcomes among postpartum mothers in punjab, India. BMC Pregnancy Childbirth. 2025;25(1):239. - PMC - PubMed
    1. Yan C, Cao R, Hu X, Hu Y, Liu H. A longitudinal study of a mHealth app and regional policies on the uptake of postpartum depression referral after positive screening in Shenzhen. BMC Pregnancy Childbirth. 2024;24(1):536. - PMC - PubMed
    1. Hutton L, Price BA, Kelly R, McCormick C, Bandara AK, Hatzakis T et al. Assessing the privacy of mHealth apps for Self-Tracking: heuristic evaluation approach. Jmir Mhealth Uhealth. 2018;6(10). - PMC - PubMed
    1. Arakawa Y, Haseda M, Inoue K, Nishioka D, Kino S, Nishi D, et al. Effectiveness of mHealth consultation services for preventing postpartum depressive symptoms: a randomized clinical trial. BMC Med. 2023;21(1):221. - PMC - PubMed

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