ArticleHealthcare (Basel, Switzerland)2020
mHealth Apps Assessment among Postpartum Women with Obesity and Depression.
Article in Healthcare (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- mHealth apps for maternal mental well-being among pregnant and postpartum women: a systematic review.mHealth · 2026Review
- A Mobile Health Approach for Monitoring Hypertensive and Mental Health Conditions to Avoid Preventable Delays in Postpartum Care.medRxiv : the preprint server for health sciences · 2025Article
- Exploring the Requirements for an mHealth App to Prevent and Manage Perinatal Anxiety and Depression.Health science reports · 2025Article
- Empowering postpartum women: the role of mHealth apps in promoting mental health and obesity prevention.BMC women's health · 2025Article
- Evaluation scale and behavioral model construction for intention to use postpartum exercise rehabilitation mobile application based on user experience.Frontiers in psychology · 2025Article
- Article
- Evaluation of depression and obesity indices based on applications of ANOVA, regression, structural equation modeling and Taguchi algorithm process.Frontiers in psychology · 2023Article
- Factors Influencing Continued Usage Behavior on Mobile Health Applications.Healthcare (Basel, Switzerland) · 2022Article
- Determinants Impacting User Behavior towards Emergency Use Intentions of m-Health Services in Taiwan.Healthcare (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPregnancy has become the main constituent for women to become overweight or obese during the postpartum phase. This could lead women to suffer from postpartum depression as well. Information technology (IT) has become more prevalent in the healthcare industry. It offers patients the opportunity to manage their health conditions via the use of several applications, one being the mHealth applications.
objectiveThe main purpose of this study is to experiment and understand the effects the mHealth applications (i.e., fitness and nutrition applications) have on the body mass index (BMI) and depression levels amongst postpartum women.
methodsOnline questionnaires were sent to postpartum women within one year after their pregnancy, of which 819 completed questionnaires were returned. The frequency of the mHealth applications usage was categorized into daily, weekly, rarely and never streams. Therefore, the frequency of use of the mHealth applications for BMI and depression levels was analyzed based on the available statistical data. Descriptive statistics, ANOVA, and Dunnet tests were applied to analyze the experimental data.
resultsOut of 819 respondents, 37.9% and 42.1% of them were overweight and obese, respectively. Almost 32.9% of the respondents were likely depressed, and 45.6% were at an increased risk. This study reports that only 23.4% and 28.6% of respondents never used the fitness and nutrition applications. The impact of the frequency of using the fitness applications on BMI and depression levels was obvious. This means that with the increased use of the fitness applications, there was also a significant effect in maintaining and decreasing the BMI and depression levels amongst Malaysians postpartum women. However, from the data of weekly and daily use of fitness applications, we found that the contribution toward the BMI and depression levels was high (
conclusionThe efficiency of the fitness applications toward the BMI and depression levels has been proven in this research work. While nutrition applications did not affect the BMI and depression levels, some of the respondents were still categorized as weekly and daily users. Thus, the improvements in BMI and depression levels are associated with the types of mHealth app that had been used.
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Registered trials
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 Socratic graph.