Developing an android-based application for early detection of postpartum depression symptoms in Indonesia

Supplementary Files

Data Set


ADDIE model
digital application
postpartum depression

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Nurbaeti, I., Syafii, M., & Lestari, K. B. (2021). Developing an android-based application for early detection of postpartum depression symptoms in Indonesia. Belitung Nursing Journal, 7(2), 118–124.
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Accepted for publication: 2021-03-16
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Background: Postpartum depression has become a mental health problem in Indonesia. Screening symptoms of postpartum depression as early as one month during the postpartum period is needed. A smartphone application is considered one of the fastest ways for screening.

Objective: To develop an android-based application to early detect the symptoms of postpartum depression and evaluate its effectiveness.

Methods: The smartphone application was developed using Analysis, Design, Development, Implementation, and Evaluation (ADDIE) instruction model. The survey design was carried out to evaluate the effectiveness of the application among 109 postpartum mothers selected using convenience sampling. Data were collected from August to October 2019 in South Tangerang, Indonesia.

Results: The evaluation showed that the application is mostly positive. The appearance of the application is adequate (92.67%), easy to download (89.90%), understandable (96.33%), easy to fill-in (94.50%), beneficial (96.33%), new (90.83%), and reflecting psychological conditions (90.83%).

Conclusion: The symptoms of postpartum depression can be measured by the android-based application. It is therefore recommended to Indonesian mothers use this app to detect postpartum depression symptoms early. This app also helps nurses and midwives to prevent depression among postpartum mothers. Also, the app can be imitated by other developers for non-Indonesian mothers.

Supporting Agencies

Universitas Islam Negeri Syarif Hidayatullah Jakarta under the research grant scheme for collaborative research (Un.01/KPA/511/2019)


Copyright (c) 2021 Irma Nurbaeti, Moch Syafii, Kustati Budi Lestari

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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