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Title: | Smart Diagnosing System Design To Accelerating Early Detection Of Postpartum Blues |
Authors: | Maharani Sulistyawati Batubara, Intan Silvy Irdianty, Mellia Aziz Pramudita, Dias |
Keywords: | blues, early detection, mother, postpartum, smart diagnosing system |
Issue Date: | 2022 |
Abstract: | Background: Untreated mothers with postpartum blues are at greater risk of severe mental health disorders. At the same time, early detection tools are manually provided and paper-based, and they cannot offer accessible access to center-compiled data despite their lack of priority in mental health services. Methods: Using a mixed-methods study design, the researcher used semi-structured interviews, while the quantitative approach was conducted using demographic questionnaires and a survey resulting from the interviews. A total of 16 participants were chosen for the qualitative study, and 60 respondents participated in the quantitative study. The sample for the study was screened by using the Edinburgh Postnatal Depression Scale (EPDS) within the area of Sibela Healthcare Center in Surakarta. Data collection used instrument tests and observation sheets and was analyzed by the Chi-Square statistical test. Results: Quantitative data analyses identified a relationship between age and the incidence of postpartum blues in mothers (p-value of 0.004; OR 0.053). This study showed that mothers aged < 21 and > 35 years old have a 0.067 times higher development of postpartum blues than mothers aged 21-35. Conclusion: Both qualitative and quantitative data suggest that postpartum mothers need support from husbands in overcoming the blues. Mothers and husbands need a comprehensive digital mobile phone service that involves professional health workers, health service providers, and referral systems. |
URI: | http://localhost:8080/xmlui/handle/123456789/11458 |
Appears in Collections: | VOL 7 NO 2 2022 |
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