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确定关键指标,以开发一款用于发展中国家产后抑郁症早期筛查的新型移动应用程序。

Identifying key indicators to develop a novel mobile application for early screening of postpartum depression in developing countries.

作者信息

Mustafina Sumaiya Nuha, Islam Muhammad Nazrul, Mahjabin Mohammad Ratul, Mannan M M Rushadul, Islam Md Motaharul

机构信息

Department of Computer Science and Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka, 1216, Bangladesh.

Department of Computer Science and Engineering, United International University (UIU), Dhaka, Bangladesh.

出版信息

BMC Health Serv Res. 2025 Feb 20;25(1):287. doi: 10.1186/s12913-025-12429-x.

Abstract

Postpartum depression (PPD) poses significant risks to both maternal and child health, yet it remains underdiagnosed and undertreated, particularly in developing countries like Bangladesh. Factors such as hormonal changes, lack of communal support and socioeconomic stressors primarily contribute to its prevalence. Despite advancements in research, technological solutions for PPD support are lacking in regions where mental health is deemed negligible. Thus, the objectives of this research are to reveal the underlying factors contributing to PPD among mothers in developing countries and to propose a novel application based on these factors for PPD detection. A Design Science Research (DSR) approach is adopted to achieve these objectives. In this research, firstly 17 factors that could serve as effective indicators for detecting PPD were identified through interviews with 12 key informants, including doctors and patients. Next, for each identified factor, visual and scenario-based questionnaires were designed to facilitate effective screening through user feedback. Then, an Android application, 'PPD Screening App', was developed, which provides users with visual, auditory, and multilingual (in English and Bengali) scenario-based questionnaires for each identified factor, as well as the questionnaires proposed in the Edinburgh Postnatal Depression Scale (EPDS) for PPD detection. Finally, the developed application was evaluated with 45 new mothers in the postpartum period and demonstrated high accuracy (96%) compared to the traditional screening method (84%). The effectiveness of the application was also explored in relation to participants' demographic profiles (age and IT literacy), and participants provided very positive feedback on the usability of the application. This research thus contributes in improving early detection and intervention for PPD, ultimately enhancing maternal and child well-being.

摘要

产后抑郁症(PPD)对母婴健康构成重大风险,但仍未得到充分诊断和治疗,尤其是在孟加拉国等发展中国家。激素变化、缺乏社会支持和社会经济压力等因素是其普遍存在的主要原因。尽管研究取得了进展,但在心理健康被视为微不足道的地区,缺乏针对PPD支持的技术解决方案。因此,本研究的目的是揭示发展中国家母亲中导致PPD的潜在因素,并基于这些因素提出一种用于PPD检测的新型应用程序。采用设计科学研究(DSR)方法来实现这些目标。在本研究中,首先通过与包括医生和患者在内的12名关键信息提供者进行访谈,确定了17个可作为检测PPD有效指标的因素。接下来,针对每个确定的因素,设计了基于视觉和情景的问卷,以通过用户反馈促进有效筛查。然后,开发了一款安卓应用程序“PPD筛查应用程序”,它为用户提供针对每个确定因素的视觉、听觉和多语言(英语和孟加拉语)情景问卷,以及爱丁堡产后抑郁量表(EPDS)中提出的用于PPD检测的问卷。最后,对45名产后新妈妈进行了该应用程序的评估,与传统筛查方法(84%)相比,该应用程序显示出较高的准确率(96%)。还探讨了该应用程序与参与者人口统计学特征(年龄和信息技术素养)的有效性关系,参与者对该应用程序的可用性给予了非常积极的反馈。因此,本研究有助于改善PPD的早期检测和干预,最终提高母婴福祉。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c57e/11844140/613dcb937bc0/12913_2025_12429_Fig1_HTML.jpg

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