Marcano Belisario Jose Salvador, Doherty Kevin, O'Donoghue John, Ramchandani Paul, Majeed Azeem, Doherty Gavin, Morrison Cecily, Car Josip
Global eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, UK.
School of Computer Science and Statistics, University of Dublin Trinity College, Dublin, Ireland.
BMJ Open. 2017 May 29;7(5):e014469. doi: 10.1136/bmjopen-2016-014469.
Depression is a common mental health disorder during pregnancy, with important consequences for mothers and their children. Despite this, it goes undiagnosed and untreated in many women attending antenatal care. Smartphones could help support the prompt identification of antenatal depression in this setting. In addition, these devices enable the implementation of ecological momentary assessment techniques, which could be used to assess how mood is experienced during pregnancy. With this study, we will assess the feasibility of using a bespoke mobile application (app) running on participants' own handsets for the longitudinal (6 months) monitoring of antenatal mood and screening of depression.
We will use a randomised controlled study design to compare two types of assessment strategies: retrospective + momentary (consisting of the Edinburgh Postnatal Depression Scale plus five momentary and two contextual questions), and retrospective (consisting of the Edinburgh Postnatal Depression Scale only). We will assess the impact that these strategies have on participant adherence to a prespecified sampling protocol, dropout rates and timeliness of data completion. We will evaluate differences in acceptance of the technology through a short quantitative survey and open-ended questions. We will also assess the potential effect that momentary assessments could have on retrospective data. We will attempt to identify any patterns in app usage through the analysis of log data.
This study has been reviewed and approved by the National Research Ethics Service Committee South East Coast-Surrey on 15 April 2016 as a notice of substantial amendment to the original submission (9 July 2015) under the Research Ethics Committee (REC) reference 15/LO/0977. This study is being sponsored by Imperial College London under the reference number 15IC2687 and has been included in the UK Clinical Research Network Study Portfolio under the Central Portfolio Management System number 19280. The findings of this study will be disseminated through academic peer-reviewed publications, poster presentations and abstracts at academic and professional conferences, discussion with peers, and social media. The findings of this study will also inform the PhD theses of JSMB and KD.
抑郁症是孕期常见的心理健康障碍,对母亲及其子女会产生重大影响。尽管如此,许多接受产前护理的女性的抑郁症仍未得到诊断和治疗。智能手机有助于在这种情况下及时识别产前抑郁症。此外,这些设备能够实施生态瞬时评估技术,可用于评估孕期情绪体验。通过本研究,我们将评估使用参与者自己手机上运行的定制移动应用程序(应用)对产前情绪进行纵向(6个月)监测和抑郁症筛查的可行性。
我们将采用随机对照研究设计,比较两种评估策略:回顾性+瞬时性(由爱丁堡产后抑郁量表加上五个瞬时性问题和两个情境问题组成)和回顾性(仅由爱丁堡产后抑郁量表组成)。我们将评估这些策略对参与者遵守预先指定的抽样方案、脱落率和数据完成及时性的影响。我们将通过简短的定量调查和开放式问题评估对该技术的接受度差异。我们还将评估瞬时评估对回顾性数据可能产生的潜在影响。我们将通过分析日志数据来尝试识别应用使用中的任何模式。
本研究已于2016年4月15日得到国家研究伦理服务委员会东南海岸-萨里委员会的审查和批准,作为对原始提交材料(2015年7月9日)的重大修订通知,研究伦理委员会(REC)参考编号为15/LO/0977。本研究由伦敦帝国理工学院赞助,参考编号为15IC2687,并已纳入英国临床研究网络研究组合,中央组合管理系统编号为19280。本研究的结果将通过学术同行评审出版物、海报展示以及在学术和专业会议上的摘要、与同行的讨论以及社交媒体进行传播。本研究的结果还将为JSMB和KD的博士论文提供参考。