Department of Women's and Children's Health, Uppsala University, 751 85, Uppsala, Sweden.
Department of Microbiology, Tumor and Cell Biology, Centre for Translational Microbiome Research, Karolinska Institutet, 171 77, Stockholm, Sweden.
Sci Rep. 2022 Dec 8;12(1):21253. doi: 10.1038/s41598-022-25107-3.
To utilize modern tools to assess depressive and anxiety symptoms, wellbeing and life conditions in pregnant women during the first two waves of the COVID-19 pandemic in Sweden. Pregnant women (n = 1577) were recruited through the mobile application Mom2B. Symptoms of depression, anxiety and wellbeing were assessed during January 2020-February 2021. Movement data was collected using the phone's sensor. Data on Google search volumes for "Corona" and Covid-related deaths were obtained. Qualitative analysis of free text responses regarding maternity care was performed. Two peaks were seen for depressive symptoms, corresponding to the two waves. Higher prevalence of anxiety was only noted during the first wave. A moderating effect of the two waves in the association of depression, anxiety, and well-being with Covid deaths was noted; positive associations during the first wave and attenuated or became negative during the second wave. Throughout, women reported on cancelled healthcare appointments and worry about partners not being allowed in hospital. The association of mental health outcomes with relevant covariates may vary during the different phases in a pandemic, possibly due to adaptation strategies on a personal and societal/healthcare level. Digital phenotyping can help healthcare providers and governmental bodies to in real time monitor high-risk groups during crises, and to adjust the support offered.
利用现代工具评估瑞典 COVID-19 大流行前两波期间孕妇的抑郁和焦虑症状、幸福感和生活状况。通过移动应用程序 Mom2B 招募孕妇（n=1577）。在 2020 年 1 月至 2021 年 2 月期间评估抑郁、焦虑和幸福感症状。使用手机传感器收集运动数据。获取有关“Corona”和与新冠相关死亡的谷歌搜索量数据。对有关产妇护理的自由文本回复进行定性分析。抑郁症状出现两个高峰，与两波相对应。仅在第一波期间注意到焦虑的患病率更高。注意到抑郁、焦虑和幸福感与新冠死亡之间的两个波的关联具有调节作用；第一波期间呈正相关，第二波期间减弱或呈负相关。在此期间，女性报告取消了医疗保健预约，并担心伴侣不被允许住院。心理健康结果与相关协变量的关联可能在大流行的不同阶段发生变化，这可能是由于个人和社会/医疗保健层面的适应策略所致。数字表型可以帮助医疗保健提供者和政府机构在危机期间实时监测高危人群，并调整提供的支持。
