Eric Hurwitz, Samantha Meltzer-Brody, Zachary Butzin-Dozier, Rena C Patel, Noémie Elhadad, Melissa A Haendel
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引用次数: 0
Abstract
Background: Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and maternal morbidity. Wearable technologies, such as smartwatches and fitness trackers (eg, Fitbit), offer continuous and longitudinal digital phenotyping for mood disorder diagnosis and monitoring, with device wear time being an important yet understudied aspect.
Objective: We aimed to suggest that wear time of a wearable device may provide additional information about perinatal mental health to facilitate screening and early detection of PPD. We proposed that wear time of a wearable device may also be valuable for managing other mental health disorders.
Methods: Using the All of Us Research Program dataset, we identified females who experienced childbirth with and without PPD using computational phenotyping. We compared the percentage of days and number of hours per day females with and without PPD wore Fitbit devices during prepregnancy, pregnancy, postpartum, and PPD periods, determined by electronic health records. Comparisons between females with and without PPD were conducted using linear regression models. We also assessed the correlation between Fitbit wear time consistency (measured as the maximum number of consecutive days the Fitbit was worn) during prepregnancy and PPD periods in females with and without PPD using the Pearson correlation. All analyses were run with Bonferroni correction.
Results: Our findings showed a strong trend, although nonsignificant after multiple testing correction, that females in the PPD cohort wore their Fitbits more than those in non-PPD cohort during the postpartum (PPD cohort: mean 69.9%, 95% CI 42.7%-97%; non-PPD cohort: mean 50%, 95% CI 25.5%-74.4%; P=.02) and PPD periods (PPD cohort: mean 66.6%, 95% CI 37.9%-95.3%; non-PPD cohort: mean 46.4%, 95% CI 20.5%-72.2%; P=.02). We found no difference in the number of hours per day females in the PPD and non-PPD cohorts wore their Fitbit during any period of pregnancy. Finally, there was no relationship between the consistency of Fitbit wear time during prepregnancy and PPD periods (r=-0.05, 95% CI -0.46 to 0.38; P=.84); however, there was a trend, though nonsignificant, in Fitbit wear time consistency among females without PPD (r=0.25, 95% CI -0.02 to 0.49; P=.07).
Conclusions: We hypothesize that increased Fitbit wear time among females with PPD may be attributed to hypervigilance, given the common co-occurrence of anxiety symptoms. Future studies should assess the link between PPD, hypervigilance, and wear time patterns. We envision that wear time patterns of a wearable device combined with digital biomarkers such as sleep and physical activity could enhance early PPD detection using machine learning by alerting clinicians to potential concerns and facilitating timely screenings, which may have implications for other mental health disorders.
背景:产后抑郁症(PPD)是一种情绪障碍,影响七分之一的分娩后妇女,但往往未被充分筛查和发现。如果不进行诊断和治疗,产后抑郁症与儿童和孕产妇的长期发育挑战有关。可穿戴技术,如智能手表和健身追踪器(如Fitbit),为情绪障碍诊断和监测提供了连续和纵向的数字表型,设备佩戴时间是一个重要但尚未得到充分研究的方面。目的:我们的目的是提示可穿戴设备的佩戴时间可以提供围产期心理健康的额外信息,以促进PPD的筛查和早期发现。我们提出,可穿戴设备的佩戴时间也可能对管理其他精神健康障碍有价值。方法:使用All of Us Research Program数据集,我们使用计算表型识别出患有和不患有PPD的分娩女性。我们比较了有和没有PPD的女性在孕前、孕期、产后和PPD期间每天佩戴Fitbit设备的天数和小时数的百分比,这些都是由电子健康记录决定的。使用线性回归模型对患有和未患有PPD的女性进行比较。我们还使用Pearson相关性评估了有或没有PPD的女性在孕前和PPD期间Fitbit佩戴时间一致性(以Fitbit佩戴的最长连续天数来测量)之间的相关性。所有分析均采用Bonferroni校正。结果:我们的研究结果显示了一种强烈的趋势,PPD队列中的女性在产后佩戴fitbit的次数多于非PPD队列(PPD队列:平均69.9%,95% CI 42.7%-97%;非ppd队列:平均50%,95% CI 25.5%-74.4%;P= 0.02)和PPD期(PPD队列:平均66.6%,95% CI 37.9%-95.3%;非ppd队列:平均46.4%,95% CI 20.5%-72.2%;P = .02点)。我们发现PPD组和非PPD组的女性在怀孕期间每天佩戴Fitbit的时间没有差异。最后,孕前Fitbit佩戴时间的一致性与PPD期间没有关系(r=-0.05, 95% CI -0.46 ~ 0.38;P =点);然而,在没有PPD的女性中,Fitbit佩戴时间一致性有趋势,尽管不显著(r=0.25, 95% CI -0.02 ~ 0.49;P = . 07)。结论:我们假设,女性PPD患者Fitbit佩戴时间的增加可能归因于过度警觉,因为焦虑症状通常同时出现。未来的研究应该评估PPD、过度警惕和穿戴时间模式之间的联系。我们设想,可穿戴设备的佩戴时间模式与睡眠和身体活动等数字生物标志物相结合,可以通过机器学习提醒临床医生潜在的问题并促进及时筛查,从而提高早期PPD的检测,这可能对其他精神健康疾病有影响。