Unlocking the potential of wearable device wear time to enhance postpartum depression screening and detection

Abstract

Postpartum depression (PPD) is a mood disorder affecting one in seven women after childbirth that is often under-screened and under-detected. 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 (e.g., Fitbit), offer continuous and longitudinal digital phenotyping for mood disorder diagnosis and monitoring, with device wear time being an important yet understudied aspect. Using the All of Us Research Program (AoURP) dataset, we assessed the percentage of days women with PPD wore Fitbit devices across pre-pregnancy, pregnancy, postpartum, and PPD periods, as determined by electronic health records. Wear time was compared in women with and without PPD using linear regression models. Results showed a strong trend that women in the PPD cohort wore their Fitbits more those without PPD during the postpartum (PPD: mean=72.9%, SE=13.8%; non-PPD: mean=58.9%, SE=12.2%, P-value=0.09) and PPD time periods (PPD: mean=70.7%, SE=14.5%; non-PPD: mean=55.6%, SE=12.9%, P-value=0.08). We hypothesize this may be attributed to hypervigilance, given the common co-occurrence of anxiety symptoms among women with PPD. Future studies should assess the link between PPD, hypervigilance, and wear time patterns. We envision that device wear patterns with digital biomarkers like sleep and physical activity could enhance early PPD detection using machine learning by alerting clinicians to potential concerns facilitating timely screenings, which may have implications for other mental health disorders.

Competing Interest Statement

MAH is a founder of Alamya Health.

Funding Statement

The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. Individual authors were supported by the following funding sources: NIMH R01131542 (RCP), NHGRI U24HG011449 (EH and MAH), NHGRI RM1HG010860 (EH and MAH).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All of Us Institutional Review Board gave ethical approval for this work.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

Individuals who successfully complete the requisite training can access the data utilized in this analysis via the All of Us Researcher Workbench.

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