2026 ECNP Congress

PS01-1052

Mobile app-based detection and symptom trajectories of postpartum depression using ecological momentary assessment: a prospective cohort validation study

Jessie Jingxia Lin — F. Jin, K.W. Chan, Y. Fu, R.C.K. Chung · The Hong Kong Polytechnic University, Rehabilitation Sciences, Hong Kong, Hong Kong SAR- China

2026 ECNP Congress

Introduction

Postpartum depression (PPD) is a common and clinically significant condition affecting women during the first year after childbirth [1]. In Hong Kong, routine screening at discrete postpartum time points may miss fluctuating or emerging symptoms [2]. Ecological momentary assessment (EMA), delivered via mobile technology, enables repeated real-time monitoring of mood in daily life. However, evidence on the validity and feasibility of app-based EMA for detecting perinatal depressive symptoms in local Chinese populations remains limited.

Aims

This study aimed to evaluate the validity of the mobile application MotherCare for early detection of depressive symptoms during the prenatal and postnatal periods by comparing app-based Whooley questionnaire scores with Edinburgh Postnatal Depression Scale (EPDS) scores. Secondary aims were to examine symptom trajectories over six months and identify time-varying and time-invariant factors associated with depressive symptoms.

Methods

This single-group prospective cohort validation pilot study recruited pregnant women from two public hospitals and the community in Hong Kong between April 2024 and July 2025. Eligible participants were Chinese-speaking women aged 18 years or above, in the first or second trimester, and owners of an iOS or Android smartphone. After baseline assessment, participants used the MotherCare app for 6 months, spanning about 3 months pre-birth to 3 months postpartum. EMA data were collected using three prompts per day over five consecutive days in each monthly assessment period, for a total of 90 prompts. Retrospective assessments, including the EPDS and the 21-item Depression Anxiety Stress Scale (DASS 21), were completed at baseline and monthly thereafter. Analyses included Spearman correlation, multilevel modelling, hierarchical cluster analysis, latent growth curve modelling, and descriptive qualitative analysis.

Results

Of 328 women screened, 121 were enrolled and analyzed; 114 completed six-month follow-up, giving a dropout rate of 5.8%. Participants completed a mean of 56 of 90 EMA prompts, a response rate of 62%. App-based Whooley scores were significantly and positively correlated with EPDS scores across all six monthly assessments, with Spearman coefficients from 0.459 to 0.731 (all P<0.001), supporting convergent validity. Hierarchical cluster analysis identified two baseline groups: low risk (n=80) and high risk (n=41). Latent growth curve modelling showed that baseline cluster membership significantly predicted the intercept of depressive symptoms in the first month, indicating higher initial symptoms in the high-risk group, but did not predict the slope of symptom change over six months. Baseline demographic characteristics were not significantly associated with depressive symptoms. In contrast, multilevel analyses showed that greater physical pain, fatigue, anxiety, poorer sleep quality, and lower exercise participation were significantly associated with higher depressive symptoms over time. Qualitative feedback indicated that the app was generally acceptable and easy to use, although some participants reported feeling burdened by frequent assessments and wanted more active clinical support.

Conclusions

MotherCare showed feasibility and convergent validity for monitoring perinatal depressive symptoms. App-based EMA may complement routine screening and identify women at risk.

Acknowledgment: Funded by Hong Kong Health and Medical Research Fund (20211201).

References

  1. Goodman, S.H., Rouse, M.H., Connell, A.M., Broth, M.R., Hall, C.M., Heyward, D., 2011. Maternal depression and child psychopathology: A meta-analytic review. Clinical child and family psychology review 14(1),1-27.
  2. Family Health Service, Department of Health, Hong Kong, 2007. Comprehensive Child Development Service (CCDS) evaluation report. Hong Kong: Family Health Service, Department of Health, Hong Kong.