Study Protocol of an App-Based Prevention Program for Perinatal Depression

Abstract

The prevalence of perinatal depression (PND) in China is continuously rising, and the suicide rate among pregnant women is remarkably high. Preventing the occurrence of PND based on the management of primary health care is of great significance. Improving adherence to intervention programs is a key concern for PND prevention. Thus, a new intervention strategy based on mobile health could bring a new perspective to prevent the occurrence of PND and reduce the sample dropout rate. A single-blind, cluster randomized controlled trial will be performed to evaluate the effectiveness of a personalized, dynamic, and stratified intervention strategy based on an app. Four health centers will be randomly selected and randomly assigned to an intervention group (two centers) and a control group (two centers). Participants ( n = 426) will be enrolled from the four selected health centers, with 213 in each group. The intervention group will receive the interventions personalized by the feature-matching algorithm of the user profile and be reassigned to the low-risk group (Edinburgh Postnatal Depression Scale [EPDS] < 9) or moderate/high-risk group (9 ≤ EPDS < 13 and EPDS ≥ 13, but not meeting the criteria for PND) for intervention based on each EPDS score until 6 months after delivery. The control group will receive the same intervention components of the app but without the dynamic, personalized, and stratified function. Depression status, negative emotion symptoms, parental competence, and sample dropout rate will be measured at different weeks of pregnancy (12–16 [baseline], 24, 37) and at 42 days, 3 months, and 6 months after delivery. Follow-up evaluation (t 6 : 12 months after delivery) will also be conducted. If the intervention is effective, it will provide a personalized, time-friendly, and dynamic intervention for preventing PND. This phenomenon can effectively reduce the sample dropout rate and provide an empirical basis for promoting maternal mental health.