Reducing the risk of perinatal depression using an app-based cognitive behavioral therapy program: protocol of a randomized controlled trial

利用基于应用程序的认知行为疗法降低围产期抑郁症风险:一项随机对照试验方案

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Abstract

INTRODUCTION: Cognitive behavioral therapy (CBT) is recognized as one of the most effective methods for reducing the risk of perinatal depression. However, the traditional face-to-face delivery format limits its accessibility. With the advent of digital technology, app-based CBT offers new possibilities, yet its preventive role in perinatal depression remains insufficiently explored. This study aims to determine if pregnant women using an app-based CBT program report reduced depressive and anxious symptoms compared to a control group. METHODS: A two-arm parallel randomized controlled trial of 290 pregnant women will be conducted at Jintang County Maternity and Child Health Hospital in Chengdu, China. Eligible participants who consent to participate will be recruited at 20-24 weeks of gestation and randomly assigned to either the intervention group, which will complete an 8-week mobile app-based CBT program (CareMom), or a control group, which will receive an attention-matched 8-week relaxation training program, also delivered via a mobile app. Randomization will be performed using a computer-generated random number sequence. Primary outcomes include changes in scores on the Edinburgh Postnatal Depression Scale, the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder 7-item from baseline to 6 weeks postpartum. Outcome analyses will be performed on both the intention-to-treat and per-protocol populations. DISCUSSION: This trial evaluates an app-based CBT program for reducing the risk of perinatal depression. Improved maternal mental health not only benefits the mothers themselves but also may facilitate more optimal parenting behaviors, which could exert a positive influence on the cognitive, emotional, and behavioral development of the infant. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT06672432, identifier NCT06672432.

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