Effectiveness of digital health interventions for perinatal depression: a systematic review and meta-analysis

Abstract

Abstract Pregnant women and new mothers within 1 year after delivery are at a high risk of depression, yet many do not get the help they need due to wide reasons heralding stigma, access, cost, time, and shortage of human resources. Hence, compelling the exploration of alternate and potentially cost-effective means of delivering care, including the leverage of digital tools. This review aimed to evaluate the effectiveness of digital health interventions in reducing depressive symptoms among perinatal women. Literatures were sought from seven academic databases alongside the references of previous reviews. Included studies were all quantitative study types involving the use of digital health interventions for perinatal women not more than 1-year post-delivery. Standardized mean difference and standard error were used to perform random-effect model meta-analysis. Sensitivity and subgroup analyses were performed to determine certainty and modifiers of the findings, respectively. Forty-eight studies were included in this review with 28 studies used for meta-analyses. Numerous digital channels were identified; however, none specified the use of a digital health theory in its development. The digital health interventions showed a small positive significant effect over the controls (standardized mean difference = 0.29, P = 0.003, I2 = 34%), and this was significantly influenced by intervention delivery and facilitation modes, time of initiation of the intervention, and period covered by the intervention. Although digital health interventions may hold some potential for perinatal depression, scaling the interventions may be challenging sequel to overlooked influences from the interactions within the human–computer–society complex.