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Published on: June 20, 2020
The Effectiveness of Early Intervention Programs for Children Aged 0-3: A Systematic Review and Meta-Analysis
Min Qiu1, Shuhua Zhang1, Weiyan Liao1
1Faculty of Education and Human Development, The Education University of Hong Kong, Hong Kong SAR, China.
Background:
Existing syntheses on infant early interventions focus on single-risk cohorts and overlook implementation moderators. To address these gaps, this systematic review and meta-analysis adopts a transdiagnostic approach to evaluate interventions across diverse risk profiles and identify predictive intervention characteristics, including setting, provider, and duration.
Methods:
PubMed, Web of Science, Scopus, CINAHL, and PsycINFO were searched up to February 2026 for peer-reviewed English randomized controlled trials (RCTs), cluster RCTs, or quasi-RCTs evaluating early interventions for children aged 0-3, control groups, and extractable developmental data. Study quality was assessed using the Cochrane Risk of Bias 2 tool. Standardized mean differences (SMDs) were pooled using a random-effects model, with subgroup analyses investigating the influence of intervention duration, setting, provider, and infant risk factors (PROSPERO: CRD420261436569).
Results:
Across 17 studies (n = 1987), early intervention did not have a statistically significant overall benefit for motor development (SMD = 0.49, p = 0.12). However, exploratory subgroup analyses suggested larger pooled motor effects among professionally delivered and clinic-based interventions (SMD = 1.16), while exploratory language benefits were observed among interventions lasting less than six months (SMD = 1.52). For preterm infants, targeted interventions suggested initial promise for physical growth (SMD = 0.55) but not motor function (SMD = 0.69, p = 0.60).
Conclusions:
Intervention effectiveness depends on delivery format, setting, and population. Exploratory analyses suggested that intervention characteristics such as provider type and duration may contribute to outcome variability across domains. Despite small trial sample sizes and high statistical heterogeneity, these overall estimates should be interpreted as descriptive benchmarks rather than uniform treatment effects; interpretation therefore focuses on subgroup findings.