Age matters in pediatric pain care: Bayesian meta-reanalysis of virtual reality trials

BACKGROUND: Immersive virtual reality proved effective in pediatric procedural pain and anxiety management, yet the extent to which age modifies these effects remains uncertain. Notably, the two most recent and widely cited meta-analyses (Eijlers et al., 2019 and Tas et al., 2022) reported conflicting conclusions. METHODS: We performed a Bayesian meta-reanalysis of the above mentioned meta-analyses. We extracted standardized mean differences (SMD) for pain (n = 21) and anxiety (n = 10), plus study-level age, sex distribution, quality score, and procedure type. Primary outcomes were pooled SMDs; the secondary outcome was the age effect estimated with a Bayesian random-effects meta-regression. We report pooled effects, age slope (ΔSMD/year), heterogeneity, 95% credible intervals (CrI), and posterior probabilities (P[β_age>0]). RESULTS: > 0] = 0.991), indicating attenuation of benefit with increasing age. CONCLUSION: Immersive virtual reality proves effective in pediatric procedural pain and anxiety management, with benefits diminishing with increasing age. Bayesian evidence synthesis should be increasingly applied to pediatric research, where studies are small and highly heterogeneous. IMPACT: Immersive virtual reality significantly reduces procedural pain and anxiety in children, but its effectiveness decreases with increasing age. This Bayesian meta-reanalysis reconciles conflicting findings from prior frequentist meta-analyses, showing that age is a key determinant of non-pharmacological pain management efficacy. Findings advocate for age-specific implementation of immersive virtual reality and encourage adoption of Bayesian evidence synthesis methods to better inform pediatric clinical guidelines where studies are small and heterogeneous.