Beyond Traditional Continuous Performance Tests: The Incremental Diagnostic Value of Distractor-Embedded Paradigms

Objective Distractor-embedded continuous performance test (CPT) paradigms have been developed to enhance the ecological validity and diagnostic precision of attention-deficit/hyperactivity disorder (ADHD) assessment. This study aimed to quantitatively synthesize the diagnostic performance of distractor-embedded CPT models and evaluate their incremental validity beyond traditional CPT paradigms.Methods A systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines. PubMed, Scopus, and Web of Science were searched through February 2026. Studies were included if they employed distractor-embedded CPT paradigms and reported sufficient data to compute standardized mean differences between ADHD and control groups. Hedges g was calculated for each study. Random-effects meta-analyses (DerSimonian–Laird method) were performed to estimate pooled effect sizes.Results Eight studies comprising 2,135 participants were included. The pooled standardized mean difference was 1.14 (95% confidence interval: 0.53–1.75), indicating substantial separation between ADHD and control groups. Subgroup analyses revealed comparable pooled effects for MOXO-based (|g|=1.26) and virtual reality (VR)–based paradigms (|g|=1.30), with lower heterogeneity observed in VR-based studies. Domain-specific analyses showed the largest effect for attention (g=1.35), followed by impulsivity (g=0.82) and hyperactivity (g=0.80). Incremental validity findings demonstrated improved diagnostic precision when eye-tracking augmentation and multivariate composite scoring methods were applied. Sensitivity analyses confirmed stability of the pooled estimates.Conclusion Distractor-embedded and ecologically enriched CPT paradigms demonstrate robust diagnostic discrimination in ADHD assessment. Multimodal and integrated models may provide incremental advantages over conventional CPT approaches. These findings support the integration of ecologically valid and multimodal objective measures into ADHD diagnostic frameworks.