A Structured Framework for Cumulative Research Reporting in Psychology: Integrating Replication, Effect Sizes, and Meta-Analytic Evidence

The accumulation of scientific knowledge in psychology is often impeded by the predominance of isolated empirical studies that rarely integrate their findings quantitatively with prior evidence. This limitation contributes to fragmented knowledge bases, inconsistent effect size estimates, and reduced cumulative scientific progress. The present article proposes and formalizes a Cumulative Integrated Reporting (CIR) framework, a structured methodology for empirical reporting designed to improve the systematic integration of new findings within the existing body of literature. The CIR framework consists of four interconnected components: (a) mandatory reporting of effect sizes with appropriate uncertainty estimates, (b) formal comparison with effect sizes from prior studies and relevant meta-analyses, (c) Bayesian-compatible updating of cumulative evidence distributions, and (d) transparent documentation of methodological moderators that could account for cross-study heterogeneity. We illustrate the framework with an applied example using the association between emotional regulation and perceived stress, demonstrating how a single observed effect (r = -.34) can be meaningfully situated within a prior distribution of cumulative evidence. We discuss implications for journal reporting standards, graduate training, and the reformulation of replication as a continuous epistemic practice rather than a discrete binary event. The CIR framework represents a methodologically tractable and practically implementable step toward transforming psychology's reporting culture from one oriented toward confirmatory hypothesis testing to one oriented toward cumulative quantitative synthesis.