INTRODUCTION: Meta-accuracy, the degree to which individuals accurately infer how others perceive them, is fundamental to social interactions. Yet the field draws on diverse methods across disciplines, and variation in conceptualizations and approaches has not been systematically captured. This review synthesizes the meta-accuracy literature across relational contexts, research foci, attribute domains, and measurement approaches. METHOD: Following PRISMA 2020 guidelines, we searched five databases (January 2025; coverage through December 31, 2024) for peer-reviewed empirical studies assessing meta-accuracy. Two reviewers independently screened 1,336 records and extracted data using a preregistered protocol (OSF: https://doi.org/10.17605/OSF.IO/VMH6W). RESULTS: Ninety-three studies met inclusion criteria: dyadic meta-accuracy (DMA; k = 56; 60.2%), generalized meta-accuracy (GMA; k = 17; 18.3%), and combined approaches (k = 20; 21.5%). DMA and GMA differed in interaction settings and acquaintance levels; research foci diverged across disciplines; most studies targeted personality traits; and measurement approaches varied across studies. The majority of studies were cross-sectional (k = 88; 94.6%) and most samples were tertiary students (k = 60; 64.5%). CONCLUSION: This review systematically maps the conceptual, methodological, and contextual diversity in meta-accuracy research. We propose three priorities: (1) standardizing terminology to distinguish DMA from GMA, (2) transparent reporting of measurement approaches, and (3) developing unified frameworks that bridge disciplinary boundaries to support integrated future research.
Harper et al. (Mon,) studied this question.