Tehran University of Medical Sciences Nursing Practice Today 2383-1154 12 3 2025 06 10 214 220 Hamid Sharif-Nia Psychosomatic Research Center, Mazandaran University of Medical Sciences, Sari, Iran AND Department of Nursing, Amol Faculty of Nursing and Midwifery, Mazandaran University of Medical Sciences, Sari, Iran Jason W. Osborne Department of Statistics, Miami University, Oxford, Ohio, USA 2025 05 27 2025 06 10 Meta-analysis is a vital statistical tool in psychometric research, enabling the synthesis of multiple studies to enhance the reliability and validity of measurement instruments. This study applies meta-analytic techniques to exploratory factor analysis (EFA) to establish a structured framework for aggregating factor structures across psychological and health-related assessments. Given the variations in factor solutions due to methodological and sample differences, a systematic synthesis is essential. The study outlines key methodological considerations, including data extraction, effect size computation using Epsilon-Squared (ω²), heterogeneity analysis, and statistical synthesis via a random-effects model. Findings indicate that meta-analysis can improve the generalizability of factor structures, with Factor 1 accounting for an average ω² of 0.72 across studies. The results highlight the importance of refining statistical approaches to address factor heterogeneity and enhance psychometric meta-analytic practices. This research contributes to the advancement of valid and reliable measurement frameworks in psychological and health sciences. https://npt.tums.ac.ir/index.php/npt/article/view/4118 https://npt.tums.ac.ir/index.php/npt/article/download/4118/657