Rapid Automatized Naming (RAN) as a Kindergarten Predictor of Future Reading in English: A Systematic Review and Meta-analysis

Abstract

Rapid automatized naming (RAN) has been shown to be a strong correlate of reading abilities. RAN also predicts future reading across different ages, ability levels, and languages, and is often used in literacy screening. Thus, understanding the specific relations between early RAN and later reading difficulties is important, particularly for screening. This systematic review and meta-analysis (with N = 60 samples; k = 373 effect sizes; n = 10,513 participants), was the first to test the extent to which measures of RAN assessed before grade school predict future reading performance in English-speaking children. We also tested whether characteristics of the RAN tasks, reading measures, or sample demographics moderate this relationship. We found that overall, kindergarten/preschool RAN is correlated with grade-school reading at r = −.38, similar in magnitude to previous concurrent meta-analyses that included various ages and languages. We found that alphanumeric RAN tasks were more strongly related to future reading than were non-alphanumeric tasks, as well as that RAN significantly predicts all types of reading measures tested, but more strongly predicts real word than nonword reading. To assess the role of RAN’s unique predictive power, we also meta-analyzed the semipartial correlations of early RAN with later reading when controlling for phonological awareness (PA); the result of rsp = −.25 demonstrates RAN’s significant, unique contribution beyond PA. These results support shared cognitive resource models in which the similarity between RAN and reading tasks accounts for their correlation. We provide practical guidelines for based on these data for early screening for reading difficulties and dyslexia.