OBJECTIVE: Executive function (EF) is a commonly used but difficult to operationalize construct. In this study, we considered EF and related components as they are commonly presented in the neuropsychological literature, as well as the literatures of developmental, educational, and cognitive psychology. These components have not previously been examined simultaneously, particularly with this level of comprehensiveness, and/or at this age range or with this sample size. We expected that the EF components would be separate but related, and that a bifactor model would best represent the data relative to alternative models. METHOD: We assessed EF with 27 measures in a large sample (N = 846) of late elementary school-age children, many of whom were struggling in reading, and who were demographically diverse. We tested structural models of EF, from unitary models to methodological models, utilizing model-comparison factor analytic techniques. We examined both a common factor as well as a bifactor structure. RESULTS: Initial models showed strong overlap among several latent EF variables. The final model was a bifactor model with a common EF, and five specific EF factors (working memory-span/manipulation and planning; working memory-updating; generative fluency, self-regulated learning; metacognition). CONCLUSIONS: Results speak to the commonality and potential separability of EF. These results are discussed in light of prevailing models of EF and how EF might be used for structure/description, prediction, and for identifying its mechanism for relevant outcomes. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
OBJECTIVE: Executive function (EF) is a commonly used but difficult to operationalize construct. In this study, we considered EF and related components as they are commonly presented in the neuropsychological literature, as well as the literatures of developmental, educational, and cognitive psychology. These components have not previously been examined simultaneously, particularly with this level of comprehensiveness, and/or at this age range or with this sample size. We expected that the EF components would be separate but related, and that a bifactor model would best represent the data relative to alternative models. METHOD: We assessed EF with 27 measures in a large sample (N = 846) of late elementary school-age children, many of whom were struggling in reading, and who were demographically diverse. We tested structural models of EF, from unitary models to methodological models, utilizing model-comparison factor analytic techniques. We examined both a common factor as well as a bifactor structure. RESULTS: Initial models showed strong overlap among several latent EF variables. The final model was a bifactor model with a common EF, and five specific EF factors (working memory-span/manipulation and planning; working memory-updating; generative fluency, self-regulated learning; metacognition). CONCLUSIONS: Results speak to the commonality and potential separability of EF. These results are discussed in light of prevailing models of EF and how EF might be used for structure/description, prediction, and for identifying its mechanism for relevant outcomes. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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