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Self-Regulation has been studied from different research directions, which show a variety of conceptual as well as empirical similarities (Jones, Bailey, Barnes & Partee 2016; Zhou, Chen, & Main, 2012).
I. Executive Functions (EF) originate from neurocognitive research and are described as an accumulation of (meta-) cognitive processes that serve the goal-oriented self-regulation of an individual (Daseking, Melzer, Rißling & Petermann, 2015; Friedman & Miyake, 2017).
II. Effortful Control (EC) originates from temperament research and is defined as the efficiency of executive attention, including the ability to inhibit a dominant response, to activate a subdominant response, to proceed in a planned manner and to recognize conflicts or errors (Rothbart and Bates, 2006). EC is considered relatively stable over time intraindividually and is usually measured by questionnaires.
The aim of this poster is to examine the overlap between the constructs of executive function and effortful control in early childhood by different measures. 88 children (49 female; M-age = 3.93, SD = .78) were tested with a computerized battery designed to assess EF at the age 3-6 years (EF-Touch; Willoughby & Blair, 2012, 2011; Willoughby, Blair, Wirth & Greenberg, 2010). Parents completed questionnaires to measure Executive Function (BRIEF-P; Daseking & Petermann, 2013) and temperament (CBQ; Rothbart, Ahadi, Hershey & Fisher, 2001). We found significant correlations between EF and the CBQ EC (see Table 1): BRIEF-P Inhibition and BRIEF-P Updating correlate with CBQ-EC. No correlations were found between EF-Touch Scales and EC. While questionnaires reported by parents show strong relationships between EF and EC, children’s performance on computerized tasks failed to correlate to parents’ reports in most cases. However, CBQ Negative Affect and CBQ Surgency did not relate to the measures of EF (see Table 1). The findings indicate that considerable similarities and overlaps in the definitions and core components of EF and EC exist. Data analysis is ongoing. We will analyse the data using structural equation modelling for the final poster.
Henning Schmidt, Helmut-Schmidt-University
Presenting Author
Monika Daseking, Helmut-Schmidt-University
Non-Presenting Author
Caterina Gawrilow, University of Tübingen
Non-Presenting Author
Julia Karbach, University of Koblenz-Landau
Non-Presenting Author
Julia Kerner auch Körner, Helmut-Schmidt-University Hamburg
Non-Presenting Author