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Do Executive Attentional Processes Uniquely or Commonly Explain Psychometric g and Correlations in the Positive
Stefan J Troche1, Helene M von Gugelberg1, Olivier Pahud1
1Institute of Psychology, University of Bern, Fabrikstrasse 8, CH-3012 Bern, Switzerland.
The positive manifold in intelligence tests, often attributed to shared executive processes, was investigated. This study found that while executive functions explain commonalities, they do not fully account for the positive manifold in intelligence.
Area of Science:
- Cognitive Psychology
- Psychometrics
- Neuroscience
Background:
- The positive manifold, a consistent finding of positive correlations among diverse intelligence tests, underpins many intelligence theories.
- Process Overlap Theory (POT) posits that this positive manifold arises from overlapping domain-general executive processes.
Purpose of the Study:
- To empirically test Process Overlap Theory's central assumption regarding the origin of the positive manifold.
- To investigate the specific contributions of executive attention and decision-making speed to the positive manifold.
Main Methods:
- Re-analysis of an existing dataset (N=228) using psychometric intelligence measures (reasoning, speed, memory).
- Assessment of executive attention (sustained and selective) and decision-making speed using specific cognitive tasks.
- Application of structural equation modeling and network analyses to examine relationships.
Main Results:
- Selective attention, sustained attention, and decision-making speed accounted for the shared variance within the positive manifold.
- These executive functions did not explain the unique portions of the positive manifold.
- Evidence supporting POT's core hypothesis that overlapping domain-general processes solely create the positive manifold was not found.
Conclusions:
- The investigated domain-general executive processes do not fully explain the positive manifold in intelligence.
- While executive functions contribute to commonalities in intelligence test performance, other factors likely influence unique variance.
- Further research is needed to explore other potential domain-general processes that might align with POT's predictions.
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