1,207
Views
20
CrossRef citations to date
0
Altmetric
Original Articles

Insight in Cognition: Self-Awareness of Performance Across Cognitive Domains

, , , &
Pages 95-102 | Published online: 05 Dec 2012
 

Abstract

Loss of cognitive functions, as apparent through self-awareness, is considered an important indicator of cognitive deficits and is therefore commonly used in clinical practice. However, little is known about self-awareness of cognitive performance, including its accuracy, its basis, and whether people can distinguish their performance across different cognitive domains. In the present study, 20 university students (M age = 21.7 ± 2.2 years, 9 males) and 20 middle-aged participants (M age = 52.8 ± 3.9 years, 10 males) gave estimations of their performances on executive functioning, memory, attention, and visuoperception before and after confrontation with their capacities. A repeated-measures analysis of variance with age group as a between-subjects factor was performed on the calculated estimation errors, before and after neuropsychological testing. Overall, the estimation errors were significantly higher before than after experience with test performance, ps < .01, partial η²s = .17. An overall effect of domain (four levels), ps < .001, partial η²s = .22 was found. These results suggest that self-awareness is domain-specific, and although it is adaptive to the experience of mental effort, it is most dependent on preexisting beliefs about one's own cognitive abilities.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 398.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.