Cognitive aging on latent constructs for visual processing capacity: a novel structural equation modeling framework with causal assumptions based on a theory of visual attention

Research output: Contribution to journalJournal articlepeer-review

  • Simon Nielsen
  • Inge Linda Wilms
We examined the effects of normal ageing on visual cognition in a sample of 112 healthy adults aged 60-75. A testbattery was designed to capture high-level measures of visual working memory and low-level measures of visuospatial attention and memory. To answer questions of how cognitive ageing affects specific aspects of visual processing capacity, we used confirmatory factor analyses in Structural Equation Modelling (SEM; Model 2), informed by functional structures that were modelled with path analyses in SEM (Model 1). The results show that ageing effects were selective to measures of visual processing speed compared to visual short-term memory (VSTM) capacity (Model 2). These results are consistent with some studies reporting selective ageing effects on processing speed, and inconsistent with other studies reporting ageing effects on both processing speed and VSTM capacity. In the discussion we argue that this discrepancy may be mediated by differences in age ranges, and variables of demography. The study demonstrates that SEM is a sensitive method to detect cognitive ageing effects even within a narrow age-range, and a useful approach to structure the relationships between measured variables, and the cognitive functional foundation they supposedly represent.

Translated title of the contributionTest af aldersmæssig visuospatial opmærksomhed og hukommelse: Kausale modeller af test niveau med basis i estimater fra A Theory of Visual Attention
Original languageEnglish
Article number1596
JournalFrontiers in Psychology
Volume5
Pages (from-to)1-13
Number of pages13
ISSN1664-1078
DOIs
Publication statusPublished - 2015

    Research areas

  • Faculty of Social Sciences - cognitive aging, visual perception, cognitive assessment, Structures Equation Modelling, TVA, visual attention, visual memory

ID: 123947638