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Journal of Aging Research
Volume 2017, Article ID 8514582, 6 pages
https://doi.org/10.1155/2017/8514582
Research Article

Measuring Fluid Intelligence in Healthy Older Adults

1Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada T2N 1N4
2Department of Psychology, University of Toronto, 1265 Military Trail, Toronto, ON, Canada M1C 1A4

Correspondence should be addressed to Mohammed K. Shakeel; ac.yraglacu@lihtalak.demmahom

Received 25 October 2016; Revised 30 November 2016; Accepted 12 January 2017; Published 30 January 2017

Academic Editor: Elke Bromberg

Copyright © 2017 Mohammed K. Shakeel and Vina M. Goghari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The present study evaluated subjective and objective cognitive measures as predictors of fluid intelligence in healthy older adults. We hypothesized that objective cognitive measures would predict fluid intelligence to a greater degree than self-reported cognitive functioning. Ninety-three healthy older (>65 years old) community-dwelling adults participated. Raven’s Advanced Progressive Matrices (RAPM) were used to measure fluid intelligence, Digit Span Sequencing (DSS) was used to measure working memory, Trail Making Test (TMT) was used to measure cognitive flexibility, Design Fluency Test (DFT) was used to measure creativity, and Tower Test (TT) was used to measure planning. The Cognitive Failures Questionnaire (CFQ) was used to measure subjective perceptions of cognitive functioning. RAPM was correlated with DSS, TT, and DFT. When CFQ was the only predictor, the regression model predicting fluid intelligence was not significant. When DSS, TMT, DFT, and TT were included in the model, there was a significant change in the model and the final model was also significant, with DFT as the only significant predictor. The model accounted for approximately 20% of the variability in fluid intelligence. Our findings suggest that the most reliable means of assessing fluid intelligence is to assess it directly.