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Experimental Aging Research
An International Journal Devoted to the Scientific Study of the Aging Process
Volume 37, 2011 - Issue 5
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Original Articles

The Contribution of Set Switching and Working Memory to Sentence Processing in Older Adults

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Pages 516-538 | Received 05 Mar 2009, Accepted 24 Apr 2010, Published online: 17 Nov 2011
 

Abstract

This study evaluates the involvement of switching skills and working-memory capacity in auditory sentence processing in older adults. The authors examined 241 healthy participants, aged 55 to 88 years, who completed four neuropsychological tasks and two sentence-processing tasks. In addition to age and the expected contribution of working memory, switching ability, as measured by the number of perseverative errors on the Wisconsin Card Sorting Test, emerged as a strong predictor of performance on both sentence-processing tasks. Individuals with both low working-memory spans and more perseverative errors achieved the lowest accuracy scores. These findings are consistent with compensatory accounts of successful performance in older age.

Acknowledgments

This project was supported in part by the Clinical Science Research and Development Service, US Department of Veterans Affairs, by grants AG14345 (PI: Martin L. Albert) and AG 027532 (PI: Mira Goral) from the National Institute on Aging, and by Merit Reviews to Christopher Brady and Avron Spiro by the Clinical Science Research and Development Service, US Department of Veterans Affairs. The authors thank Christopher Brady, Rebecca Williams, Elaine Dibbs, Jordan Awerbach, Becky Brown, Jason Cohen, Josh Berger, and Keely Sayers for their contributions to this project. The authors also thank all the participants. The authors thank Jeffrey Elias and two anonymous reviewers for their comments on earlier versions of the manuscript.

Notes

1We selected individuals who performed high on the MMSE to assure a sample of healthy aging. It is possible, albeit less likely, that individuals with mild cognitive impairment will perform high on the MMSE. When we repeated the analyses including individuals with lower MMSE scores (26–30), the results were largely unchanged.

2The tests reported here are part of a larger battery administered to these participants in the Language in the Aging Brain project. Additional tests include naming and memory tests. In this paper, we chose to focus only on the relations between sentence processing and three cognitive domains: working memory, inhibition, and switching, and so we report data from relevant tests.

3Half of the participants were instructed to press a response button with their right hand when they thought the sentence was plausible (“likely to be true”) and with the left hand when they thought the sentence was implausible (“unlikely to be true”); the other half pressed with the left hand for plausible sentences and the right hand for implausible ones. The data were collapsed for the analysis.

4Response time data are not reported in this paper.

5Hearing acuity was tested in a sound-treated booth for the majority of the participants; however, a portion of the participants were tested in a quiet room. To adjust for this difference, we regressed each participant's speech thresholds on the type of room (booth or quiet room) in which they were tested. We adjusted for the use of a hearing aid and for whether the participant reported any of three hearing-related issues: having a hearing loss in one or both ears, having trouble hearing even when wearing a hearing aid, and being treated for hearing problems. The predicted scores for each participant were then used as the hearing acuity measure.

6Handling missing data was particularly important because one of our covariates, the Wisconsin Card Sorting Task, had a great deal of missingness (if participants had already taken the WCST, it would not be meaningful to administer it to them again). MI allows us to make use of partially observed cases, which would otherwise get thrown out but are often quite informative. Amelia II software (Honaker, King, & Blackwell, Citation2007) was used to generate 10 imputations, in accordance with standard recommendations. A very mild prior was necessary to obtain good convergence and all recommended diagnostics were satisfactory.

*Note: Bolded numbers represent significant correlations.

*Note: Bolded variables represent significant results; Measures are converted to z scores.

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