The prediction of Change: Normative neuropsychological trajectories

Attix, Deborah K.; Story, Tyler J.; Chelune, Gordon J.; Ball, J. D.; Stutts, Michael L.; Hart, Robert P.; Barth, Jeffrey T.

doi:10.1080/13854040801945078

Cited by 65 publications

(44 citation statements)

References 60 publications

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“…31 Longitudinal studies may be more sensitive in identifying the relationship between cognition and WMH, in part because demographic variables may influence the change association less than they do the baseline relationships.…”

Section: Discussionmentioning

confidence: 99%

Differential Patterns of Cognitive Decline in Anterior and Posterior White Matter Hyperintensity Progression

Marquine

Attix

Goldstein

et al. 2010

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Background and Purpose White matter hyperintensities (WMHs) found on brain MRI in elderly individuals are largely thought to be due to microvascular disease, and its progression has been associated with cognitive decline. The present study sought to determine patterns of cognitive decline associated with anterior and posterior WMH progression. Methods Subjects included 110 normal controls, ages ≥60 years, who were participants in the Duke Neurocognitive Outcomes of Depression in the Elderly study. All subjects had comprehensive cognitive evaluations and MRI scans at baseline and after 2 years. Cognitive composites were created in five domains: complex processing speed, working memory, general memory, visual-constructional skills, and language. Change in cognition was calculated utilizing standard regression-based models accounting for variables known to impact serial testing. A semi-automated segmentation method was utilized to measure WMH extent in anterior and posterior brain regions. Hierarchical multiple linear regression models were used to evaluate which of the five measured cognitive domains was most strongly associated with regional (anterior and posterior) and total WMH progression, after adjusting for demographics (age, sex and education). Results Decline in complex processing speed was independently associated with both anterior (r2 = 0.06, p = 0.02) and total WMH progression (r2 =0.05, p = 0.04). In contrast, decline in visual-constructional skills was uniquely associated with posterior progression (r2= 0.05, p <0.05). Conclusions Distinct cognitive profiles are associated with anterior and posterior WMH progression among normal elders. These differing profiles need to be considered when evaluating the cognitive correlates of WMH.

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Section: Discussionmentioning

confidence: 99%

Differential Patterns of Cognitive Decline in Anterior and Posterior White Matter Hyperintensity Progression

Marquine

Attix

Goldstein

et al. 2010

Stroke

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“…As described in Suchy et al (2011), two screenings of cognitive status approximately one year apart were conducted in a sample of older adults. Self-reported Openness was assessed using a comprehensive, normed measure of Five Factor Model (FFM) personality factors (NEO PI-R; Costa & McCrae, 1992) as a predictor of future decline in cognitive status as evidenced by a dementia screening measure, while controlling for demographic characteristics and baseline performance, consistent with methodology used in prior research on performance change (Attix et al, 2009;Duff et al, 2007). The use of a general dementia screening assessment and the timing of the repeat assessment meant that baseline personality associations with decline would most likely reflect incipient cognitive decline.…”

Section: Introductionmentioning

confidence: 99%

Preliminary evidence for low openness to experience as a pre-clinical marker of incipient cognitive decline in older adults

Williams

Suchy

Kraybill

2013

Journal of Research in Personality

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“…This ignores properties of the test such as reliability and practice effects, and it also discounts statistical effects such as regression to the mean (McCaffrey, Duff, & Westervelt, 2000). Various statistical methods have been proposed to account for these potential confounds, ranging from simple standard deviation difference methods (see Frerichs & Tuokko, 2005), to reliable change model of varying complexity (see Hinton-Bayre, 2010), to standardized regression-based (SRB) methods (e.g., Attix et al, 2009). See Duff (2012) and Heilbronner et al (2010) for a more detailed discussion of these and other issues related to serial assessment in neuropsychology.…”

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confidence: 99%

Reliable Change on Neuropsychological Tests in the Uniform Data Set

Gavett

Ashendorf

Gurnani

2015

J Int Neuropsychol Soc

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Objective Longitudinal normative data obtained from a robust elderly sample (i.e., believed to be free from neurodegenerative disease) are sparse. The purpose of the present study was to develop reliable change indices (RCIs) that can assist with interpretation of test score changes relative to a healthy sample of older adults (ages 50+). Method Participants were 4217 individuals who completed at least 3 annual evaluations at one of 34 past and present Alzheimer’s Disease Centers throughout the United States. All participants were diagnosed as cognitively normal at every study visit, which ranged from three to nine approximately annual evaluations. One-year RCIs were calculated for 11 neuropsychological variables in the Uniform Data Set by regressing follow-up test scores onto baseline test scores, age, education, visit number, post-baseline assessment interval, race, and sex in a linear mixed effects regression framework. In addition, the cumulative frequency distributions of raw score changes were examined to describe the base rates of test score changes. Results Baseline test score, age, education, and race were robust predictors of follow-up test scores across most tests. The effects of maturation (aging) were more pronounced on tests related to attention and executive functioning, whereas practice effects were more pronounced on tests of episodic and semantic memory. Interpretation of longitudinal changes on 11 cognitive test variables can be facilitated through the use of reliable change intervals and base rates of score changes in this robust sample of older adults. A web-based calculator is provided to assist neuropsychologists with interpretation of longitudinal change.

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The prediction of Change: Normative neuropsychological trajectories

Cited by 65 publications

References 60 publications

Differential Patterns of Cognitive Decline in Anterior and Posterior White Matter Hyperintensity Progression

Differential Patterns of Cognitive Decline in Anterior and Posterior White Matter Hyperintensity Progression

Preliminary evidence for low openness to experience as a pre-clinical marker of incipient cognitive decline in older adults

Reliable Change on Neuropsychological Tests in the Uniform Data Set

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