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95 Delving Beyond the Test Score: Linguistic Markers of Cognitive Impairment on Paragraph Recall
- Stacy L Andersen, Seho Park, Nicole Roth, Paola Sebastiani, Megan Barker, Zhiwei Zheng, Sanford Auerbach Auerbach, Stephanie Cosentino, Rhoda Au, David J Libon
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 766-767
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- Article
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Objective:
Cognitive tests requiring spoken responses, such as paragraph recall, are rich in cognitive-related information that is not captured using traditional scoring methods. This study aimed to determine if linguistic features embedded in spoken responses may differentiate between individuals who are and are not cognitively impaired.
Participants and Methods:Participants in the Long Life Family Study completed a neuropsychological assessment which included the WMS-R Logical Memory I paragraph recall. For a subset of participants (N=709), test responses were digitally recorded and manually transcribed. We used Linguistic Inquiry Word Count, a text analysis program, to quantify word counts, grammatical features (e.g, prepositions, verb tenses), and the use of content words related to specific semantic categories (e.g., work-related, numbers) for immediate (IR) and delayed recall (DR). We used regression models with Generalized Estimating Equations adjusted by age, sex, education, and within-family correlation to select features associated with cognitive status (normal cognition [NC] versus cognitive impairment [CI]; Bonferroni-corrected threshold p<0.001). Next, we developed a “polyfeature score” (PFS) for both immediate and delayed recall, each calculated as a weighted sum of the selected linguistic features. We then built a logistic regression model to evaluate the predictive value of each PFS for identifying cognitively impaired individuals. In secondary analyses, we used regression models as above to identify features associated with mild cognitive impairment subtype (amnestic [aMCI] versus nonamnestic [naMCI]; threshold p< .05).
Results:The sample included 599 participants with NC and 110 with CI (mean age = 72.3 ± 11.0 years, 54% female). The regression identified 8 linguistic features for IR and 7 for DR that significantly predicted cognitive status. Decreased use of content words related to work (e.g., employed, school, police) and biological processes (e.g., cook, cafeteria, eat) and the use of negations (e.g., no, not, can’t) were predictive of cognitive impairment in both recall conditions. In contrast, the use of other content word categories were predictive of cognitive status in only one recall condition (IR: leisure, cognitive processes, space; DR: drives, number). The use of fewer prepositions in IR, more first-person pronouns in DR, and fewer words in the past tense in DR were each associated with cognitive impairment. Word count was not predictive of cognitive status. Both PFSs were highly associated with cognitive status (PFS_IR ß= 0.74, p< 0.001; PFS_DR ß= 0.86, p= 0.001) with high discriminative value (PFS_IR AUC= 0.93, sensitivity = 0.81, specificity= 0.91; PFS_DR AUC= 0.95, sensitivity= 0.77, specificity= 0.88). In the CI subset, linguistic features differed between those classified as aMCI (n= 24) and naMCI (n= 40). Two function word categories predicted aMCI in IR whereas decreased word count, two function word categories, and two content word categories predicted aMCI in DR (all p< .05)
Conclusions:Linguistic features from paragraph recall provide high predictive value for classifying cognitive status increasing its potential as a cognitive screener in clinical settings. Additionally, each recall condition identified unique linguistic features associated with cognitive impairment which may aid differentiation of cognitive impairment subtypes and elucidate processes underlying deficits in learning and recall.
5 - Evolutionary medicine of sleep disorders: Toward a science of sleep duration
- Edited by Patrick McNamara, Boston University, Robert A. Barton, University of Durham, Charles L. Nunn
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- Book:
- Evolution of Sleep
- Published online:
- 10 March 2010
- Print publication:
- 12 October 2009, pp 107-122
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Summary
Introduction
Evolutionary medicine is a relatively new field of inquiry that attempts to apply the findings and principles of evolutionary anthropology and biology to medical disorders (Armelagos, 1991; Cohen, 1989; Nesse & Williams, 1998; Stearns, 1999; Stearns & Koella, 2007; Trevathan, Smith, & McKenna, 1999, 2008; Williams & Nesse, 1991). Although a fair number of medical disorders have been explored from the evolutionary medicine perspective (see the collection of papers in Stearns, 1999, and Trevathan et al., 1999, 2008), sleep disorders have not been among them. This is unfortunate, as application of evolutionary theory to problems of sleep disorders will likely yield significant new insights into both the causes and solutions of all of the major sleep disorders.
In this chapter, we discuss several of these major sleep disorders as well as some of the less common ones. Our choice of which disorders to cover was rather arbitrary: we chose those where, we believe, evolutionary analysis is currently in a position to shed new light on the symptomatology of the disorder as well as on its potential ultimate causes. We were particularly interested in disorders that might also shed light on a potential science of sleep durations.
Why sleep durations? Time spent asleep is one of the most important aspects of sleep, as it is directly linked to the restorative qualities of sleep. If you do not get enough sleep, you do not feel well.