Random Item Generation Is Affected by Age

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Bibliographic Details
Title:	Random Item Generation Is Affected by Age
Language:	English
Authors:	Multani, Namita, Rudzicz, Frank, Wong, Wing Yiu Stephanie, Namasivayam, Aravind Kumar, van Lieshout, Pascal
Source:	Journal of Speech, Language, and Hearing Research. Oct 2016 59(5):1172-1178.
Availability:	American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
Peer Reviewed:	Y
Page Count:	7
Publication Date:	2016
Document Type:	Journal Articles Reports - Research
Descriptors:	Executive Function, Cognitive Ability, Older Adults, Young Adults, Comparative Analysis, Correlation, Age Differences, Aging (Individuals), Color, Interference (Learning), Visual Stimuli, Reaction Time, Verbal Ability, Intelligence Tests, Vocabulary, Cognitive Measurement, Statistical Analysis
Assessment and Survey Identifiers:	Peabody Picture Vocabulary Test, Stroop Color Word Test
DOI:	10.1044/2016_JSLHR-L-15-0077
ISSN:	1092-4388
Abstract:	Purpose: Random item generation (RIG) involves central executive functioning. Measuring aspects of random sequences can therefore provide a simple method to complement other tools for cognitive assessment. We examine the extent to which RIG relates to specific measures of cognitive function, and whether those measures can be estimated using RIG only. Method: Twelve healthy older adults (age: M = 70.3 years, SD = 4.9; 8 women and 4 men) and 20 healthy young adults (age: M = 24 years, SD = 4.0; 12 women and 8 men) participated in this pilot study. Each completed an RIG task, along with the color Stroop test, the Repeatable Battery for the Assessment of Neuropsychological Status, and the Peabody Picture Vocabulary Test--Fourth Edition (Dunn & Dunn, 2007). Several statistical features extracted from RIG sequences, including recurrence quantification, were found to be related to the other measures through correlation, regression, and a neural-network model. Results: The authors found significant effects of age in RIG and demonstrate that nonlinear machine learning can use measures of RIG to accurately predict outcomes from other tools. Conclusions: These results suggest that RIG can be used as a relatively simple predictor for other tools and in particular seems promising as a potential screening tool for selective attention in healthy aging.
Abstractor:	As Provided
Entry Date:	2016
Accession Number:	EJ1119076
Database:	ERIC

Description
Abstract:	Purpose: Random item generation (RIG) involves central executive functioning. Measuring aspects of random sequences can therefore provide a simple method to complement other tools for cognitive assessment. We examine the extent to which RIG relates to specific measures of cognitive function, and whether those measures can be estimated using RIG only. Method: Twelve healthy older adults (age: M = 70.3 years, SD = 4.9; 8 women and 4 men) and 20 healthy young adults (age: M = 24 years, SD = 4.0; 12 women and 8 men) participated in this pilot study. Each completed an RIG task, along with the color Stroop test, the Repeatable Battery for the Assessment of Neuropsychological Status, and the Peabody Picture Vocabulary Test--Fourth Edition (Dunn & Dunn, 2007). Several statistical features extracted from RIG sequences, including recurrence quantification, were found to be related to the other measures through correlation, regression, and a neural-network model. Results: The authors found significant effects of age in RIG and demonstrate that nonlinear machine learning can use measures of RIG to accurately predict outcomes from other tools. Conclusions: These results suggest that RIG can be used as a relatively simple predictor for other tools and in particular seems promising as a potential screening tool for selective attention in healthy aging.
ISSN:	1092-4388
DOI:	10.1044/2016_JSLHR-L-15-0077