Can we improve the clinical assessment of working memory? An evaluation of the Wechsler Adult Intelligence Scale–Third Edition using a working memory criterion construct

Abstract

Working memory is the cognitive ability to hold a discrete amount of information in mind in an accessible state for utilization in mental tasks. This cognitive ability is impaired in many clinical populations typically assessed by clinical neuropsychologists. Recently, there have been a number of theoretical shifts in the way that working memory is conceptualized and assessed in the experimental literature. This study sought to determine to what extent the WAIS-III working memory index (WMI) measures the construct studied in the cognitive working memory literature, whether an improved WMI could be derived from the subtests that comprise the WAIS-III, and what percent of variance in individual WAIS-III subtests is explained by working memory. It was hypothesized that subtests beyond those currently used to form the WAIS-III WMI would be able to account for a greater percentage of variance in a working memory criterion construct than the current WMI. Multiple regression analyses (n = 180) revealed that the best predictor model of subtests for assessing working memory was composed of the Digit Span, Letter-Number Sequencing, Matrix Reasoning, and Vocabulary. The Arithmetic subtest was not a significant contributor to the model. These results are discussed in the context of how they relate to Engle's (2006, 2007) new conceptualization of working memory mechanisms. KeywordsNeuropsychological Assessment; Working Memory; WAIS-III; Dual-Component Model Working memory refers to the cognitive system that stores information in an accessible state for utilization in complex mental tasks. This system also allows for updating and manipulation of relevant information. It is composed of both passive storage and dynamic control processes in order to hold information in an active form (Baddeley, 2001). Working memory is impaired in a wide variety of neuropsychiatric conditions, including dementia

Explaining individual differences in cognitive processes underlying hindsight bias

“…In the latter task, the examiner reads a string of digits and the participant reproduces the digits in the reverse order. Both subtests have high internal reliability (Digit Span: Fisher's z = .90; Letter-Number Sequencing: Fisher's z = .82; Wechsler, 1997) and have been shown to measure the same construct as working memory tasks used in cognitive experimental research (e.g., n-back task; Kane & Engle, 2002;Hill et al, 2010). Given the strong correlations between these two measures in our sample (older: r = .64, p < .001; younger: r = .47, p < .001), we created a working memory composite by converting the data on both variables to z scores and then summing them (Edgington, 1995, p. 183).…”

Anxiety mediates the effect of acute stress on working memory performance when cortisol levels are high: a moderated mediation analysis

“…However, the LNS was chosen as it has been argued that the LNS requires more executive processing than the Digit Span (Engle, Tuholski, Laughlin, & Conway, 1999), and it has low practice effects (Beglinger et al, 2005). Additional strengths of the LNS are that it was constructed to fit Baddeley’s working memory framework (Hudetz, Hudetz, & Klayman, 2000), it has been shown to be the best predictor of fluid intelligence (Shelton, Elliott, Hill, Calamia, & Gouvier, 2009), and it was a strong predictor of a working memory criterion that was comprised of subtests that included the n-back and listening span tasks (Hill et al, 2010). …”

The contributions of handedness and working memory to episodic memory

“…The LNS test shares a significantly moderate correlation (between 0.40 to 0.45) with laboratory-based WM tasks of operation span, listening span, and the modified lag span (Shelton et al, 2009). Although literature suggests that both the digitspan and LNS tests measure WM (Hill, Elliott, Shelton, Pella, O'Jile, & Gouvier, 2010), there is evidence that the LNS also depends on executive functioning, attention, processing speed, and spatial abilities (Crowe, 2000;Egeland, 2015;Haut, Kuwabara, Leach, & Arias, 2000). Furthermore, complex WM tasks are shown to be better predictors of higher order cognitive abilities than are simple WM tasks (Bayliss, Jarrold, Baddeley, & Gunn, 2003).…”