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Kayla Kotalik, Charles J Golden, Casey Morocho, D’Shawn Harrigan, Nisha Kajani, Lara Rifai, A-197 Does the Wechsler Adult Intelligence Scale Predict Functioning on the Trail Making Test Part B in a Clinical Adult Population Sample, Archives of Clinical Neuropsychology, Volume 37, Issue 6, September 2022, Page 1352, https://doi.org/10.1093/arclin/acac060.197
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Abstract
Objective: To test if the WAIS-IV Indexes predicts functioning on the TMT B.
Method: The adult clinical sample was recruited from a large de-identified database. The participants (n=392) consisted of 51.1% White, 14% Black, 25.4% Latinx, and 9.5% Other. The diagnostic makeup of the sample was divided into 38.7% psychiatric, 30.5% neurological, 21.4% mixed, and 9.2% had no diagnosis. From the sample, 56.7% were female and 43% of the participants were male. The mean age was 33.32, (SD=13.52) and mean education was 13.66 (SD= 2.23).
Results: A hierarchical multiple regression model was significant, F(10, 381) = 23.87, p < .001, R2 = .385. Overall, PRI accounted for 0.7% of the variance, WMI 2.8%, PSI 8.9%, and education 4.1% of the variance. VCI, age, gender, and race were nonsignificant.
Conclusion: The results indicate the strongest predictor of TMT B performance is processing speed followed by education. Crowe (1998) suggested working memory could explain more variance of TMT B than alternation factors such as set shifting. However, the results of this study indicate working memory is a much smaller contributor. Working memory may be a less significant predictor since the alphabet and numbers are already learned. Still, education was a moderately strong predictor, which was consistent with previous literature as TMT B performance increases with higher levels of education and decreases with lower levels of education. Approximately 61.5% of the overall variance was not accounted for, which may reflect the contribution of cognitive flexibility.
