Regional white matter pathology in mild cognitive impairment: differential influence of lesion type on neuropsychological functioning.

BACKGROUND AND PURPOSE: Associations between regional white matter lesion pathology and neuropsychological performance across the aging spectrum are not well understood and, to date, research has been largely contradictory and inconclusive. The current study set out to clarify some of the inconsistencies in the literature by relating volumetric analyses of white matter lesions (deep white matter lesions and periventricular lesions) to neuropsychological performance in a large clinical sample of older adults diagnosed with mild cognitive impairment. METHODS: Seventy older adults with mild cognitive impairment were administered a comprehensive neuropsychological battery. White matter lesions identified on T2-weighted FLAIR images were quantified using a semi-automated volumetric approach (pixel thresholding). RESULTS: Results showed that, in contrast to performance on memory and naming tasks, total white matter lesions strongly predicted executive impairments, slowed processing speed, and visuospatial/construction difficulties. In addition, separate regression analyses demonstrated that results were primarily accounted for by deep white matter lesions (but not periventricular lesions), most likely due to frontal-subcortical circuitry disruption. Moreover, deep white matter lesions, but not periventricular lesions, significantly predicted overall poorer neuropsychological functioning after controlling for age, education, and level of depression. CONCLUSIONS: Taken together, findings demonstrate a differential influence of lesion type on cognitive impairment in mild cognitive impairment and implicate deep white matter lesions as being most detrimental in terms of neuropsychological functioning. Clinical, theoretical, and methodological implications of these results are discussed.

A dynamic multilevel model of demographic diversity and misfit effects.

In this study, the authors proposed and evaluated the linkages of a dynamic multilevel model of demographic diversity and misfit effects in a large sample of quick-service restaurants. Using a cross-level approach, the authors studied an employee's demographic misfit in relation to coworkers' demographics as a predictor of turnover risk over time. At the business-unit level, they studied changes in restaurant demographic diversity in relation to changes in profitability over time and unit turnover rates in relation to profitability. The authors also studied the impact of the match between the racial compositions of the restaurants and their communities on profitability. The results supported linkages between demographic misfit and turnover and partially supported a negative association between racial diversity and changes in profitability.

An investigation of race and sex similarity effects in interviews: a multilevel approach to relational demography.

This research studied the effects of race and sex similarity on ratings in one-on-one highly structured college recruiting interviews (N = 708 interviewers and 12203 applicants for 7 different job families). A series of hierarchical linear models provided no evidence for similarity effects, although the commonly used D-score and analysis-of-variance-based interaction approaches conducted at the individual level of analysis yielded different results. The disparate results demonstrate the importance of attending to nested data structures and levels of analysis issues more broadly. Practically, the results suggest that organizations using carefully administered highly structured interviews may not need to be concerned about bias due to the mismatch between interviewer and applicant race or sex.