Higher-order factor structures for the WISC-IV: implications for neuropsychological test interpretation

Recent Advances in Neuropsychological Test Interpretation for Clinical Practice

Much attention in the field of clinical neuropsychology has focused on adapting to the modern healthcare environment by advancing telehealth and promoting technological innovation in assessment. Perhaps as important (but less discussed) are advances in the development and interpretation of normative neuropsychological test data. These techniques can yield improvement in diagnostic decision-making and treatment planning with little additional cost. Brooks and colleagues (Can Psychol 50: 196-209, 2009) eloquently summarized best practices in normative data creation and interpretation, providing a practical overview of norm development, measurement error, the base rates of low scores, and methods for assessing change. Since the publication of this seminal work, there have been several important advances in research on development and interpretation of normative neuropsychological test data, which may be less familiar to the practicing clinician. Specifically, we provide a review of the literature on regression-based normed scores, item response theory, multivariate base rates, summary/factor scores, cognitive intraindividual variability, and measuring change over time. For each topic, we include (1) an overview of the method, (2) a rapid review of the recent literature, (3) a relevant case example, and (4) a discussion of limitations and controversies. Our goal was to provide a primer for use of normative neuropsychological test data in neuropsychological practice.

Factor structure of the new Scandinavian WISC-V version: Support for a five-factor model

The fifth version of Wechsler Intelligence Scale for Children is designed to measure five distinct aspects of intelligence, incorporating a new fluid reasoning index to the four indexes of the previous fourth version. Several factor analyses, however, have failed to support the fifth factor. The Scandinavian version is the only national version not showing clear superiority for the five-factor solution in the Manual. In the present study, we analyze WISC-V protocols from a clinical sample of 237 children tested with the new Scandinavian version. We perform six confirmatory factor analyses (CFA) testing three hierarchical-, two bifactor-, and one correlated candidate factor models. The study shows that the three-factor model does not fit the data, and that all four- and five-factor models showed good fit. The four-factor bifactor model was somewhat better than the five-bifactor and hierarchical models, but the correlated five-factor model was the superior model. Finding support for five-factors in a clinical sample representative of those most probable to be tested with the test, strengthen the claim that also the Scandinavian version measure a distinct fluid factor as intended by the test owners, and thus that clinicians may use the index scores as their main level of analysis. Review of previous CFAs show that the choice of statistical methods for CFA, bifactor or hierarchical/correlated, influence whether second order factor models are better than g-factor models.

Don’t Use a Bifactor Model Unless You Believe the True Structure Is Bifactor

The current article provides a response to concerns raised by Dombrowski, McGill, Canivez, Watkins, & Beaujean (2020) regarding the methodological confounds identified by Decker, Bridges, Luedke, and Eason (2020) for using a bifactor (BF) model and Schmid–Leiman (SL) procedure in previous studies supporting a general factor of intelligence (i.e., “g”). While Dombrowski et al. (2020) raised important theoretical and practical issues, the theoretical justification for using a BF model and SL procedure to identify cognitive dimensions remain unaddressed, as well as significant concerns for using these statistical methods as the basis for informing the use of cognitive tests in clinical applications.

Dimensional Evaluation of Cognitive Measures: Methodological Confounds and Theoretical Concerns

The current study provides a methodological review of studies supporting a general factor of intelligence as the primary model for contemporary measures of cognitive abilities. A further evaluation is provided by an empirical evaluation that compares statistical estimates using different approaches in a large sample of children (ages 9–13 years, N = 780) administered a comprehensive battery of cognitive measures. Results from this study demonstrate the ramifications of using the bifactor and Schmid–Leiman (BF/SL) technique and suggest that using BF/SL methods limit interpretation of cognitive abilities to only a general factor. The inadvertent use of BF/SL methods is demonstrated to impact both model dimensionality and variance estimates for specific measures. As demonstrated in this study, conclusions from both exploratory and confirmatory studies using BF/SL methods are significantly questioned, especially for studies with a questionable theoretical basis. Guidelines for the interpretation of cognitive test scores in applied practice are discussed.

Validation of a new tool for evaluating subjects' satisfaction with medicine package leaflets: a cross-sectional descriptive study

BACKGROUND

Package leaflets of medicines need to be intelligible, but tools for their evaluation are scarce.

OBJECTIVE

To validate a new tool for assessing subjects' satisfaction with medicine package leaflets (LiS-RPL).

DESIGN AND SETTING

Cross-sectional descriptive study conducted in two regions of Portugal (Lisbon and Centre).

METHODS

503 participants (53.1% male) were selected according to convenience and homogenously distributed into three groups: 1 to 6; 7 to 12; and > 12 years of schooling. LiS-RPL was developed based on international regulation guidelines and was initially composed of 14 items. Twelve package leaflets were tested. Dimensionality calculations included: exploratory factor analysis and minimum rank factor analysis; Kaiser-Meyer-Olkin index and Bartlett's sphericity test to assess matrix adequacy for exploratory factor analysis; exploratory bifactor analysis with Schmid-Leiman solution to detect possible existence of a broad second-order factor; and Bentler's Simplicity Index and Loading Simplicity Index to assess factor simplicity. Diverse coefficients were calculated to assess reliability.

RESULTS

Minimum rank factor analysis detected a two-factor or single-factor structure. Exploratory factor analysis with 12 items showed a two-factor structure, explaining 69.11% of the variance. These items were strongly correlated with each other (r = 0.80). Schmid-Leiman: all items seemed to represent the general factor (loadings above 0.50), which was 76.4% of the extracted variance. Simplicity indices were good (percentile 99): Bentler's Simplicity Index of 0.99 and Loading Simplicity Index of 0.48. Internal consistency indexes indicated good reliability. LiS-RPL was shown to be homogenous.

CONCLUSION

LiS-RPL is a validated tool for evaluating subjects' satisfaction with medicine package leaflets.

Latent-variable modeling of brain gray-matter volume and psychopathy in incarcerated offenders

Advanced statistical modeling has become a prominent feature in psychological science and can be a useful approach for representing the neural architecture linked to psychopathology. Psychopathy, a disorder characterized by dysfunction in interpersonal-affective and impulsive-antisocial domains, is associated with widespread neural abnormalities. Several imaging studies suggest that underlying structural deficits in paralimbic regions are associated with psychopathy. Although these studies are useful, they make assumptions about the organization of the brain and its relevance to individuals displaying psychopathic features. Capitalizing on statistical modeling, in the present study (N = 254), we used latent-variable methods to examine the structure of gray-matter volume in male offenders, and assessed the latent relations between psychopathy and gray-matter factors reflecting paralimbic and nonparalimbic regions. Results revealed good fit for a 4-factor gray-matter paralimbic model and these first-order factors were accounted for by a superordinate paralimbic "system" factor. Moreover, a superordinate psychopathy factor significantly predicted the paralimbic, but not the nonparalimbic factor. The latent-variable paralimbic model, specifically linked with psychopathy, goes beyond understanding single brain regions within the system and provides evidence for psychopathy-related gray-matter volume reductions in the paralimbic system as a whole. (PsycINFO Database Record