Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.

(1) Background: There is a need for a brief assessment of cognitive function, both in patient care and scientific research, for which the Montreal Cognitive Assessment (MoCA) is a psychometrically reliable and valid tool. However, fine-grained normative data allowing for adjustment for age, education, and/or sex are lacking, especially for its Memory Index Score (MIS). (2) Methods: A total of 820 healthy individuals aged 18–91 (366 men) completed the Dutch MoCA (version 7.1), of whom 182 also completed the cued recall and recognition memory subtests enabling calculation of the MIS. Regression-based normative data were computed for the MoCA Total Score and MIS, following the data-handling procedure of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI). (3) Results: Age, education level, and sex were significant predictors of the MoCA Total Score (Conditional R² = 0.4, Marginal R² = 0.12, restricted maximum likelihood (REML) criterion at convergence: 3470.1) and MIS (Marginal R² = 0.14, REML criterion at convergence: 682.8). Percentile distributions are presented that allow for age, education and sex adjustment for the MoCA Total Score and the MIS. (4) Conclusions: We present normative data covering the full adult life span that can be used for the screening for overall cognitive deficits and memory impairment, not only in older people with or people at risk of neurodegenerative disease, but also in younger individuals with acquired brain injury, neurological disease, or non-neurological medical conditions.

Objective:Parkinson’s disease with mild cognitive impairment (PD-MCI) is a risk factor for progression to PD dementia (PDD) at a later stage of the disease. The consensus criteria of PD-MCI use a traditional test-by-test normative comparison. The aim of this study was to investigate whether a new multivariate statistical method provides a more sensitive tool for predicting dementia status at 3- and 5-year follow-ups. This method allows a formal evaluation of a patient’s profile of test scores given a large aggregated database with regression-based norms.Method:The cognitive test results of 123 newly diagnosed PD patients from a previously published longitudinal study were analyzed with three different methods. First, the PD-MCI criteria were applied in the traditional way. Second, the PD-MCI criteria were applied using the large aggregated normative database. Last, multivariate normative comparisons (MNCs) were made using the same aggregated normative database. The outcome variable was progression to dementia within 3 and 5 years.Results:The MNC was characterized by higher sensitivity and higher specificity in predicting progression to PDD at follow-up than the two PD-MCI criteria methods, although the difference in classification accuracy did not reach statistical significance.Conclusion:We conclude that MNCs could allow for a more accurate prediction of PDD than the traditional PD-MCI criteria, because there are encouraging trends in both increased sensitivity and increased specificity. (JINS, 2019,25, 678–687)

In decision making, people may rely on their own information as well as on information from external sources, such as family members, peers, or experts. The current study investigated how these types of information are used by comparing four decision strategies: 1) an internal strategy that relies solely on own information; 2) an external strategy that relies solely on the information from an external source; 3) a sequential strategy that relies on information from an external source only after own information is deemed inadequate; 4) an integrative strategy that relies on an integration of both types of information. Of specific interest were individual and developmental differences in strategy use. Strategy use was examined via Bayesian hierarchical mixture model analysis. A visual decision task was administered to children and young adolescents (N=305, ages 9–14). Individual differences but no age-related changes were observed in either decision accuracy or strategy use. The internal strategy was dominant across ages, followed by the integrative and sequential strategy, respectively, while the external strategy was extremely rare. This suggests a reluctance to rely entirely on information provided by external sources. We conclude that there are individual differences but not developmental changes in strategy use pertaining to perceptual decision-making in 9- through 14-year-olds. Generalizability of these findings is discussed with regard to different forms of social influence and varying perceptions of the external source. This study provides stepping stones in better understanding and modeling decision making processes in the presence of both internal and external information.

In clinical neuropsychology, it is often necessary to estimate a patient’s premorbid level of cognitive functioning in order to evaluate whether his scores on cognitive tests should be considered abnormal. In practice, test results from before the onset of brain pathology are rarely available, and the patient’s level of education is used instead as an estimate of his premorbid level. Unfortunately, level of education may be expressed on many different scales of education, which are difficult to use interchangeably. Here, we introduce a new scale that has the capacity to replace existing scales and can be used interchangeably with any of them: the Universal Scale of Intelligence Estimates (USIE). To achieve this, we propose to map all levels of existing educational scales to standard IQ scores. This USIE point estimate is supplemented with an estimation interval. We assert that USIE offers some important benefits for clinical practice and research.