Friday, September 23, 2022

What do undergraduates learn about human intelligence? An analysis of introductory psychology textbooks.

https://psycnet.apa.org/fulltext/2018-07714-001.html

Human intelligence is an important construct in psychology, with far-reaching implications, providing insights into fields as diverse as neurology, international development, and sociology. Additionally, IQ scores can predict life outcomes in health, education, work, and socioeconomic status. Yet, students of psychology are often exposed to human intelligence only in limited ways. To ascertain what psychology students typically learn about intelligence, we analyzed the content of 29 of the most popular introductory psychology textbooks to learn (a) the most frequently taught topics related to human intelligence, (b) the accuracy of information about human intelligence, and (c) the presence of logical fallacies about intelligence research. We found that 79.3% of textbooks contained inaccurate statements and 79.3% had logical fallacies in their sections about intelligence. The five most commonly taught topics were IQ (93.1% of books), Gardner's multiple intelligences (93.1%), Spearman's g (93.1%), Sternberg's triarchic theory (89.7%), and how intelligence is measured (82.8%). Conversely, modern models of intelligence were only discussed in 24.1% of books, with only one book discussing the Carroll three-stratum model by name and no book discussing bifactor models of intelligence. We conclude that most introductory psychology students are exposed to some inaccurate information and may have the mistaken impression that nonmainstream theories (e.g., Sternberg's or Gardner's theories) are as empirically supported as g theory. This has important implications for the undergraduate curriculum and textbook authors. Readers should be aware of the limitations of the study, including the choice of standards for accuracy for the study and the inherent subjectivity required for some of the data collection process.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Thursday, September 22, 2022

The genetics of specific cognitive abilities - ScienceDirect

Posted this earlier in year when I saw in preprint.  Formal pub now out.

https://www.sciencedirect.com/science/article/pii/S0160289622000708

Most research on individual differences in performance on tests of cognitive ability focuses on general cognitive ability (g), the highest level in the three-level Cattell-Horn-Carroll (CHC) hierarchical model of intelligence. About 50% of the variance of g is due to inherited DNA differences (heritability) which increases across development. Much less is known about the genetics of the middle level of the CHC model, which includes 16 broad factors such as fluid reasoning, processing speed, and quantitative knowledge. We provide a meta-analytic review of 747,567 monozygotic-dizygotic twin comparisons from 77 publications for these middle-level factors, which we refer to as specific cognitive abilities (SCA), even though these factors are not independent of g. Twin comparisons were available for 11 of the 16 CHC domains. The average heritability across all SCA is 56%, similar to that of g. However, there is substantial differential heritability across SCA and SCA do not show the developmental increase in heritability seen for g. We also investigated SCA independent of g (SCA.g). A surprising finding is that SCA.g remain substantially heritable (53% on average), even though 25% of the variance of SCA that covaries with g has been removed. Our review highlights the need for more research on SCA and especially on SCA.g. Despite limitations of SCA research, our review frames expectations for genomic research that will use polygenic scores to predict SCA and SCA.g. Genome-wide association studies of SCA.g are needed to create polygenic scores that can predict SCA profiles of cognitive abilities and disabilities independent of g.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Specific Learning Disability Identification in an RtI Method: Do Measures of Cognitive Ability Matter? - Hajovsky - Learning Disabilities Research & Practice - Wiley Online Library

 Specific Learning Disability Identification in an RtI Method: Do Measures of Cognitive Ability Matter? - Hajovsky - Learning Disabilities Research & Practice - Wiley Online Library 
https://onlinelibrary.wiley.com/doi/10.1111/ldrp.12292

This study examined the extent to which cognitive ability index scores predicted multidisciplinary teams' (MDT) SLD identification within a response-to-intervention (RtI) method after accounting for RtI slope and norm-referenced achievement scores. Results showed that four achievement composite scores (i.e., basic reading, reading comprehension, math computation, and math problem solving) and two cognitive ability index scores (i.e., crystallized ability, working memory) predicted MDT-determined SLD, explaining 81% of the variance. The inclusion of academic achievement and cognitive ability index scores predicted MDT-determined SLD with 90% accuracy; cognitive ability index scores only increased specificity (sensitivity = 95%; specificity = 79%). RtI slope did not predict MDT-determined SLD, which was a required component of the evaluation.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Saturday, September 10, 2022

g's little helpers – VOTAT and NOTAT mediate the relation between intelligence and complex problem solving - ScienceDirect

 g's little helpers – VOTAT and NOTAT mediate the relation between intelligence and complex problem solving - ScienceDirect 
https://www.sciencedirect.com/science/article/abs/pii/S0160289622000666


Abstract
Intelligence and complex problem solving (CPS) correlate closely, but little is known about the mechanism that translates intelligence into successful CPS. Therefore, this study considered the strategic exploration behaviors VOTAT (vary-one-thing-at-a-time) and NOTAT (vary no-thing-at-a-time) as possible mediators. A sample of 495 high-school students worked on nine CPS tasks, six of which with solely direct effects and three with direct and eigendynamic effects. We expected substantial mediation effects if the applied strategic behaviors were optimal to identify the particular underlying effect types (i.e., direct effects: VOTAT; direct and eigendynamic effects: VOTAT and NOTAT). The model for tasks with only direct effects revealed VOTAT and NOTAT to be substantial mediators: Whereas VOTAT showed substantial positive relations to intelligence and CPS performance, NOTAT unexpectedly showed substantial negative relations. Both VOTAT and NOTAT resulted in significant indirect mediation effects. The model for tasks with direct and eigendynamic effects showed substantial positive relations of VOTAT and NOTAT to intelligence and CPS-performance and resulted in significant and positive indirect mediation effects. Moreover, the indirect effects differed between VOTAT and NOTAT and across the two facets of CPS performance. Overall, strategic exploration behaviors are relevant for explaining the g-CPS-relation.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Friday, September 02, 2022

Capital Defendants with Intellectual Disability | Journal of the American Academy of Psychiatry and the Law

 Capital Defendants with Intellectual Disability | Journal of the American Academy of Psychiatry and the Law 
http://jaapl.org/content/50/3/484?etoc

In Jackson v. Payne, 9 F.4th 646 (8th Cir. 2021), the U.S. Court of Appeals for the Eighth Circuit affirmed the federal district court ruling that defendant Alvin Bernal Jackson was intellectually disabled and thus was ineligible for the death penalty. The Eighth Circuit found that the district court's ruling, which did not credit Mr. Jackson's adaptive functioning strengths, was consistent with Arkansas' statutory requirements and U.S. Supreme Court precedent.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Psychological assessment reports for linguistically minoritized clients: Considerations for ethical and professional practice. - PsycNET

 Psychological assessment reports for linguistically minoritized clients: Considerations for ethical and professional practice. - PsycNET 
https://psycnet.apa.org/record/2022-96586-001

Abstract
According to the national census, approximately a fifth of the adult population in the United States uses a language other than English in their home. Less precise information is available regarding the language preferences of children and adolescents, D/deaf individuals, and other individuals in the United States who are not represented in national surveys. The field of psychology has increasingly acknowledged and addressed the lived experiences of culturally and linguistically minoritized individuals in the United States through relevant research and clinical practice guidelines. As a result, more accessible and equitable practices for psychological assessments have been developed when working with linguistically minoritized clients. Unfortunately, there is a paucity of information in the extant literature regarding drafting psychological assessment reports for linguistically minoritized clients. This article explores the ethical and professional responsibilities of psychologists when engaged in this work and provides proposed practices for drafting and delivering accessible assessment reports for linguistically minoritized clients. Recommendations are provided regarding how psychologists can share the results of an assessment with a referral source using written English and also support a client in accessing the information in their primary language. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Monday, August 29, 2022

J. Intell. | Special Issue : Assessment of Human Intelligence—State of the Art in the 2020s

J. Intell. | Special Issue : Assessment of Human Intelligence—State of the Art in the 2020s
https://www.mdpi.com/journal/jintelligence/special_issues/LRE0G69EF7

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Friday, August 26, 2022

How robust is the relationship between neural processing speed and cognitive abilities? - Schubert - Psychophysiology - Wiley Online Library

 How robust is the relationship between neural processing speed and cognitive abilities? - Schubert - Psychophysiology - Wiley Online Library 
https://onlinelibrary.wiley.com/doi/10.1111/psyp.14165

Individual differences in processing speed are consistently related to individual differences in cognitive abilities, but the mechanisms through which a higher processing speed facilitates reasoning remain largely unknown. To identify these mechanisms, researchers have been using latencies of the event-related potential (ERP) to study how the speed of cognitive processes associated with specific ERP components is related to cognitive abilities. Although there is some evidence that latencies of ERP components associated with higher-order cognitive processes are related to intelligence, results are overall quite inconsistent. These inconsistencies likely result from variations in analytic procedures and little consideration of the psychometric properties of ERP latencies in relatively small sample studies. Here we used a multiverse approach to evaluate how different analytical choices regarding references, low-pass filter cutoffs, and latency measures affect the psychometric properties of P2, N2, and P3 latencies and their relations with cognitive abilities in a sample of 148 participants. Latent correlations between neural processing speed and cognitive abilities ranged from -.49 to -.78. ERP latency measures contained about equal parts of measurement error variance and systematic variance, and only about half of the systematic variance was related to cognitive abilities, whereas the other half reflected nuisance factors. We recommend addressing these problematic psychometric properties by recording EEG data from multiple tasks and modeling relations between ERP latencies and covariates in latent variable models. All in all, our results indicate that there is a substantial and robust relationship between neural processing speed and cognitive abilities when those issues are addressed

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Monday, August 22, 2022

A meta-analysis on air traffic controllers selection: cognitive and non-cognitive predictors - ScienceDirect

 A meta-analysis on air traffic controllers selection: cognitive and non-cognitive predictors - ScienceDirect 
https://www.sciencedirect.com/science/article/abs/pii/S000187912200080X?via%3Dihub

Abstract
This psychometric meta-analysis investigated the relation of cognitive and non-cognitive factors to the training success of Air Traffic Controllers by synthesizing 51 studies (N = 65,839). Cognitive factors were classified by Cattel-Horn-Carrol theory. Cognitive composite scores and work samples were also included. Non-cognitive factors consisted of Big Five personality traits, biodata, motivation and non-cognitive composite scores. Medium effect was measured for cognitive factors (k = 45, p = .37). Quantitative knowledge, processing speed, work sample, short-term working memory, cognitive composite and visuo-spatial processing predictors showed large effects (p > .30). Significant moderating effects of criterion nature and period of publication were observed. Initial training (k = 30, p = .50) was generally better predicted than on-the-job training (k = 25, p = .18). Better predictive validity was measured from the 60's to nowadays. For non-cognitive factors, only a small effect was measured (k = 24, p = .15). Non-cognitive composites and education showed large effects (p > .30). No significant relation was measured between Big Five personality traits and success criteria. The present findings suggest that selection processes used for Air Traffic Controllers should focus on cognitive predictors or other methods of assessments. Data and scripts can be found at https://osf.io/mkyw7/.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Monday, August 15, 2022

Intelligence Correlates with the Temporal Variability of Brain Networks - ScienceDirect

 Intelligence Correlates with the Temporal Variability of Brain Networks - ScienceDirect 
https://www.sciencedirect.com/science/article/abs/pii/S0306452222004043?via%3Dihub

Abstract
Intelligence is the ability to recognize and understand objective things, and use knowledge and experience to solve problems. Highly intelligent people show the ability to switch between different thought patterns and shift their mental focus. This suggests a link between intelligence and the dynamic interaction of brain networks. Thus, we investigated the relationships between resting-state dynamic brain network remodeling (temporal variability) and scores on the Wechsler Adult Intelligent Scale using a large dataset comprising 606 individuals. We found that performance intelligence was associated with greater temporal variability in the functional connectivity patterns of the dorsal attention network. High variability in these areas indicates flexible connectivity patterns, which may contribute to cognitive processes such as attention selection. In addition, performance intelligence was related to greater temporal variability in the functional connectivity patterns of the salience network. Thus, this study revealed a close relationship between performance intelligence and high variability in brain networks involved in attentional choice, spatial orientation, and cognitive control.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Saturday, August 06, 2022

J. Intell. | Free Full-Text | Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This

 J. Intell. | Free Full-Text | Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This 
https://www.mdpi.com/2079-3200/10/3/49

Abstract
Despite substantial evidence for the link between an individual's intelligence and successful life outcomes, questions about what defines intelligence have remained the focus of heated dispute. The most common approach to understanding intelligence has been to investigate what performance on tests of intellect is and is not associated with. This psychometric approach, based on correlations and factor analysis is deficient. In this review, we aim to substantiate why classic psychometrics which focus on between-person accounts will necessarily provide a limited account of intelligence until theoretical considerations of within-person accounts are incorporated. First, we consider the impact of entrenched psychometric presumptions that support the status quo and impede alternative views. Second, we review the importance of process-theories, which are critical for any serious attempt to build a within-person account of intelligence. Third, features of dynamic tasks are reviewed, and we outline how static tasks can be modified to target within-person processes. Finally, we explain how multilevel models are conceptually and psychometrically well-suited to building and testing within-individual notions of intelligence, which at its core, we argue is cognitive flexibility. We conclude by describing an application of these ideas in the context of microworlds as a case study. View Full-Text
Keywords: cognitive flexibilityergodic assumptionformative modelsmultilevel modelscomplex problem-solving

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Friday, August 05, 2022

Reassessment of innovative methods to determine the number of factors: A simulation-based comparison of exploratory graph analysis and next eigenvalue sufficiency test. - PsycNET

 Reassessment of innovative methods to determine the number of factors: A simulation-based comparison of exploratory graph analysis and next eigenvalue sufficiency test. - PsycNET 
https://psycnet.apa.org/doiLanding?doi=10.1037%2Fmet0000527

Brandenburg, N., & Papenberg, M. (2022). Reassessment of innovative methods to determine the number of factors: A simulation-based comparison of exploratory graph analysis and next eigenvalue sufficiency test. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000527

Next Eigenvalue Sufficiency Test (NEST; Achim, 2017) is a recently proposed method to determine the number of factors in exploratory factor analysis (EFA). NEST sequentially tests the null-hypothesis that k factors are sufficient to model correlations among observed variables. Another recent approach to detect factors is exploratory graph analysis (EGA; Golino & Epskamp, 2017), which rules the number of factors equal to the number of nonoverlapping communities in a graphical network model of observed correlations. We applied NEST and EGA to data sets under simulated factor models with known numbers of factors and scored their accuracy in retrieving this number. Specifically, we aimed to investigate the effects of cross-loadings on the performance of NEST and EGA. In the first study, we show that NEST and EGA performed less accurately in the presence of cross-loadings on two factors compared with factor models without cross-loadings: We observed that EGA was more sensitive to cross-loadings than NEST. In the second study, we compared NEST and EGA under simulated circumplex models in which variables showed cross-loadings on two factors. Study 2 magnified the differences between NEST and EGA in that NEST was generally able to detect factors in circumplex models while EGA preferred solutions that did not match the factors in circumplex models. In total, our studies indicate that the assumed correspondence between factors and nonoverlapping communities does not hold in the presence of substantial cross-loadings. We conclude that NEST is more in line with the concept of factors in factor models than EGA. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Impact Statement
Exploratory factor analysis (EFA) is a method to develop hypotheses concerning common factors governing correlations among variables. This makes EFA a valuable instrument in various fields of psychology (such as test development). A key problem in EFA is to determine the optimal number of factors that fits observed correlations and keeps resulting models parsimonious. Contemporary research on this problem does not provide consensus on the optimal solution. Next Eigenvalue Sufficiency Test (NEST; Achim, 2017) and exploratory graph analysis (EGA; Golino & Epskamp, 2017) are recently proposed methods to approach this problem. Both were shown to determine accurately the number of factors in simulated factor models in which variables indicated one factor each. In our report, we compare NEST and EGA with simulated factor models in which each variable indicated multiple factors to varying degrees. These conditions suit validation of methods to detect factors because the premise of an unknown number of factors implies that one may not assume how many factors link to individual variables. We conducted two simulation studies: In Study 1, we show that methods detect factors less accurately when variables indicated multiple factors each and highlight that EGA suffered stronger than NEST. In Study 2, we simulated circumplex models—a particular class of factor models—and show that NEST achieved high accuracy while EGA was strikingly inaccurate. We discuss reasons for the methods' performances and argue that the signal that EGA detects is incongruent on a statistical level with the understanding of factors in factor analysis. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

******************************************
Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
******************************************