Sunday, February 07, 2016

Research Byte: Schooling duration rather than chronological age predicts working memory between 6 and 7 years: Memory Maestros Study. - PubMed



Schooling duration rather than chronological age predicts working memory between 6 and 7 years: Memory Maestros Study. - PubMed

OBJECTIVE: Low working memory (WM) is strongly linked with poor academic…

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Neuro-hit or neuro-myth?



Neuro-hit or neuro-myth?

Teachers and parents have a great enthusiasm for the brain sciences and the light they can shed on children's and adults' learning in educational environments. We share that…

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Friday, February 05, 2016

Research Byte: Does Music Training Enhance Literacy Skills? A Meta-Analysis



Does Music Training Enhance Literacy Skills? A Meta-Analysis

Keywords: music training, reading, literacy, phonological awareness, meta-analysis, brain development Citation: Gordon RL, Fehd HM and…

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Thursday, February 04, 2016

Research Byte: A general intelligence factor in dogs via BrowZine

Why not?

Research Byte: The relations between CHC cognitive abilities and aspects of social support

Which aspects of social support are associated with which cognitive abilities for which people?

ArticleinThe Journals of Gerontology Series B Psychological Sciences and Social Sciences · January 2016with12 Reads
Impact Factor: 3.21 · DOI: 10.1093/geronb/gbv119

Abstract

Objectives.
To assess the relations between 11 aspects of social support and five cognitive abilities (vocabulary, reasoning, spatial visualization, memory, and speed of processing) and to determine whether these relations between social support and cognition are moderated by age or sex.

Method.
A sample of 2,613 individuals between the ages of 18 and 99 years completed a battery of cognitive tests and a questionnaire assessing aspects of social support. A measure of general intelligence was computed using principal components analysis. Multiple regressions were used to evaluate whether each aspect of support and/or its interactions with age or sex predicted each cognitive ability and g.

Results.
Several aspects of social support were significantly related to all five cognitive abilities and to g. When g was included as a predictor, there were few relations with specific cognitive abilities. Age and sex did not moderate any of the relations.

Discussion.
These results suggest that contact with family and friends, emotional and informational support, anticipated support, and negative interactions are related to cognition, whereas satisfaction with and tangible support were not. In addition, these aspects of support were primarily related to g, with the exception of family contact. Social support– cognition relations are comparable across the life span and the sexes.

Wednesday, February 03, 2016

Research Byte: Cognitive training enhances intrinsic brain connectivity in childhood. - Abstract



Cognitive training enhances intrinsic brain connectivity in childhood. - Abstract

Type: Journal Article, Randomized Controlled Trial, Research Support, Non-U.S. Gov't, Research Support, N.I.H.,…

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Monday, February 01, 2016

Book nook: WJ IV Clinical Use and Interpretation edited book (Flanagan and Alfonso) now available (2016)



I believe that this WJ IV resource is now available.  A link to information regarding the book from publisher is here.  A PDF copy of the book at can be downloaded here.

I am not a contributor or author of this book.  However, as per stated conflict of interests, I need to disclose that I am a coauthor of the WJ IV and thus have a potential  indirect financial interest in the success of this book.

Kudos to Dawn and Vinny and all the contributors

Thursday, January 28, 2016

"Intelligent" intelligence testing with the W IV Tests of Cognitive Ability #3: Within-CHC assessment trees - a Gf "tease"

I have decided to temporarily skip the planned third installment in this series, and provide a "tease" for a small fraction of the "intelligent" testing material I will be positing in this series.  I will post an introduction to "intelligent" intelligence testing is (as per Kaufman and as applied to the WJ IV COG/OL) after this tease post.

One feature of Alan Kaufman's "intelligent" testing with the Wecshler series has been the provision of supplemental test groupings--groups of tests that may measure a shared common ability, but a group that is not one of the test's published clusters or indexes.

I have developed what I call "Within-CHC domain assessment and interpretation trees" for all 7 CHC domains in the WJ IV COG.  I developed these assessment trees by reviewing and integrating the following sources of information.


Close examination of the CFA results in the WJ IV Technical Manual (TM)

Close examination of the EFA, cluster analysis and MDS results in WJ IV TM

Additional unpublished EFA, CFA, cluster analysis and MDS (2D & 3D) completed post-WJ IV publication (across ages 6-19)

Review of supplemental/clinical groupings for the WJ, WJ-R and WJ III (e.g., McGrew, 1986; 1984--my two WJ COG books)

Extensive unpublished “Beyond CHC”  analysis of the WJ III data

Theoretical and clinical considerations


Below is the within-Gf assessment tree.  Click on image to enlarge for clear viewing


The dark arrows with bold font labels designate the Gf clusters provided by the WJ IV.  You will see Gf, Gf-Ext, and Quantitative Reasoning.  The dashed lines suggest other tests that might be important to inspect when evaluating a person's Gf abilities.  Note the line from Gf-Ext to the Visualization test.  It is labeled Gf-Ext 4/Gf+Gv hybrid.  This label is not in bold, indicating that it is not a cluster with score norms.  Close inspection of all data analyses of the WJ IV norm data found the Visualization test tending to "hang out" or near the primary Gf tests.  Also, as reported by Carroll (1993), sometimes Gv and Gf tests frequently would form a Gf/Gv hybrid factor (it is well known that some times factor analysis has a hard time differentiating Gf and Gv indicators).  This grouping  suggests that examiners should look to see if the Visualization test is consistent with the other Gf tests....which may reflect more shared Gf variance than anything specific to the Visualization test.

Also notice the Quantitative Reasoning-Ext (RQ) supplemental grouping,  This suggests that if the Quantitative Reasoning score is either high or low, on should inspect the Number Matrices and Applied Problems tests from the ACH battery---they, at times, will "follow" the scores on the Quantitative Reasoning  cluster.

Finally, one set of CFA models in the WJ IV TM suggested a possible Gf-Verbal vs Gf-Quantitative split.  The Verbal Reasoning supplemental grouping consists of the Concept Formation, Analysis-Synthesis, Oral Vocabulary, and Passage Comprehension tests.  Below the is a section of the CFA results that support the possible Gf-Verbal and Gf-Quantitative distinction.  This information is in the WJ IV Technical Manual.  This information suggests that the TM can be your "friend."  It contains considerable valuable information regarding tests that are not part of a cluster, but that showed evidence of some shared variance with a possible published cluster, or new clinical supplemental test groupings I will present.

Given that I know that people tend to not to devour technical manuals like I do, my assessment trees are aids that incorporate all of this information in visual-graphic form--saving you from having to extract this potential interpretation-relevant information from the TM.

Stay tuned.  Some of the within-CHC assessment trees suggest many more test groupings to consider for clinical interpretation (than this Gf example.)

I, Kevin McGrew, am solely responsible for this content.  The information presented here (and in this series) does not necessarily reflect the views of my WJ IV coauthors or that of the publisher of the WJ IV. 

Click on images to enlarge



Wednesday, January 27, 2016

Research Byte: Neurocognitive and Behavioral Predictors of Math Performance in Children With and Without ADHD via BrowZine

Neurocognitive and Behavioral Predictors of Math Performance in Children With and Without ADHD
Antonini, T. N.; Kingery, K. M.; Narad, M. E.; Langberg, J. M.; Tamm, L.; Epstein, J. N.
Journal of Attention Disorders, Vol. 20 Issue 2 – 2016: 108 - 118

10.1177/1087054713504620

University of Minnesota Users:
http://login.ezproxy.lib.umn.edu/login?url=http://jad.sagepub.com/cgi/doi/10.1177/1087054713504620

Non-University of Minnesota Users: (Full text may not be available)
http://jad.sagepub.com/cgi/doi/10.1177/1087054713504620

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Research Byte: Mathematical Problem-Solving Abilities and Chess | SAGE Open



Mathematical Problem-Solving Abilities and Chess | SAGE Open

Abstract Chess is thought to be a game demanding high cognitive abilities to be played well. Although many studies proved the link between…

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Research Byte: The Frequency of Rapid Pupil Dilations as a Measure of Linguistic Processing Difficulty



Cool assessment concept.

The Frequency of Rapid Pupil Dilations as a Measure of Linguistic Processing Difficulty

by Vera Demberg, Asad SayeedWhile it has long been known that the pupil reacts to cognitive load, pupil size has…

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Research Byte: Siblings' sex is linked to mental rotation performance in males but not females via BrowZine

Siblings' sex is linked to mental rotation performance in males but not females
Frenken, Hannah; Papageorgiou, Kostas A.; Tikhomirova, Tatiana; Malykh, Sergey; Tosto, Maria G.; Kovas, Yulia
Intelligence, Vol. 55 – 2016: 38 - 43

10.1016/j.intell.2016.01.005

University of Minnesota Users:
http://login.ezproxy.lib.umn.edu/login?url=http://www.sciencedirect.com/science/article/pii/S0160289616300174

Non-University of Minnesota Users: (Full text may not be available)
http://www.sciencedirect.com/science/article/pii/S0160289616300174

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Sunday, January 24, 2016

"Intelligent" testing with the WJ IV Tests of Cognitve Ability #2: Connecting the dots of relevant intelligence research

Click on image to enlarge.

Research that falls under the breadth of the topic of human intelligence is extensive. 

For decades I have attempted to keep abreast with intelligence-related research, particularly research that would help with the development, analysis, and interpretation of applied intelligence tests.   I frequently struggled with integrating research that focused on brain-behavior relations or networks, neural efficiency, etc.  I then rediscovered a simple three-level categorization of intelligence research by Earl Hunt.  I modified it into a four-level model, and the model is represented in the figure above.

In this "intelligent" testing series, primary emphasis will be on harnessing information from the top "psychometric level" of research to aid in test interpretation.  However, given the increased impact of cognitive neuropsychological research on test development, often one must turn to level 2 (information processing) to understand how to interpret specific tests.

This series will draw primarily from the first two levels, although there may be times were I import knowledge from the two brain-related levels.

To better understand this framework, and put the forthcoming information in this series in proper perspective, I would urge you to view the "connecting the dots" video PPT that I previously posted at this blog. 

Here it is.  The next post will start into the psychometric level information that serves as the primary foundation of "intelligent" intelligence testing.



Friday, January 22, 2016

"Intelligent" testing with the WJ IV Tests of Cognitive Ability: #1: The big picture perspective

Today I am launching a new series called "Intelligent" testing with the WJ IV Tests of Cognitive Ability (credit goes to Dr. Alan Kaufman for coining this term and approach to clinical intelligence test interpretation).

Since the WJ IV was published in 2014, after spending more than a year traveling the country introducing the WJ IV battery to various professional groups, it has become clear that users are hungry for more advanced interpretation material, particularly for the cognitive ability tests.

I have been busy the past 6 months completing all kinds of new analyses, reading literature, and revisiting the information in the technical manual.  As a result, I have developed some new advanced interpretation material for the cognitive (and related oral language) tests.  I will be presenting a large portion of this material at my half-day workshop at NASP in New Orleans in February.

Before presenting the new material, I first believe it is important that individuals have a proper "big picture" perspective on the strengths and limitations of intelligence testing.  I have presented this big picture material in a brief YouTube video I posted previously.  It is provided (again) below.  There will be one more additional "big picture" post prior to delving into the WJ IV specific information.

Stay tuned.  The scheduling of these posts will be on a "as I have time" basis.


Research Byte: Processing speed differences between 70- and 83-year-olds matched on childhood IQ via BrowZine

Processing speed differences between 70- and 83-year-olds matched on childhood IQ
Deary, Ian J.; Ritchie, Stuart J.
Intelligence, Vol. 55 – 2016: 28 - 33

10.1016/j.intell.2016.01.002

University of Minnesota Users:
http://login.ezproxy.lib.umn.edu/login?url=http://www.sciencedirect.com/science/article/pii/S0160289616000039

Non-University of Minnesota Users: (Full text may not be available)
http://www.sciencedirect.com/science/article/pii/S0160289616000039

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Tuesday, January 19, 2016

Research Byte: Study suggests writing places greater demands on working memory than reading and listening

Logo of advcogpsychAbout ACPSubscribeSumit a manuscriptACP Journal
 
Adv Cogn Psychol. 2015; 11(4): 147–155.
Published online 2015 Dec 31. doi:  10.5709/acp-0179-6
PMCID: PMC4710969

Writing, Reading, and Listening Differentially Overload Working Memory Performance Across the Serial Position Curve

Abstract

Previous research has assumed that writing is a cognitively complex task, but has not determined if writing overloads Working Memory more than reading and listening. To investigate this, participants completed three recall tasks. These were reading lists of words before recalling them, hearing lists of words before recalling them, and hearing lists of words and writing them as they heard them, then recalling them. The experiment involved serial recall of lists of 6 words. The hypothesis that fewer words would be recalled overall when writing was supported. Post-hoc analysis revealed the same pattern of results at individual serial positions (1 to 3). However, there was no difference between the three conditions at serial position 4, or between listening and writing at positions 5 and 6 which were both greater than recall in the reading condition. This suggests writing overloads working memory more than reading and listening, particularly in the early serial positions. The results show that writing interferes with working memory processes and so is not recommended when the goal is to immediately recall information.
Keywords: working memory, reading, listening, writing, serial recall