Research Alert: The development of a universal screening measure for young children: Assessing social and emotional competencies in early childhood.

A quick FYI email post.  Article is NOT open access.😕

 

The development of a universal screening measure for young children: Assessing social and emotional competencies in early childhood. 
https://psycnet.apa.org/record/2027-67366-001

 

Wadington, M., Eklund, K., Kilgus, S. P., & von der Embse, N. P. (2026). The development of a universal screening measure for young children: Assessing social and emotional competencies in early childhood. School Psychology. Advance online publication. https://doi.org/10.1037/spq0000747

---

Abstract

Research highlights the importance of the early identification of social, emotional, and behavioral concerns in young children; however, there are limitations regarding the usability and technical adequacy of available measures. The purpose of the present study was the initial development and validation of the Social, Academic, and Emotional Behavior Risk Screener–Early Childhood measure, a novel tool designed to assess social, emotional, and behavioral functioning for preschool-aged children. Current analyses examined internal structure, reliability, concurrent validity, and diagnostic accuracy. Data were collected from 299 children, ages 2–6, and 42 educators from six early childhood centers in the Midwest and Southeastern regions of the United States. Results of a series of factor analyses provided support for a four-factor model and yielded adequate estimates of the internal consistency reliability of each factor. Correlational and receiver operating characteristic curve findings yielded strong support for the concurrent validity and diagnostic accuracy of the Social, Academic, and Emotional Behavior Risk Screener–Early Childhood Total Behavior, Social Behavior, Early Learning Behavior, and Challenging Behavior scales relative to Devereux Early Childhood Assessment for Preschoolers–Second Edition scales. Less support was found for the Anxious Behavior scale. Limitations, implications for practice, and future directions are also discussed. 

Research Alert: Measuring Woodcock-Johnson-5 Test-Taking Behavioral Differences Due to Tap Latency in Tablet Devices on Speed Tasks

This is a quick FYI email-based post.  Unfortunately, this is not an open access article 😕.

 

Measuring Woodcock-Johnson-5 Test-Taking Behavioral Differences Due to Tap Latency in Tablet Devices on Speed Tasks - Grace Qingyi Zhang, Kailee Kodama Muscente, A. Jordan Wright, 2026.  Journal of Psychoeducational Assessment.
https://journals.sagepub.com/doi/10.1177/07342829261449558?_gl=1*wci1m7*_up*MQ..*_ga*MTQ5OTYyMzgyNC4xNzc4MzY4NDQx*_ga_60R758KFDG*czE3NzgzNjg0NDEkbzEkZzAkdDE3NzgzNjg0NDEkajYwJGwwJGgxMjM0NDIxMzIw

 

Abstract

With the growing use of touchscreen devices in cognitive and academic testing, understanding the impact of tap latency is important for ensuring test fairness, particularly as related to speed tasks. The present study aims to understand how tap latency influences participant test-taking behaviors and performance. Using a counterbalanced within-subjects design, 203 participants aged 5–19 completed three WJ V speeded subtests on both low-latency normative administration devices (i.e., iPads) and Android tablets with an experimentally imposed, noticeable 340-ms tap latency. While the scores achieved across the two different devices were generally consistent, the actual Android scores were significantly higher than scores predicted based solely on latency-related time loss across all tasks, suggesting behavioral compensation from the tap delay. While an argument can be made that scores are comparable and thus acceptable, given tap latency’s behavioral effects and the absence of validated post-hoc score correction models, it is recommended that WJ V speeded tests be conducted on devices with minimal and consistent latency and devices with unknown, variable, or consistently higher than 340-ms tap latency should be used with caution for speeded testing.

 

Some select article quotes (and my comments) from the article:

 

The present findings also provide evidence for the behavioral impact of tap latency, such that participants tested on high-latency tablets adapted their behavior in ways that mitigated its effects.

 

Therefore, many non-iPad devices may exhibit latencies larger than 340 ms, which could result in more pronounced behavioral differences in these tasks. As such, we recommend that WJ V speeded tests be administered on devices with low and stable tap latency, ideally iPads given its minimal tap latency and its use in the normative sample…

 

• My comment:  By changing their cognitive strategies, which was evidenced by adaptation in their behavior, the non-standard iPad high latency Android condition introduced construct irrelevant variance into the subjects scores—that is, by changing their strategies to compensate for slower latencies, the subjects changed what the speeded test was measuring…a threat to construct validity.  The authors recommend the use of the iPad’s noted in the WJ V Technical Manual (LaForte, Dailey, & McGrew, 2025).

 

Riverside Insights Recommendation (click here for web page)

 

• When administering the WJ V, Riverside Insights recommends the examinee device to be an iPad with a screen size of 10” or larger, as that is how the test was standardized. Because the assessment is browser-based, we recognize the examinee can be on any tablet touchscreen device with a screen of 10” or larger and Riverside Insights cannot control the device used. Please note, using a tablet device other than an iPad on timed tests may result in differences in scores, based on the latency times of different devices. Riverside Insights strongly encourages the use of an iPad, especially on timed tests.

 

COI statement:  I am a coauthor of the WJ V, as well as prior editions (WJ III and WJ V). However, all WJ V authors no longer receive traditional sales-based royalties—payment for authoring services occurred prior to the release of the WJ V.  My more complete COI statement is available here. 

Research Alert: #Attentioncontrol ability is associated with #frontoparietal control #network interactions | PNAS - #AC #PFIT #CHC #schoolpsychologists #schoolpsychology #cognition #intelligence

Quick email-based FYI post.  Sorry—not open access article.😕  There is considerable research literature that suggests attentional control (AC as per CHC taxonomy) is a fundamental underlying cognitive mechanism of intelligence.  Click here for prior posts at IQs Corner re AC.

 

 

Attention control ability is associated with frontoparietal control network interactions | PNAS 
https://www.pnas.org/doi/abs/10.1073/pnas.2526828123

 

Significance

Attention control is fundamental to human cognition, and people differ in this trait to maintain focus. These individual differences shape success in school, work, and health, but their neural basis remains unclear. Our study shows that attention control is reflected in the brain’s dynamic interaction. Individuals higher in attention control demonstrated more coordination between the frontoparietal control network with other attention networks, as well as the locus coeruleus, a major neuromodulatory hub. Remarkably, these signatures are present even in the absence of cognitive load. These findings demonstrate that attention control is not just momentary fluctuations, but a stable trait embedded in large-scale brain dynamics, providing a framework for understanding the neural organization of individual differences.

Abstract

Attention control predicts academic achievement, professional success, and health outcomes. However, the neural basis of stable, individual differences in attention control remains unclear. Prior research has emphasized momentary fluctuations in attentional engagement, often overlooking enduring individual differences. Here, we applied the quasi-periodic pattern analysis of infraslow functional magnetic resonance imaging (fMRI) dynamics in a large sample (N = 196) to test whether trait attention control is reflected in network-level brain activity as well as the locus coeruleus (LC). Using latent-variable measures of attention control, working memory capacity, and fluid intelligence, we isolated the unique contribution of attention control across rest, 1-back, and 3-back conditions. As cognitive demand increased, individuals with higher attention control exhibited more coordinated activity of the frontoparietal control network (FPCN): they showed enhanced coupling with the dorsal attention network (DAN), and greater engagement with the LC and stronger decoupling from the default mode network (DMN). Even at rest, high attention individuals demonstrated stronger FPCN–DAN coupling and little to no correlation between FPCN–DMN, indicating that attentional capacity is reflected in both task-evoked reconfiguration and baseline network architecture. These findings reveal how attention control, as an ability, is instantiated in the brain’s dynamic architecture.

 

 

What is an “AI Brief” at IQs Corner?

I am currently working on expanding my skill set by incorporating AI tools. Although adapting to new technologies can be challenging, leveraging these resources offers significant benefits for professional growth.

AI Brief’s, at IQs Corner, are produced by requesting Google NotebookLM to generate a narrative summary of one or more PDF journal articles.  Google NotebookLM takes an uploaded article and with the prompt to “write a narrative summary of the article.”  While I find the first draft promising, I do fine the need to make corrections, add important links and missing information, and do more editing to enhance the briefs accuracy and informativeness. Future plans include using this AI tool to summarize multiple articles, find similarities and differences between the articles, and create comparative tables.

These incremental steps mark my transition toward utilizing AI to support one of my primary professional interests: producing informative blog and social media posts aimed at professionals such as school psychologists and special education teachers working with students who often are marginalized in educational contexts. The goal is to help bridge the gap between theory, technology, research, and practical application.

 

Feedback is encouraged and may be directed to iqmcgrew@gmail.com or via the social media platform (LinkedIn, Twitter/X, BlueSky) comment feature where this blog post was discovered. I’m hoping to add AI Briefs as a regular feature of IQs Corner Blog and associated social media platforms.

AI Brief: Is the Intellectual Functioning Component of AAIDD’s 12th Manual Satisficing?

AI Brief:  Is the Intellectual Functioning Component of AAIDD's 12th Manual Satisficing?

 (McGrew, 2021)

 

Dr. Kevin McGrew with assist from Google NotebookLM

 

In a commentary published in Intellectual and Developmental Disabilities, Kevin S. McGrew  evaluated the intellectual functioning section (prong 1) of the AAIDD’s 12th edition manual (2021) for diagnosing intellectual disabilities (ID). He commends the organization for finally adopting the Cattell-Horn-Carroll (CHC) theory, which aligns the manual with modern scientific consensus on cognitive abilities. However, the author expresses significant concern about the manual’s contradictory guidance on part scores, arguing that its ambiguous stance could lead to legal and diagnostic confusion. McGrew also highlights various technical measurement issues and numerous copyediting errors that he believes undermine the manual's status as an authoritative resource. He suggests that while the manual is satisfactory in its theoretical shift, it does not provide the precise clarity needed for high-stakes clinical and judicial settings.

 

_______________________

 

In his review of the 12th edition of the American Association on Intellectual and Developmental Disabilities (AAIDD) manual, McGrew (2021; link for downloading article) evaluates whether the "Intellectual Functioning Component" (aka.,prong 1 of a three-prong definition of intellectual disability—ID) provides a "satisficing"—or satisfactory and sufficient—solution for practitioners and scholars.[1] McGrew draws on over 45 years of experience in school psychology and intelligence research, theory, and test development. In addition, he draws on his expert work and consultation (since 2009) on Atkins intellectual disability (ID) death penalty cases in legal settings. McGrew provides an evaluation of the AAIDD’s manual's prong 1 (intellectual functioning) theoretical grounding, technical guidance, and professional polish. He does not evaluate the other two ID prongs (adaptive behavior and age of onset).

Advancement in Intelligence Theory

McGrew awards the manual a Grade B+ for its formal adoption of the Cattell-Horn-Carroll (CHC) theory of intelligence. This shift aligns the AAIDD manual with the contemporary consensus taxonomy of cognitive abilities, moving away from outdated models. However, McGrew notes that the manual "muddies the CHC waters" by giving preferential treatment to fluid (Gf) and crystallized (Gc) intelligence while neglecting other broad CHC abilities like learning efficiency (Gl), working memory (Gwm), retrieval fluency (Gr), auditory processing (Ga), visual-spatial processing (Gv), and processing speed (Gs). He suggests that a visual-graphic model of the CHC hierarchical model would have been a beneficial addition for users.

Measurement and Organizational Challenges

The manual receives a Grade B- for its treatment of major measurement issues. While it provides adequate coverage of such measurement issues as the standard error of measurement (SEM), confidence intervals, and the Flynn effect (aka., norm obsolescence), McGrew criticizes the lack of a topic index, which makes finding specific guidance very frustrating. For instance, practice effects are obscurely placed under "progressive error" in the glossary, and the Flynn effect is curiously categorized under "Making a Retrospective Diagnosis," despite being relevant to historical and current intellectual assessments.

The Part-Score Controversy

The most critical evaluation—a Grade C—is reserved for the manual's handling of part scores. McGrew identifies three primary failures in this area:

 

●      Inconsistency: The manual contradicts itself by advising against the use of part scores as proxies for general intelligence (psychometric g) while simultaneously suggesting that their valid use requires 3–6 subtests of Gf and Gc.

●      Variance with Other Authorities: This "just say no to part scores" stance conflicts with other major authoritative sources, such as the DSM-5, which acknowledges that highly discrepant subtest scores may invalidate an overall IQ score.

●      Scientific and Legal Tensions: McGrew argues that the manual fails to address the "General-2-individual" (G2i) legal principle which acknowledges that group-based scientific research (e.g., suggesting full-scale scores are always superior) may not apply to every unique individual case—the G2i principle conundrum is that scientists generalize; but courts must particularize to an individual. He warns that without clearer guidance; legal entities may fill the void with "remedies of dubious quality.”

Editorial Quality and Professionalism

McGrew gives the manual a Grade D for style and substance, citing at least 20 copyedit errors in the sections relevant to the intellectual functioning prong alone. These include misspellings of prominent researchers, incorrect terminology like "test e-norms," and frequent "misplaced italics.” He contends that such preventable errors tarnish the manual’s status as an "authoritative" and "definitive" source for diagnosing intellectual disabilities.

Conclusion

McGrew concludes that while the endorsement of CHC theory is a significant positive revision, the manual’s obfuscation regarding part scores and its numerous editorial flaws represent major missed opportunities. He emphasizes that practitioners cannot wait another decade for the next edition to offer more robust guidance, particularly in high-stakes legal and diagnostic settings. He concludes that while he may be a "tough grader," his critiques are intended to push AAIDD toward more robust and clearer guidance in future editions or supplements

[1] Nobel laureate Herb Simon advanced the behavioral economics concept of satisficing (Simon, 1956)—the idea that, although we may aspire to optimal solutions, real-world constraints often require us to settle on what is both satisfactory and sufficient (hence, the portmanteau term satisficing).

Research Alert: Transition Out of School for #Autistic Young People: An Umbrella Review - Norah Richards, Elizabeth Pellicano, Emeline Han, Jessica Spiegler, Laura Crane, 2026

Quick FYI email delivered research alert.  Open access article you can download👍

 

Transition Out of School for Autistic Young People: An Umbrella Review - Norah Richards, Elizabeth Pellicano, Emeline Han, Jessica Spiegler, Laura Crane, 2026 
https://journals.sagepub.com/doi/10.3102/00346543261442123?_gl=1*19f1ikj*_up*MQ..*_ga*NTgxMDAwMzM1LjE3NzgxNTY4NDk.*_ga_60R758KFDG*czE3NzgxNTY4NDkkbzEkZzAkdDE3NzgxNTY4NDkkajYwJGwwJGg3NzE5MDc1MjQ.

 

Abstract

Objective: An umbrella review to synthesize the fragmented evidence on the experiences and outcomes of transitions out of school for autistic young people, including those with intellectual disability (ID), and to identify recommendations for practice, research, and policy. Methods: An integrated narrative synthesis of 25 reviews covering 435 primary studies. Findings: Reviews were generally well-conducted, but primary evidence quality was variable. Early individualized planning and collaboration were consistent facilitators. Barriers included exclusion from decision-making, fragmented coordination, and uneven access. Long-term outcomes or adverse events were rarely considered. Few reviews included ID-specific analyses or examined intersectionality. Conclusions: The evidence base remains conceptually narrow, with limited guidance on equitable transition outcomes. Recommendations: Plan with, not for, autistic young people, including those with ID and other intersecting identities. Practice, research, and policy should align to prioritize, measure, and report meaningful outcomes.

Pardon typos and spelling errors-Message may be sent from iPhone and I've always had spelling problems :)

*

AI Brief: The trilogy-of-the-mind individual difference construct (cognitive, conative, affective) “band is getting back together” as CAMML

I am currently working to expand my skill set by incorporating AI tools. Although adapting to new technologies can be challenging, leveraging these resources offers significant benefits for professional growth.

This AI Brief was produced by requesting Google NotebookLM—recommended by Dr. Adam Lockwood—to generate a narrative summary of my 2022 PDF article describing the Cognitive-Affective-Motivation-Model of Learning (CAMML). While I found the first results promising, I made more edits to enhance its accuracy and informativeness. My next goal is to use AI to summarize multiple articles, find similarities and differences, and potentially create comparative tables (again following guidance graciously provided by Dr. Lockwood).

These incremental steps mark my transition toward utilizing AI to support one of my primary professional interests: producing informative blog and social media posts aimed at professionals such as school psychologists and special education teachers working with students who often are marginalized in educational contexts. The goal is to help bridge the gap between theory, technology, research, and practical application.

 

Feedback is encouraged and may be directed to iqmcgrew@gmail.com or via the social media platform (LinkedIn, Twitter/X, BlueSky) comment feature where this blog post was discovered. I’m hoping to add AI Briefs as a regular feature of IQs Corner Blog and associated social media platforms.

 

 

AI Brief: The trilogy-of-the-mind individual difference construct (cognitive, conative, affective) “band is getting back together” as CAMML

 

Dr. Kevin McGrew with assist from Google NotebookLM

 

The Cognitive-Affective-Motivation Model of Learning (CAMML; McGrew, 2002)[1] is a proposed theoretical framework designed to integrate contemporary motivational, affective, and cognitive constructs into a unified model for the practice of school psychology. The central thesis of the framework is that school psychologists must move beyond a narrow focus on intelligence (general intelligence or psychometric g in particular) to embrace an updated "trilogy-of-the-mind" model, which views intellectual functioning as the inseparable interaction of cognition, conation (motivation/volition), and affect.

Theoretical Foundations and the Rebirth of Conation

 

The CAMML framework is heavily rooted in the seminal work of Richard Snow, specifically his research on aptitude trait complexes. McGrew argues that the field of school psychology has historically neglected Snow’s broader definition of aptitude—which includes personality and motivational differences alongside cognitive abilities—and instead, has favored a restricted view of aptitude as synonymous with IQ or psychometric g.

 

CAMML seeks to resurrect conation (the proactive part of motivation connecting cognition and affect to behavior) as a core pillar of intellectual functioning. By "standing on the shoulders of giants" like Snow, Spearman, and Wechsler, the model asserts that cognitive processes cannot be understood in isolation from the "nonintellectual" (conative) factors that drive and direct them. For example, David Wechsler defined intelligence as "the aggregate or global capacity of the individual to act purposefully, to think rationally, and to deal effectively with his environment." While this is the core of Wechsler’s definition, he also strongly emphasized this capacity is influenced by non-intellective (conative) variables such as drive, persistence, interest, emotional states, and personality traits.

 

Structural Components of the CAMML Framework

 

The model organizes individual differences characteristics into three functional categories, which could be called the 3-D model.

 

●      Affective “Dispositions”: These are distal-to-learning traits, primarily represented by the Big 5 personality traits (specifically Openness and Conscientiousness) and their associated social-emotional facets (e.g, curiosity, creativity, persistence, focus, determination). These personality traits act as dispositions that indirectly influence learning through more proximal mechanisms.

 

●      Motivational "Drivers": Motivation is conceptualized as the initiation of behavior, formed by achievement orientations (e.g., goals, interests) and self-beliefs (e.g., self-efficacy, self-concept). These constructs are typically domain-specific (e.g., math) and work in synergistic "complexes" to energize a student's readiness to act.[2]

 

●      Volitional "Directors": Volition, or self-regulated learning (SRL), represents the post-decisional phase of action. These are the mechanisms that direct, control, and regulate behavior toward goals once a commitment to learn has been made.

 

A more detailed list of the 3-D CAMML domain constructs and definitions is available here. See figure below for a visual representation of the major affective and conative MACM constructs (click on image to enlarge for easy viewing and reading).

 

The "Crossing the Rubicon" Investment Model

 

The functional heart of CAMML is the "Crossing the Rubicon" model, which illustrates the pathway from initial desire to engaged motivated learning. In this model:

 

1. Pre-decisional Phase: Achievement orientations and self-beliefs drive or prepare the learner to start a wish—>want—> intention sequence, that eventually eventuates in motivated action.

2. Commitment: When the learner "crosses the Rubicon," they are making a firm commitment to motivated action through cognitive engagement.

3. Action Phase: Volitional (SRL) strategies steer the cyclical process via action results feedback while the learner invests cognitive abilities (such as those defined by CHC theory) to acquire knowledge.

4. Outcomes: This personal investment of fluid cognitive processes (Cattell's general gf that subsumes broad Gf, Gv, Ga, Gwm, Gl, Gr, and Gs abilities) during learning results in the development of crystallized knowledge systems (Cattell’s general gc that subsumes broad Gc, Grw, Gq, and Gkn abilities).

 

See figure below for visual representation of “the CAMML crossing the Rubicon model of motivated learning” (click on image to enlarge for easy viewing and reading).

 

Implications for School Psychology Practice

 

CAMML advocates for a paradigm shift in assessment and intervention. It suggests that school psychologists should transition from routine, comprehensive cognitive testing toward more time-efficient selective, referral-focused cognitive assessments combined with the assessment of key conative (non-cognitive) characteristics that contribute to learning aptitude complexes. This approach prioritizes identifying manipulable instructional levers, such as a student's motivational orientation (e.g., intrinsic motivation, interests, goal orientation), self-beliefs (e.g., locus of control, self-efficacy, growth or competence mindset), rather than relying exclusively on cognitive ability scores (especially full-scale IQ or g) that have proven hard to modify.

 

The framework provides a "whole-child" perspective to better address the nuances of individual differences, particularly as students move from the traditional “industrial” model of education (i.e., regularly scheduled, structured, in-class teacher-directed learning) to more of an “information-age” paradigm of education—a paradigm that requires a fuller expression of independent motivated self-regulated learning (SRL).

PS - other CAMML related posts on this blog can be found by clicking here.

[1] All relevant references can be found in McGrew (2022).

[2] The motivation constructs included in the CAMML framework are drawn from earlier efforts to develop the McGrew Model of Achievement Competence Motivation (MACM). A detailed explanation of the evolution and development of the MACM model is available elsewhere (McGrew et al., 2004). A series of recent MACM PowerPoint® modules is available here.