Intraindividual variability in children is related to informant ratings of attention and executive function
Bibliographic record
Abstract
Objective: Attention and executive function (EF) deficits are ubiquitous in neurodevelopmental disorders including Attention Deficit/Hyperactivity Disorder (ADHD), as are high levels of intraindividual variability (IIV). Attention and EF are typically assessed using informant ratings and objective measures; however, discrepancies between different metrics often make it difficult to fully characterize a child’s attention capabilities, and IIV has been proposed as a potentially useful discriminator. Our objective was to explore the relationship between IIV, using the residualized intraindividual standard deviation (rISD) method, and informant ratings of attention and EF in a mixed pediatric sample, to determine the potential utility of IIV for aiding attention diagnostics. Another commonly used, though controversial, IIV indicator, the coefficient of variation (ICV), was calculated for comparison purposes.Method: We assessed 51 children with varying degrees of attention and EF deficits. Measures included parent and teacher responses on the Comprehensive Executive Function Inventory (CEFI) and response times (RT) on a go/no-go task, which were used to estimate IIV.Results: Mean RT, rISD, and ICV were significantly related to parent and teacher ratings of attention, though ICV showed a relatively weaker association. rISD also showed associations with parent ratings of working memory and self-monitoring, as well as teacher ratings of working memory.Conclusion: The significant, and relatively stronger, relationship between rISD and parent and teacher ratings of attention supports the use of this metric, compared to mean RT and ICV. The rISD indicator of IIV thus shows potential utility as a unique and objective measure of attention in children across various neurodevelopmental disorders and, with additional research, may prove useful for diagnosis of attention problems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".