Executive function in phenylketonuria (PKU): Insights from the Behavior Rating Inventory of Executive Function (BRIEF) and a large sample of individuals with PKU.
Bibliographic record
Abstract
OBJECTIVE: Previous research has documented executive function (EF) impairments in individuals with early treated phenylketonuria (ETPKU). It remains unclear, however, whether some aspects of EF may be more affected than others. A number of factors, including small sample sizes and variability in EF tasks, have likely contributed to past mixed findings. The present objective was to elucidate further the EF profile associated with ETPKU, particularly as it relates to report-based assessment of EF. METHOD: Data from 286 individuals (5-48 years of age) with ETPKU on the child and adult versions of the Behavior Rating Inventory of Executive Function (BRIEF), a well-established report-based assessment tool, were analyzed. RESULTS: The Working Memory scale showed the largest effect size in both young and older ETPKU samples, with 19% of children and 29% of adults scoring in the "abnormally elevated" range. In addition, EF impairment appeared more general (i.e., affecting more domains) in the adult sample as compared to the child sample. Exploratory analyses also suggested that the presence/absence of overall impairment on the BRIEF among our ETPKU participants could be predicted based on a small subset of items. A 10-item subset showed total classification accuracy values of 90% and above for both groups. CONCLUSIONS: Working memory represents an aspect of EF that appears to be particularly affected in individuals with ETPKU. Findings also provide preliminary support of the viability for the development and/or adoption of an abbreviated screening measure for EF difficulties in children and adults with ETPKU. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".