Goal Management Training improves everyday executive functioning for persons with spina bifida: Self-and informant reports six months post-training
Bibliographic record
Abstract
Executive dysfunction accounts for significant disability for many patients with spina bifida (SB), thus indicating the need for effective interventions aimed at improving executive functioning in this population. Goal Management Training™ (GMT) is a cognitive rehabilitation approach that targets disorganised behaviour resulting from executive dysfunction, and has received empirical support in studies of other patient groups. The purpose of this study was to determine if GMT would lead to perceived improved executive functioning in the daily lives of patients with SB, as evidenced by reduced report of dysexecutive problems in daily life on self- and informant questionnaires. Thirty-eight adults with SB were included in this randomised controlled trial (RCT). Inclusion was based upon the presence of executive functioning complaints. Experimental subjects (n = 24) received 21 hours of GMT, with efficacy of GMT being compared to results of subjects in a wait-list condition (n = 14). All subjects were assessed at baseline, post-intervention, and at six-month follow-up. Self-report measures indicated that the GMT group's everyday executive functioning improved significantly after training, lasting at least 6 months post-treatment. There were no significant effects on informant-report questionnaires. Overall, these findings indicate that executive difficulties in everyday life can be ameliorated for individuals with congenital brain dysfunction.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".