Executive function, self-regulation and attribution in acquired brain injury: A scoping review
Bibliographic record
Abstract
Impairments in executive function, self-regulation and attribution individually have been implicated in impairment in goal-directed behaviour, resulting in reduced participation in daily activities by individuals with brain injury. There is minimal literature that explicitly addresses the relationships among these constructs, how these may be affected by brain injury and the implications for rehabilitation. The objectives of this study were to determine what is known about the relationship between executive function, self-regulation and attribution, and to understand how these inter-relationships affect goal-directed behaviour in adults with acquired brain injury. A scoping review of the cognitive neuroscience, neuropsychology, rehabilitation, educational and social psychology literature from 1985 to 2011 was performed. The identified literature provided definitions of the constructs and insight into the relationships between them according to their neural underpinnings and theoretical models. These data also provided for the development of a new model illustrating the hypothesised relationships between constructs. This review and the model developed, suggest that attribution may play an important role in executive function and self-regulation. Rehabilitation interventions that address formulation of appropriate attributions should be considered in conjunction with those targeting self-regulation and executive function for individuals with brain injury.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".