Comparing Attention Process Training and Activity-based Attention Training after acquired brain injury. A randomized controlled study
Bibliographic record
Abstract
OBJECTIVES: To compare the effects of 2 interventions for attention deficits in people with acquired brain injury, Attention Process Training (APT) and Activity--based Attention Training (ABAT), on activity and participation. DESIGN: Randomized controlled study. PATIENTS: The study included 51 patients in out-patient rehabilitation 4-12 months after stroke or traumatic brain injury. METHODS: Intervention: 20 h of attention training. MEASUREMENTS: Assessment of Work Performance (AWP), Work Ability Index (WAI), Canadian Occupational Performance Measure (COPM), and Rating Scale of Attentional Behavior (RSAB). RESULTS: Between-group comparisons showed significantly improved process skills after APT: Mental Energy (p = 0.000, ES = 1.84), Knowledge (p = 0.003, ES = 1.78), Temporal Organization (p = 0.000, ES=1.43) and Adaptation (p = 0.001, ES = 1.59). For within-group comparisons significant improvement was found between pre- and post-measures for both groups on COPM Performance (APT: p = 0.001, ES=1.85; ABAT: p = 0.001, ES = 1.84) and Satisfaction (APT: p = 0.000, ES=1.92; ABAT: p = 0.000, ES = 2.40) and RSAB Total Score (ABAT: p = 0.027, ES = 0.81; APT: p = 0.007, ES = 1.03). CONCLUSION: We found significant differences favouring APT before ABAT for process skills (AWP). There were no discernible differences in global measures of activity between the 2 approaches: both groups improved significantly, as indicated by ES. The results of this study highlight the complexities of influencing behaviour on the level of body functions while measuring effects on activity.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".