Training brain injury rehabilitation therapists to use generalized teaching and interaction skills
Bibliographic record
Abstract
Persons sustaining a brain injury often exhibit aberrant response patterns and skill deficits that require remediation. To promote recovery, rehabilitation staff must be competent in use of therapeutic teaching and interaction skills. This study focused on teaching 13 direct-care rehabilitation therapists these skills in a multiple baseline design across skill dimensions. Performance-based approaches were used to promote acquisition of therapist skills, and the 'general case' strategy was used to enhance generalization. The general case approach involved use of multiple examples of teaching and interaction situations selected to sample the range of variability in the rehabilitation setting. Therapists were videotaped in simulations of various teaching and interaction situations before and after staff training. These observations were coded for correct use of teaching and interaction skills. Therapists demonstrated mean increases of approximately 30 percentage points in correct skill use after training. The present training format appears to provide an efficient strategy for training staff to promote rehabilitation efforts.
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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 | 0.001 |
| 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) | 0.001 | 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 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".