An Examination of Feedback Use in Rehabilitation Settings
Bibliographic record
Abstract
Purpose: Examine therapists' use of extrinsic feedback in rehabilitation settings and determine its consistency with motor learning literature. Determine differences between perceived and actual feedback use of therapists. Participants: Therapists (n = 6) practicing in a private clinic with a minimum of one year of clinical experience. Patients (n = 15) receiving active therapy within a private clinic. Procedures: Two researchers observed 15 active therapy appointments. Participants were blinded to the purpose of the study. Characteristics of feedback provided by therapists were documented. Therapists completed surveys regarding perceptions of personal feedback use. Statistical Analyses: Spearman's Rho correlations determined inter-rater reliability. Differences between therapists' perceived and actual feedback use were examined using Wilcoxon Signed Ranks test. Extrinsic feedback characteristics were examined through mixed factorial ANOVAs. Results: The use of knowledge of results (KR) and terminal feedback was over-perceived by therapists, while the use of concurrent feedback was under-perceived. Motivational feedback was provided more often than knowledge of performance (KP) and KR, while KP was provided more than KR. Concurrent feedback was used more often than terminal feedback. No differences were found between distinct and accumulated feedback use. Conclusions: Therapists must be encouraged to use feedback principles that promote development and maintenance (i.e., learning) of motor skills.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".