Canadian physiotherapists' self-reported attentional focus use for instructions and feedback in rehabilitation
Bibliographic record
Abstract
Research on a wide array of populations and tasks has shown that adopting an external focus (EF) of attention (i.e., attention on movement outcome) enhances motor performance and learning as compared to adopting an internal focus (IF; attention on movement kinematics). Given that the goal of much research is to have findings translated into applied settings, the aim of this study was to determine the relative percentage of time that Canadian physiotherapists would use IF and EF statements in their practice. To do this, a questionnaire was designed that included six scenarios: three for which physiotherapists would provide feedback and three for which instruction would be given to clients. For each scenario, an IF and an EF cue were presented and physiotherapists selected the percentage of time each would be provided to a client. Questionnaires were distributed both online and as paper copies through clinics, and at the CPA's annual forum; preliminary data was collected for N=62 physiotherapists (mean age= 43 ± 12 years). Overall, results showed that participants self-reported an average relative frequency of IF statements of 66.6% (SD=19.6) for feedback and 70.5% (SD=16.0) for instruction. However, cue provision appears to be task-dependent, since a majority of physiotherapists self-reported providing EF cues more often than IF ones for a functional reaching task and a strength training scenario. Gaining a comprehension of rehabilitation tasks, and the effect of their unique features for physiotherapists' use of attentional focus cues, is essential to inform the design of possible future educational workshops.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".