Factors influencing attentional focus cueing: Structured interviews with Canadian physiotheraPIsts
Bibliographic record
Abstract
Attentional focus research has revealed that individuals adopting an external focus of attention (i.e. on the movement outcome) exhibit enhanced motor performance and learning compared to those adopting an internal focus (i.e. on the movement kinematics); however, observational studies have shown that these findings have not been translated into physiotherapy practice. Specific to this research, a first project with Canadian physiotherapists showed that they self-reported using internally focused statements at a higher relative frequency (~70%) than externally focused ones (~30%). These findings appeared to be exercise dependent as two of the six scenarios used in the 'Therapists' Perception of Motor Learning Principles Questionnaire (TPMLPQ)' showed greater use of external focus than internal focus cues. The current study sought to expand on those results by exploring the factors that influence physiotherapists' attentional focus cueing. Ontario-based physiotherapists working in private practice (N = 8) were recruited to complete the TPMLPQ and to participate in one-on-one interviews. A component of the interview targeted factors that influenced their responses to the six scenarios. Key factors identified by the physiotherapists related to client and task characteristics, and their personal experiences and education. Other influencing elements were the desire to cue efficiently and the practice of adapting to clients' successes/failures. Overall, the findings confirmed that physiotherapists had a bias towards using internal cueing and provided us with an understanding of some underlying reasons as to why it is used more frequently. Importantly, this shows the need to translate the attentional focus research into Canadian physiotherapy practice.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".