The Optimization of Lateral Ankle Sprain Management Practices Among Physiotherapists in the Canadian Armed Forces
Bibliographic record
Abstract
Lateral ankle sprains (LAS) are the 3rd most common injury sustained by military members, affecting their physical readiness and thereby the operational readiness of the military. To limit the impact of LAS on the operational readiness of the Canadian Armed Forces (CAF), this thesis used three studies to investigate an approach to optimize the LAS management practices of CAF Physiotherapists. Firstly, a literature review determined the LAS management practices recommended by current best research evidence. Subsequently, 52 CAF Physiotherapists were surveyed to establish their LAS management practices. Comparing these sources revealed that over 84.6% of the respondents reported using evidence based practices across all stages of healing. However, respondents also reported a relative delay in prescribing balance strengthening exercises until the sub-acute stage of healing, and reported a limited use of balance functional performance measures across all stages of healing. A focus group of CAF Physiotherapists further explored their LAS management practices and investigated any factors affecting the implementation of a comprehensive rehabilitation program derived from current research evidence. Seven participants confirmed delaying their prescription of strengthening exercises and using a limited number of balance functional performance measures¸ but denied barriers to implementing the rehabilitation program in garrison or on deployment. A pilot study investigated the feasibility of conducting a randomized trial to determine the value of adding manual ankle mobilizations to the rehabilitation program to improve ankle dorsiflexion in 20 CAF members with LAS. It was concluded that the study design was feasible in a CAF setting, yet there were no statistically significant differences in ankle dorsiflexion between the mobilization (95.2±47.5mm) and sham groups (94.7±36.9mm) at 2 weeks (p=0.84). However, while clinically important changes in ankle dorsiflexion and self-reported function were reported by both groups, the magnitude of change was larger in the mobilization group. The recommendations of this thesis may be clinically applied by CAF Physiotherapists to optimize their LAS management practices and limit the impact of LAS on CAF operational readiness
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 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".