Physiotherapy management of tennis elbow: An international online survey
Bibliographic record
Abstract
Tennis elbow, formally known as lateral elbow tendinopathy, is a relatively common musculoskeletal disorder of the elbow affecting approximately 1 to 3% of the general population (1). Conservative, nonsurgical, management is the preferred first line treatment for tennis elbow (2), and as such physiotherapists around the world are uniquely placed to offer a variety of management strategies. Unfortunately, current international physiotherapy practices for the management of tennis elbow are largely unknown and understanding these practices will enable better management for patients suffering from this condition. The aim of this project is to develop an understanding of the current physiotherapy management of tennis elbow internationally and to understand whether there are difference in the management strategies between countries. For the purpose of this study physiotherapy management refers to all aspects of clinical care including assessment, treatment, and coordination of continuity of care within the professional scope of practice. To achieve this aim we have developed an anonymous online survey which will be sent to registered physiotherapists of 11 countries. The selected countries are Member Organisations of the International Federation of Orthopaedic Manual Therapy (IFOMPT), where the English language is deemed one of the official languages of the country. These 11 countries include: Australia, Canada, England, Hong Kong, Ireland, New Zealand, Northern Ireland, Scotland, South Africa, United States of America, and Wales. Information collected within the survey includes: Demographic data (e.g. age, gender, level of education), Clinician’s knowledge of tennis elbow Frequency of use for common and less common assessment techniques and patient reported outcome measures Frequency of use for common and less common treatment techniques Clinician’s perceived confidence level in the assessment and treatment of tennis elbow Clinician’s opinion on key questions such as how many appointments are required to resolve the condition. References 1. Shiri R, ViikariJuntura E, Varonen H, Heliövaara M. Prevalence and determinants of lateral and medial epicondylitis: A population study. American Journal of Epidemiology. 2006;164(11):10651074. 2. Coombes BK, Bisset L, Vicenzino B. Management of lateral elbow tendinopathy: One size does not fit all. Journal of Orthopaedic and Sports Physical Therapy. 2015;45(11):938949.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".