A Standardized, Evidence-Based Massage Therapy Program for Decentralized Elite Paracyclists: Creating the Model
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Evidence suggests that para-athletes are injured more often than able-bodied athletes. The benefits of massage therapy for these disabled athletes are yet to be explored. This paper documents the process followed for creating a massage program for elite paracycling athletes with the goal to assess effects on recovery, rest, performance, and quality of life both on and off the bike. SETTING: Massage therapists' private practices throughout the United States. PARTICIPANTS: A United States Paracycling team consisting of 9 elite athletes: 2 spinal cord injury, 2 lower limb amputation, 1 upper limb amputation, 1 transverse myelitis, 1 stroke, 1 traumatic brain injury, and 1 visually impaired. DESIGN: The process used to develop a massage therapy program for para-cyclists included meetings with athletes, coaching staff, team exercise physiologist, and sports massage therapists; peer-reviewed literature was also consulted to address specific health conditions of para-athletes. RESULTS: Team leadership and athletes identified needs for quicker recovery, better rest, and improved performance in elite paracyclists. This information was used to generate a conceptual model for massage protocols, and led to creation of the intake and exit questionnaires to assess patient health status and recovery. Forms also were created for a general health intake, therapist information, and a therapist's SOAAP notes. DISCUSSION: The conceptual model and questionnaires developed herein will help to operationalize an exploratory study investigating the feasibility of implementing a standardized massage therapy program for a decentralized elite paracycling team.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".