Baseline Has no Effect on Change in Forward Shoulder Posture, Range of Motion, and Muscle Excitation Following Myofascial Release: A Velocity-dependent Investigation
Bibliographic record
Abstract
A Velocitydependent InvestigationPurpose: Rate dependence, where the initial value of a variable plays a crucial role in determining the extent and/or direction of change following an intervention, is a known factor contributing to an individual's response to drug and non-drug interventions.Surprisingly, it is not known if there is a rate-dependent effect on outcomes following a massage therapy intervention.We assessed whether there is a rate-dependent effect on forward shoulder posture (FSP), pectoralis major length (PECL), and muscle excitation of the upper (UT), middle (MT), and lower trapezius (LT), and pectoralis major (PEC) following 4 minutes of myofascial release (MFR) to the pectoral fascia.Methods: Fifty-nine right-handed participants (27±9 years, 30 females) with FSP, but otherwise asymptomatic shoulders with one MFR treatment administered by a registered massage therapist were recruited.FSP, PECL, and muscle excitation during a reaching task were measured before (PRE) and after the treatment (POST).Correlations were conducted on the difference between PRE and POST values and the sum of PRE and POST values divided by two for all variables.Results: There were no significant correlations between change scores and the average PRE and POST scores for any variable.Conclusion: There is no rate-dependent effect on FSP, PECL, and muscle excitation following a 4-minute MFR intervention.These results are the first to suggest that baseline characteristics do not influence individual responses to a massage intervention.Future work should aim to determine whether speed dependence varies with different doses and types of massage interventions and patient-reported outcomes (pain, anxiety, function, etc.) and muscle/tissue characteristics (stiffness, etc.).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".