A Commentary on the Role of Randomized Controlled Trials in Massage Therapy
Bibliographic record
Abstract
Some massage therapists (MTs) view research as a way to demonstrate to other healthcare professionals (OHPs) that massage therapy is safe and effective and should be an integral part of patients’ health care. This desire for credibility through research, however, requires studies that are acceptable to medical professionals. Therefore, researchers have begun to study massage therapy, primarily using randomized controlled trials (RCTs). Many of the RCTs of massage therapy, rather than proving efficacy, have been met with criticism, including their lack of reproducibility and lack of a suitable control. The belief that RCTs will save the profession of MT, or any health care practice, by proving treatments work, is unfounded. Evidence hierarchies suggest that practitioners should accept the results of RCTs, or the systematic review of RCTs, as the gold standard for efficacy research. Privileging one methodology over another does not use the benefits of the multiple approaches to research available. Researchers should consider whether there are other methodologies that allow for rigorous investigation of massage therapy in a way that would be useful for stakeholders of this research. It is only through research that is rigorously and authentically conducted that the credibility of massage therapy will be established.
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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 | 0.290 | 0.676 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.014 | 0.024 |
| Open science | 0.023 | 0.008 |
| Research integrity | 0.102 | 0.111 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".