Clarifying Definitions for the Massage Therapy Profession: the Results of the Best Practices Symposium†
Bibliographic record
Abstract
BACKGROUND: Massage therapists are at times unclear about the definition of massage therapy, which creates challenges for the profession. It is important to investigate the current definitions and to consider the field as a whole in order to move toward clarity on what constitutes the constructs within the profession. PURPOSE: To determine how a sample of experts understand and describe the field of massage therapy as a step toward clarifying definitions for massage and massage therapy, and framing the process of massage therapy practice. SETTING: A two-day symposium held in 2010 with the purpose of gathering knowledge to inform and aid in the creation of massage therapy best practice guidelines for stress and low back pain. PARTICIPANTS: Thirty-two experts in the field of massage therapy from the United States, Europe, and Canada. DESIGN: Qualitative analysis of secondary cross-sectional data using a grounded theory approach. RESULTS: Three over-arching themes were identified: 1) What is massage?; 2) The multidimensional nature of massage therapy; and 3) The influencing factors on massage therapy practice. DISCUSSION: The data offered clarifying definitions for massage and massage therapy, as well as a framework for the context for massage therapy practice. These clarifications can serve as initial steps toward the ultimate goal of creating new theory for the field of massage therapy, which can then be applied in practice, education, research, and policy. CONCLUSIONS: Foundational research into how experts in the profession understand and describe the field of massage therapy is limited. Understanding the potential differences between the terms massage and massage therapy could contribute to a transformation in the profession in the areas of education, practice, research, policy and/or regulation. Additionally, framing the context for massage therapy practice invites future discussions to further clarify practice issues.
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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 | 0.139 | 0.168 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".