The Characteristics, Experiences and Perceptions of Registered Massage Therapists in New Zealand: Results from a National Survey of Practitioners
Bibliographic record
Abstract
BACKGROUND: Massage therapy is widely recognized as offering many health benefits, with a growing number of studies finding it has value in stress management, pain reduction, and overcoming physical limitations. However, there are few studies of massage therapists practices and perceptions in New Zealand and internationally. This paper reports the findings from the first national survey examining the characteristics, perceptions, and experiences of New Zealand-based massage therapists on a range of aspects related to their role and practices. PURPOSE: This study sought to ascertain the characteristics, experiences, and perceptions of massage therapists in New Zealand, particularly in the aspects of: integration of health care; attitudes and practices related to research; and evidence and attitudes to registration. SETTING: Massage practice in New Zealand (nationwide survey). PARTICIPANTS: Members of Massage New Zealand (a massage practitioners association). RESEARCH DESIGN: Massage practitioners were surveyed online, using a 65-part questionnaire, on a range of characteristics of their practices and their attitudes to research, integration, and registration. Statistical analysis was performed using STATA. Statistical significance was set at 0.05. MAIN OUTCOME MEASURES: = .004). The majority of MTs (79%) supported integration with conventional practitioners, and 83% referred clients to general practitioners, with 75% receiving referrals from general practitioners. Ninety-three percent of MTs supported registration, with 67% of those supporting statutory registration. CONCLUSION: Massage practitioners perceive that they make a significant contribution to health care, but area of practice, such as research, and referral and integration into mainstream health care require more in-depth investigation.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".