Research utilization and evidence-based practice among Saskatchewan massage therapists
Bibliographic record
Abstract
While massage therapy (MT) is an increasingly used health care service with a growing evidence base, there is insufficient information about the extent to which MT practice is evidence-based. The purpose of this study was to provide a comprehensive view of Saskatchewan MT's research utilization to inform the development of evidence-based massage therapy practice. The main objectives of the study were to describe MT's perceptions of research, their appraised self-efficacy in research literacy and to identify the characteristic of practitioners who use research. Using a survey design all 815 registered members of the Massage Therapist Association of Saskatchewan were invited to complete a mail-out questionnaire. A total of 333 questionnaires were completed and returned for a 41% response rate. Univariate and logistic regression analysis was conducted using SPSS 17.0. While overall perceptions of research were positive, self-efficacy in research literacy was low and research utilization was limited. Characteristics associated with research use included referring to online research databases and peer-reviewed journals, belief that practice should be based on research, and 20 or greater hours per week of practice. Provincial regulatory status may be the first step to quality service delivery and research literacy training and support is needed for practitioners.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".