Experienced Practitioners’ Beliefs Utilized to Create a Successful Massage Therapist Conceptual Model: a Qualitative Investigation
Bibliographic record
Abstract
BACKGROUND: The massage therapy profession in the United States has grown exponentially, with 35% of the profession's practitioners in practice for three years or less. Investigating personal and social factors with regard to the massage therapy profession could help to identify constructs needed to be successful in the field. PURPOSE: This data-gathering exercise explores massage therapists' perceptions on what makes a successful massage therapist that will provide guidance for future research. Success is defined as supporting oneself and practice solely through massage therapy and related, revenue-generating field activity. PARTICIPANTS AND SETTING: Ten successful massage therapy practitioners from around the United States who have a minimum of five years of experience. RESEARCH DESIGN: Semistructured qualitative interviews were used in an analytic induction framework; index cards with preidentified concepts printed on them were utilized to enhance conversation. An iterative process of interview coding and analysis was used to determine themes and subthemes. RESULTS: Based on the participants input, the categories in which therapists needed to be successful were organized into four main themes: effectively establish therapeutic relationships, develop massage therapy business acumen, seek valuable learning environments and opportunities, and cultivate strong social ties and networks. The four themes operate within specific contexts (e.g., regulation and licensing requirements in the therapists' state), which may also influence the success of the massage therapist. CONCLUSIONS: The model needs to be tested to explore which constructs explain variability in success and attrition rate. Limitations and future research implications are discussed.
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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 | 0.030 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".