Attitudes, beliefs, and practices regarding medication prescribing for musculoskeletal conditions: a protocol for a national Q-methodology study of Swiss chiropractors.
Bibliographic record
Abstract
BACKGROUND: Since 1995, chiropractors in Switzerland have been licensed to prescribe medications for treating musculoskeletal conditions. However, controversy remains over whether or not medication prescribing should be pursued within the chiropractic profession internationally. OBJECTIVE: To assess Swiss chiropractors' attitudes, beliefs, and practices regarding their existing medication prescription privileges. METHODS: A Q-methodology approach will be used to collect data for the assessment. In addition, scope expansion and frequency of prescribing by Swiss chiropractors will be queried using a 13-item questionnaire. Recruitment will be conducted by e-mail and all members of the Swiss Chiropractic Association will be eligible to participate. Data will be analyzed using by-person factor analysis and descriptive statistics. DISCUSSION: This will be the first national update on attitudes toward prescribing medications among Swiss chiropractors since 2003, and the first using Q-methodology. The results of this study are important as they will inform future directions and research regarding chiropractic prescription rights.
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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 | 0.052 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.008 |
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".