Characteristics of global naturopathic education, regulation, and practice frameworks: results from an international survey
Bibliographic record
Abstract
BACKGROUND: This descriptive study provides the first examination of global naturopathic education, regulation and practice frameworks that have potential to constrain or assist professional formation and integration in global health systems. Despite increasing public use, a significant workforce, and World Health Organization calls for national policy development to support integration of services, existent frameworks as potential barriers to integration have not been examined. METHODS: This cross-sectional survey utilized purposive sampling of 65 naturopathic organisations (educational institutions, professional associations, and regulatory bodies) from 29 countries. Organizational representatives completed an on-line survey, conducted between Nov 2016 - Aug 2019. Frequencies and cross-tabulation statistics were analyzed using SPSSv.25. Qualitative responses were hand-coded and thematically analysed where appropriate. RESULTS: Sixty-five of 228 naturopathic organizations completed the survey (29% response rate) from 29 of 46 countries (63% country response rate). Most education programs (68%) were delivered via a national framework. Higher education qualifications (60%) predominated. Organizations influential in education were professional associations (75.4%), particularly where naturopathy was unregulated, and accreditation bodies (41.5%) and regulatory boards (33.8%) where regulated. Full access to controlled acts, and to health insurance rebates were more commonly reported where regulated. Attitude of decision-makers, opinions of other health professions and existing legislation were perceived to most impact regulation, which was globally heterogeneous. CONCLUSION: Education and regulation of the naturopathic profession has significant heterogeneity, even in the face of global calls for consistent regulation that recognizes naturopathy as a medical system. Standards are highest and consistency more apparent in countries with regulatory frameworks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".