Supportive but “worried”: perceptions of naturopaths, homeopaths and Chinese medicine practitioners through a regulatory transition in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: In line with recent World Health Organization recommendations, many jurisdictions are taking steps to regulate practitioners of traditional, complementary and alternative medicine (TCAM). Previous studies have examined TCAM practitioners' generally-supportive views about professional regulation; however, little research has been conducted on TCAM practitioners' experiences and perspectives amidst an active regulatory process. In 2006 and 2007, the province of Ontario, Canada announced it would grant self-regulatory status to three TCAM practitioner groups--homeopaths, naturopaths and Chinese medicine practitioners/acupuncturists. METHODS: In 2011 and 2012, part-way through each group's regulatory process, we surveyed all practitioners from these three groups (n=1047) that could be identified from public registries and professional associations. The data presented here are derived from the sub-sample of homeopaths (n=234), naturopaths (n=273) and Chinese medicine practitioners/acupuncturists (n=181) who provided answers to an open-ended question about their opinions of the regulatory process at the end of the survey. An inductive, thematic analysis of qualitative survey responses was conducted. RESULTS: Survey responses affirmed a pro-regulatory stance across all groups, but revealed considerable 'worry' amongst practitioners as to how the regulations might be implemented. Four primary 'worry-related' themes emerged: a) regulation's potential administrative and financial burden on practitioners; b) scope-related concerns; c) implementation of fair registration standards; and d) whether regulation might erode the groups' distinctive worldviews. Some occupationally-specific concerns appeared related to each group's particular stage of professionalization. Other 'worries' may be related to the relative marginality of TCAM practitioner groups within biomedically-dominant national health care systems, and the possibility that inter-professional hierarchies may be emerging between particular TCAM groups. Specific concerns around overlapping practice scopes between TCAM and other professions raised questions about the implementation of non-monopolistic regulatory models such as Ontario's. CONCLUSIONS: Overall, this study will help inform regulators and TCAM practitioner groups to navigate the unique challenge of regulating health care providers long excluded from national health care systems, who frequently work from within paradigms distinct from mainstream biomedicine.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".