Knowledge, practices, and attitudes of certified medical marijuana consultants in Washington state
Bibliographic record
Abstract
Background: Washington is the only U.S. state to recognize and certify the medical marijuana consultant role. Medical marijuana customers have the option to use the services of a consultant for advice on the selection of marijuana products that may benefit a qualifying terminal or debilitating medical condition, the risks and benefits of these products, and the risks and benefits of methods of administration of these products. The purpose of this study was to investigate of the knowledge, practices, and attitudes regarding medical marijuana among certified medical marijuana consultants in Washington State, and to identify sources of information used by medical marijuana consultants to advise patients regarding the use of marijuana for medical conditions. Methods: A cross-sectional mixed-mode survey was administered to a random sample of 360 Washington State medical marijuana consultants selected from the state Department of Health’s list of 740 consultants with active certification as of December 2017. Results: Most respondents (84–100%) correctly identified conditions that qualify a patient to receive an authorization to use medical marijuana. Fewer respondents (8–31%) accurately identified conditions that do not qualify a patient to receive a medical marijuana authorization, such as depression and anxiety. Consultants heartily endorsed marijuana for medical conditions and believed it carries little risk. Many felt the required training for the consultant role did not sufficiently prepare them to understand scientific information regarding marijuana benefits and risks, although they expressed reliance on this course for counseling patients. Conclusions: While consultants were generally knowledgeable regarding law and practice, additional training is advised to clarify both current evidence and current health implications of marijuana, especially for mental health conditions. State or national expansion of legal recognition of medical marijuana should include evidence-based training policies for those in positions to influence the public’s purchase and use of marijuana for health conditions.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".