Clinician responses to cannabis use during pregnancy and lactation: a systematic review and integrative mixed-methods research synthesis
Bibliographic record
Abstract
BACKGROUND: Perinatal cannabis use is increasing, and clinician counselling is an important aspect of reducing the potential harm of cannabis use during pregnancy and lactation. To understand current counselling practices, we conducted a systematic review and integrative mixed-methods synthesis to determine "how do perinatal clinicians respond to pregnant and lactating patients who use cannabis?" METHODS: We searched 6 databases up until 2021-05-31. Eligible studies described the attitudes, perceptions, or beliefs of perinatal clinician about cannabis use during pregnancy or lactation. Eligible clinicians were those whose practice particularly focusses on pregnant and postpartum patients. The search was not limited by study design, geography, or year. We used a convergent integrative analysis method to extract relevant findings for inductive analysis. RESULTS: Thirteen studies were included; describing perspectives of 1,366 clinicians in 4 countries. We found no unified approach to screening and counselling. Clinicians often cited insufficient evidence around the effects of perinatal cannabis use and lacked confidence in counselling about use. At times, this meant clinicians did not address cannabis use with patients. Most counselled for cessation and there was little recognition of the varied reasons that patients might use cannabis, and an over-reliance on counselling focussed on the legal implications of use. CONCLUSION: Current approaches to responding to cannabis use might result in inadequate counselling. Counselling may be improved through increased education and training, which would facilitate conversations to mitigate the potential harm of perinatal cannabis use while recognizing the benefits patients perceive.
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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 | 0.009 | 0.201 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".