Making informed choices about cannabis use during pregnancy and lactation: A qualitative study of information use
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Cannabis use during pregnancy and lactation continues to increase as some perceive cannabis to be helpful for symptom management and coping. As such, pregnant and lactating people are faced with challenging decisions, weighing benefits against the potential risks of cannabis use. To help clinicians facilitate informed choices, we explored the self-identified information needs of pregnant and lactating people who are deciding whether or not to use cannabis. We aimed to describe the modes and sources of their information-seeking and their satisfaction with the information they found. METHODS: We interviewed 52 people in Canada who made the decision to start, stop, or continue using cannabis during pregnancy and lactation. Participants were recruited from advertisements in prenatal clinics and on social media. We utilized an inductive approach to analysis focused on information used in decision-making about cannabis use, including the process of seeking and evaluating that information. RESULTS: Participants were deliberate in their search for information, most commonly seeking information on risks of use. Information sources were mainly online material or people in their social networks. Clinicians were not commonly described as a knowledgeable or supportive source of information. Overwhelmingly, participants described the information they found as insufficient and emphasized the need for more comprehensive and trustworthy sources of information. CONCLUSIONS: Participants identified distinct and unmet information needs associated with their decision to use cannabis. They described a desire for clear evidence about the impact of cannabis use, including information about how to balance the benefits they perceived from cannabis use with the risks of harm.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it