Women's perceptions and experiences with cannabis use in menopause: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: Since the legalization of recreational cannabis in 2018, the use of cannabis for medical reasons has increased in Canada. The aim of this study was to explore the experiences and perceptions of midlife women using cannabis for medical purposes coinciding with menopause symptom management. METHODS: Semistructured, one-on-one interviews were conducted using a qualitative description method. This was the second phase of a mixed methods study, where interviewees were purposefully selected from a sample of women (ages 35 and over, located in Alberta) surveyed during the first phase of the study. Interviews were by phone or virtual meeting, audio-recorded, and transcribed verbatim. Qualitative content analysis was applied to analyze the data collected. RESULTS: Twelve interviews were conducted between December 2020 and April 2021. Menopause was perceived as a complex experience for women. Cannabis was described as a therapeutic agent, providing symptom relief through the menopause transition. Women reported similarities in their menopause and cannabis use experiences in the lack of information available, limited role of healthcare providers, feelings of stigmatization, and emphasis on self-education. Women self-managed their cannabis use, learning from their own experiences or the anecdotal sharing of others', accessed cannabis from a variety of medical and nonmedical sources, and relied on experimentation, and a range of supports were described. CONCLUSION: Midlife women pursued the use of cannabis medically to manage symptoms that overlap with menopause. Understanding how and why midlife women use cannabis medically can provide insight for future research and the development of educational resources to support women in menopause.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".