The use of cannabis and perceptions of its effect on fertility among infertility patients
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
Abstract STUDY QUESTION What is the prevalence of cannabis use and the perceptions of its impact on fertility among infertility patients? SUMMARY ANSWER A total of 13% of infertility patients used cannabis within the last year, and current usage is associated with patient perceptions of negative effects of cannabis on fertility and pregnancy. WHAT IS KNOWN ALREADY Cannabis use is increasing among the general population and pregnant women, particularly in places where cannabis use is legal despite having known and potential negative effects on fertility and pregnancy. STUDY DESIGN, SIZE, DURATION A cross-sectional patient survey study was performed between July 2017 and September 2017. Patients attending a university-affiliated hospital-based fertility clinic (n = 290) were invited to complete a written survey. Inclusion criteria were limited to the ability to read English. There were no exclusion criteria. PARTICIPANTS/MATERIALS, SETTING, METHODS Of the 290 patients approached, 270 (93%) agreed to participate. The questions covered demographics, cannabis usage, perceptions of the effect of cannabis on fertility and pregnancy, cessation of use due to infertility and personal history of disclosing cannabis use to healthcare providers (HCP). MAIN RESULTS AND THE ROLE OF CHANCE The results showed that 13% of respondents disclosed use of cannabis in the past year (past year users) and 38% had not used cannabis in the past year but had previously used cannabis (>1 year users) while 49% had never used cannabis (never users). Baseline demographics were similar for the three groups, but across four measures of fertility and pregnancy health, past-year users perceived less of a negative effect compared to >1 year users, and never users (P values of 0.02, 0.03, 0.01, <0.001 for questions on pregnancy, offspring health, male fertility and female fertility, respectively). Of past year users, 72% said they had or would disclose use to their HCP, but only 9.4% reported that their HCP had actually instructed them to discontinue use. LIMITATIONS, REASONS FOR CAUTION Self-reported patient surveys are subject to reporting bias and may not reflect actual use and perceptions. WIDER IMPLICATIONS OF THE FINDINGS This study suggests that cannabis use is common among infertility patients. Given the known negative impacts of cannabis on pregnancy, the authors would have expected informed infertility patients to cease cannabis use as part of their efforts to conceive. As the prevalence of cannabis use in the last year among infertility patients is similar to that in the general Canadian population, it is unclear whether the prevalence of cannabis use in the sample population merely reflects the average usage in society or, after taking into account those who reduced their usage to improve their fertility, is a factor contributing to infertility and thus prompting fertility referral. Given concern about the potential negative impact of cannabis use on fertility, and that only 9% of past year users had been instructed by an HCP to cease cannabis use, HCPs should consider the benefits of counselling about cannabis cessation for patients who are attempting to conceive. Future research should focus on analysing the effects of cannabis use on female fertility and determining whether a reduction in use among patients with infertility can improve conception rates. STUDY FUNDING/COMPETING INTEREST(S) Michelle Shin, Clinical Research Associate, is supported by the University of Toronto GREI Fellowship Fund, which is sponsored by unrestricted research grants from EMD Serono, Merck Canada and Ferring Pharmaceuticals. The authors have no potential conflicts of interest to disclose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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