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Record W4292120683 · doi:10.2196/37448

Canadian Resources on Cannabis Use and Fertility, Pregnancy, and Lactation: Scoping Review

2022· article· en· W4292120683 on OpenAlexafffundvenueabout
Ayni Sharif, Kira Bombay, Malia S. Q. Murphy, Rebecca K. Murray, Lindsey Sikora, Kelly D. Cobey, Daniel J. Corsi

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsChildren's Hospital of Eastern OntarioOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsFertilityBreastfeedingPregnancyMedicineCannabisPublic healthFamily medicinePopulationEnvironmental healthNursingPediatricsPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Cannabis use among reproductive-aged Canadians is increasing, but our understanding of its impacts on fertility, pregnancy, and breast milk is still evolving. Despite the availability of many web-based resources, informed decision-making and patient counseling are challenging for expectant families and providers alike. OBJECTIVE: We aimed to conduct a scoping review of publicly available web-based Canadian resources to provide information on the effects of cannabis on fertility, pregnancy, and breast milk. METHODS: Following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews), we systematically searched 8 databases between January 1, 2010, and November 30, 2020, and web pages of 71 Canadian obstetrical, government, and public health organizations. We included English resources discussing the effects of cannabis on fertility, pregnancy, breastfeeding, or the exposed fetus and infant. Epidemiological characteristics, readability, and content information were extracted and summarized. RESULTS: A total of 183 resources met our inclusion criteria. Resources included content for public audiences (163/183, 89.1%) and health care providers (HCPs; 31/183, 16.9%). The resources were authored by national-level (46/183, 25.1%), provincial or territorial (65/183, 35.5%), and regional (72/183, 39.3%) organizations. All provinces and territories had at least one resource attributed to them. The majority (125/183, 68.3%) were written at a >10 grade reading level, and a few (7/183, 3.8%) were available in languages other than English or French. The breadth of content on fertility (55/183, 30.1%), pregnancy (173/183, 94.5%), and breast milk or breastfeeding (133/183, 72.7%) varied across resources. Common themes included citing a need for more research into the effects of cannabis on reproductive health and recommending that patients avoid or discontinue cannabis use. Although resources for providers were consistent in recommending patient counseling, resources targeting the public were less likely to encourage seeking advice from HCPs (23/163, 14.1%). CONCLUSIONS: Canadian resources consistently identify that there is no known safe amount of cannabis that can be consumed in the context of fertility, pregnancy, and breastfeeding. Areas of improvement include increasing readability and language accessibility and encouraging bidirectional communication between HCPs and patients. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2020-045006.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.169
Threshold uncertainty score0.340

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.090
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0420.067
Science and technology studies0.0040.002
Scholarly communication0.0050.003
Open science0.0040.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0140.001

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.

Opus teacher head0.037
GPT teacher head0.323
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2022
Admission routes4
Has abstractyes

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