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Record W3004789288 · doi:10.1177/1941738120901670

Cannabis Use and Sport: A Systematic Review

2020· review· en· W3004789288 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSports Health A Multidisciplinary Approach · 2020
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsCannabisAthletesMedicineContext (archaeology)Sports medicineMEDLINESystematic reviewElite athletesPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

CONTEXT: Cannabis use has increased, in large part due to decriminalization. Despite this increase in usage, it remains unclear what proportion of athletes use cannabis and what effect it has on athletic performance and recovery. OBJECTIVE: To systematically review cannabis use among athletes, including epidemiology, effect on performance and recovery, and regulations for use in sport. DATA SOURCES: PubMed, MEDLINE, and EMBASE databases were queried from database inception through November 15, 2018. A hand search of policies, official documents, and media reports was performed for relevant information. STUDY SELECTION: All studies related to cannabis use in athletes, including impact on athletic performance or recovery, were included. STUDY DESIGN: Systematic review. LEVEL OF EVIDENCE: Level 4. DATA EXTRACTION: Demographic and descriptive data of included studies relating to epidemiology of cannabis use in athletes were extracted and presented in weighted means or percentages where applicable. RESULTS: Overall, 37 studies were included, of which the majority were cross-sectional studies of elite and university athletes. Among 11 studies reporting use among athletes (n = 46,202), approximately 23.4% of respondents reported using cannabis in the past 12 months. Two studies found a negative impact on performance, while another 2 studies found no impact. There was no literature on the influence of cannabis on athletic recovery. Across athletic organizations and leagues, there is considerable variability in acceptable thresholds for urine tetrahydrocannabinol levels (>15 to 150 ng/mL) and penalties for athletes found to be above these accepted thresholds. CONCLUSION: Overall, these results suggest that approximately 1 in 4 athletes report using cannabis within the past year. Based on the available evidence, cannabis does not appear to positively affect performance, but the literature surrounding this is generally poor. Given the variability in regulation across different sport types and competition levels, as well as the growing number of states legalizing recreational cannabis use, there is a need to improve our understanding of the effects of cannabis use on the athlete and perhaps adopt a clearer and overarching policy for the use of cannabis by athletes in all sports and at all levels.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.505
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0110.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.381
Teacher spread0.317 · 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