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Record W4385792581 · doi:10.1111/add.16315

Cannabis and sport: A World Anti‐Doping perspective

2023· editorial· en· W4385792581 on OpenAlexaff
Thomas J. Hudzik, Marilyn A. Huestis, Sabina Strano Rossi, Yorck‐Olaf Schumacher, Peter Harcourt, Richard Budgett, Mark Stuart, J.N.A. Tettey, Irene Mazzoni, Olivier Rabin, Anne Danion, Michael D. Culler, David J. Handelsman, Mario Thevis, Audrey Kinahan

Bibliographic record

VenueAddiction · 2023
Typeeditorial
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsWorld Anti-Doping Agency
Fundersnot available
KeywordsCannabisAthletesCannabidiolMedicinePopulationPsychiatryPsychologyFamily medicineEnvironmental healthPhysical therapy

Abstract

fetched live from OpenAlex

It is the opinion of the World Anti-Doping Agency (WADA) that cannabis should remain a banned substance in sport. The purpose of this editorial is to briefly summarize the elements of the discussion leading to the continued ban in sport. Cannabis availability and its subsequent use, misuse and incidence of use disorder are increasing globally [1], even as the potency of the plant, gauged by delta-9-tetrahydrocannabinol (∆9-THC content), continues to increase [2]. It is not known what proportion of top-level athletes regularly consume cannabis. However, a recent review of self-reports that included more than 46000 athletes suggests that the proportion of athletes using cannabis is no different from the age-matched general population [3]. The World Anti-Doping Agency (WADA) banned cannabis in competition in all sports when the 2004 List of Prohibited Substances and Methods was first released under the World Anti-Doping Code [4]. It has since revisited and updated the cannabinoid category to include synthetic cannabinoids, increase reporting thresholds and to specifically exempt cannabidiol. In response to stakeholder requests, the WADA Executive Committee asked for a review of the status of cannabis. Ad hoc committees conducted a scientific, ethical and medical review of the effects of cannabis, focusing upon the primary psychoactive ingredient, ∆9-THC, among the more than 100 distinct cannabinoids within the cannabis plant. For any substance or method to be considered for inclusion in the Prohibited Substances List as per the World Anti-Doping Code, two of the following three equally-important criteria must be met: (1) it enhances or has the potential to enhance sport performance, (2) it represents an actual or potential risk to the health of the athlete and (3) it violates the spirit of the sport as defined in the Code. In 2022, WADA reviewed more than 2700 articles for the present exercise. Inclusion of a scientific study or review to be further discussed was aided by adherence to scientific principles, where appropriate. This included application of rigorous methods, such as randomization of subjects to treatment groups, use of placebo controls and blinding of both subject and experimenter. Publication in a peer-reviewed scientific journal was required, and greater emphasis was placed upon studies that had results which were independently replicated. This enabled the Expert List, Athletic, Ethical and Health, Medical and Research committees to review the most current science and issue independent opinions on the subject. Finally, as part of the scientific review process, world leading experts on cannabis and addiction behavior were consulted to validate the conclusions of the committees. Perspectives were mixed on the first List inclusion criterion. There were no rigorously conducted studies reviewed that indicated any direct ergogenic effect of cannabis. Nonetheless, a number of reports suggested that other benefits may be conferred by use of the drug, such as reduction in pain or anxiety [5, 6] associated with athletic competition. Some athletes report benefit following athletic performance, by facilitating recovery and reducing pain. Hence, while there may be benefits perceived by some athletes, there were no scientific data to support performance enhancement. There was far more agreement on the second criterion—actual or potential risk to the health of the athlete. There is a comprehensive historical literature as well as a rapidly growing body of contemporary literature supporting the assertion that cannabis use can negatively impact the health, safety or wellbeing of the athlete. Acute intoxication can result in deficits in reaction time, temporal estimation and dexterity [7-11] as well as in psychiatric symptoms [12]. Not all studies detected similar changes; results will vary with the dose, route, subjects’ experience and test methods employed. Chronic, frequent use of cannabis is associated with an increased risk of cannabis use disorder, as recently reviewed by Robinson and colleagues [13], as well as potentially other long-term changes [14, 15], including an increased risk of precipitation of severe mental illness [16]. There is a growing body of evidence that cannabis use can affect brain development and anatomy in adolescents and young adults [17-19], although the consequences of these changes are not yet firmly established. The potential of cannabis use to compromise the health and safety of the athlete qualifies the application of this criterion. WADA emphasizes that prohibition of cannabis is in-competition only, which is defined as after 23:59 hours on the day prior to competition. The current decision limit of 180 ng/ml of ∆9-THC-COOH in urine and a cut-off of 150 ng/ml, plus the uncertainty of measurement of 30 ng/ml, takes this into account. Because of these high thresholds, primarily chronic, frequent cannabis users and athletes consuming high doses in-competition will be detected. Therefore, the cut-off generally will not affect the freedom of an athlete who wishes to legally consume cannabis outside of competition. Athletes who have a need for medicinal cannabis treatment should request a therapeutic use exemption (TUE). Marilyn Huestis: Conceptualization (equal); writing—review and editing (equal). Sabina Strano-Rossi: Conceptualization (equal); data curation (equal); writing—review and editing (equal). Yorck-Olaf Schumacher: Conceptualization (equal); validation; writing—review and editing (equal). Peter Harcourt: Conceptualization (supporting). Richard Budgett: Conceptualization (equal); writing—review and editing (equal). Mark Stuart: Conceptualization (equal); writing—review and editing (equal). Justice Tettey: Conceptualization (equal); writing—review and editing (equal). Irene Mazzoni: Conceptualization (equal); data curation (equal); project administration (equal); resources (equal); writing—review and editing (equal). Olivier Rabin: Conceptualization (equal); supervision (equal); writing—review and editing (equal). Anne Danion: Conceptualization (equal); data curation (equal); project administration (equal); resources (supporting); writing—review and editing (equal). Michael Culler: Conceptualization (equal); writing—review and editing (equal). David Handelsman: Conceptualization (equal); writing—review and editing (equal). Mario Thevis: Conceptualization (equal); writing—review and editing (equal). Audrey Kinahan: Conceptualization (equal); project administration (equal); supervision (equal); writing—review and editing (equal). None. No competing interests declared by any author. Data were derived from public domain resources.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.309
Teacher spread0.298 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations8
Published2023
Admission routes1
Has abstractyes

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