NSC-ADID position statement on performance impairment in safety-sensitive positions related to cannabis and other cannabinoids
Bibliographic record
Abstract
The Alcohol, Drugs, and Impairment Division (ADID) of the National Safety Council (NSC) is a group of approximately 100 professionals, mostly forensic toxicologists, that develop tools such as position statements and assist NSC with policy to reduce death and injury from alcohol, drugs, and impairment. The following position statement was approved by a majority vote of the ADID. The ADID of the NSC supports policies that substantially reduce or eliminate safety risks from the use of cannabis (marijuana), other products with delta-9-tetrahydrocannabinol (Δ9-THC), its isomers and derivatives, and other impairing cannabinoids by persons in safety-sensitive positions. Some examples are Δ8-THC, Δ10-THC, Δ9-THC acetate (THC-O, THC-O acetate), Δ9-tetrahydrocannabiphorol (THC-P), and hexahydrocannabinol (HHC). “A safety-sensitive position can be defined as one that, if not performed in a safe manner, can cause direct and significant damage to property, and/or injury to the employee, others around them, the public and/or the environment” [1, 2]. Examples include pilots, police, military personnel, health care personnel, commercial drivers, and nuclear facility staff. Cannabis and related products can impair numerous aspects of human performance to include cognitive and psychomotor functions such as alertness, reaction time, estimating distance, decision-making, and memory. The National Academies of Sciences, Engineering and Medicine, (NASEM) concluded in 2017, “There is substantial evidence of a statistical association between cannabis use and increased risk of motor vehicle crashes” [3]. Δ9-THC has sites of action in the human brain associated with cognitive and psychomotor functions that are not reflected in its concentration in blood [4]. Therefore, when assessing impairment associated with cannabis use, Δ9-THC concentrations in biological fluids do not correlate with the degree of human performance impairment. There is no support from the literature for a Δ9-THC threshold concentration in biological fluids to ensure that there is no performance impairment in safety-sensitive positions. Recent studies proposed various wait-times depending on the route of consumption. For example, 5 h [5] or 8–12 h [6] after inhalation, and 12 h [6] after ingestion prior to performing in a safety-sensitive position. However, these proposals are not rigorous enough to ensure public safety, as almost all the studies reviewed involved single acute dosing and inhaled route of administration. There are large research gaps regarding vaping, oral, high doses, and multiple dosing of all routes of administration. Clear, robust scientific evidence from published studies is lacking to support persons working in safety-sensitive positions within 24 h after last use of cannabis and/or related products [7–14]. Some scientific evidence exists to support that some persons can safely perform safety-sensitive duties 1 week after last cannabis use [15, 16]. The bulk of scientific evidence reviewed would support most persons performing in a safety-sensitive position 1 month after last cannabis use [17–25]. Employers need to assess each job function and associated risk for accidents when defining cannabis use policies. A large body of research indicates that the use of cannabis and related products is more likely than not incompatible with the performance of safety-sensitive functions. NSC advised in 2019, “We urge employers to implement policies stating no amount of cannabis consumption is acceptable for those who work in safety sensitive positions” [26]. NSC maintains the safest policy that cannabis and related product use is incompatible with those persons engaged in safety-sensitive tasks and positions. NSC supports transferring workers to nonsafety-sensitive positions when using cannabis and other impairing cannabinoid products for recreational and/or medical purposes. None declared. No new data were generated or analyzed in support of this research.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".