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Record W2897200828 · doi:10.9778/cmajo.20180164

Cannabis use and driving-related performance in young recreational users: a within-subject randomized clinical trial

2018· article· en· W2897200828 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCMAJ Open · 2018
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal General Hospital
Fundersnot available
KeywordsRecreationRandomized controlled trialCannabisSubject (documents)PsychologyRecreational useMedicinePhysical therapyPsychiatryComputer scienceInternal medicineWorld Wide WebBiologyEcology

Abstract

fetched live from OpenAlex

<h3>Background:</h3> With the legalization of cannabis in Canada, young adults, who are already at risk of automobile crashes, may increase their use of cannabis, which may further increase the risk of crashes. We examined the effects of inhaled cannabis on driving-related performance in healthy 18- to 24-year-old recreational cannabis users. <h3>Methods:</h3> In this within-subject randomized study, participants completed tests in the no-cannabis state and at 1, 3 and 5 hours after inhalation of a standard 100-mg dose of cannabis. We then measured performance (in useful-field-of-view and driving-simulation tests) and self-reported perceptions (driving ability and safety, cannabis effects). Repeated-measures analysis of variance (for cannabis effects on continuous performance measures), Cochran <i>Q</i> tests (for performance-related crash risk and binary complex simulator task scores) and correlational analyses (for self-reported perceptions relative to performance) were employed. <h3>Results:</h3> Forty-five participants completed all 180 testing sessions. Significant effects of cannabis (relative to no cannabis) were noted on complex useful-field-of-view tasks at 3 hours (complex divided-attention task: 70 ± 24 ms v. 37 ± 12 ms, 95% confidence intervals [CIs] 28–114 ms v. 29–45 ms, <i>t</i> = −2.98, df = 41, <i>p</i> = 0.005; complex selective-attention task: 102 ± 66 ms v. 64 ± 18 ms, 95% CIs 60–144 ms v. 53–75 ms, <i>t</i> = −2.42, df = 41, <i>p</i> = 0.02) and 5 hours (complex selective-attention task: 82 ± 29 ms v. 61 ± 19 ms, 95% CIs 62–100 ms v. 48–75 ms, <i>t</i> = −2.32, df = 41, <i>p</i> = 0.03) after cannabis use when the tasks were novel (performed in a cannabis state at the first session). Participants were significantly more likely to be classified as having a high crash risk (on the basis of simulator tasks) after cannabis use (χ<i><sup>2</sup></i> = 13.23, df = 1, <i>p</i> &lt; 0.001, odds ratio 4.31, 95% CI 0.41–45.2) and reported significantly lower perceived driving ability and safety after cannabis use relative to non-use. <h3>Interpretation:</h3> Among young recreational cannabis users, a 100-mg dose of cannabis by inhalation had no effect on simple driving-related tasks, but there was significant impairment on complex tasks, especially when these were novel. These effects, along with lower self-perceived driving ability and safety, lasted up to 5 hours after use. <h3>Trial registration:</h3> The trial was registered with Health Canada (NOL [No Objection Letter] no. 215101).

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.384
Teacher spread0.323 · 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