The acute effects of low dose of alcohol on simulated driving performance on young male and female drivers with high versus low testosterone levels
Bibliographic record
Abstract
Background: According to the World Health Organization, road traffic crashes represent the single leading cause of death for young people. Road traffic crashes are largely preventable, yet the precise mechanisms underlying individual driving risk remain relatively unidentified. Some risky drivers are over-represented among those involved in serious and fatal road traffic crashes, including those who misuse alcohol. Understanding what drives their risk taking is a key to developing evidence-based and effective prevention programs. Research focusing on the causes of risky driving has examined neurobiological markers of risk taking, such as cortisol, serotonin, and adrenaline. The steroid hormone testosterone has received substantial attention in relation to risk taking, but not specifically related to driving behaviour. Testosterone has been associated with sensation seeking and impulsivity, two consistent correlates of risky driving. Furthermore, interactions between testosterone and alcohol in relation to sensation seeking and impulsivity have been observed, potentially making testosterone a specific factor in driving while impaired with alcohol. In this experiment, four hypotheses were tested: H1) Young drivers with higher testosterone level show higher mean speed in simulation than young drivers with lower testosterone level; H2) Alcohol moderates the relationship between testosterone level and mean speed; H3) Sex moderates the relationship between testosterone level and mean speed; H4) Sensation seeking and impulsivity mediate the relationship between testosterone level and mean speed under alcohol. Methods: This study is part of a larger between-subject, randomized, placebo-controlled experiment. Eleven male and eleven female drivers aged 18-34 years were recruited and their saliva assayed for endogenous testosterone level using radioimmunoassay. Participants also responded to questionnaires assessing sensation seeking and impulsive personality characteristics, and performed two driving simulation tasks, one at BAC (blood alcohol content) of 0% (no-alcohol condition) and another at a positive BAC of 0.02% - 0.05% (i.e., alcohol condition). Results: H1 was not supported by the findings; young drivers with higher testosterone level did not report higher simulated speed than young drivers with lower testosterone level, p > .05. H2 was supported. A significant alcohol X testosterone interaction was detected (p = .04; partial Eta-squared = .20). Specifically, young drivers with higher testosterone level reported higher mean speed than drivers with lower testosterone level, but only after alcohol consumption. Sex was not a significant moderator of the relationship between testosterone level and simulated speed (p > .05). Neither sensation seeking nor impulsivity mediated the relationship between testosterone level and simulated speed under alcohol (p > .05).Conclusion: Interaction between testosterone hormone and alcohol may be one mechanism contributing to risky driving under legal BAC (in Canada < 0.08%). Practically, findings from this study can help future development of educational programs, based on age and sex, to better inform young drivers about neurobiological factors that can affect their ability to drive.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".