Assessing the impact of the 2015 introduction of increased penalties and enhanced public awareness and enforcement activities on texting while driving among adults in Ontario, Canada
Bibliographic record
Abstract
Objective: Texting while driving (TWD) is considered a particularly hazardous form of distracted driving. It is highly prevalent among young drivers, but fewer studies of TWD among adult drivers exist and these prevalence rates may approach those of younger drivers. The effectiveness of measures to prevent distracted driving, and TWD specifically, is unclear. On September 1, 2015, Ontario introduced increased penalties for distracted driving accompanied by public education programs to increase public awareness of the new regulations. Provincial police also introduced enhanced enforcement efforts. The current study examined self-reported TWD in a representative sample of Ontario adults before and after introduction of the new legislation and the enhanced public education and enforcement efforts.Methods: Data were based on telephone interviews with 1,846 respondents who reported having driven in the past year. Data were derived from the 2015–2016 cycles of the Centre for Addiction and Mental Health (CAMH) Monitor, an ongoing cross-sectional telephone survey of adults aged 18+ years in Ontario, Canada. A binary logistic regression analysis of TWD in the previous 30 days was conducted, adjusting for demographic characteristics (sex, age), driving exposure, and introduction of the legislation (before versus after).Results: The proportion of the sample reporting TWD declined significantly from 37.6% before the law was introduced to 24.2% after the law was introduced. The impact appeared to be most pronounced among drivers who reported TWD more frequently. Adjusted odds of TWD declined 42% following introduction of the legislation and associated enhanced public education and enforcement.Conclusions: These results identify a decrease in TWD following the introduction of enhanced penalties with corresponding public education and enforcement efforts, adding to the existing evaluative evidence base to inform transportation safety policy. These results also support the need to examine TWD and its determinants among all age groups.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".