Evaluation of an Adolescent Hospital-Based Injury Prevention Program
Bibliographic record
Abstract
BACKGROUND: IMPACT (Impaired Minds Produce Actions Causing Trauma) is an adolescent, hospital-based program aimed to prevent injuries and their consequences caused by alcohol or drug impairment and other high-risk behaviors. The overall objective of this evaluation was to determine the effect of the program on students' knowledge and behavior regarding drinking and driving, over time. METHODS: A randomized control trial between students randomly selected to attend IMPACT and those not selected served as a control group. Students completed a questionnaire before the program and at three posttime periods (1 week, 1 month, and 6 months). Panel data models were used to analyze the effects of the experiment on students' knowledge of alcohol and crash issues and negative driving behaviors (no seat belt, driving while using a cell phone, involved in conversation, eating, annoyed with other drivers, and drowsy). Descriptive statistics and logistic regression models were used to analyze the effect of IMPACT on students' influence on friends and family about road safety. RESULTS: This study consisted of 269 students (129 IMPACT; 140 control) with an overall response rate of 84% (range, 99% presurvey to 71% at 6 months). The IMPACT group had a 57%, 38%, and 43% increase in the number of correct answers on alcohol and crash issues during the three time periods, respectively (p < 0.05). Students in the IMPACT group would try to influence friends and family to improve their road safety twice as often as 1-week postprogram (odds ratio 1.94, confidence interval 1.07, 3.53). The models did not suggest that the program had an effect on negative driving behaviors. Men and students who drove more frequently had worse driving behavior. CONCLUSIONS: Our evaluation demonstrates that the IMPACT program had a statistically significant, positive effect on students' knowledge of alcohol and crash issues that was sustained over time. IMPACT had an initial effect on students' behaviors in terms of peer influence toward improving road safety (i.e., buckling up, not drinking, and driving) 1 week after the program, but this effect diminished after 1 month. Other negative driving behaviors had low prevalence at baseline and were not further influenced by the program.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".