Understanding the psychosocial factors influencing the risky behaviour of young drivers
DOI: 10.1016/j.trf.2009.08.003
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Summary
This study investigates the psychosocial factors influencing risky driving behaviors among young drivers aged 17–24, a demographic disproportionately represented in road crash fatalities. Motivated by the need to improve road safety interventions beyond current approaches that primarily address passenger restrictions, the research examines how social learning, social identity, and thrill-seeking variables contribute to the initiation and maintenance of risky driving. The authors aim to determine whether Akers’ social learning theory provides a comprehensive explanation for these behaviors or if additional theoretical frameworks offer significant predictive power. The researchers employed a cross-sectional survey design involving 165 licensed young drivers (105 women, 60 men) in south-east Queensland, Australia. Data were collected via a self-administered questionnaire informed by preliminary qualitative interviews. The instrument measured sociodemographic variables (age, gender, driving exposure), self-reported risky driving behaviors, and psychosocial constructs derived from Akers’ social learning theory (imitation, differential association, anticipated rewards, and punishments), Social Identity Theory (group identity), and thrill-seeking scales. Statistical analyses included bivariate correlations and hierarchical multiple regression to assess the variance in risky driving explained by these factors. The results indicated that sociodemographic variables accounted for 19% of the variance in self-reported risky driving. Akers’ social learning variables explained an additional 42% of the variance, significantly outperforming other factors. Specifically, imitation of risky behaviors by parents and peers, higher anticipated rewards for risky driving, and lower anticipated punishments were significant predictors. In contrast, thrill-seeking and social identity variables did not explain any significant additional variance when entered after social learning variables. An alternative regression model confirmed that social learning variables remained the strongest predictors, accounting for 27% of variance even when thrill-seeking and group identity were prioritized. Furthermore, self-reported risky driving was significantly correlated with traffic offenses, particularly when passengers were present, though not directly with crash involvement. The study concludes that Akers’ social learning theory offers a robust framework for understanding young driver behavior, with imitation and reinforcement mechanisms being the primary drivers of risk. The findings suggest that road safety policies and interventions should directly incorporate these psychosocial factors, focusing on modifying the rewards and punishments associated with risky driving and addressing the influence of parental and peer modeling. By targeting these specific social learning mechanisms, interventions may prove more efficacious than current strategies that largely ignore the underlying social dynamics of young driver behavior.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-17 |
| archive | success | semantic_scholar | — | — | 6 | 2026-06-25 |
| extract | success | pdftotext | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-26 |
| chunk | success | chunk | — | — | 1 | 2026-06-26 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-26 |
| enrich | failed | — | — | — | 4 | 2026-06-25 |
| promote | success | — | — | — | 1 | 2026-06-17 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-26 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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