The relative impact of work-related stress, life stress and driving environment stress on driving outcomes
DOI: 10.1016/j.aap.2011.02.004
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Summary
This study investigates the relative impact of work-related stress, life stress (daily hassles), and driving environment stress on driving outcomes, specifically unsafe driving behaviors. Motivated by previous research linking stress to crash involvement but lacking clarity on the specific contributions of different stress sources, the authors aimed to determine how extraneous stressors interact with driving-specific stress to influence driver behavior. The study posits that stress is a dynamic system where cognitive and emotional processes from one life domain (e.g., work or home) can "spill over" into the driving environment, affecting safety. The researchers employed a correlational, cross-sectional survey design involving 247 public sector employees from Queensland, Australia, who regularly drove for work purposes. Participants completed a comprehensive questionnaire including the Job-Related Tension Scale, the Driver Stress Inventory (DSI), a modified Daily Stress Inventory, the Driver Behaviour Questionnaire (DBQ), and the General Health Questionnaire-12. The study utilized confirmatory factor analysis (CFA) to identify latent stress factors and structural equation modeling (SEM) to test the predictive relationships between these stress factors and three categories of unsafe driving acts: errors, lapses, and violations. The results confirmed a three-factor model of stress: DSI negative affect (dislike of driving, fatigue), DSI risk-taking (aggression, thrill-seeking, hazard monitoring), and extraneous influences (daily hassles, work-related stress, general mental health). Moderate intercorrelations between these factors supported the spillover hypothesis. SEM revealed distinct pathways for different unsafe acts. The DSI negative affect factor significantly influenced both lapses and errors. In contrast, the DSI risk-taking factor was the strongest predictor of violations. Crucially, daily hassles independently influenced both lapses and violations, demonstrating that extraneous stress impacts driving behavior beyond on-road stressors. Work-related stress showed weaker correlations with unsafe acts compared to daily hassles and driving-specific stress. The findings imply that driver stress is not compartmentalized but is part of a holistic system influenced by life and work demands. The study highlights that negative emotional responses to driving and daily hassles significantly contribute to cognitive lapses and errors, while risk-taking tendencies drive intentional violations. These results suggest that road safety interventions should focus on increasing driver awareness of the dangers of excessive emotional responses to both driving events and daily hassles. Furthermore, training programs should aim to improve self-regulation and coping strategies for managing stress across all life domains to mitigate their negative impact on driving safety.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-19 |
| archive | success | semantic_scholar | — | — | 6 | 2026-06-26 |
| 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 | success | semantic_scholar | — | — | 4 | 2026-06-26 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| 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.
Topics
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- stress driving
- human error taxonomy
- affect mood
- anger road rage
- stress arousal performance
- shift work driving
Information type
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- Empirical Findings: physiological data
- Theoretical Contribution: theory or model, computational model