Psychological and sociodemographic characteristics of accident involved drivers : a survey of the literature.

Lynn, Cheryl · 1976 · ROSA P / Virginia Transportation Research Council

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Summary

This 1976 literature review by Cheryl W. Lynn examines the psychological and sociodemographic characteristics of drivers involved in traffic accidents, aiming to identify variables that could predict negligent driving behavior. The study was motivated by the recognition that while roadway and vehicle factors were well-studied, the driver remained the most influential yet least quantifiable variable in accident causation. The primary objective was to assess the state of research regarding the psychology of negligent driving, determine if crash occurrence follows predictable patterns rather than chance, and identify areas for future research that could yield valid predictive models for high-risk drivers. The methodology consists of a comprehensive survey of existing literature, organized chronologically and by theoretical complexity. Lynn evaluates several major philosophical constructs and empirical studies, including the "natural selection" hypothesis, demographic and driving record theories, accident proneness, life stress or crisis theories, and personality factor analyses. The review synthesizes findings from various researchers, such as Selzer, Waller, and Harano, examining data on fatally injured drivers, violation records, and psychological autopsies. The analysis critiques previous studies for methodological limitations, such as small sample sizes, retrospective data collection, and the lack of prospective validation. The review finds that demographic groups, particularly young males, are disproportionately represented in crash data, suggesting non-random patterns in accident occurrence. However, traditional predictors like past driving records and single demographic variables have limited predictive validity due to inconsistencies in record-keeping and the instability of risk factors. The concept of "accident proneness" as a stable trait is largely discredited; instead, research supports a distinction between long-term risk (associated with chronic psychological issues) and short-term risk (triggered by acute life stressors like marital conflict or financial pressure). Studies indicate that fatally injured drivers often exhibit severe psychopathology, including alcoholism, paranoia, and suppressed aggression, particularly in single-vehicle crashes. While life stress and personality traits correlate with accident involvement, individual variables rarely offer sufficient predictive power. The significance of this review lies in its conclusion that multivariate techniques offer the most promising path for predicting driver risk. A study by Harano, McBride, and Peck demonstrated that combining biographical, attitudinal, and perceptual variables could classify drivers with significantly higher accuracy than previous methods. The paper concludes that while past research has successfully identified relevant variables, it has failed to produce robust predictive tools. Future research must employ rigorous, prospective designs and multivariate analysis to refine these observations into sensitive criteria capable of forecasting negligent behavior and enabling targeted highway safety interventions.

Key finding

Multivariate studies correctly classified 68.9% of accident-free drivers and 71.2% of accident-involved drivers, achieving a higher prediction success rate than previous univariate approaches, though overall predictive ability remained limited.

Methodology

review

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• sex gender
• demographic disparities
• novice drivers
• incidence prevalence
• human error taxonomy
• sensation seeking

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes, observational prevalence
• Theoretical Contribution: theory or model