Driver selection and training for human service agencies

NHTSA · 1983 · ROSA P / United States. Department of Transportation

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This 1983 report, prepared by the University of Tennessee for the U.S. Department of Health and Human Services, addresses the critical need for standardized driver selection and training protocols within human service agencies. These agencies provide transportation for disadvantaged populations, including the elderly, handicapped, and low-income individuals, often filling gaps left by traditional public transit. The research is motivated by the high costs of motor vehicle accidents and the unique nature of human service driving, which requires a specific mix of driving proficiency and passenger assistance skills. Unlike standard transit drivers who focus primarily on operation, human service drivers must often provide significant physical and emotional support to vulnerable passengers, making appropriate personnel selection essential for safety and program effectiveness. The report analyzes factors influencing driver performance, distinguishing between demographic variables and non-demographic traits. It reviews statistical data on accident relativity related to age, marital status, and sex, but argues that these demographic proxies are insufficient and potentially discriminatory. Instead, the authors emphasize non-demographic predictors such as driving history, physical health, and psychological traits. Key findings indicate that driver error accounts for 90 percent of accidents, with a small percentage of drivers responsible for a disproportionate share of incidents. The report highlights that individuals with chronic health conditions (e.g., epilepsy, heart disease) or those taking medications with sedative side effects pose higher risks. Furthermore, it identifies "alienation"—psychological isolation and lack of identification with the agency’s mission—as a significant predictor of poor driving behavior and high turnover. The study proposes a comprehensive framework for driver selection and training. Selection criteria should prioritize functional ability over chronological age, requiring applicants to demonstrate at least four years of driving experience, a clean driving record, good physical condition, and emotional stability. The report stresses the importance of assessing an applicant’s willingness to identify with the agency’s mission and their capacity for patience and tolerance. Training recommendations include professionalizing the driver role through instruction in defensive driving, first aid, passenger assistance techniques, and human relations skills. The authors argue that training is only effective if drivers are motivated and feel a sense of professionalism and responsibility. The significance of this work lies in its guidance for managing risk and cost in human service transportation. By implementing rigorous selection and training programs, agencies can reduce accident rates, lower insurance costs, and improve service quality for beneficiaries. The report concludes that effective management involves treating drivers as professionals rather than temporary staff, thereby reducing alienation and enhancing safety. It provides specific tools, including interview forms and physical examination guidelines, to help agencies establish robust driver management systems tailored to the specific needs of their client populations.

Key finding

Driver error accounts for 90 percent of all accidents, and selecting drivers based on individual psychological traits and driving history is more effective for safety than relying on broad demographic generalizations.

Methodology

review

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

StageOutcomeToolModelPromptAttemptsCompleted
discover success rosap 2 2026-05-23
archive success 1 2026-05-23
extract success cached 2 2026-06-10
clean success 1 2026-06-01
chunk success 1 2026-06-01
embed success 1 2026-06-02
enrich skipped 3 2026-07-02
promote success 1 2026-05-23
summarize success llm qwen3.6-27b-prismaquant summ-v5 3 2026-06-10
tag success vector_similarity 19 2026-06-11
verify success 2 2026-06-10

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.

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).