National Survey of Distracted and Drowsy Driving Attitudes and Behavior: 2002: Volume 3: Methods

Royal, Dawn · 2003 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This report, Volume III of the 2002 National Survey of Distracted and Drowsy Driving Attitudes and Behavior, details the methodological framework used by The Gallup Organization to collect data for the National Highway Traffic Safety Administration (NHTSA). The study was motivated by the need to update findings from a 1997 survey on speeding and unsafe driving, expanding the scope to include aggressive driving, distracted driving, and drowsy driving. The primary objective was to generate statistically valid, nationally representative data on driver behaviors and attitudes to inform the development of safety programs aimed at reducing dangerous driving practices. The research employed a multi-stage sampling procedure to survey drivers aged 16 and older residing in non-institutionalized dwellings with working telephones. Two independent survey versions were fielded: one focusing on speeding and the other on unsafe and aggressive driving, both containing modules on distracted and drowsy driving. Between February 4 and April 14, 2002, Gallup conducted 4,010 telephone interviews (2,004 for the Speed survey and 2,006 for the Unsafe survey) using a stratified Casady-Lepkowski Random-Digit-Dial (RDD) design. This approach ensured equal probability of selection for residential telephone numbers, including unlisted lines. Interviews were conducted in English and Spanish via a computer-assisted telephone interviewing (CATI) system, with an average duration of 19 minutes. To maximize response rates, interviewers utilized a rigorous call design involving up to seven attempts per household across various times and days. The final samples were weighted in five stages to adjust for unequal selection probabilities, non-response bias, and demographic discrepancies relative to U.S. Census projections. The methodology yielded CASRO response rates of 34.4% for the Speed study and 30.5% for the Unsafe study, which are considered standard for national probability samples. The report provides detailed sampling error calculations, indicating that the complex sampling design resulted in a design effect that widened confidence intervals by approximately 10% compared to a simple random sample. For the total sample of 4,010, the sampling error at a 95% confidence level is approximately ±1.5 percentage points. The document also outlines strict confidentiality protocols, ensuring that respondent identities were not linked to the released data. The significance of this methodological report lies in its establishment of a robust baseline for understanding distracted and drowsy driving behaviors. By documenting the precise sampling, weighting, and error estimation techniques, the report validates the reliability of the associated findings volumes. This data infrastructure allows NHTSA to accurately estimate the prevalence of specific behaviors, such as cell phone use and passenger interaction, and to project national statistics on crash attributions. Consequently, the methods described here support evidence-based policy making and the evaluation of traffic safety interventions by providing a clear, quantifiable picture of driver attitudes and behaviors across the United States.

Key finding

The survey methodology involved conducting 4,010 telephone interviews with a nationally representative sample of drivers aged 16 and older using a stratified random-digit-dial design and computer-assisted telephone interviewing.

Methodology

survey

Sample size: 4010

Provenance

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Topics

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• incidence prevalence
• temporal
• mobile phones
• exposure measurement
• distraction detection algorithms
• visual

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: observational prevalence, behavioral performance data
• Methodological Resource: dataset resource