Long-haul truck drivers experience poor sleep health and heightened accident rates, and undiagnosed sleep disorders contribute to these negative outcomes. Subjective sleep disorder screening tools may aid in detecting drivers’ sleep disorders. This study sought to evaluate the value of subjective screening methods for detecting latent sleep disorders and identifying truck drivers at-risk for poor sleep health and safety-relevant performance. Using cross-sectional data from 260 long-haul truck drivers, we: 1) used factor analysis to identify possible latent sleep disorders; 2) explored the construct validity of extracted sleep disorder factors by determining their associations with established sleep disorder risk factors and symptoms; and 3) explored the predictive validity of resulting sleep disorder factors by determining their associations with sleep health and safety-relevant performance. Five latent sleep disorder factors were extracted: 1) circadian rhythm sleep disorders; 2) sleep-related breathing disorders; 3) parasomnias; 4) insomnias; 5) and sleep-related movement disorders. Patterns of associations between these factors generally corresponded with known risk factors and symptoms. One or more of the extracted latent sleep disorder factors were significantly associated with all the sleep health and safety outcomes. Using subjective sleep problems to detect latent sleep disorders among long-haul truck drivers may be a timely and effective way to screen this highly mobile occupational segment. This approach should constitute one component of comprehensive efforts to diagnose and treat sleep disorders among commercial transport operators
