The Sleep-Wake Activity Inventory: a self-report measure of daytime sleepiness

The purpose of this study was to develop a valid multidimensional self-report measure of sleepiness. There were 554 subjects who completed the inventory. The structure of the Sleep-Wake Activity Inventory (SWAI) was derived from principal components analysis. The independent predictive strength of the factors was assessed by forward stepwise regression analysis with the average sleep latency on the Multiple Sleep Latency Test (MSLT) as the dependent variable. The scores on each of the factors were also compared by the level of sleepiness determined by the MSLT (pathological, diagnostic gray area, and normal). Factor analysis showed the existence of six factors on the SWAI (Excessive Daytime Sleepiness [EDS], Psychic Distress, Social Desirability, Energy Level, Ability to Relax and Nocturnal Sleep). The EDS factor was the best predictor of average MSLT. It was also able to differentiate pathological levels of sleepiness from both the diagnostic gray and normal levels of sleepiness. EDS factor scores were sensitive to changes in sleep physiology as improved scores followed normalization of sleep-disordered breathing. The SWAI was shown to be easy to complete, have a multi-dimensional structure, have a EDS factor useful in the prediction of average MSLT scores, be sensitive to differential levels of sleepiness, and change as a result of effective treatment.