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Research Article| Volume 34, ISSUE 11, P810-820, December 01, 1993

The sleep-wake activity inventory: A self-report measure of daytime sleepiness

  • Leon Rosenthal
    Correspondence
    Address reprint requests to Leon Rosenthal, MD, HFH Sleep Disorders Center, 2921 West Grand Blvd, Detroit, MI 48202.
    Footnotes
    Affiliations
    Sleep Disorders and Research Center, Henry Ford Hospital, Detroit, MI, USA
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  • Timothy A. Roehrs
    Footnotes
    Affiliations
    Sleep Disorders and Research Center, Henry Ford Hospital, Detroit, MI, USA
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  • Tom Roth
    Footnotes
    Affiliations
    Sleep Disorders and Research Center, Henry Ford Hospital, Detroit, MI, USA
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  • Author Footnotes
    ∗∗ The authors thank Frank Zorick, M.D., Robert M. Wittig, M.D., Edward Stepanski, Ph.D., Yzuru Takeshita, Ph.D., and David Haeffner, Ph.D., for their comments on the items of the SWAI; Milton Kramer, M.D., for data collection at the Bethesda Oak Hospital Sleep Center; and the technical and secretarial staff at the HFH Sleep Disorders Center for data collection.
DOI:https://doi.org/10.1016/0006-3223(93)90070-T
The sleep-wake activity inventory: A self-report measure of daytime sleepiness
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      Abstract

      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 multidimensional 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.

      Keywords

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      Article info

      Publication history

      Received in revised form: August 19, 1993
      Received: January 29, 1993

      Footnotes

      ☆This work was supported by NIMH grant MH-00860, awarded to Dr. Leon Rosenthal.

      Identification

      DOI: https://doi.org/10.1016/0006-3223(93)90070-T

      Copyright

      © 1993 Published by Elsevier Inc.

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