Individualized sleep promotion in acute care hospitals: Identifying factors that affect patient sleep

Appl Nurs Res. 2019 Aug:48:63-67. doi: 10.1016/j.apnr.2019.05.006. Epub 2019 May 11.

Abstract

Background/aim: One major challenge of inpatient sleep promotion is that there is no "one-size-fits-all" intervention as patients' sleep may be bothered by different factors. A tool evaluating factors that disturb patient sleep is greatly needed as a foundation for generating a personalized action plan to address the patient's specific need for sleep. Unfortunately such tools are currently unavailable in clinical practice. In this study we developed and psychometrically evaluated a brief assessment tool for sleep disruptors important for hospitalized patients, the Factors Affecting Inpatient Sleep (FAIS) scale.

Methods: The FAIS items were developed by literature review and validated by content validity testing. A survey collected from 105 hospitalized patients was used to select the most significant sleep disruptors. Psychometric evaluation using survey data included item analysis, principal components analysis, and internal consistency reliability.

Results: The final FAIS scale included 14 items in three subscales explaining 56.4% of the total variance: 1) emotional or physical impairment due to illness or hospitalization; 2) sleep disturbance due to discomfort or care plan schedule; 3) sleep interruption due to hospital environment or medical care. The Cronbach's alpha coefficient for the FAIS scale was 0.87, and the reliability of the subscales ranged from 0.72 to 0.81.

Conclusion: The FAIS is a brief tool assessing sleep disruptors important for patients, and is empirically grounded, judged to have content validity, and has demonstrated psychometric adequacy. The FAIS scale can be used to guide the development of an individualized patient-centered sleep promotion plan.

Keywords: Inpatient sleep; Instrument development; Sleep promotion.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aged
  • Female
  • Hospitalization*
  • Humans
  • Inpatients*
  • Male
  • Middle Aged
  • Psychometrics
  • Sleep*