Related Experiment Video
Updated: Jun 3, 2026
Multi-Modal Home Sleep Monitoring in Older Adults
Published on: January 26, 2019
Can standardized sleep questionnaires be used to identify excessive daytime sleeping in older post-acute
Megan Skibitsky1, Maria Orlando Edelen, Jennifer L Martin
1David Geffen School of Medicine, University of California, Los Angeles, CA, USA. megan.skibitsky@hsc.utah.edu
Objectives:
Excessive daytime sleeping is associated with poorer functional outcomes in rehabilitation populations and may be improved with targeted interventions. The purpose of this study was to test simple methods of screening for excessive daytime sleeping among older adults admitted for postacute rehabilitation.
Design:
Secondary analysis of data from 2 clinical samples.
Setting:
Two postacute rehabilitation (PAR) units in southern California.
Participants:
Two hundred twenty-six patients older than 65 years with Mini-Mental State Examination (MMSE) score higher than 11 undergoing rehabilitation.
Measurements:
The primary outcome was excessive daytime sleeping, defined as greater than 15% (1.8 hours) of daytime hours (8 am to 8 pm) sleeping as measured by actigraphy.
Results:
Participants spent, on average, 16.2% (SD 12.5%) of daytime hours sleeping as measured by actigraphy. Thirty-nine percent of participants had excessive daytime sleeping. The Pittsburgh Sleep Quality Index (PSQI) was significantly associated with actigraphically measured daytime sleeping (P = .0038), but the Epworth Sleepiness Scale (ESS) was not (P = .49). Neither the ESS nor the PSQI achieved sufficient sensitivity and specificity to be used as a screening tool for excessive daytime sleeping. Two additional models using items from these questionnaires were not significantly associated with the outcome.
Conclusions:
In an older PAR population, self-report items from existing sleep questionnaires do not identify excessive daytime sleeping. Therefore we recommend objective measures for the evaluation of excessive daytime sleeping as well as further research to identify new self-report items that may be more applicable in PAR populations.
