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Measuring behavioral and mood disruptions in nursing home residents using the Minimum Data Set

A L Horgas1, J A Margrett

  • 1College of Nursing, Institute on Aging, University of Florida, USA. ahorgas@nursing.ufl.edu

Insights

The Minimum Data Set (MDS) may not accurately measure depressive or disruptive behaviors in nursing home residents. Caregiver ratings using the Revised Memory and Behavior Problems Checklist (RMBPC) showed better validity than the MDS for these behaviors.

Area of Science:

  • Gerontology
  • Psychiatry
  • Health Services Research

Background:

  • The Minimum Data Set (MDS) is a standardized tool for assessing nursing home residents' biopsychosocial status.
  • Accurate assessment of cognition, depression, and behavior is crucial for resident care.

Purpose of the Study:

  • To examine the validity of MDS subscales for cognition, depressive symptoms, and behavioral disruptions.
  • To compare MDS measures with other established assessment tools in nursing home residents.

Main Methods:

  • A pilot study involving 135 nursing home residents (mean age 84).
  • Compared MDS subscales with diagnoses of dementia/depression and caregiver ratings on the Revised Memory and Behavior Problems Checklist (RMBPC).

Main Results:

  • MDS indicated high prevalence of cognitive behaviors but low prevalence of disruptive/depressed behaviors, contrasting with RMBPC findings.
  • Most MDS subscales did not differentiate residents with/without dementia or depression, unlike RMBPC caregiver ratings.
  • MDS and RMBPC subscales showed modest correlation only in residents without dementia.

Conclusions:

  • Findings question the validity of MDS for measuring depressive and disruptive behaviors in nursing home residents.
  • Caution is advised when using MDS as the sole outcome measure for these behaviors.
  • Utilizing multiple assessment measures is recommended for a comprehensive evaluation.

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