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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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DEMQOL and DEMQOL-Proxy: a Rasch analysis.

A A Jolijn Hendriks1, Sarah C Smith2, Theopisti Chrysanthaki2,3

  • 1Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK. jolijn.hendriks@lshtm.ac.uk.

Health and Quality of Life Outcomes
|August 24, 2017
PubMed
Summary

Revised scoring for DEMQOL and DEMQOL-Proxy using Rasch modeling enhances health-related quality of life assessments for people with dementia. These improved patient-reported outcome measures offer more reliable comparisons in clinical settings.

Keywords:
DEMQOLDEMQOL-ProxyItem analysisRasch measurement theory

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Area of Science:

  • Psychometrics
  • Health Services Research
  • Gerontology

Background:

  • Dementia Quality of Life (DEMQOL) and DEMQOL-Proxy are key patient-reported outcome measures (PROMs) for assessing health-related quality of life in people with dementia (PWD).
  • Increasing demand for routine PROM use necessitates robust instruments for reliable comparisons at individual and clinical levels.
  • Current PROMs require re-evaluation to ensure fitness for purpose in diverse healthcare settings.

Purpose of the Study:

  • To re-evaluate the psychometric properties of DEMQOL and DEMQOL-Proxy using modern psychometric methods.
  • To ensure the instruments are fit for purpose for reliable and valid comparisons.
  • To develop improved scoring methods for enhanced clinical utility.

Main Methods:

  • Rasch measurement model applied to DEMQOL (1428 PWDs) and DEMQOL-Proxy (1022 carers).
  • Evaluation of scale-to-sample targeting, item threshold ordering, item fit, differential item functioning (sex, age, relationship), local independence, unidimensionality, and reliability.
  • Comparison of performance between the full item set and a reduced item set.

Main Results:

  • A smaller item set demonstrated superior performance for both DEMQOL and DEMQOL-Proxy compared to the original full item set.
  • Revised scoring algorithms were developed based on the reduced item set.
  • The Rasch model analysis confirmed improved psychometric properties with the revised scoring.

Conclusions:

  • The study successfully improved the scoring of DEMQOL and DEMQOL-Proxy utilizing the Rasch measurement model.
  • The revised instruments offer enhanced reliability and validity for quality of life assessments in people with dementia.
  • Future research should address identified issues concerning content and response options to further refine these PROMs.