Articlegold2012

The importance of rating scales in measuring patient-reported outcomes

Jyoti Khadka · Vijaya Kumari Gothwal · Colm McAlinden · Ecosse Luc Lamoureux · Konrad Pesudovs

153 citations0/0 files storedHealth and Quality of Life Outcomes

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Psychometric Methodologies and Testing Health Systems, Economic Evaluations, Quality of Life Health Education and Validation

Abstract

BACKGROUND: A critical component that influences the measurement properties of a patient-reported outcome (PRO) instrument is the rating scale. Yet, there is a lack of general consensus regarding optimal rating scale format, including aspects of question structure, the number and the labels of response categories. This study aims to explore the characteristics of rating scales that function well and those that do not, and thereby develop guidelines for formulating rating scales. METHODS: Seventeen existing PROs designed to measure vision-related quality of life dimensions were mailed for self-administration, in sets of 10, to patients who were on a waiting list for cataract extraction. These PROs included questions with ratings of difficulty, frequency, severity, and global ratings. Using Rasch analysis, performance of rating scales were assessed by examining hierarchical ordering (indicating categories are distinct from each other and follow a logical transition from lower to higher value), evenness (indicating relative utilization of categories), and range (indicating coverage of the attribute by the rating scale). RESULTS: The rating scales with complicated question format, a large number of response categories, or unlabelled categories, tended to be dysfunctional. Rating scales with five or fewer response categories tended to be functional. Most of the rating scales measuring difficulty performed well. The rating scales measuring frequency and severity demonstrated hierarchical ordering but the categories lacked even utilization. CONCLUSION: Developers of PRO instruments should use a simple question format, fewer (four to five) and labelled response categories.

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1961Probabilistic Models for Some Intelligence and Attainment Tests 1978A Rating Formulation for Ordered Response Categories 2000Optimal number of response categories in rating scales: reliability, validity, discriminating power, and respondent preferences 2002Optimizing rating scale category effectiveness.2002Understanding self-rated health 1999Investigating rating scale category utility.2007Rating scales as outcome measures for clinical trials in neurology: problems, solutions, and recommendations 1998Applications of Latent Trait and Latent Class Models in the Social Sciences

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