Psychometric considerations in evaluating health-related quality of life measures

Abstract

How does one determine if a measure of health-related quality of life (HRQL) is adequate for clinical trials? Psychometric methods are frequently used to answer this question. What is psychometrics all about? In this paper we address these questions, discussing common psychometric evaluation procedures applied to HRQL measures. Specifically, we discuss issues regarding the evaluation of reliability and validity (including responsiveness).

The clinical validity of the treatment satisfaction survey for intraocular pressure in ocular hypertensive and glaucoma patients

“…Accordingly, several validated surveys have been developed over the past several years that evaluate the impact of glaucoma on a patient's activities of daily living and vision. [1][2][3][4][5][6][7][8][9] Further, several years ago Laibovitz et al 10 validated the Comparison of Ophthalmic Medications for Quality of Life questionnaire (COMQoL), which was designed to compare specifically the tolerability of ophthalmic medications and to evaluate the effect of ocular hypotensive therapy on side effects, routine living activities, quality of life, compliance, and patient satisfaction with medication. The data were used to show an increased preference for dorzolamide compared to pilocarpine due to reasons of side effects and patient satisfaction.…”

A structured review of outcome measures used for the assessment of rehabilitation interventions for spinal cord injury

“…7 Estimates need to be higher (aX0.9) where instruments are to be applied to individuals. 9 Validity. Addresses whether an instrument measures what it is intended to measure.…”

“…7 Frequently, this involves demonstrating that a measure is closely correlated with different measures of the same trait ('convergent validity'), or that a measure correlates little with measures intended to indicate a different trait ('discriminant validity'). 9 More recently, Rasch analysis: a more stringent assessment of underlying scale structure and dimensionality, is increasingly being undertaken. 12 Rasch models test how well instruments conform to uni-dimensionality, hierarchy and interval location of items by examining patterns of individuals' performance on the range of items in a scale and patterns of items' difficulty or severity.…”

“…This property is particularly important for instruments applied in clinical trials. 9 Responsiveness preferably needs to be assessed in a prospective study, where change in the health status is likely to occur for the majority. Here, effect sizes are commonly employed (other methods include using paired t-test comparisons or the responsiveness statistic 8 ), which is a method of calculating the magnitude of change measured by an instrument in a standardized way which allows direct comparisons to be made between different instruments and scales.…”

Quality of life and understanding of disease status among cancer patients of different ethnic origin

“…If different components of QoL have a variable impact on overall QoL among people speaking different languages and of different ethnic origin, it is important to develop questionnaires that are valid for different populations. The translation of questionnaires developed in one culture into the language of another can be problematic because of difficulties in achieving equivalent conceptual dimensions (Cella et al, 1993;Hays et al, 1993;Sartorius and Kuyken, 1994;The WHOQOL Group, 1994;Yabroff et al, 1996;Ware et al, 1998). Despite these problems, several QoL questionnaires, including the Functional Assessment of Cancer Therapy -General (FACT-G) instrument used in the present study, have been translated into many languages and validated for different ethnic groups (Aaronson et al, 1992;Bonomi et al, 1996).…”