Summary
Selecting the best health-related quality of life (HRQL) measures for sleep/wake research requires evaluation of congruity between each measure’s conceptual framework and the proposed research study’s hypotheses, design, and sample. As a first step, the study team works to identify the most salient HRQL concepts, often with the help of focus groups and patient interviews. Next, a brief review of anthologies and electronic resources may be sufficient to find candidate measures addressing the relevant concepts. Judging the relative merits of the candidate HRQL measures requires careful analysis. A comprehensive and systematic approach for comparing the quality and suitability of candidate HRQL measures based on literature is recommended. Considerations and criteria for assessing the psychometric evidence of measurement quality, including validity, reliability, responsiveness to change, and sensitivity to group differences, are presented. Also discussed are useful attributes such as population norms and precedents for determining the minimally important difference (MID). To insure successful implementation, pilot testing of the chosen measures with the target population is encouraged. This chapter also provides an overview of a new and exciting methodology, item response theory (IRT), that is leading to the refinement of HRQL measures. IRT also enables computer-adaptive testing (CAT), where concept indicators (e.g., individual questions about a concept such as daytime sleepiness) are successively selected from an item bank and shown to each patient in an order tailored to that of patient’s previous response choices. The results rapidly and accurately estimate that patient’s true score while yielding scores that can be grouped across patients or followed over time. This chapter ends with a list of practical issues like the patient burden, costs, and copyright that impact the choice of HRQL tools, along with a list of resources for locating measures.
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Gross, C.R., Wyrwich, K.W. (2008). Criteria for Evaluating Quality of Life Measurement Tools. In: Verster, J.C., Pandi-Perumal, S.R., Streiner, D.L. (eds) Sleep and Quality of Life in Clinical Medicine. Humana Press. https://doi.org/10.1007/978-1-60327-343-5_3
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