Academic journal article Psychological Test and Assessment Modeling

The Measuring Your Health Study: Leveraging Community-Based Cancer Registry Recruitment to Establish a Large, Diverse Cohort of Cancer Survivors for Analyses of Measurement Equivalence and Validity of the Patient Reported Outcomes Measurement Information System® (PROMIS®) Short Form Items

Academic journal article Psychological Test and Assessment Modeling

The Measuring Your Health Study: Leveraging Community-Based Cancer Registry Recruitment to Establish a Large, Diverse Cohort of Cancer Survivors for Analyses of Measurement Equivalence and Validity of the Patient Reported Outcomes Measurement Information System® (PROMIS®) Short Form Items

Article excerpt

Introduction

Studies evaluating patient-reported outcomes (PROs) in patients with many chronic health conditions, including cancer, have identified significant differences in PROs by age and across race/ethnic groups (Angel & Thoits, 1987; Osmond, Vranizan, Schillinger, Stewart, & Bindman, 1996; Raczynski et al., 1994; Shetterly, Baxter, Mason, & Hamman, 1996; Stewart & Napoles-Springer, 2003). However, the extent to which these variations reflect true differences or measurement bias remain unclear (Fullerton, Wallace, & Concha-Garcia, 1993; Skinner, Teresi, Holmes, Stahl, & Stewart, 2001; Teresi & Holmes, 1994). Differential Item Functioning (DIF), a type of measurement bias, occurs when individuals in different groups, such as race or age, respond differently to an item within a unidimensional measure, while reporting the same overall score or trait. DIF can affect the overall interpretations of PRO constructs by age, race/ethnicity and gender (Edwards, Doleys, Fillingim, & Lowery, 2001; Ibrahim, Burant, Mercer, Siminoff, & Kwoh, 2003; Sheffield, Biles, Orom, Maixner, & Sheps, 2000; Weiss, Emanuel, Fairclough, & Emanuel, 2001). Studies of commonly-administered generic and disease-specific PRO measures suggest that DIF is likely responsible for some of the observed group differences in both cancer and general populations (Crane, Gibbons, Narasimhalu, Lai, & Cella, 2007; Fleishman & Lawrence, 2003; Hahn et al., 2005; Teresi, Ramirez, Lai, & Silver, 2008). Therefore, while PROs have gained increasing recognition as legitimate endpoints in the evaluation of medical interventions' effects on function and well-being (Clauser, Ganz, Lipscomb, & Reeve, 2007; Ganz & Gotay, 2007), it is important to evaluate PRO measures for DIF to ensure their validity when administered within and across diverse populations. Given the expanding cultural diversification of the US population (Humes, Jones, & Ramirez, 2011), establishing the validity of PRO measures to accurately examine constructs across broad heterogeneous populations takes on increasing relevance.

In 2004, the National Institutes of Health launched the Patient Reported Outcomes Measurement Information System® (PROMIS®) "Roadmap Initiative" to use modern psychometric techniques to improve the measurement of symptoms and health outcomes by building and evaluating item banks from common, accessible tools (Cella et al., 2007). This initiative created PRO measures covering a wide range of symptoms and function, establishing a standardized scoring framework that could be used across illnesses, chronic health conditions, and the general population. Initial validity and reliability efforts for PROMIS® measures rarely included enough racially and ethnically diverse patients to establish the validity of these measures for the U.S. population. The Measuring Your Health (MY-Health) study was designed to fill this evidence gap and evaluate eight PROMIS domains across multiple race-ethnic and age groups in a diverse cohort of cancer patients. It has accomplished this by partnering with four Surveillance, Epidemiology, and End Results (SEER) program cancer registries to draw a population-based sample of recently diagnosed cancer patients, and oversampling race/ethnic minorities and younger patients. This collaboration has allowed the MY-Health study cohort to provide an extensive and generalizable cross-cultural validation of the PROMIS measures in a large community-based sample. The goal of this paper is to provide detailed information on the MY-Health study design, implementation, and participant cohort used in the PROMIS validation papers presented in this special issue. It also discusses the challenges and benefits of recruiting and enrolling a diverse community-based cancer cohort.

Methods

Identification and Recruitment. Between 2010 and 2012, we identified eligible patients for the MY-Health study in partnership with four SEER cancer registries located in California (two), Louisiana, and New Jersey. …

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