The electronic administration of PRO measures offers many advantages over paper administration. We provide a general framework for decisions regarding the level of evidence needed to support modifications that are made to PRO measures when they are migrated from paper to ePRO devices. The key issues include: 1) the determination of the extent of modification required to administer the PRO on the ePRO device and 2) the selection and implementation of an effective strategy for testing the measurement equivalence of the two modes of administration. We hope that these good research practice recommendations provide a path forward for researchers interested in migrating PRO measures to electronic data collection platforms.

Introduction The U.S. Food and Drug Administration’s patient-reported outcome (PRO) guidance document defines content validity as “the extent to which the instrument measures the concept of interest” (FDA, 2009, p. 12). “Construct validity is now generally viewed as a unifying form of validity for psychological measurements, subsuming both content and criterion validity” (Strauss & Smith, 2009, p. 7). Hence both qualitative and quantitative information are essential in evaluating the validity of measures. Methods We review classical test theory and item response theory approaches to evaluating PRO measures including frequency of responses to each category of the items in a multi-item scale, the distribution of scale scores, floor and ceiling effects, the relationship between item response options and the total score, and the extent to which hypothesized “difficulty” (severity) order of items is represented by observed responses. Conclusion Classical test theory and item response theory can be useful in providing a quantitative assessment of items and scales during the content validity phase of patient-reported outcome measures. Depending on the particular type of measure and the specific circumstances, either one or both approaches should be considered to help maximize the content validity of PRO measures.

Patient-reported outcomes (PROs) are an important means of evaluating the treatment benefit of new medical products. It is recognized that PRO measures should be used when assessing concepts best known by the patient or best measured from the patient’s perspective. As a result, there is growing emphasis on well defined and reliable PRO measures. In addition, advances in technology have significantly increased electronic PRO (ePRO) data collection capabilities and options in clinical trials. The movement from paper-based to ePRO data capture has enhanced the integrity and accuracy of clinical trial data and is encouraged by regulators. A primary distinction in the types of ePRO platforms is between telephone-based interactive voice response systems and screen-based systems. Handheld touchscreen-based devices have become the mainstay for remote (i.e., off-site, unsupervised) PRO data collection in clinical trials. The conventional approach is to provide study subjects with a handheld device with a device-based proprietary software program. However, an emerging alternative for clinical trials is called bring your own device (BYOD). Leveraging study subjects’ own Internet-enabled mobile devices for remote PRO data collection (via a downloadable app or a Web-based data collection portal) has become possible due to the widespread use of personal smartphones and tablets. However, there are a number of scientific and operational issues that must be addressed before BYOD can be routinely considered as a practical alternative to conventional ePRO data collection methods. Nevertheless, the future for ePRO data collection is bright and the promise of BYOD opens a new chapter in its evolution.

This work represents a series of initial steps in the development of this rating scale. The next steps are to conduct psychometric analysis and evaluate the role of insight.

Purpose The purpose of this analysis was to determine the unique contribution of household income to the variance explained in psychological well-being (PWB) among a sample of colorectal cancer (CRC) survivors. Methods This study is a secondary analysis of data collected as part of the Health-Related Quality of Life in Long-Term Colorectal Cancer Survivors Study, which included CRC survivors with (cases) and without (controls) ostomies. The dataset included socio-demographic, health status, and health-related quality of life (HRQOL) information. HRQOL was assessed with the modified City of Hope Quality of Life (mCOH-QOL)-Ostomy questionnaire and SF-36v2. To assess the relationship between income and PWB, a hierarchical linear regression model was constructed combining data from both cases and controls. Results After accounting for the proportion of variance in PWB explained by the other independent variables in the model, the additional variance explained by income was significant (R2 increased from 0.228 to 0.250; p = 0.006). Conclusions Although the study design does not allow causal inference, these results demonstrate a significant relationship between income and PWB in CRC survivors. The findings suggest that for non-randomized group comparisons of HRQOL, income should, at the very least, be included as a control variable in the analysis.