Further refinement of the Patient-Reported Impact of Dermatological Diseases (PRIDD) measure using classical test theory and item response theory.

Abstract

Existing dermatology-specific Patient-Reported Outcome Measures (PROMs) do not fully capture the substantial physical, psychological and social impact of dermatological conditions on patients' lives and are not recommended for use according to the COSMIN criteria. Most were developed with insufficient patient involvement and relied on classical psychometric methods. We are developing the new Patient-Reported Impact of Dermatological Diseases (PRIDD) measure for use in research and clinical practice in partnership with patients. To examine the factor structure of PRIDD, determine the definitive selection of items for each subscale, and establish structural validity and internal consistency through classical and modern psychometric methods. Two cross-sectional online surveys were conducted. Adults (≥ 18 years) worldwide living with a dermatological condition were recruited through the membership network of the International Alliance of Dermatology Patient Organizations (GlobalSkin). They completed the PRIDD questionnaire and a demographics questionnaire via an online survey. We examined missing data and distribution of scores for each item. The factor structure was assessed using confirmatory and exploratory factor analysis (Survey 1). Internal consistency was examined using Cronbach's α. Rasch measurement theory analyses were conducted, including iterative assessment of rating scale function, fit to the Rasch model, unidimensionality, reliability, local dependence, targeting and differential item functioning (DIF) (Surveys 1 and 2). Participants in Surveys 1 and 2 numbered 483 and 504 people, respectively. All items had ≤ 3% missing scores and all five response options were used. A four-factor model showed the best fit. PRIDD and all four subscales were internally consistent but showed some misfit to the Rasch measurement model. Adjustments were made to rectify disordered thresholds, remove misfitting items, local dependency and DIF, and improve targeting. The resulting 16-item version and subscales fit the Rasch model, showed no local dependency or DIF at the test level, and were well targeted. This field test study produced the final PRIDD measure, consisting of 16 items across four domains. The data triangulated and refined the conceptual framework of impact and provide evidence of PRIDD's structural validity and internal consistency. The final step in the development and validation of the PRIDD measure is to test the remaining measurement properties.