title: Item response theory analysis of the patient satisfaction with cancer-related care measure: a psychometric investigation in a multicultural sample of 1,296 participants.
abstract: BACKGROUND
  We developed and validated a Patient Satisfaction with Cancer-Related Care (PSCC) measure using classical test theory methods. The present study applied item response theory (IRT) analysis to determine item-level psychometric properties, facilitate development of short forms, and inform future applications for the PSCC.
  
  
  METHODS
  We applied unidimensional IRT models to PSCC data from 1,296 participants (73% female; 18 to 86 years). An unconstrained graded response model (GRM) and a Rasch Model were fitted to estimate indices for model comparison using likelihood ratio (LR) test and information criteria. We computed item and latent trait parameter estimates, category and operating characteristic curves, and tested information curves for the better fitting model.
  
  
  RESULTS
  The GRM fitted the data better than the Rasch Model (LR = 828, df = 17, p < 0.001). The log-likelihood (-17,390.38 vs. -17,804.26) was larger, and the AIC and BIC were smaller for the GRM compared to the Rash Model (AIC = 34,960.77 vs. 35,754.73; BIC = 35,425.80 vs. 36,131.92). Item parameter estimates (IPEs) showed substantial variation in items' discriminating power (0.94 to 2.18). Standard errors of the IPEs were small (threshold parameters mostly around 0.1; discrimination parameters 0.1 to 0.2), confirming the precision of the IPEs.
  
  
  CONCLUSIONS
  The GRM provides precise IPEs that will enable comparable scores from different subsets of items, and facilitate optimal selections of items to estimate patients' latent satisfaction level. Given the large calibration sample, the IPEs can be used in settings with limited resources (e.g., smaller samples) to estimate patients' satisfaction.
authors.affiliation: Department of Psychology, Neurocognitive Translational Research Lab, Cancer Control & Survivorship Program, University of Notre Dame, 109 Haggar Hall, Notre Dame, IN, 46556, USA, PJeanPierre@nd.edu.
authors.forename: Pascal
authors.initials: P
authors.lastname: Jean-Pierre
authors.forename: Ying
authors.initials: Y
authors.lastname: Cheng
authors.forename: Electra
authors.initials: E
authors.lastname: Paskett
authors.forename: Can
authors.initials: C
authors.lastname: Shao
authors.forename: Kevin
authors.initials: K
authors.lastname: Fiscella
authors.forename: Paul
authors.initials: P
authors.lastname: Winters
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009369:Neoplasms / Q000208:ethnology / Q000523:psychology* / Q000628:therapy*; D062526:Patient Navigation / Q000379:methods; D017060:Patient Satisfaction / Q000208:ethnology*; D011594:Psychometrics / Q000379:methods*; D014481:United States; D035862:Vulnerable Populations / Q000208:ethnology; D055815:Young Adult