title: Development of the PROMIS health expectancies of smoking item banks.
abstract: BACKGROUND
  Smokers' health-related outcome expectancies are associated with a number of important constructs in smoking research, yet there are no measures currently available that focus exclusively on this domain. This paper describes the development and evaluation of item banks for assessing the health expectancies of smoking.
  
  
  METHODS
  Using data from a sample of daily (N = 4,201) and nondaily (N = 1,183) smokers, we conducted a series of item factor analyses, item response theory analyses, and differential item functioning analyses (according to gender, age, and race/ethnicity) to arrive at a unidimensional set of health expectancies items for daily and nondaily smokers. We also evaluated the performance of short forms (SFs) and computer adaptive tests (CATs) to efficiently assess health expectancies.
  
  
  RESULTS
  A total of 24 items were included in the Health Expectancies item banks; 13 items are common across daily and nondaily smokers, 6 are unique to daily, and 5 are unique to nondaily. For both daily and nondaily smokers, the Health Expectancies item banks are unidimensional, reliable (reliability = 0.95 and 0.96, respectively), and perform similarly across gender, age, and race/ethnicity groups. A SF common to daily and nondaily smokers consists of 6 items (reliability = 0.87). Results from simulated CATs showed that health expectancies can be assessed with good precision with an average of 5-6 items adaptively selected from the item banks.
  
  
  CONCLUSIONS
  Health expectancies of smoking can be assessed on the basis of these item banks via SFs, CATs, or through a tailored set of items selected for a specific research purpose.
authors.affiliation: RAND Health, RAND Corporation, Boston, MA; orlando@rand.org.
authors.forename: Maria Orlando
authors.initials: MO
authors.lastname: Edelen
authors.affiliation: RAND Health, RAND Corporation, Santa Monica, CA;
authors.forename: Joan S
authors.initials: JS
authors.lastname: Tucker
authors.affiliation: RAND Health, RAND Corporation, Pittsburgh, PA;
authors.forename: William G
authors.initials: WG
authors.lastname: Shadel
authors.affiliation: RAND Health, RAND Corporation, Santa Monica, CA;
authors.forename: Brian D
authors.initials: BD
authors.lastname: Stucky
authors.affiliation: RAND Health, RAND Corporation, Pittsburgh, PA;
authors.forename: Jennifer
authors.initials: J
authors.lastname: Cerully
authors.affiliation: CSE/CRESST, Graduate School of Education and Information Studies, University of California, Los Angeles, Los Angeles, CA.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Li
authors.affiliation: CSE/CRESST, Graduate School of Education and Information Studies, University of California, Los Angeles, Los Angeles, CA.
authors.forename: Mark
authors.initials: M
authors.lastname: Hansen
authors.affiliation: CSE/CRESST, Graduate School of Education and Information Studies, University of California, Los Angeles, Los Angeles, CA.
authors.forename: Li
authors.initials: L
authors.lastname: Cai
mesh_terms: D000293:Adolescent; D000328:Adult; D002138:Calibration; D016208:Databases, Factual; D005006:Ethnicity; D005163:Factor Analysis, Statistical; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D011594:Psychometrics / Q000379:methods*; D015203:Reproducibility of Results; D012907:Smoking / Q000523:psychology*; D011795:Surveys and Questionnaires; D055815:Young Adult