title: Improving measurement of injection drug risk behavior using item response theory.
abstract: BACKGROUND
  Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored.
  
  
  OBJECTIVE
  To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning.
  
  
  METHODS
  Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning.
  
  
  RESULTS
  Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data.
  
  
  CONCLUSIONS
  Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.
authors.affiliation: Department of Psychology, Michigan State University , East Lansing, MI , USA.
authors.forename: Patrick
authors.initials: P
authors.lastname: Janulis
mesh_terms: D016208:Databases, Factual; D055030:Drug Users / Q000523:psychology*; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012309:Risk-Taking; D015819:Substance Abuse, Intravenous / Q000523:psychology*; D011795:Surveys and Questionnaires