title: Identification of physician and patient attributes that influence the likelihood of screening for intimate partner violence.
abstract: OBJECTIVE
  Effective assessment of intimate partner violence (IPV) demands that everyone at risk be screened. To identify potential barriers, paper-and-pencil case scenarios identified possible practitioner and patient attributes that influence IPV screening.
  
  
  METHODS
  First-year residents responded to one of four short written scenarios describing a divorced female patient with nonlocalized abdominal pain; variables were patient's age and abdominal bruising. Residents rated their likelihood of screening for IPV and seven other screening tasks and self-assessed their competence in performing each task. Regression analyses assessed the influence of resident and patient characteristics on screening likelihood.
  
  
  RESULTS
  Patient bruising, younger patient age, and resident self-assessed competence best predicted IPV screening. Men were less likely than women to screen for IPV.
  
  
  CONCLUSIONS
  Although most physicians receive training on IPV in medical school, barriers to IPV screening still exist. Identifying obstacles to IPV risk-assessment is an essential prerequisite for improving educational programs that promote routine IPV screening.
authors.affiliation: Department of Physiology, University of Massachusetts Medical School, Worcester 01655, USA. Julie.Jonassen@umassmed.edu
authors.forename: Julie A
authors.initials: JA
authors.lastname: Jonassen
authors.forename: Kathleen M
authors.initials: KM
authors.lastname: Mazor
mesh_terms: D000367:Age Factors; D002983:Clinical Competence; D003288:Contusions / Q000175:diagnosis; D005260:Female; D006801:Humans; D007396:Internship and Residency; D016013:Likelihood Functions; D016014:Linear Models; D008297:Male; D008403:Mass Screening / Q000706:statistics & numerical data*; D010820:Physicians / Q000523:psychology / Q000706:statistics & numerical data; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012737:Sex Factors; D013179:Spouse Abuse / Q000175:diagnosis*; D011795:Surveys and Questionnaires; D014481:United States