title: Simulation training for breast and pelvic physical examination: a systematic review and meta-analysis.
abstract: BACKGROUND
  Breast and pelvic examinations are challenging intimate examinations. Technology-based simulation may help to overcome these challenges.
  
  
  OBJECTIVE
  To synthesise the evidence regarding the effectiveness of technology-based simulation training for breast and pelvic examination.
  
  
  METHODS
  Our systematic search included MEDLINE, EMBASE, CINAHL, PsychINFO, Scopus, and key journals and review articles; the date of the last search was January 2012.
  
  
  METHODS
  Original research studies evaluating technology-enhanced simulation of breast and pelvic examination to teach learners, compared with no intervention or with other educational activities.
  
  
  METHODS
  The reviewers evaluated study eligibility and abstracted data on methodological quality, learners, instructional design, and outcomes, and used random-effects models to pool weighted effect sizes.
  
  
  RESULTS
  In total, 11 272 articles were identified for screening, and 22 studies were eligible, enrolling 2036 trainees. In eight studies comparing simulation for breast examination training with no intervention, simulation was associated with a significant improvement in skill, with a pooled effect size of 0.86 (95% CI 0.52-1.19; P < 0.001). Four studies comparing simulation training for pelvic examination with no intervention had a large and significant benefit, with a pooled effect size of 1.18 (95% CI 0.40-1.96; P = 0.003). Among breast examination simulation studies, dynamic models providing feedback were associated with improved outcomes. In pelvic examination simulation studies, the addition of a standardised patient to the simulation model and the use of an electronic model with enhanced feedback improved outcomes.
  
  
  CONCLUSIONS
  In comparison with no intervention, breast and pelvic examination simulation training is associated with moderate to large effects for skills outcomes. Enhanced feedback appears to improve learning.
authors.affiliation: General Internal Medicine, Mayo Clinic School of Graduate Medicine, 200 First Street SW, Rochester, MN 55905, USA. dilaveri.christina@mayo.edu
authors.forename: C A
authors.initials: CA
authors.lastname: Dilaveri
authors.forename: J H
authors.initials: JH
authors.lastname: Szostek
authors.forename: A T
authors.initials: AT
authors.lastname: Wang
authors.forename: D A
authors.initials: DA
authors.lastname: Cook
mesh_terms: D002983:Clinical Competence; D003198:Computer Simulation; D004501:Education, Medical / Q000379:methods*; D018961:Educational Technology; D005260:Female; D006176:Gynecology / Q000193:education*; D006801:Humans; D008348:Manikins; D009774:Obstetrics / Q000193:education*; D016544:Patient Simulation; D010808:Physical Examination
keywords: Breast examination; pelvic examination; simulation training