title: To what extent does nonanalytic reasoning contribute to visual learning in cytopathology?
abstract: BACKGROUND
  Acquisition of visual interpretation skills in cytopathology may involve 2 strategies. Analytic strategies require trainees to base their interpretive decisions on carefully considered and often exhaustive cytomorphologic feature lists, a process that can be time-consuming and inefficient. In contrast, nonanalytic pattern recognition strategies are rarely encouraged during training, even though this approach is characteristic of expert diagnostic behavior. This study evaluated the potential role of nonanalytic learning in cytopathology as an efficient alternative to analytic training.
  
  
  METHODS
  Forty-nine cytology novice participants undertook an initial image interpretation test to obtain baseline diagnostic accuracy (test 1). Twenty-four participants subsequently received training in basic cervical cytomorphology and were given a list of cell features for future reference (the "analytic" group). The remaining 25 participants were simply shown 20 nonannotated paired images of normal and abnormal cervical cells (the "nonanalytic" group). Following a practice phase, both groups were retested (test 2). Prior to a final test (test 3), participants in both groups were instructed to adopt a combined analytic/nonanalytic diagnostic strategy. Diagnostic accuracy and response times were measured in each test.
  
  
  RESULTS
  Diagnostic accuracy in both groups improved significantly between tests 1 and 2 (P<.001) but decreased between tests 2 and 3 (P<.05). Speed of response to test images was generally faster under nonanalytic than under analytic conditions.
  
  
  CONCLUSIONS
  Nonanalytic reasoning in cytopathology image interpretation can be as accurate as traditional feature-based reasoning. Encouraging trainees to adopt pattern recognition strategies may help to expedite the acquisition of visual interpretation skills in cytopathology training programs, yet combining analytic and nonanalytic reasoning do not appear to be effective.
authors: Cervical Screening Wales, Cardiff, United Kingdom. aevered@cardiffmet.ac.uk
authors: Andrew
authors: A
authors: Evered
authors: Darren
authors: D
authors: Walker
authors: Andrew A
authors: AA
authors: Watt
authors: Nick
authors: N
authors: Perham
mesh_terms: D000293:Adolescent; D000328:Adult; D003581:Cytodiagnosis / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D018307:Neoplasms, Squamous Cell / Q000175:diagnosis*; D010364:Pattern Recognition, Visual; D011379:Prognosis; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*; D055815:Young Adult; D002578:Uterine Cervical Dysplasia / Q000175:diagnosis*