title: Clinical reasoning processes: unravelling complexity through graphical representation.
abstract: BACKGROUND
  Clinical reasoning is a core skill in medical practice, but remains notoriously difficult for students to grasp and teachers to nurture. To date, an accepted model that adequately captures the complexity of clinical reasoning processes does not exist. Knowledge-modelling software such as mot Plus (Modelling using Typified Objects [MOT]) may be exploited to generate models capable of unravelling some of this complexity.
  
  
  OBJECTIVE
  This study was designed to create a comprehensive generic model of clinical reasoning processes that is intended for use by teachers and learners, and to provide data on the validity of the model.
  
  
  METHODS
  Using a participatory action research method and the established modelling software (mot Plus), knowledge was extracted and entered into the model by a cognitician in a series of encounters with a group of experienced clinicians over more than 250 contact hours. The model was then refined through an iterative validation process involving the same group of doctors, after which other groups of clinicians were asked to solve a clinical problem involving simulated patients.
  
  
  RESULTS
  A hierarchical model depicting the multifaceted processes of clinical reasoning was produced. Validation rounds suggested generalisability across disciplines and situations.
  
  
  CONCLUSIONS
  The MOT model of clinical reasoning processes has potentially important applications for use within undergraduate and graduate medical curricula to inform teaching, learning and assessment. Specifically, it could be used to support curricular development because it can help to identify opportune moments for learning specific elements of clinical reasoning. It could also be used to precisely identify and remediate reasoning errors in students, residents and practising doctors with persistent difficulties in clinical reasoning.
authors.affiliation: Centre for Applied Pedagogy in Health Sciences (CPASS), University of Montreal, and Department of Neurology, Montreal General Hospital, Montreal, Quebec, Canada. bernard.charlin@umontreal.ca
authors.forename: Bernard
authors.initials: B
authors.lastname: Charlin
authors.forename: Stuart
authors.initials: S
authors.lastname: Lubarsky
authors.forename: Bernard
authors.initials: B
authors.lastname: Millette
authors.forename: Françoise
authors.initials: F
authors.lastname: Crevier
authors.forename: Marie-Claude
authors.initials: MC
authors.lastname: Audétat
authors.forename: Anne
authors.initials: A
authors.lastname: Charbonneau
authors.forename: Nathalie
authors.initials: N
authors.lastname: Caire Fon
authors.forename: Lea
authors.initials: L
authors.lastname: Hoff
authors.forename: Christian
authors.initials: C
authors.lastname: Bourdy
mesh_terms: D002983:Clinical Competence / Q000592:standards*; D003196:Computer Graphics; D003194:Computer-Assisted Instruction; D003658:Decision Making, Computer-Assisted; D004504:Education, Medical, Undergraduate / Q000379:methods*; D006801:Humans; D011340:Problem Solving