Interactions between Metacognitive Disposition and Clinical Knowledge Use in Novice Nurses' Clinical Problem-Solving: Some Case Studies

Wednesday, 15 July 2009: 4:05 PM

Krystyna M. Cholowski, PhD, RN
School of Nursing & Midwifery, University of Newcastle, Callaghan, Australia
Robert H. Cantwell, PhD
School of Education, University of Newcastle, Callaghan, Australia

Learning Objective 1: The learner will be able to identify the influence of metacognitive preferences in individual nurse’s approaches to clinical problem-solving

Learning Objective 2: The learner will be able to identify instructional strategies aimed at facilitating higher-level competency in clinical problem-solving

Purpose: Previous research indicated that pre-service nurses’ academic and clinical performance could be explained in part by reference to both their dispositional approach to learning and dispositional approach to self-regulation (see Cantwell & Moore, 1998, Cantwell, 1997; Cholowski & Chan, 2001).These studies demonstrated an advantage to a deep and adaptive learning approaches and a concomitant disadvantage to a surface and inflexible or irresolute approaches. However, the data did not extend to an in situ analysis of these relationships in the context of clinical problem solving. It is well recognised in the metacognitive literature that dispositions are at their most powerful when there is close concordance between the task and the disposition. However, the more fine grained the task, the less predictive is the disposition

Methods: Six final year nurses engaged in a clinical problem solving activity utilising a “think aloud” methodology. Participants were selected on the basis of their scores on Cantwell and’s (1996) Strategic Flexibility Questionnaire and Biggs’ (1987) Study Process Questionnaire. Participants were asked to consider how they would deal with four clinical situations. These included managing an intoxicated patient in emergency, responding to an apparently incomplete patient medication record, responding to a mobility issue with an elderly patient and managing a cardiac patient experiencing an anxiety disorder. Transcribed protocols were analysed for the structural complexity of the content discussed and for the depth and breadth of strategy use.

Results: The analysis revealed the pattern of both content and strategy components to be consistent with expectations. Students higher on deep learning and adaptive self-regulation provided more comprehensive accounts of the clinical problems. Students with a surface approach to learning and less functional self-regulation generally provided less comprehensive accounts. 

Conclusion: The paper discusses these results in relation to the perceptual and processing biases associated with extant metacognitive beliefs.