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Decision-making in clinical nursing: investigating contributing factors

Authors

  • Kerry Hoffman MN RN,

  • Judith Donoghue PhD RN,

  • Christine Duffield PhD RN


Kerry Hoffman, School of Nursing and Midwifery, Faculty of Health, University of Newcastle, Callaghan, NSW 2308, Australia.
E-mail: kerry.hoffman@newcastle.edu.au

Abstract

Background.  This article describes the results of a study which investigated the contextual factors influencing clinical decision-making. Education and experience have been suggested by some as having a positive effect on clinical decision-making, and have been listed as being of high importance. Values, knowledge, clinical setting and stress have also been identified as being important to decision-making, with various rankings given by different researchers.

Aim.  The study was undertaken to determine relationships between occupational orientation (value to role), educational level, experience, area of practice, level of appointment, age and clinical decision-making in Australian nurses. The predictive ability of each factor on clinical decision-making was determined.

Method.  This correlational study examined Australian nurses’ decision-making about some common nursing interventions and ‘occupational orientation’, educational level, experience, level of appointment, area of clinical speciality and age. A model was constructed using stepwise selection regression to predict the ‘weight’ of each variable in clinical decision-making.

Results.  Education and experience were not significantly related to decision-making. The factor that accounted for the greatest variability to clinical decision-making was holding a professional occupational orientation, followed by level of appointment, area of clinical speciality, and age in that order.

Conclusion.  In contrast to other studies, experience and educational level were not found to influence decision-making strongly, the value of role was the most significant predictor. The model developed, however, only accounted for a low amount of variability in decision-making. The findings indicate that there are other factors affecting clinical decision-making that still require identification.

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