Symposium 2 Methods for investigating decision making in nursing practice
Symposium lead and chair:
Lenard Dalgleish, Professor of Decision Making, Department of Nursing & Midwifery, University of Stirling, Stirling, United Kingdom len.dalgleish@stir.ac.uk
Symposium focus:
Many methods are used to study judgment and decision making. At the 2007 RCN conference we organised a symposium that focussed on the use of case vignettes as a method. However, this is only one of the many ways to study judgment and decision making in nursing and midwifery. Other methods include think-aloud protocols, observation and patient simulators. This symposium will present three different methods. Each paper will present results from their research and discuss the strengths and limitations of the methods they used. This symposium will help researchers choose an appropriate method for their question about decision making being asked. For example, some methods are better for finding out about the process by which nurses make decisions while others focus on the factors influencing the decisions made.
Abstract 1: ‘Think aloud’ and observation – two methods of data collection that offer differing benefits in the study of decision making
Professor Leanne Aitken, Professor of Critical Care Nursing, Griffith University & Princess Alexandra Hospital, Brisbane, Australia.
Decision making is a complex function affected by the nature of the task, the decision environment and the characteristics of the decision maker. To effectively study decision making the data collection method must be able to reveal the multiple decisional components that are relevant to the question under investigation.
Two data collection methods that have frequently been used, both independently and jointly, to explore decision making processes and outcomes in healthcare include ‘think aloud’ and observation. ‘Think aloud’, also referred to as concurrent verbal protocol, involves the audio-taping of the decision makers’ thoughts as they work through a decision scenario. ‘Think aloud’ provides detailed information regarding both processes and outcomes of the process, allowing identification of the rules that decision makers use as they move through a decision. ‘Think aloud’ has the potential to alter the decision making process or alternatively miss data if the decision maker ceases verbalising cognitive processes or uses automated intuitive processes. Observation of decision making provides real time, detailed information summarising the types of decisions that nurses make and is beneficial in describing the outcomes of the decision making process. The effectiveness of observation is limited to decision making processes or outcomes that are observable. Further, it is open to bias in that the data collector will only record what they note, may misinterpret actions or may incorrectly link multiple activities together. This paper will examine the challenges and considerations of using either ‘think aloud’ or observation as a data collection method in the field of decision making. The relationship between each of these data collection methods and the research question will be examined. Example data from studies of sedation in critical care will be used as an illustration.
Use of patient simulators for research on clinical decision making in nursing. Dr Anne Pingenot, HealthQWest post-doctoral research fellow, Department of Nursing and Midwifery, University of Stirling. Simulators have been used for research on pilot decision making for several decades. One of the unique areas of research for which simulators can be used is the study of how people actually react to specific situations. This is particularly valuable when trying to decompose complex decision environments to identify key variables important to specific decisions. It is a small leap from decision making studies of pilots flying simulated aircraft to healthcare personnel attending simulated patients. Patient simulators, although not quite real, can be programmed to respond physiologically to interventions on the part of the provider, giving realistic feedback so that the dynamics of a complex system can be studied. The University of Stirling has been using patient simulators for teaching Nurse Prescriber students for out of hours work in hospitals. Decisions made by students attending a patient simulator at the end of their training are being studied to determine how teaching strategies affect their ability to differentiate key clinical cues to make clinical management decisions.
Abstract 2: The use of auto-ethnography in studying decision-making in intensive care: Strengths and weaknesses
Claire Kydonaki, PhD student in Nursing Studies, University of Edinburgh
Nurses need to be able and confident to make fast and rigorous decisions about the care of their patients, especially in demanding areas, such as critical care. An area of critical care that demands nurses’ effective decision-making and requires further investigation is the area of mechanical ventilation and in particular the process of weaning. This paper will show how auto-ethnography and self-reflexivity together with the use of ‘think-aloud’ method can be used as a research tool to study decision making in the weaning process. The researcher, as a staff nurse in a 10-bedded general ICU in Scotland, used participant observation with the ‘think aloud’ technique to go deeper into the behaviour and thinking process in relation to the weaning of ventilated patients. She talked through her thoughts and decision activities while she was managing the patient’s ventilation by using a microphone, in order to explore her behaviour and input. She recorded and transcribed the verbal data collected from two patient cases that were mechanically ventilated and in the process of weaning. The data extracted have not been analyzed yet, but analysis will be completed in time for presentation at the symposium. The researcher will use thematic analysis to identify major concepts; she will reflect on her behaviour and uncover possible strengths and weaknesses of using the ‘think aloud’ method for collecting observational data when studying decision