Carolyn A Unsworth1, Shane A Thomas. 1. School of Occupational Therapy, La Trobe University, Bundoora, Australia. c.unsworth@latrobe.edu.au
Abstract
PURPOSE: Using a Social Judgment Theory approach, mathematical models of clinical decisions can be developed to predict new decisions. However, since these models are often developed under 'laboratory conditions' using hypothetical cases rather than real world client samples, questions may be raised concerning the external validity of such models. The purpose of this research was to validate a discharge housing decision making model developed with hypothetical clients with stroke with a real sample. This process is referred to as external validation. METHODS: Cross-tabulations were performed to compare the model discharge housing prediction against the team's actual recommendations for 60 clients from three rehabilitation centres. A sensitivity and specificity analysis was used to compare the model predictions against the client's actual discharge housing. RESULTS: A simple mathematical model was constructed to accurately predict housing recommendations. However, the predictive power of the model appeared to be limited by clinician/team consideration of unmeasured factors such as client personality and motivation. CONCLUSION: It is suggested that the housing decision model developed may be useful for rehabilitation teams as a starting point when discussing the best place to recommend a client reside on discharge from rehabilitation. Such a model may assist teams to standardise their decision processes and minimise the potential for unwarranted bias.
PURPOSE: Using a Social Judgment Theory approach, mathematical models of clinical decisions can be developed to predict new decisions. However, since these models are often developed under 'laboratory conditions' using hypothetical cases rather than real world client samples, questions may be raised concerning the external validity of such models. The purpose of this research was to validate a discharge housing decision making model developed with hypothetical clients with stroke with a real sample. This process is referred to as external validation. METHODS: Cross-tabulations were performed to compare the model discharge housing prediction against the team's actual recommendations for 60 clients from three rehabilitation centres. A sensitivity and specificity analysis was used to compare the model predictions against the client's actual discharge housing. RESULTS: A simple mathematical model was constructed to accurately predict housing recommendations. However, the predictive power of the model appeared to be limited by clinician/team consideration of unmeasured factors such as client personality and motivation. CONCLUSION: It is suggested that the housing decision model developed may be useful for rehabilitation teams as a starting point when discussing the best place to recommend a client reside on discharge from rehabilitation. Such a model may assist teams to standardise their decision processes and minimise the potential for unwarranted bias.