Predictive Models for Assistance Dogs
A study looked at early predictive success of a potential assistance dog. At this time, the determination is not finalized until weeks into training, when the dog is close to 2 years old. Dogs in the study were evaluated with two candidate measures employed by Canine Companions for Independence (CCI), a national assistance dog organization headquartered in Santa Rosa, CA. The procedure utilized the Canine Behavioral Assessment and Research Questionnaire (C-BARQ) and a standardized temperament assessment known internally as the In-For-Training (IFT) test. Three predictive models were developed using C-BARQ scores, IFT scores, and a combination of scores. All three final models had accuracies ranging from 64 to 68%. Model predictions were most accurate for dogs predicted to have the lowest probability of success (ranging from 85 to 92% accurate for dogs in the lowest 10% of predicted probabilities), and moderately accurate for identifying the dogs most likely to succeed (ranging from 62 to 72% for dogs in the top 10% of predicted probabilities). Combining C-BARQ and IFT predictors into a single model did not improve overall accuracy, although it did improve accuracy for dogs in the lowest 20% of predicted probabilities. These results suggest that both types of assessments have the potential to be used as powerful screening tools, which can help earlier assistance dog selection and training.
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