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Periodic Retraining of Animal Care Assessors Recommended to Ensure Accuracy of Animal Care Assessments

A Post-Doctoral Research Fellow with the Western College of Veterinary Medicine recommends periodic retraining of animal care assessors to ensure the accuracy and consistency of on farm animal care assessments. Animal care assessments are typically used to provide feedback to producers for continued improvement.

In partnership with the Natural Sciences and Engineering Research Council, the University of Saskatchewan and pork sector stakeholders, researchers with the Western College of Veterinary Medicine have created a systematic and robust training program to expand the knowledge base of observers and improve the accuracy and consistency of their pig care assessments.

Dr. Giuliana Miguel Pacheco, a Doctor of Veterinary Medicine and a Post-Doctoral Research Fellow in the Department of Large Animal Clinical Sciences, says these assessments need to be consistent to avoid creating problems due to inaccurate assessments.

Clip-Dr. Giuliana Miguel Pacheco-Western College of Veterinary Medicine:

We measure consistency comparing the level of accuracy of the assessment of the assessors versus an experienced assessor and within themselves. For the latter we compare the  assessment they did on the first day of training and the one they did a week later. Using the systematic training approach our assessors had what we call a good level of consistency within themselves and a substantial to almost perfect with the trainer or experienced assessor.

All this means that they measured the indicators very similar to the trainers, so to the experienced assessor. However, we noticed that some of the consistency reduced a week after the training. This means that the assessor's accuracy is reducing over time.

So, in our case we retrain our assessors a month later and test again later for accuracy and we found that this improved. Based on this we recommend that retraining should be part of animal care assessment training programs to maintain the quality and robustness of the data collected.

Source : Farmscape

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