Developing a tool to assess the health-related quality of life in calves with respiratory disease: tool refinement and construct validity testing

Bovine respiratory disease (BRD) is a major source of morbidity and mortality in calves and detection of the disease can be challenging. Diagnostic tools for BRD are typically based on the assessment of clinical signs. As experience of disease is associated with a poor quality of life and this poor emotional experience can be expressed in observable behaviour patterns, a quality-of-life approach might identify new indicators of disease. Health-related quality of life (HRQOL) approaches are widely used in human medicine but are rarely used in livestock. This study aimed to refine and validate an HRQOL tool for calves with BRD that had been created in a previous study. The tool contained 13 items/indicators across two domains (clinical signs and behavioural expression). One hundred preweaned dairy-bred calves were scored daily using the HRQOL tool and also using the industry-recognised Wisconsin health score as a ‘gold standard’. The score assigned to each of the 13 items of the HRQOL tool was summed to give an accumulated HRQOL score for each calf/day. To refine the tool, the items within the tool were compared to each other to identify high levels of correlation or redundancy. This resulted in the retention of three items within the clinical signs domain (body and head posture, respiratory effort and ear carriage) and four within the behavioural expression domain (vigour, movement to feed, motivation at feed and volume of feed consumed). To determine whether the refined HRQOL tool could successfully differentiate sick from healthy animals, the Wisconsin score was used to create two matched groups of 28 ‘sick’ and 28 ‘healthy’ calves. There was a significant difference in the HRQOL scores between the two groups (H = 14.09, df = 1, P = 0.000) suggesting that the new tool could differentiate between ‘healthy’ and ‘sick’ calves. In terms of the two domains, there was a significant difference (P < 0.001) between the ‘healthy’ and ‘sick’ calves for the overall HRQOL tool score for the clinical signs domain, but there was no significant difference (P = 0.154) between ‘healthy’ and ‘sick’ calves in the overall HRQOL score for the behavioural expression domain; however, the combined tool was the most accurate. Overall, this study has demonstrated that the new HRQOL tool can differentiate between sick and healthy calves. Some or all of the indicators could be used alongside existing disease-detection tools for preweaned calves. However, future work would be needed to validate this HRQOL tool in other production systems.