ABSTRACT
[This corrects the article DOI: 10.3389/fvets.2024.1374858.].
ABSTRACT
Introduction: Chronic pain can profoundly affect the wellbeing of dogs and our understanding is limited regarding the multidimensional impact it has on dog quality of life. This study aimed to assess the factors that are significant and predictive of behavior problems in dogs using the Animal Welfare Assessment Grid (AWAG) to further understand what factors influence their welfare. Methods: Seventy six AWAG assessments were undertaken across 46 dogs that clinicians diagnosed as having musculoskeletal conditions that caused chronic pain. Wilcoxon-rank sum tests were used to assess the difference in scores between dogs with behavior disorders and a cohort of healthy dogs (n = 143). Results: All physical factors besides body condition, and all psychological, environmental, and procedural factors were significantly different between healthy dogs and dogs with chronic pain, evidencing how chronic pain impacts all domains of a dog's life. Spearman Rank Correlation Coefficient (RS) revealed several significant strong positive correlations such as the association between the severity of clinical symptoms with poorer mobility and the frequency at which the dog experienced fearful stimuli. Logistic regression showed that fears and anxieties frequency, the dog's reaction to stressors, engagement with enrichment, and social interactions were significant predictors of chronic pain in dogs. Discussion: This highlights that typical signs of musculoskeletal disorders such as gait changes, stiffness, lameness might manifest after behavioral changes such as increased fearfulness, prolonged recovery from a stressful event, a reduced interested in social interactions, toys or play. Owners only seeking veterinary attention when the presence of physical signs of disease are evident may result in a delayed veterinary attention resulting in reduced welfare. Regular veterinary assessments combined with use of the AWAG can proactively identify these behavioral indicators and result in prompt treatment and improved quality of life.
ABSTRACT
Behavioural disorders in dogs are common and have severe welfare consequences for dogs. This study aimed to assess the factors that are significant and predictive of behaviour problems in dogs using the animal welfare assessment grid (AWAG) to further understand what factors influence their welfare. 177 AWAG assessments were undertaken across 129 dogs that clinicians deemed to have a behavioural disorder. Wilcoxon rank-sum tests were used to assess the difference in scores between dogs with behaviour disorders and a cohort of healthy dogs (n = 117). This analysis showed that all physical factors besides body condition, all procedural factors besides procedure pain, and all psychological, and environmental factors were significantly different between healthy dogs and dogs with behaviour disorders. Spearman rank correlation coefficient (RS) revealed several significant strong positive correlations including the procedural impact on the dog's daily routine with aggression towards unfamiliar people and procedure pain, as well as other correlations between the dog's behaviour during assessment with the frequency at which they encounter fears and anxieties, clinical assessment and procedure pain, and reaction to stressors and social interactions. These findings highlight the interdependent nature of the various influences of welfare. Logistic regression analysis identified that aggression towards the caregiver, fears and anxieties frequency, and choice, control, and predictability were all significant predictors of behaviour disorders. The findings have important implications for veterinary, behaviour, and animal welfare professionals as any changes across these factors may indicate poor welfare linked to emotional disorders in dogs.
ABSTRACT
Animal welfare monitoring is a vital part of veterinary medicine and can be challenging due to a range of factors that contribute to the perception of welfare. Tools can be used, however; there are few validated and objective methods available for veterinary and animal welfare professionals to assess and monitor the welfare of dogs over their lifetime. This study aimed to adapt a framework previously validated for other species, The Animal Welfare Assessment Grid (AWAG), for dogs and to host the tool on an accessible, easy to use online platform. Development of the AWAG for dogs involved using the scientific literature to decide which factors were relevant to score welfare in dogs and to also write the factor descriptors. The primary tool was trialed with veterinary professionals to refine and improve the AWAG. Content validity was assessed by subject matter experts by rating the validity of the factors for assessing dog welfare using the item-level content validity index (I-CVI) and scale-level content validity index based on the average method (S-CVI/Ave). Construct validity was evaluated by users of the tool scoring healthy and sick dogs, as well as healthy dogs undergoing neutering procedures. Mann Whitney tests demonstrate that the tool can differentiate between healthy and sick dogs, and healthy and healthy dogs post elective surgery. Test re-test reliability was tested by users conducting multiple assessments on individual dogs under non-changing conditions. Inter-rater reliability was assessed by two users scoring an individual dog at the same time in veterinary referral practice. Repeated measures ANOVA for test re-test and inter-rater reliability both show no statistical difference between scores and that the scores are highly correlated. This study provides evidence that the AWAG for dogs has good content and construct validity, alongside good test re-test and inter-rater reliability.
