Frontiers in Veterinary Science · 2024 · 17 citations · 42 references
AgricultureAnimal SciencesAnimal HealthAnimal WelfarePain ScienceAnimal Welfare AssessmentChronic PainPain AssessmentPsychosocial Factors In PainStress-related BehaviorWelfare AssessmentAssessmentsBehavioral Indicators Of PainClinical SymptomsGaitMusculoskeletal DisordersSpearman Rank Correlation CoefficientStressful ExperienceVeterinary Welfare Assessment
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: = 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.
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Reshaping Data with the<b>reshape</b>Package
Hadley Wickham · Journal of Statistical Software · 2007 · 2.9K citations · Full text