Malkani Rachel, Paramasivam Sharmini, Wolfensohn Sarah
School of Veterinary Medicine, University of Surrey, Guildford, United Kingdom.
Front Vet Sci. 2022 Sep 16;9:940017. doi: 10.3389/fvets.2022.940017. eCollection 2022.
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.
动物福利监测是兽医学的重要组成部分,由于一系列影响福利认知的因素,这项工作可能具有挑战性。不过,可以使用一些工具;然而,兽医和动物福利专业人员可用于评估和监测犬只一生福利的经过验证的客观方法却很少。本研究旨在改编先前已在其他物种中验证的框架——动物福利评估网格(AWAG),使其适用于犬只,并将该工具置于一个易于访问、使用方便的在线平台上。犬用AWAG的开发涉及利用科学文献来确定哪些因素与犬只福利评分相关,并撰写因素描述。该主要工具在兽医专业人员中进行了试用,以完善和改进AWAG。内容效度由主题专家通过使用项目级内容效度指数(I-CVI)和基于平均法的量表级内容效度指数(S-CVI/Ave)对评估犬只福利因素的效度进行评分来评估。结构效度由该工具的使用者对健康犬和患病犬,以及正在接受绝育手术的健康犬进行评分来评估。曼-惠特尼检验表明,该工具能够区分健康犬和患病犬,以及择期手术后的健康犬和健康犬。重测信度通过使用者在不变条件下对个体犬进行多次评估来测试。评分者间信度由两名使用者在兽医转诊实践中同时对一只个体犬进行评分来评估。重测信度和评分者间信度的重复测量方差分析均显示分数之间无统计学差异,且分数高度相关。本研究提供了证据,表明犬用AWAG具有良好的内容效度和结构效度,以及良好的重测信度和评分者间信度。