Replication Data for Neary et al 2022 - Recognizing post-castration pain in piglets

This data was collected using an online Qualtrics survey (SAP, Provo, UT, USA) distributed (August-September 2020) with the aim to receive responses from experienced swine industry respondents (“industry”) and respondents from the general public without swine industry work experience (“public”) at a 1:1 ratio. Industry respondents were recruited via Facebook and by direct email to industry stakeholders and university faculty within the authors’ network. Facebook posts were not sponsored and were not distributed in any Facebook groups. Facebook users, swine industry contacts and university faculty were invited to disseminate the survey to others with a relevant background, including farm owners, operators, technicians and veterinarians. Simultaneously, public respondents were recruited through Amazon Mechanical Turk (Amazon Web Services, Seattle WA, USA) and received a monetary compensation for their time through the website. Industry respondents did not receive compensation. Inclusion criteria required respondents to be over the age of 18 and living in the U.S. Responses were entered anonymously.
We received 129 complete survey responses. Five were omitted because respondents did not live in the U.S., and 5 were omitted because respondents failed the attention check question. Survey respondents were categorized as either ‘public respondents’ which was defined as having no professional swine industry experience, or as ‘industry respondents’ which was defined as having any professional, paid swine industry experience. We included 119 completed surveys in the data analysis, 66 from the public respondents (55%) and 53 from industry respondents (45%).
Respondents completed a short training module on classifying piglet grimace levels (indicators of pain) based on three facial features using the Piglet Grimace Scale (Viscardi & Turner, 2018). They were then asked to score 12 images on the scale and complete a series of questions about their demographic background, industry experience, and knowledge of swine agricultural practices.
The primary anonymized data is found in pgs_mturk_working_data.csv. with additional data from coding of the images by 4 experts in gold_standard_csv.csv. Together, these form the basis for the 2022 publication "Recognizing post-castration pain in piglets: a survey of swine industry stakeholders and the general public" in Frontiers in Veterinary Medicine. The instrument and summary demographic statistics are in Survey_Instrument_and_Demographics_Table.docx.
R Code used to produce the analyses reported in the paper is in pgs_data_prep_and_analysis_anonymized.R. Additional output data used for further analysis can be found  in the remaining 2 csv files, as well as labelled_tables.xlsx.

本数据集通过在线Qualtrics调查（SAP公司，美国犹他州普罗沃）收集而来，该调查于2020年8月至9月期间分发，旨在以1:1的比例收集来自具有养猪业经验（以下简称“行业”）的受访者以及无养猪业工作经验的公众（以下简称“公众”）的反馈。行业受访者通过Facebook和作者网络内的行业利益相关者和大学教师直接电子邮件招募。Facebook帖子未进行赞助，也未在任何Facebook群组中分发。Facebook用户、养猪业联系人和大学教师被邀请向具有相关背景的其他人士推广该调查，包括农场主、操作员、技术人员和兽医。同时，公众受访者通过亚马逊Mechanical Turk（亚马逊网络服务，美国华盛顿州西雅图）招募，并通过网站获得时间补偿。行业受访者未获得补偿。入选标准要求受访者年满18岁且居住在美国。所有反馈以匿名方式录入。我们共收到129份完整的调查反馈，其中5份因受访者不居住在美国而被排除，另外5份因受访者未能通过注意力检查问题而被排除。调查受访者被归类为“公众受访者”，定义为无专业养猪业经验；或“行业受访者”，定义为具有任何专业、付费养猪业经验。在数据分析中，我们纳入了119份完成的调查，其中66份来自公众受访者（占55%），53份来自行业受访者（占45%）。受访者完成了一个关于根据三个面部特征（疼痛指标）对仔猪面部表情级别进行分类的短期培训模块（基于Viscardi和Turner于2018年提出的仔猪面部表情量表）。随后，他们被要求根据该量表对12张图片进行评分，并完成一系列关于其人口统计背景、行业经验和养猪农业实践知识的问卷。主要匿名数据位于pgs_mturk_working_data.csv文件中，此外，由4位专家对图片进行编码的数据位于gold_standard_csv.csv文件中。这些数据共同构成了2022年在《Frontiers in Veterinary Medicine》上发表的《识别仔猪去势术后疼痛：养猪业利益相关者和公众的调查》一文的基石。工具和总结的人口统计统计数据位于Survey_Instrument_and_Demographics_Table.docx文件中。用于生成论文中报告的分析的R代码位于pgs_data_prep_and_analysis_anonymized.R文件中。用于进一步分析的额外输出数据可找到于剩余的2个csv文件中，以及labelled_tables.xlsx文件中。