Rural Economy and Development Programme, Teagasc Food Research Centre Ashtown, Ashtown, Dublin, Ireland.
Teagasc-Agriculture and Food Development Authority, Carlow, Ireland.
J Agromedicine. 2024 Oct;29(4):531-546. doi: 10.1080/1059924X.2024.2365638. Epub 2024 Jun 18.
Measuring attitudes of farmers to safe farming practices using quantitative causal relationship approaches is central to improving understanding of (un)safe practices. This knowledge is important in the development of effective farm safety interventions. However, the accuracy of quantitative attitudinal studies in explaining farmers' decision-making faces a potential measurement challenge, i.e. a high level of optimism bias. In this paper, we present research that develops and tests farm safety attitudinal questions that are framed around "real-life" farming practices with the objective of reducing optimism bias.
We apply construal level theory (CLT) to support the design of vignettes that reflect common risk scenarios faced by farmers. Applying qualitative analysis of 274 fatal farm incidents that occurred in Ireland between 2004 and 2018 we identify the occupational behaviors (what farmers do), social (who are farmers), spatial (where farming takes place), and temporal (when farming happens) dimensions of risks resulting in most deaths. The results informed subsequent co-design activities with farm safety experts and farm advisors to develop "real-life" scenarios, attitudinal questions, and response options. The questionnaire was piloted and subsequently implemented to collect data from a sample of 381 farmers with either tractors or livestock. The results of the survey were compared to previous attitudinal research on farmer's attitudes to safety in Ireland to establish if there was as follows: i) increased variance in the responses, and ii) a statistically significant difference in the attitudes of respondents compared to the results reported in previous studies.
The findings established that when farmers were provided with real-life scenarios, their responses were less optimistic and more varied, i.e. there was a greater range of responses, compared to previous studies.
Applying CTL to the development of attitudinal survey instruments anchors attitudinal questions within farming specific occupational, social, spatial, and temporal contexts. The use of vignettes that draw on real-life scenarios offers the potential for improved design of surveys that seek to understand farmer/worker practices. The results suggest that this approach can improve the measurement of attitudes to farm safety.
使用定量因果关系方法衡量农民对安全农业实践的态度,对于理解(不安全)实践至关重要。这种知识对于开发有效的农场安全干预措施非常重要。然而,定量态度研究在解释农民决策方面的准确性面临着潜在的测量挑战,即高度的乐观偏见。在本文中,我们提出了一项研究,该研究开发并测试了围绕“真实”农业实践构建的农场安全态度问题,旨在减少乐观偏见。
我们应用构念水平理论(CLT)来支持设计反映农民面临的常见风险情景的情境,对 2004 年至 2018 年期间在爱尔兰发生的 274 起致命农场事故进行定性分析,确定导致大多数死亡的职业行为(农民做什么)、社会(谁是农民)、空间(农场发生的地点)和时间(农场发生的时间)维度的风险。结果为随后与农场安全专家和农场顾问合作设计“真实”情景、态度问题和响应选项提供了信息。该问卷进行了试点,并随后在 381 名拥有拖拉机或牲畜的农民中进行了实施,以收集数据。调查结果与爱尔兰之前关于农民对安全态度的态度研究进行了比较,以确定是否存在以下情况:i)响应的方差增加,ii)与之前研究报告的结果相比,受访者的态度存在统计学上的显著差异。
研究结果表明,当农民提供真实情景时,他们的反应不那么乐观,而且更加多样化,即与之前的研究相比,有更多的反应。
将 CTL 应用于态度调查工具的开发将态度问题锚定在特定于农业的职业、社会、空间和时间背景下。使用基于真实情景的情境可以为理解农民/工人实践的调查设计提供改进的潜力。结果表明,这种方法可以提高对农场安全态度的测量。