Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Department of Business Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands.
BMC Public Health. 2020 Mar 30;20(1):411. doi: 10.1186/s12889-020-8416-3.
Goals play an important role in the choices that individuals make. Yet, there is no clear approach of how to incorporate goals in discrete choice experiments. In this paper, we present such an approach and illustrate it in the context of lifestyle programs. Furthermore, we investigate how non-health vs. health goals affect individuals' choices via non-goal attributes.
We used an unlabeled discrete choice experiment about lifestyle programs based on two experimental conditions in which either a non-health goal (i.e., looking better) or a health goal (i.e., increasing life expectancy) was presented to respondents as a fixed attribute level for the goal attribute. Respondents were randomly distributed over the experimental conditions. Eventually, we used data from 407 Dutch adults who reported to be overweight (n = 212 for the non-health goal, and n = 195 for the health goal).
Random parameter logit model estimates show that the type of goal significantly (p < 0.05) moderates the effect that the attribute diet has on lifestyle program choice, but that this is not the case for the attributes exercise per week and expected weight loss.
A flexible diet is more important for individuals with a non-health goal than for individuals with a health goal. Therefore, we advise policy makers to use information on goal interactions for developing new policies and communication strategies to target population segments that have different goals. Furthermore, we recommend researchers to consider the impact of goals when designing discrete choice experiments.
目标在个人决策中起着重要作用。然而，目前尚不清楚如何将目标纳入离散选择实验中。本文提出了一种方法，并在生活方式计划的背景下进行了说明。此外，我们还研究了非健康目标与健康目标如何通过非目标属性影响个体的选择。
我们使用了一种未标记的基于生活方式计划的离散选择实验，该实验基于两种实验条件，其中目标属性为固定属性水平，分别为非健康目标（即看起来更好）或健康目标（即增加预期寿命）。受访者被随机分配到实验条件中。最终，我们使用了来自 407 名荷兰超重成年人的数据（非健康目标组 n=212，健康目标组 n=195）。
随机参数对数模型估计结果表明，目标类型显著（p<0.05）调节了属性饮食对生活方式计划选择的影响，但属性锻炼频率和预期体重减轻则并非如此。
对于有非健康目标的个体来说，灵活的饮食比有健康目标的个体更重要。因此，我们建议政策制定者利用目标交互的信息制定新的政策和沟通策略，以针对具有不同目标的人群。此外，我们建议研究人员在设计离散选择实验时考虑目标的影响。
