降低科学好奇心量表(SCS)的管理需求:一项验证研究

Matthew P. Motta, D. Chapman, Kathryn Haglin, D. Kahan
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引用次数: 1

摘要

对科学好奇的人——那些喜欢消费科学相关信息的人——不太可能对有争议的科学持有两极分化的观点。因此,科学好奇心引起了社会科学学者的极大兴趣。然而,通过科学好奇心量表(SCS;Kahan等人,2017)是高度时间密集型的;可能阻碍其广泛使用。在本文中,我们提出了两种减少SCS给药时间的新方法。一种方法是向受访者提供随机选择的项目子集(“随机子集法”;RS”)。另一种方法只要求所有受访者回答四个核心问题(“简化形式法”;射频”)。在三个具有全国代表性的美国成年人调查中,我们评估了这些替代方案的结构、聚合和预测有效性。在所有研究中,RS和RF版本的SCS似乎得到了很好的验证。最后,我们讨论了研究人员如何将这些见解应用到他们自己的研究中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reducing the Administrative Demands of the Science Curiosity Scale (SCS): A Validation Study
Science curious people -- those who enjoy consuming science-related information -- are less likely to hold polarized views about contentious science. Consequently, science curiosity is of great interest to scholars across the social sciences. However, measuring science curiosity via the science curiosity scale (SCS; Kahan et al., 2017) is highly time intensive; potentially impeding its widespread usage. In this paper, we present two new methods for reducing SCS administration time. One method presents respondents with a randomly selected subset of items (the "Random Subset Method; RS"). The other asks all respondents a core set of just four items (the "Reduced-Form Method; RF"). In three nationally representative surveys of U.S. adults, we assess the construct, convergent, and predictive validity of these alternatives. Across studies, the RS and RF versions of the SCS appear to be well validated. We conclude by discussing how researchers can apply these insights into their own research.
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