Comparing the Performance of Agree/Disagree and Item-Specific Questions Across PCs and Smartphones

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Jan Karem Höhne, M. Revilla, Timo Lenzner
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引用次数: 15

Abstract

The use of agree/disagree (A/D) questions is a common technique to measure attitudes. For instance, this question format is employed frequently in the Eurobarometer and International Social Survey Programme (ISSP). Theoretical considerations, however, suggest that A/D questions require a complex processing. Therefore, many survey researchers have recommended the use of item-specific (IS) questions, since they seem to be less burdensome. Parallel to this methodological discussion is the discussion around the use of mobile devices for responding to surveys. However, until now, evidence has been lacking as to whether the use of mobile devices for survey response affects the performance of established question formats. In this study, implemented in the Netquest panel in Spain (N = 1,476), we investigated the cognitive effort and response quality associated with A/D and IS questions across PCs and smartphones. For this purpose, we applied a split-ballot design defined by device type and question format. Our analyses revealed longer response times for IS questions than A/D questions, irrespective of the device type and scale length. Also, the IS questions produced better response quality than their A/D counterparts. All in all, the findings indicate a more conscientious response to IS questions compared to A/D questions.
比较PC和智能手机中同意/不同意和项目特定问题的表现
使用同意/不同意(A/D)问题是衡量态度的常用技巧。例如,欧洲晴雨表和国际社会调查方案经常采用这种问题格式。然而,理论上的考虑表明,A/D问题需要复杂的处理。因此,许多调查研究人员建议使用项目特定(IS)问题,因为它们似乎不那么麻烦。与这一方法论讨论平行的是关于使用移动设备回应调查的讨论。然而,到目前为止,还缺乏证据表明使用移动设备进行调查回复是否会影响既定问题格式的性能。在这项由西班牙Netquest小组实施的研究中(N=1476),我们调查了PC和智能手机中与A/D和IS问题相关的认知努力和反应质量。为此,我们采用了由设备类型和问题格式定义的拆分投票设计。我们的分析显示,无论设备类型和量表长度如何,IS问题的回答时间都比A/D问题长。此外,IS问题比A/D问题的回答质量更好。总之,调查结果表明,与a/D问题相比,对IS问题的回答更加认真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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