The choice of response alternatives in COVID-19 social science surveys

Author:

Wright Daniel B.,Wolff Sarah M.,Jaspal Rusi,Barnett Julie,Breakwell Glynis M.

Abstract

Social science research is key for understanding and for predicting compliance with COVID-19 guidelines, and this research relies on survey data. While much focus is on the survey question stems, less is on the response alternatives presented that both constrain responses and convey information about the assumed expectations of the survey designers. The focus here is on the choice of response alternatives for the types of behavioral frequency questions used in many COVID-19 and other health surveys. We examine issues with two types of response alternatives. The first are vague quantifiers, like “rarely” and “frequently.” Using data from 30 countries from the Imperial COVID data hub, we show that the interpretation of these vague quantifiers (and their translations) depends on the norms in that country. If the mean amount of hand washing in a country is high, it is likely “frequently” corresponds to a higher numeric value for hand washing than if the mean in the country is low. The second type are sets of numeric alternatives and they can also be problematic. Using a US survey, respondents were randomly allocated to receive either response alternatives where most of the scale corresponds to low frequencies or where most of the scale corresponds to high frequencies. Those given the low frequency set provided lower estimates of the health behaviors. The choice of response alternatives for behavioral frequency questions can affect the estimates of health behaviors. How the response alternatives mold the responses should be taken into account for epidemiological modeling. We conclude with some recommendations for response alternatives for behavioral frequency questions in surveys.

Funder

British Academy award

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3