{"title":"Nonparticipation Bias in Accelerometer-Based Studies and the Use of Propensity Scores","authors":"Christopher Antoun, Alexander Wenz","doi":"10.1177/08944393241254463","DOIUrl":null,"url":null,"abstract":"Relatively little attention has been paid to the effects of nonparticipation on data quality in population-based studies that use accelerometers to measure physical activity. We examine these issues using data from the 2013 Longitudinal Internet Studies for the Social Sciences (LISS) panel and 2013–2014 National Health and Nutrition Examination Survey (NHANES) accelerometer studies, both of which collected survey data in advance and therefore permit comparisons of self-reported physical activity between participants and nonparticipants to the accelerometer studies. While individuals with high levels of self-reported physical activity are overrepresented in the participant samples, the differences are modest in both studies. However, in the LISS panel this difference led to overestimates of physical activity that are not fully corrected by propensity score weighting adjustments (i.e., non-ignorable selection bias). This finding underscores the importance of assessing the potential influence of nonparticipation on accelerometer-derived estimates of physical activity.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Science Computer Review","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/08944393241254463","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Relatively little attention has been paid to the effects of nonparticipation on data quality in population-based studies that use accelerometers to measure physical activity. We examine these issues using data from the 2013 Longitudinal Internet Studies for the Social Sciences (LISS) panel and 2013–2014 National Health and Nutrition Examination Survey (NHANES) accelerometer studies, both of which collected survey data in advance and therefore permit comparisons of self-reported physical activity between participants and nonparticipants to the accelerometer studies. While individuals with high levels of self-reported physical activity are overrepresented in the participant samples, the differences are modest in both studies. However, in the LISS panel this difference led to overestimates of physical activity that are not fully corrected by propensity score weighting adjustments (i.e., non-ignorable selection bias). This finding underscores the importance of assessing the potential influence of nonparticipation on accelerometer-derived estimates of physical activity.
期刊介绍:
Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.