Sunghee Lee1, Fernanda Alvarado-Leiton2, Wenshan Yu1, Rachel Davis3, Timothy P Johnson4. 1. Institute for Social Research, University of Michigan, 426 Thompson St, Ann Arbor, MI, 48104, USA. 2. Institute for Social Research, University of Michigan, 426 Thompson St, Ann Arbor, MI, 48104, USA. Electronic address: mleiton@umich.edu. 3. Department of Health Promotion, Education, and Behavior, University of South Carolina, 915 Greene St, Columbia, 29208, USA. 4. Department of Public Administration, University of Illinois-Chicago, 412 S Peoria St, Chicago, IL, 60607, USA.
Abstract
BACKGROUND: Acquiescent response style (ARS) refers to survey respondents' tendency to choose response categories agreeing to questions regardless of their content and is hypothesized as a stable respondent trait. While what underlies acquiescence is debatable, the effect of ARS on measurement is clear: bias through artificially increased agreement ratings. With certain population subgroups (e.g., racial/ethnic minorities in the U.S.) are associated with systemically higher ARS, it causes concerns for research involving those groups. For this reason, it may be necessary to classify respondents as acquiescers or a nonacquiescers, which allows independent analysis or accounting for this stylistic artifact. However, this classification is challenging, because ARS is latent, observed only as a by-product of collected data. OBJECTIVES: To propose a screener that identifies respondents as acquiescers. METHODS: With survey data collected for ARS research, various ARS classification methods were compared for validity as well as implementation practicality. RESULTS: The majority of respondents was classified consistently into acquiescers or nonacquiescers under various classification methods. CONCLUSIONS: We propose a method based on illogical responses given to two balanced, theoretically distant multi-item measurement scales as a screener.
BACKGROUND: Acquiescent response style (ARS) refers to survey respondents' tendency to choose response categories agreeing to questions regardless of their content and is hypothesized as a stable respondent trait. While what underlies acquiescence is debatable, the effect of ARS on measurement is clear: bias through artificially increased agreement ratings. With certain population subgroups (e.g., racial/ethnic minorities in the U.S.) are associated with systemically higher ARS, it causes concerns for research involving those groups. For this reason, it may be necessary to classify respondents as acquiescers or a nonacquiescers, which allows independent analysis or accounting for this stylistic artifact. However, this classification is challenging, because ARS is latent, observed only as a by-product of collected data. OBJECTIVES: To propose a screener that identifies respondents as acquiescers. METHODS: With survey data collected for ARS research, various ARS classification methods were compared for validity as well as implementation practicality. RESULTS: The majority of respondents was classified consistently into acquiescers or nonacquiescers under various classification methods. CONCLUSIONS: We propose a method based on illogical responses given to two balanced, theoretically distant multi-item measurement scales as a screener.