The Impact of Attentiveness Interventions on Survey Data.
Social and behavioral science researchers who use survey data are vigilant about data quality, with an increasing emphasis on avoiding common method variance (CMV) and insufficient effort responding (IER). Each of these errors can inflate and deflate substantive relationships, and there are both a p...
| Publicado en: | Educational & Psychological Measurement Vol. 85; no. 4; pp. 696 - 728 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
| Publicado: |
Sage Publications Inc.
Aug2025
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=186128849&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 186128849 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00131644 EPM jtl: Educational & Psychological Measurement issn: 00131644 maglogo: Y pubinfo: dt: Aug2025 vid: 85 iid: 4 pid: 344 pub: Sage Publications Inc. artinfo: ui: 186128849 10.1177/00131644241311851 ppf: 696 ppct: 32 formats: tig: atl: The Impact of Attentiveness Interventions on Survey Data. aug: au: Fuller, Christie M. Simmering, Marcia J. Waterwall, Brian Ragland, Elizabeth Twitchell, Douglas P. Wall, Alison affil: Boise State University, ID, USA Louisiana Tech University, Ruston, LA, USA East Carolina University, Greenville, NC, USA Crest Operations, LLC, Pineville, LA, USA University of Louisiana Monroe, LA, USA Southern Connecticut State University, New Haven, CT, USA su: United States Self-evaluation Social media Universities & colleges Attention Motivation (Psychology) Communication College students Databases Scale analysis (Psychology) Probability theory Descriptive statistics Chi-squared test Surveys Research One-way analysis of variance Content mining Mice (Computers) Confidence intervals Factor analysis Data analysis software Data quality Body movement sug: subj: Self-evaluation Social media Universities & colleges Attention Motivation (Psychology) Communication College students United States Computer and peripheral equipment manufacturing Computer Terminal and Other Computer Peripheral Equipment Manufacturing Colleges, Universities, and Professional Schools Databases Scale analysis (Psychology) Probability theory Descriptive statistics Chi-squared test Surveys Research One-way analysis of variance Content mining Mice (Computers) Confidence intervals Factor analysis Data analysis software Data quality Body movement keyword: common method variance factual manipulation check insufficient effort responses survey data common method variance factual manipulation check insufficient effort responses survey data ab: Social and behavioral science researchers who use survey data are vigilant about data quality, with an increasing emphasis on avoiding common method variance (CMV) and insufficient effort responding (IER). Each of these errors can inflate and deflate substantive relationships, and there are both a priori and post hoc means to address them. Yet, little research has investigated how both IER and CMV are affected with the use of these different procedural or statistical techniques used to address them. More specifically, if interventions to reduce IER are used, does this affect CMV in data? In an experiment conducted both in and out of the laboratory, we investigate the impact of attentiveness interventions, such as a Factual Manipulation Check (FMC) on both IER and CMV in same-source survey data. In addition to typical IER measures, we also track whether respondents play the instructional video and their mouse movement. The results show that while interventions have some impact on the level of participant attentiveness, these interventions do not appear to lead to differing levels of CMV. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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