Leading Strategies to Identify and Prevent Careless Responding During Online Surveys

Abstract

Online surveys enjoy widespread use, but data collected via online surveys are often warped by careless responding (CR) or insufficient effort responding. This occurs when survey respondents give inadequate attention to survey items (Huang, Curran, Keeney, Poposki, & DeShon, 2012; Meade & Craig, 2012). CR manifests in a variety of survey behaviors that introduce error and can lead to a range of psychometric problems, including: inaccurate correlations and alpha estimates (Bowling et al., 2016; Curran & Kotrba, 2012), distorted factor analysis (Huang et al., 2012; Woods, 2006), spurious results (Huang, Liu, & Bowling, 2012), and bias (Ward, Meade, Allred, Pappalardo, & Stoughton, 2017). These issues can be avoided by preventing CR. Unfortunately, prevention strategies in the CR literature have had limited success and need further exploration and development (Ward & Pond, 2015; Ward & Meade, 2018). The four papers in this symposium showcase cutting-edge approaches to CR identification and prevention. In Search of Best Practices for Identification and Removal of Careless Responders Presenter: Richard Yentes; FMP Consulting Presenter: Adam W Meade; North Carolina State U. Raiders of the Lost Data: Wrangling Missing Data Designs and Careless Responding Presenter: Natalie Vanelli; Clemson U. Presenter: Cynthia L. S. Pury; Clemson U. Presenter: Stephen Robertson; Human Resources Research Organization Applying the Theory of Planned Behavior to Explain Careless Responding Presenter: Alyssa Marshall; Colorado State U. Presenter: Kurt Kraiger; U. of Memphis Presenter: James J. Kunz; Colorado State U. Harnessing Work Design to Prevent Careless Responding and Improve Participant Engagement Presenter: M.K. Ward; Curtin U. Presenter: Jia-Xin Tay; Centre for Transformative Work Design / Curtin U.