Journal of Business and Psychology

, Volume 27, Issue 1, pp 99–114 | Cite as

Detecting and Deterring Insufficient Effort Responding to Surveys

  • Jason L. Huang
  • Paul G. Curran
  • Jessica Keeney
  • Elizabeth M. Poposki
  • Richard P. DeShon



Responses provided by unmotivated survey participants in a careless, haphazard, or random fashion can threaten the quality of data in psychological and organizational research. The purpose of this study was to summarize existing approaches to detect insufficient effort responding (IER) to low-stakes surveys and to comprehensively evaluate these approaches.


In an experiment (Study 1) and a nonexperimental survey (Study 2), 725 undergraduates responded to a personality survey online.


Study 1 examined the presentation of warnings to respondents as a means of deterrence and showed the relative effectiveness of four indices for detecting IE responses: response time, long string, psychometric antonyms, and individual reliability coefficients. Study 2 demonstrated that the detection indices measured the same underlying construct and showed the improvement of psychometric properties (item interrelatedness, facet dimensionality, and factor structure) after removing IE respondents identified by each index. Three approaches (response time, psychometric antonyms, and individual reliability) with high specificity and moderate sensitivity were recommended as candidates for future application in survey research.


The identification of effective IER indices may help researchers ensure the quality of their low-stake survey data.


This study is a first attempt to comprehensively evaluate IER detection methods using both experimental and nonexperimental designs. Results from both studies corroborated each other in suggesting the three more effective approaches. This study also provided convergent validity evidence regarding various indices for IER.


Careless responding Random responding Inconsistent responding Online surveys Data screening 



We thank Goran Kuljanin for collecting data for the two studies. We are grateful for the constructive comments from Neal Schmitt and Ann Marie Ryan on an earlier draft of this article.


  1. Archer, R. P., & Elkins, D. E. (1999). Identification of random responding on the MMPI-A. Journal of Personality Assessment, 73, 407–421.PubMedCrossRefGoogle Scholar
  2. Archer, R. P., Fontaine, J., & McCrae, R. R. (1998). Effects of two MMPI-2 validity scales on basic scale relations to external criteria. Journal of Personality Assessment, 70, 87–102.PubMedCrossRefGoogle Scholar
  3. Babbie, E. (2001). The practice of social research (9th ed.). Belmont, CA: Wadsworth.Google Scholar
  4. Baer, R. A., Ballenger, J., Berry, D. T. R., & Wetter, M. W. (1997). Detection of random responding on the MMPI-A. Journal of Personality Assessment, 68, 139–151.PubMedCrossRefGoogle Scholar
  5. Baer, R. A., Kroll, L. S., Rinaldo, J., & Ballenger, J. (1999). Detecting and discriminating between random responding and overreporting on the MMPI-A. Journal of Personality Assessment, 72, 308–320.CrossRefGoogle Scholar
  6. Bagby, R. M., Gillis, J. R., & Rogers, R. (1991). Effectiveness of the Millon Clinical Multiaxial Inventory Validity Index in the detection of random responding. Psychological Assessment, 3, 285–287.CrossRefGoogle Scholar
  7. Barton, M. B., Harris, R., & Fletcher, S. W. (1999). Does this patient have breast cancer? The screening clinical breast examination: should it be done? How? JAMA, 282, 1270–1280.PubMedCrossRefGoogle Scholar
  8. Beach, D. A. (1989). Identifying the random responder. Journal of Psychology: Interdisciplinary and Applied, 123, 101–103.Google Scholar
  9. Behrend, T. S., Sharek, D. J., Meade, A. W., & Wiebe, E. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods. doi:10.3758/s13428-011-0081-0
  10. Berry, D. T. R., Baer, R. A., & Harris, M. J. (1991). Detection of malingering on the MMPI: a meta-analysis. Clinical Psychology Review, 11, 585–598.CrossRefGoogle Scholar
  11. Berry, D. T. R., Wetter, M. W., Baer, R. A., Larsen, L., Clark, C., & Monroe, K. (1992). MMPI-2 random responding indices: validation using a self-report methodology. Psychological Assessment, 4, 340–345.CrossRefGoogle Scholar
  12. Bruehl, S., Lofland, K. R., Sherman, J. J., & Carlson, C. R. (1998). The Variable Responding Scale for detection of random responding on the Multidimensional Pain Inventory. Psychological Assessment, 10, 3–9.CrossRefGoogle Scholar
  13. Buechley, R., & Ball, H. (1952). A new test of “validity” for the group MMPI. Journal of Consulting Psychology, 16, 299–301.PubMedCrossRefGoogle Scholar
  14. Butcher, J. N., Dahlstrom, W. G., Graham, J. R., Tellegen, A., & Kaemmer, B. (1989). Minnesota Multiphasic Personality Inventory-2 (MMPI-2): manual for administration and scoring. Minneapolis: University of Minnesota Press.Google Scholar
  15. Butcher, J. N., Williams, C. L., Graham, J. R., Archer, R. P., Tellegen, A., Ben-Porath, Y. S., et al. (1992). MMPI–A: Minnesota Multiphasic Personality Inventory–Adolescent: manual for administration, scoring, and interpretation. Minneapolis: University of Minnesota Press.Google Scholar
  16. Charter, R. A. (1994). Determining random responding for the Category, Speech-Sounds Perception, and Seashore Rhythm tests. Journal of Clinical and Experimental Neuropsychology, 16, 744–748.PubMedCrossRefGoogle Scholar
  17. Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78, 98–104.CrossRefGoogle Scholar
  18. Costa, P. T., Jr., & McCrae, R. R. (1992). NEO PI-R professional manual. Odessa, FL: Psychological Assessment Resources.Google Scholar
  19. Costa, P. T., Jr., & McCrae, R. R. (1997). Stability and change in personality assessment: The Revised NEO Personality Inventory in the Year 2000. Journal of Personality Assessment, 68, 86–94.PubMedCrossRefGoogle Scholar
  20. Costa, P. T., Jr., & McCrae, R. R. (2008). The Revised NEO Personality Inventory (NEO-PI-R). In G. J. Boyle, G. Matthews, & D. H. Saklofske (Eds.), The Sage handbook of personality theory and assessment: personality measurement and testing (pp. 179–198). London: Sage.Google Scholar
  21. Curran, P. G., Kotrba, L., & Denison, D. (2010, April). Careless responding in surveys: applying traditional techniques to organizational settings. Paper presented at the 25th annual conference of Society for Industrial and Organizational Psychology, Atlanta, GA.Google Scholar
  22. DiLalla, D. L., & Dollinger, S. J. (2006). Cleaning up data and running preliminary analyses. In F. T. L. Leong & J. T. Austin (Eds.), The psychology research handbook: a guide for graduate students and research assistants (2nd ed., pp. 241–253). Thousand Oaks, CA: Sage.Google Scholar
  23. Dwight, S. A., & Donovan, J. J. (2003). Do warnings not to fake reduce faking? Human Performance, 16, 1–23.CrossRefGoogle Scholar
  24. Evans, R. G., & Dinning, W. D. (1983). Response consistency among high F scale scorers on the MMPI. Journal of Clinical Psychology, 39, 246–248.PubMedCrossRefGoogle Scholar
  25. Gleason, J. M., & Barnum, D. T. (1991). Predictive probabilities in employee drug-testing. Risk, 2, 3–18.Google Scholar
  26. Goldberg, L. R. (1999). A broad-bandwidth, public-domain, personality inventory measuring the lower-level facets of several five-factor models. In I. Mervielde, I. Deary, F. D. Fruyt, & F. Ostendorf (Eds.), Personality psychology in Europe (Vol. 7, pp. 7–28). Tilburg, The Netherlands: Tilburg University Press.Google Scholar
  27. Goldberg, L. R., & Kilkowski, J. M. (1985). The prediction of semantic consistency in self-descriptions: characteristics of persons and of terms that affect the consistency of responses to synonym and antonym pairs. Journal of Personality and Social Psychology, 48, 82–98.PubMedCrossRefGoogle Scholar
  28. Green, S. B., & Stutzman, T. M. (1986). An evaluation of methods to select respondents to structured job-analysis questionnaires. Personnel Psychology, 39, 543–564.CrossRefGoogle Scholar
  29. Greene, R. L. (1978). An empirically derived MMPI Carelessness Scale. Journal of Clinical Psychology, 34, 407–410.CrossRefGoogle Scholar
  30. Haertzen, C. A., & Hill, H. E. (1963). Assessing subjective effects of drugs: an index of carelessness and confusion for use with the Addiction Research Center Inventory (ARCI). Journal of Clinical Psychology, 19, 407–412.PubMedCrossRefGoogle Scholar
  31. Hartwig, F., & Dearing, B. E. (1979). Exploratory data analysis. Thousand Oaks, CA: Sage.Google Scholar
  32. Hough, L. M., Eaton, N. K., Dunnette, M. D., Kamp, J. D., & McCloy, R. A. (1990). Criterion-related validities of personality constructs and the effect of response distortion on those validities. Journal of Applied Psychology, 75, 581–595.CrossRefGoogle Scholar
  33. Hsu, L. M. (2002). Diagnostic validity statistics and the MCMI-III. Psychological Assessment, 14, 410–422.PubMedCrossRefGoogle Scholar
  34. Jackson, D. N. (1976). The appraisal of personal reliability. Paper presented at the meetings of the Society of Multivariate Experimental Psychology, University Park, PA.Google Scholar
  35. Johnson, J. A. (2005). Ascertaining the validity of individual protocols from Web-based personality inventories. Journal of Research in Personality, 39, 103–129.CrossRefGoogle Scholar
  36. Kline, R. B. (2009). Becoming a behavioral science researcher: a guide to producing research that matters. New York: Guilford.Google Scholar
  37. Kurtz, J. E., & Parrish, C. L. (2001). Semantic response consistency and protocol validity in structured personality assessment: the case of the NEO-PI-R. Journal of Personality Assessment, 76, 315–332.PubMedCrossRefGoogle Scholar
  38. Lucas, R. E., & Baird, B. M. (2005). Global self-assessment. In M. Eid & E. Diener (Eds.), Handbook of multimethod measurement in psychology (pp. 29–42). Washington, DC: American Psychological Association.Google Scholar
  39. Marsh, H. W. (1987). The Self-Description Questionnaire 1: manual and research monograph. San Antonio, TX: Psychological Corporation.Google Scholar
  40. Martin, S. L., & Terris, W. (1990). The four-cell classification table in personnel selection: a heuristic device gone awry. The Industrial-Organizational Psychologist, 47(3), 49–55.Google Scholar
  41. McGrath, R. E., Mitchell, M., Kim, B. H., & Hough, L. (2010). Evidence for response bias as a source of error variance in applied assessment. Psychological Bulletin, 136, 450–470.PubMedCrossRefGoogle Scholar
  42. Meade, A. W., & Craig, S. B. (2011, April). Identifying careless responses in survey data. Paper presented at the 26th annual conference of the Society for Industrial and Organizational Psychology, Chicago, IL.Google Scholar
  43. Morey, L. C., & Hopwood, C. J. (2004). Efficiency of a strategy for detecting back random responding on the personality assessment inventory. Psychological Assessment, 16, 197–200.PubMedCrossRefGoogle Scholar
  44. Morgeson, F. P., & Campion, M. A. (1997). Social and cognitive sources of potential inaccuracy in job analysis. Journal of Applied Psychology, 82, 627–655.CrossRefGoogle Scholar
  45. Nichols, D. S., Greene, R. L., & Schmolck, P. (1989). Criteria for assessing inconsistent patterns of item endorsement on the MMPI: rationale, development, and empirical trials. Journal of Clinical Psychology, 45, 239–250.PubMedCrossRefGoogle Scholar
  46. O’Rourke, T. (2000). Techniques for screening and cleaning data for analysis. American Journal of Health Studies, 16, 205–207.Google Scholar
  47. Piedmont, R. L., McCrae, R. R., Riemann, R., & Angleitner, A. (2000). On the invalidity of validity scales: evidence from self-reports and observer ratings in volunteer samples. Journal of Personality and Social Psychology, 78, 582–593.PubMedCrossRefGoogle Scholar
  48. Pinsoneault, T. B. (1998). A Variable Response Inconsistency Scale and a True Response Inconsistency Scale for the Jesness Inventory. Psychological Assessment, 10, 21–32.CrossRefGoogle Scholar
  49. Pinsoneault, T. B. (2007). Detecting random, partially random, and nonrandom Minnesota Multiphasic Personality Inventory-2 protocols. Psychological Assessment, 19, 159–164.PubMedCrossRefGoogle Scholar
  50. Rosse, J. G., Levin, R. A., & Nowicki, M. D. (1999, April). Assessing the impact of faking on job performance and counter-productive behaviors. Paper presented at the 14th annual meeting of the Society for Industrial and Organizational Psychology, Atlanta.Google Scholar
  51. Schinka, J. A., Kinder, B. N., & Kremer, T. (1997). Research validity scales for the NEO-PI-R: development and initial validation. Journal of Personality Assessment, 68, 127–138.PubMedCrossRefGoogle Scholar
  52. Schmit, M. J., & Ryan, A. M. (1993). The Big Five in personnel selection: factor structure in applicant and nonapplicant populations. Journal of Applied Psychology, 78, 966–974.CrossRefGoogle Scholar
  53. Schmitt, N., & Stults, D. M. (1985). Factors defined by negatively keyed items: the result of careless respondents? Applied Psychological Measurement, 9, 367–373.CrossRefGoogle Scholar
  54. Seo, M. G., & Barrett, L. F. (2007). Being emotional during decision making–good or bad? An empirical investigation. Academy of Management Journal, 50, 923–940.PubMedCrossRefGoogle Scholar
  55. Smith, P. C., Budzeika, K. A., Edwards, N. A., Johnson, S. M., & Bearse, L. N. (1986). Guidelines for clean data: detection of common mistakes. Journal of Applied Psychology, 71, 457–460.CrossRefGoogle Scholar
  56. Stevens, J. P. (1984). Outliers and influential data points in regression analysis. Psychological Bulletin, 95, 334–344.CrossRefGoogle Scholar
  57. Streiner, D. L. (2003). Diagnosing tests: using and misusing diagnostic and screening tests. Journal of Personality Assessment, 81, 209–219.PubMedCrossRefGoogle Scholar
  58. Swets, J. A. (1992). The science of choosing the right decision threshold in high-stakes diagnostics. American Psychologist, 47, 522–532.PubMedCrossRefGoogle Scholar
  59. Thompson, A. H. (1975). Random responding and the questionnaire measurement of psychoticism. Social Behavior and Personality, 3, 111–115.CrossRefGoogle Scholar
  60. Tukey, J. W. (1977). Exploratory data analysis. Reading, MA: Addison-Wesley.Google Scholar
  61. van Ginkel, J. R., & van der Ark, L. A. (2005). SPSS syntax for missing value imputation in test and questionnaire data. Applied Psychological Measurement, 29, 152–153.CrossRefGoogle Scholar
  62. Wetter, M. W., Baer, R. A., Berry, D. T. R., Smith, G. T., & Larsen, L. H. (1992). Sensitivity of MMPI-2 validity scales to random responding and malingering. Psychological Assessment, 4, 369–374.CrossRefGoogle Scholar
  63. Wilkinson, L., & The Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: guidelines and explanations. American Psychologist, 54, 594–604.CrossRefGoogle Scholar
  64. Wilson, M. A., Harvey, R. J., & Macy, B. A. (1990). Repeating items to estimate the test-retest reliability of task inventory ratings. Journal of Applied Psychology, 75, 158–163.CrossRefGoogle Scholar
  65. Wise, S. L., & DeMars, C. E. (2006). An application of item response time: the effort-moderated IRT model. Journal of Educational Measurement, 43, 19–38.CrossRefGoogle Scholar
  66. Wise, S. L., & Kong, X. (2005). Response time effort: a new measure of examinee motivation in computer-based tests. Applied Measurement in Education, 18, 163–183.CrossRefGoogle Scholar
  67. Woods, C. M. (2006). Careless responding to reverse-worded items: implications for confirmatory factor analysis. Journal of Psychopathology and Behavioral Assessment, 28, 189–194.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Jason L. Huang
    • 1
  • Paul G. Curran
    • 2
  • Jessica Keeney
    • 2
  • Elizabeth M. Poposki
    • 3
  • Richard P. DeShon
    • 2
  1. 1.Department of PsychologyWayne State UniversityDetroitUSA
  2. 2.Department of PsychologyMichigan State UniversityEast LansingUSA
  3. 3.Department of PsychologyIndiana University-Purdue University IndianapolisIndianapolisUSA

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