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Detecting and Deterring Insufficient Effort Responding to Surveys

Abstract

Purpose

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.

Design/Methodology/Approach

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

Findings

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.

Implications

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

Originality/value

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.

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Fig. 1

Notes

  1. The extra item on each page, named check item, represented a failed attempt to improve on the infrequency approach. Each check item instructed participants to select a particular response option, e.g., “Please select Moderately Inaccurate for this item”, and selecting any other response category would indicate IER. We excluded check items from this study because—inconsistent with the survey instruction, the manipulation check, and the other indices—the check item index flagged an unusually high rate of IER, even in the group of motivated respondents in Cell 1 of Study 1. We suspect some respondents may have viewed the check items as a measure of personality rather than an instruction set. Additional analysis also revealed significant trait influence on responses to the check items, after controlling for the other IER indices.

  2. When severe departure from homogeneity of variance occurred, ANOVA results were verified using pairwise unequal variance t-tests. For all repeated ANOVA, the Greenhouse–Geisser adjusted p value was reported when Mauchly’s W test for sphericity was significant.

  3. We explored the correlation between (a) the extent to which each of the 30 scales contained unequal numbers of positively and negatively worded items (i.e., |N positive − N negative|) and (b) the increase in Cronbach’s alpha on each scale after removal of suspect IER using the 99% specificity long string index. The result of r = −.33, p = .07, N = 30 suggests, albeit inconclusively, that IER in the form of long string responding had a stronger impact on scales with equal rather than unbalanced number of positively and negatively worded items.

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Acknowledgments

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.

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Correspondence to Jason L. Huang.

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Huang, J.L., Curran, P.G., Keeney, J. et al. Detecting and Deterring Insufficient Effort Responding to Surveys. J Bus Psychol 27, 99–114 (2012). https://doi.org/10.1007/s10869-011-9231-8

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  • DOI: https://doi.org/10.1007/s10869-011-9231-8

Keywords

  • Careless responding
  • Random responding
  • Inconsistent responding
  • Online surveys
  • Data screening