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Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation

Author

Listed:
  • Pavel Dietz
  • Anne Quermann
  • Mireille Nicoline Maria van Poppel
  • Heiko Striegel
  • Hannes Schröter
  • Rolf Ulrich
  • Perikles Simon

Abstract

Study objectives: In order to increase the value of randomized response techniques (RRTs) as tools for studying sensitive issues, the present study investigated whether the prevalence estimate for a sensitive item π^s assessed with the unrelated questionnaire method (UQM) is influenced by changing the probability of receiving the sensitive question p. Material and methods: A short paper-and-pencil questionnaire was distributed to 1.243 university students assessing the 12-month prevalence of physical and cognitive doping using two versions of the UQM with different probabilities for receiving the sensitive question (p ≈ 1/3 and p ≈ 2/3). Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p ≈ 1/3 and p ≈ 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p ≈ 1/3 or p ≈ 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. Results: The prevalence estimate for physical doping with p ≈ 1/3 was 22.5% (95% CI: 10.8–34.1), and 12.8% (95% CI: 7.6–18.0) with p ≈ 2/3. For cognitive doping with p ≈ 1/3, the estimated prevalence was 22.5% (95% CI: 11.0–34.1), whereas it was 18.0% (95% CI: 12.5–23.5) with p ≈ 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p ≈ 1/3 and p ≈ 2/3 (physical doping: χ2 = 2.25, df = 1, p = 0.13; cognitive doping: χ2 = 0.49, df = 1, p = 0.48). Bayes factors computed with the Savage-Dickey method favored the null (“the prevalence estimates are identical under p ≈ 1/3 and p ≈ 2/3”) over the alternative (“the prevalence estimates differ under p ≈ 1/3 and p ≈ 2/3”) hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). Conclusion: The present results suggest that prevalence estimates for physical and cognitive doping assessed by the UQM are largely unaffected by the probability for receiving the sensitive question p.

Suggested Citation

  • Pavel Dietz & Anne Quermann & Mireille Nicoline Maria van Poppel & Heiko Striegel & Hannes Schröter & Rolf Ulrich & Perikles Simon, 2018. "Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-12, May.
    • Handle: RePEc:plo:pone00:0197270
    DOI: 10.1371/journal.pone.0197270
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    References listed on IDEAS

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    1. Gerty Lensvelt-Mulders & Joop Hox & Peter Heijden, 2005. "How to Improve the Efficiency of Randomised Response Designs," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(3), pages 253-265, June.
    2. Isabel Thielmann & Daniel W. Heck & Benjamin E. Hilbig, 2016. "Anonymity and incentives: An investigation of techniques to reduce socially desirable responding in the Trust Game," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(5), pages 527-536, September.
    3. repec:cup:judgdm:v:11:y:2016:i:5:p:527-536 is not listed on IDEAS
    4. Jun-Wu Yu & Guo-Liang Tian & Man-Lai Tang, 2008. "Two new models for survey sampling with sensitive characteristic: design and analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(3), pages 251-263, April.
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