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RESEARCH PRODUCT
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.
Rolf UlrichAnne QuermannAnne QuermannPerikles SimonPavel DietzPavel DietzMireille Nicoline Maria Van PoppelHeiko StriegelHannes Schrötersubject
MaleQuestionnairesPeptide Hormoneslcsh:MedicineSocial SciencesBiochemistryMathematical and Statistical Techniques0504 sociologySociologySurveys and QuestionnairesStatisticsPrevalenceMedicine and Health SciencesHuman Performanceddc:796lcsh:ScienceMathematicsDoping in SportsMultidisciplinarySocial ResearchOrganic Compounds05 social sciencesDrugsCognitionMiddle AgedChemistryAthletic & outdoor sports & gamesNeurologyResearch DesignBehavioral PharmacologyPhysical SciencesFemaleSteroidsResearch ArticleAdultAdolescentUniversitiesSubstance-Related DisordersStreet drugsBayesian MethodResearch and Analysis Methods050105 experimental psychologyYoung AdultNeuropharmacologySensitive questionRecreational Drug UseHumans0501 psychology and cognitive sciencesStudentsErythropoietinPharmacologyPsychotropic DrugsBehaviorModels StatisticalSurvey ResearchIllicit Drugslcsh:RAmphetaminesOrganic ChemistryChemical CompoundsCorrection050401 social sciences methodsBiology and Life SciencesHormonesSample size determinationlcsh:Qdescription
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 π̂$_{s}$ 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.
year | journal | country | edition | language |
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2018-01-01 | PLoS ONE |