Physical and cognitive doping in university students using the unrelated question model
Study objectives 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 [almost equal to] 1/3 and p [almo...
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| Veröffentlicht in: | PloS one 2018-05, Vol.13 (5), p.e0197270 |
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| creator | Dietz, Pavel Quermann, Anne van Poppel, Mireille Nicoline Maria Striegel, Heiko Schröter, Hannes Ulrich, Rolf Simon, Perikles |
| description | Study objectives 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 [almost equal to] 1/3 and p [almost equal to] 2/3). Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p [almost equal to] 1/3 and p [almost equal to] 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p [almost equal to] 1/3 or p [almost equal to] 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. The prevalence estimate for physical doping with p [almost equal to] 1/3 was 22.5% (95% CI: 10.8-34.1), and 12.8% (95% CI: 7.6-18.0) with p [almost equal to] 2/3. For cognitive doping with p [almost equal to] 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 [almost equal to] 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p [almost equal to] 1/3 and p [almost equal to] 2/3 (physical doping: X.sup.2 = 2.25, df = 1, p = 0.13; cognitive doping: X.sup.2 = 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 [almost equal to] 1/3 and p [almost equal to] 2/3") over the alternative ("the prevalence estimates differ under p [almost equal to] 1/3 and p [almost equal to] 2/3") hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). 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. |
| doi_str_mv | 10.1371/journal.pone.0197270 |
| format | Article |
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Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p [almost equal to] 1/3 and p [almost equal to] 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p [almost equal to] 1/3 or p [almost equal to] 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. The prevalence estimate for physical doping with p [almost equal to] 1/3 was 22.5% (95% CI: 10.8-34.1), and 12.8% (95% CI: 7.6-18.0) with p [almost equal to] 2/3. For cognitive doping with p [almost equal to] 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 [almost equal to] 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p [almost equal to] 1/3 and p [almost equal to] 2/3 (physical doping: X.sup.2 = 2.25, df = 1, p = 0.13; cognitive doping: X.sup.2 = 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 [almost equal to] 1/3 and p [almost equal to] 2/3") over the alternative ("the prevalence estimates differ under p [almost equal to] 1/3 and p [almost equal to] 2/3") hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). 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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0197270</identifier><language>eng</language><publisher>Public Library of Science</publisher><subject>Analysis ; College students ; Management ; Physical fitness ; Surveys ; Universities and colleges</subject><ispartof>PloS one, 2018-05, Vol.13 (5), p.e0197270</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27901,27902</link.rule.ids></links><search><creatorcontrib>Dietz, Pavel</creatorcontrib><creatorcontrib>Quermann, Anne</creatorcontrib><creatorcontrib>van Poppel, Mireille Nicoline Maria</creatorcontrib><creatorcontrib>Striegel, Heiko</creatorcontrib><creatorcontrib>Schröter, Hannes</creatorcontrib><creatorcontrib>Ulrich, Rolf</creatorcontrib><creatorcontrib>Simon, Perikles</creatorcontrib><title>Physical and cognitive doping in university students using the unrelated question model</title><title>PloS one</title><description>Study objectives 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 [almost equal to] 1/3 and p [almost equal to] 2/3). Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p [almost equal to] 1/3 and p [almost equal to] 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p [almost equal to] 1/3 or p [almost equal to] 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. The prevalence estimate for physical doping with p [almost equal to] 1/3 was 22.5% (95% CI: 10.8-34.1), and 12.8% (95% CI: 7.6-18.0) with p [almost equal to] 2/3. For cognitive doping with p [almost equal to] 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 [almost equal to] 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p [almost equal to] 1/3 and p [almost equal to] 2/3 (physical doping: X.sup.2 = 2.25, df = 1, p = 0.13; cognitive doping: X.sup.2 = 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 [almost equal to] 1/3 and p [almost equal to] 2/3") over the alternative ("the prevalence estimates differ under p [almost equal to] 1/3 and p [almost equal to] 2/3") hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). 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.</description><subject>Analysis</subject><subject>College students</subject><subject>Management</subject><subject>Physical fitness</subject><subject>Surveys</subject><subject>Universities and colleges</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFj01LAzEYhIMoWKv_wENOgoddk81-JMdS_CgUKlr0WF43b3dTYlKbROy_t0UP9eRpZpiHgSHkkrOci4bfrHzaOLD52jvMGVdN0bAjMuBKFFldMHF84E_JWQgrxioh63pAXh_7bTAtWApO09Z3zkTziVT7tXEdNY4mt8ubYOKWhpg0uhhoCvsy9rhrN2ghoqYfCUM03tF3r9Gek5Ml2IAXvzok87vb-fghm87uJ-PRNOuUKjPNJCyRC5Cs0Ry0UBWvK8a4xKpSIMsScMlYCwKZFlKhEgKlLosGdS3ftBiS65_ZDiwujGu9i_gVO0ghLCbPT4vR7qdkpRDlP-zs5S97dcD2CDb2wdu0PxgOwW9UF3P1</recordid><startdate>20180515</startdate><enddate>20180515</enddate><creator>Dietz, Pavel</creator><creator>Quermann, Anne</creator><creator>van Poppel, Mireille Nicoline Maria</creator><creator>Striegel, Heiko</creator><creator>Schröter, Hannes</creator><creator>Ulrich, Rolf</creator><creator>Simon, Perikles</creator><general>Public Library of Science</general><scope>IOV</scope><scope>ISR</scope></search><sort><creationdate>20180515</creationdate><title>Physical and cognitive doping in university students using the unrelated question model</title><author>Dietz, Pavel ; Quermann, Anne ; van Poppel, Mireille Nicoline Maria ; Striegel, Heiko ; Schröter, Hannes ; Ulrich, Rolf ; Simon, Perikles</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g994-d08afe13a807d1ad3951650018e559a844aef00ca3e0d389e933e8d427ed68bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Analysis</topic><topic>College students</topic><topic>Management</topic><topic>Physical fitness</topic><topic>Surveys</topic><topic>Universities and colleges</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dietz, Pavel</creatorcontrib><creatorcontrib>Quermann, Anne</creatorcontrib><creatorcontrib>van Poppel, Mireille Nicoline Maria</creatorcontrib><creatorcontrib>Striegel, Heiko</creatorcontrib><creatorcontrib>Schröter, Hannes</creatorcontrib><creatorcontrib>Ulrich, Rolf</creatorcontrib><creatorcontrib>Simon, Perikles</creatorcontrib><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dietz, Pavel</au><au>Quermann, Anne</au><au>van Poppel, Mireille Nicoline Maria</au><au>Striegel, Heiko</au><au>Schröter, Hannes</au><au>Ulrich, Rolf</au><au>Simon, Perikles</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Physical and cognitive doping in university students using the unrelated question model</atitle><jtitle>PloS one</jtitle><date>2018-05-15</date><risdate>2018</risdate><volume>13</volume><issue>5</issue><spage>e0197270</spage><pages>e0197270-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Study objectives 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 [almost equal to] 1/3 and p [almost equal to] 2/3). Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p [almost equal to] 1/3 and p [almost equal to] 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p [almost equal to] 1/3 or p [almost equal to] 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. The prevalence estimate for physical doping with p [almost equal to] 1/3 was 22.5% (95% CI: 10.8-34.1), and 12.8% (95% CI: 7.6-18.0) with p [almost equal to] 2/3. For cognitive doping with p [almost equal to] 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 [almost equal to] 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p [almost equal to] 1/3 and p [almost equal to] 2/3 (physical doping: X.sup.2 = 2.25, df = 1, p = 0.13; cognitive doping: X.sup.2 = 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 [almost equal to] 1/3 and p [almost equal to] 2/3") over the alternative ("the prevalence estimates differ under p [almost equal to] 1/3 and p [almost equal to] 2/3") hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). 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.</abstract><pub>Public Library of Science</pub><doi>10.1371/journal.pone.0197270</doi><tpages>e0197270</tpages></addata></record> |
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| source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Analysis College students Management Physical fitness Surveys Universities and colleges |
| title | Physical and cognitive doping in university students using the unrelated question model |
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