ABSTRACT
We propose a novel method to analyze time-constrained yes/no questions about a target behavior (e.g., "Did you take sleeping pills during the last 12 months?"). A drawback of these questions is that the relative frequency of answering these questions with "yes" does not allow one to draw definite conclusions about the frequency of the target behavior (i.e., how often sleeping pills were taken) nor about the prevalence of trait carriers (i.e., percentage of people that take sleeping pills). Here we show how this information can be extracted from the results of such questions employing a prevalence curve and a Poisson model. The applicability of the method was evaluated with a survey on everyday behavior, which revealed plausible results and reasonable model fit. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
ABSTRACT
Background: Pharmacological neuroenhancement (PN) is defined as the use of illicit or prescription drugs by healthy individuals for cognitive-enhancing purposes. The present study aimed (i) to investigate whether including caffeine tablets in the definition of PN within a questionnaire increases the PN prevalence estimate (framing effect), (ii) to investigate whether the health-related risk attitude is increased in students who use PN. Materials and methods: Two versions of a paper-and-pencil questionnaire (first version included caffeine tablets in the definition of PN, the second excluded caffeine tablets) were distributed among university students at the University of Graz, Austria. The unrelated question model (UQM) was used to estimate the 12-month PN prevalence and the German version of the 30-item Domain-Specific Risk-Taking (DOSPERT) scale to assess the health-related risk attitude. Moreover, large-sample z-tests (α = 0.05) were performed for comparing the PN prevalence estimates of two groups. Results: Two thousand four hundred and eighty-nine questionnaires were distributed and 2,284 (91.8%) questionnaires were included in analysis. The overall PN prevalence estimate for all students was 11.9%. One-tailed large-sample z-tests revealed that the PN estimate for students with higher health-related risk attitude was significantly higher compared to students with lower health-related risk attitude (15.6 vs. 8.5%; z = 2.65, p = 0.004). Furthermore, when caffeine tablets were included into the example of PN, the prevalence estimate of PN was significantly higher compared to the version without caffeine tablets (14.9 vs. 9.0%; z = 2.20, p = 0.014). Discussion: This study revealed that the PN prevalence estimate increases when caffeine tablets are included in the definition of PN. Therefore, future studies investigating the prevalence of, and predictors for, PN should be performed and interpreted with respect to potential framing effects. This study further revealed that the PN prevalence estimate is increased in students with a higher health-related risk attitude compared to students with a lower one. Therefore, future education and prevention programs addressing PN in the collective of students should not only inform about potential side effects of its use but also address the limited effects on cognition and potential alternatives of PN.
