| Literature DB >> 24484640 |
Sebastian Sattler1, Guido Mehlkop, Peter Graeff, Carsten Sauer.
Abstract
BACKGROUND: The use of cognitive enhancement (CE) by means of pharmaceutical agents has been the subject of intense debate both among scientists and in the media. This study investigates several drivers of and obstacles to the willingness to use prescription drugs non-medically for augmenting brain capacity.Entities:
Mesh:
Substances:
Year: 2014 PMID: 24484640 PMCID: PMC3928621 DOI: 10.1186/1747-597X-9-8
Source DB: PubMed Journal: Subst Abuse Treat Prev Policy ISSN: 1747-597X
Figure 1Factors influencing the willingness to use CE-drugs.
Descriptive statistics for the demographic variables
| Gender | | | |
| | 1,753 | 60.7 | 53.5 |
| | 1,134 | 39.3 | 46.5 |
| Age | | | |
| | 1 | 0.0 | 0.0 |
| | 37 | 1.3 | 4.3 |
| | 744 | 25.8 | 21.3 |
| | 864 | 29.9 | 23.8 |
| | 646 | 22.4 | 20.8 |
| | 282 | 9.8 | 12.6 |
| | 143 | 5.0 | 6.9 |
| | 68 | 2.4 | 3.6 |
| | 32 | 1.1 | 2.0 |
| | 24 | 0.8 | 1.2 |
| | 7 | 0.2 | 0.7 |
| | 7 | 0.2 | 0.6 |
| | 7 | 0.2 | 0.5 |
| | 25 | 0.9 | 1.5 |
| Field of study | | | |
| | 92 | 3.2 | 3.5 |
| | 943 | 32.7 | 25.9 |
| | 309 | 10.7 | 31.6 |
| | 1,135 | 39.3 | 23.3 |
| | 70 | 2,4 | 6.5 |
| | 85 | 2.9 | 1.0 |
| | 165 | 5.7 | 6.5 |
| | 88 | 3.1 | 1.8 |
Descriptive statistics for the independent metric variables measuring personal characteristics
| | | | | | ||
| Risk attitudes | Not at all willing to take risks | Very much willing to take risks | 1 | 11 | 5.47 | 2.283 |
| Academic procrastination | Very seldom | Very often | 1 | 6 | 2.77 | 0.978 |
| Study motivation | Do not agree at all | I agree completely | 1 | 6 | 4.68 | 1.074 |
| Cognitive test anxiety (CTA) | Not true at all | Completely true | 1 | 4 | 3.07 | 0.718 |
| Competencies | Very difficult | Very easy | 1 | 5 | 3.27 | 0.585 |
| Internalized social norms | Absolutely moral | Absolutely not moral | 1 | 7 | 5.58 | 1.714 |
Vignette dimensions and levels used in this study: experimental variation of five drug characteristics and three characteristics of the social environment
| Peer prevalence | A student considers using a prescription drug to enhance her memorization skills for her exam preparation. From a medical point of view, this is not necessary. This student knows that |
| of her friends or acquaintances uses such substances. | |
| Social suggestions | She |
| gets suggestions from others to try such means. | |
| Magnitude of enhancement effect | By taking such drugs, she hopes to increase the amount of memorized information by |
| compared to her normal state. | |
| Probability of enhancement effect | From a recently published study, she knows that that the effect occurs with a |
| percent chance. | |
| Probability of side effects | This study also reported that |
| Severity of side effects | developed |
| depression. Further side effects are unknown. | |
| Drug price | Someone can provide her with a package of 10 pills for |
| This is enough for 20 learning hours. | |
| Social disapproval | The use of such drugs would cause |
| criticism in her environment |
Multivariate negative binomial regression model on the willingness to use a CE-drug (n = 2,887)
| | ||
|---|---|---|
| Magnitude of enhancement effect (Ref. 5 percent): | | |
| 1.010 | [0.849,1.201] | |
| 1.329** | [1.120,1.577] | |
| Probability of enhancement effect (Ref. 5 percent): | | |
| 1.287** | [1.081,1.533] | |
| 1.392*** | [1.177,1.646] | |
| Severity of side effects (Ref. very light depression): | | |
| 0.924 | [0.781,1.093] | |
| 0.881 | [0.746,1.041] | |
| Probability of side effects (Ref. one of 1,000,000 users): | | |
| 0.955 | [0.815,1.119] | |
| 0.634*** | [0.533,0.754] | |
| Drug price (Ref. free): | | |
| 1.118 | [0.955,1.310] | |
| 0.683*** | [0.572,0.815] | |
| | | |
| Peer prevalence (Ref. none): | | |
| 1.287*** | [1.089,1.522] | |
| 1.321** | [1.113,1.568] | |
| Social suggestions (Ref. never): | | |
| 0.887 | [0.749,1.051] | |
| 1.071 | [0.907,1.265] | |
| Social disapproval (Ref. no criticism): | | |
| 0.926 | [0.788,1.090] | |
| 0.713*** | [0.600,0.846] | |
| | | |
| Risk attitudes | 1.012 | [0.980,1.045] |
| Academic procrastination | 1.112** | [1.034,1.196] |
| Study motivation | 0.897** | [0.839,0.960] |
| Cognitive test anxiety (CTA) | 1.383*** | [1.245,1.535] |
| Competencies | 1.048 | [0.915,1.199] |
| Internalized social norms | 0.673*** | [0.644,0.702] |
| Prior CE-drug use | 2.409*** | [1.873,3.097] |
| | | |
| Male (Ref. female) | 0.949 | [0.812,1.110] |
| Agec | 0.969 | [0.928,1.012] |
| Field of study (Ref. sports): | | |
| 1.260 | [0.792,2.004] | |
| 1.237 | [0.763,2.006] | |
| 1.261 | [0.797,1.995] | |
| 1.272 | [0.710,2.279] | |
| 1.285 | [0.716,2.307] | |
| 1.845* | [1.089,3.126] | |
| 1.669 | [0.981,2.839] | |
| Log-pseudolikelihood (full model) | -3566.2 | |
| Log-pseudolikelihood (base model) | -3848.1 | |
*p < 0.05, **p < .01, ***p < .001 (Wald tests, robust standard errors).
a Adjusted Incidence Rate Ratios (IRR).
b Confidence Intervals (CI).
c Age was treated as a metric variable (see Table 2 for the 14 measured categories).