Substance use to enhance academic performance among Australian university students
Introduction
The evidence base to suggest that students are using various substances to enhance their cognitive performance is growing (Housden, Morein-Zamir, & Sahakian, 2011, chap. 7), prompting calls for regulation by educational (Greely et al., 2008) and public health policy makers (Smith & Farah, 2011). Substances used by students to enhance academic performance include stimulants such as caffeine (CAF), methylphenidate (MPH) and modafinil (MOD). In addition to the ethical harms that may arise from such substance use (e.g. coercion, authenticity and justice; Sandberg & Savulescu, 2011, chap. 6), public health discourses argue significant known health risks exist (e.g. caffeine toxicity; Reissig, Strain, & Griffiths, 2009) alongside unknown health risks (e.g. long term off-label use of MPH or MOD; McCabe and Teter, 2007, Teter et al., 2010). The evidence base for substance use to enhance academic performance is largely constrained to data from the United States (US) examining the non-medical use of prescription stimulants (NMUPS) such as MPH among college students, prompting calls for data to be collected outside the US (Smith and Farah, 2011, Teter et al., 2006) and using different methods (DeSantis et al., 2008, Rabiner et al., 2009). Lucke and Hall (2012) indicate the need for such research in the Australian context is pressing. The current paper reports data from an exploratory study of Australian university student use of substances to enhance academic performance.
Substance use by students to enhance academic performance is commonly thought of as cognitive enhancement, also described as neuroenhancement, cosmetic neurology or brain doping (Partridge, Bell, Lucke, Yeates, & Hall, 2011). Cognitive enhancement is generally thought of as “the amplification or extension of core capacities of the mind, using augmentation or improvements of information processing systems” (Sandberg, 2011, chap. 5, p. 72). The cognitive skills enhanced have been defined as perception, attention, memory, comprehension, use of speech and executive function (planning, problem solving and self monitoring) (Housden et al., 2011, chap. 7, p. 113). Cognitive enhancement includes tools (e.g. an abacus), training (e.g. study), brain–computer interfaces (e.g. cochlear implants) and new senses (e.g. magnetic field perception) (Sandberg, 2011, chap. 5). It also includes natural substances demonstrated to influence cognition (e.g. CAF) along with pharmaceutically refined (e.g. Omega 3 (OM3)) or derived substances (e.g. MPH and MOD). Pharmaceutically derived substances are typically developed to treat neurological conditions such as attention deficit disorder or narcolepsy (Lanni et al., 2008) and adapted for cognitive enhancement through diversion to off-label use (Greely et al., 2008).
There is mixed evidence that the substances presumed to influence cognitive function and enhance academic performance do achieve this intention, and no evidence it meets the inflated claims of effect made in some parts of the literature (see Schermer, Bolt, de Jongh, & Olivier, 2009). While CAF has a long history of human physical and mental performance enhancement, there is mixed evidence of the effects of nutritional supplements Ginkgo Biloba (GBI) and Omega-3 (OM3) as cognition enhancers (e.g. Elsabagh et al., 2005, Kalmijn et al., 1997, Kennedy et al., 2009, Snitz et al., 2009). There are equally mixed results reported in contrasting reviews of pharmaceutically derived cognitive enhancers. There is general agreement that such substances rarely improve performance across the spectrum of cognition, and instead have niche effects for learning over time (Smith & Farah, 2011) or overcoming cognitive impairments due to sleep deprivation (Repantis, Schlattman, Laisney, & Heuser, 2010). One suggestion for such variability has been the lack of controlled randomised studies to assess the effects accounting for dose response, genetics, personality, prevailing ability and task characteristics (Smith & Farah, 2011). In the absence of reliable evidence that the substances do enhance cognition, the issue may be less about actual cognitive enhancement, and more on the belief of enhancement (Repantis et al., 2010). Irrespective of actual or perceived effect, an observable trend towards increasing use of these substances for performance enhancing purposes has emerged.
The majority of data on the use of cognitive enhancing substances is from public health research exploring the NMUPS among US college students. A systematic review of US data by Wilens et al. (2007) put past year non-medical use of prescription stimulants (NMUPS) by college students at between 5% and 35%. For example, where McCabe, Knight, Teter, and Wechsler's (2005) survey of n = 10,904 US college students showed lifetime and past year rates for NMUPS at 6.9%, the multimethod study reported by DeSantis et al. (2008) yielded a 34% lifetime rate (n = 175). By comparison, a study of n = 1547 German high school and university students found the lifetime rate of NMUPS for cognitive enhancement was 1.3% (Franke et al., 2011). A small study of n = 77 Italian university students reported a lifetime use of 16% (Castaldi et al., 2012). By comparison, a survey of prescription drug use to enhance normal level of concentration or alertness in the Australian general population found a lifetime use rate of 2.4% (Partridge, Lucke, & Hall, 2012). The variation in NMUPS lifetime use rates suggests results may be sensitive to context. The evidence base for policy discussion in the Australian context therefore needs to be expanded to account for local conditions (Lucke and Hall, 2012, Partridge et al., 2013).
The current study started as a pilot for a larger scale investigation of substance use to enhance academic performance by Australian university students. The unexpectedly enthusiastic response from n = 1729 Australian university students saw the study change in scope from a pilot to exploratory. The sample size enables the study to give a general indication of prevalence and correlates for substance use to enhance academic performance to inform future research.
Section snippets
Sampling frame
Following approval from two university human research ethics committees (HREC), students at four large South Eastern Australian universities were invited to participate in the online “Study Drugs Study”. The universities represented a mix of research and teaching intensive, and urban and rural campuses. Use of an online convenience sample represents a cost-effective way to collect data about stigmatised behaviour such as drug use appropriate to the original pilot study design. While the sample
Characteristics of the samples
A convenience sample of n = 1729 students responded. Demographic characteristics of all university students in Australia in 2011 are drawn from data collected by the Australian Government (2013); no age data was available. The sample had slightly more females (53.2%, n = 15 missing, AUS 55.7%), was 23.9 years old (SD = 7.2, range 18–70, n = 35 missing) and majority undergraduate (80.0%, AUS 70.5%); 16.9% were post-graduate coursework and 3.1% research students (n = 101 missing) (AUS 24.7% and 4.8%
Discussion
Enough Australian university students use substances to enhance academic performance to warrant further investigation. However, the results are caveat to the exploratory nature of the study. The relative lifetime use rates of stimulants are higher than those reported from the US and Germany, suggesting higher rates of use than Italian university students and the Australian general population. Australian students appear to use substances for an immediate effect (e.g. improve concentration)
Conclusions
In response to Lucke and Hall (2012), this exploratory study demonstrates the need to gather more evidence of Australian university student use of substances to enhance academic performance. This evidence is vital towards establishing education policy or possibly regulation of this class of substance use. The first question to be resolved is whether this issue is dealt with as one of health or one of performance enhancement (cf Forlini & Racine, 2009). The former can be argued in terms of
Conflict of interest
The authors declare no conflict of interest.
Acknowledgements
The authors thank the participating Universities for giving access and the students who so generously gave their time.
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