Attention-deficit/hyperactivity disorder (ADHD) is currently the most commonly diagnosed mental disorder in children, affecting between 3 to 9% of school age children (Volkow et al, 2005). The primary features of the disorder are impulsivity, lack of attention, and excessive motor activity (Pelham et al, 2001). In the majority of cases, the symptoms do not come to an end once the child enters into puberty and adolescence (Wolraich et al, 2005). Despite criticism that it is a merely a sociological phenomenon of the United States (i.e., see Stolzer, 2005), recent meta reviews have found that the worldwide prevalence of the diagnosis in adults is about 5%, with few substantive differences due to geography (Faraone et al, 2003). The most prevalent treatment for ADHD in both children and adults is psychotherapy, typically with either methylphenidate (Ritalin) or mixed amphetamine salts (Adderall). These drugs alleviate symptoms of ADHD as long as they are used, but there are little to no carryover effects once the medication is stopped (MTA Cooperative Group, 2004).
The non-medical use of these psychostimulants is high, and indeed it is the only prescription drug for which there are more nonmedical users than medical ones (McCabe and Teter, 2007). Individuals who attend college are significantly more likely to use nonmedical prescription stimulants than non-college attending individuals of the same age, even when income is adjusted for (Herman-Stahl et al, 2007). In a 2002 study of 150 undergraduates at Bates College, 36% of students admitted to using methylphenidate and/or amphetamine compounds, although that cohort included both ADHD prescribed and non-prescribed individuals (Low and Gendaszek, 2002). In a separate study of 1250 students attending a Northwestern public university, 18% of those who were not prescribed stimulants for ADHD admitted to having used them at least once, mainly for study purposes (Arria et al, 2008). In some senses this trend is not the most pressing issue. Contrary to the oft-cited “gateway drug” phenomenon, stimulant medication for children with ADHD leads to a 1.9 fold reduction of the probability for future substance abuse disorders as adolescents and adults (Wilens et al, 2003). And although acute intoxication and long-term misuse of stimulants can in some cases lead to insomnia, psychosis, and increased aggression (Caplan et al, 2007), the risk of sudden death from methylphenidate use is literally one in a million (Menhard, 2006), meaning that the physical risks are low compared to other drugs.
However, there is a risk of psychological dependence. Psychological dependence does not necessitate abuse, but instead a profound shift in self following stimulant use such that individuals come to believe and act like they could not be successful or work efficiently without the use of psychostimulants. It has been argued (Barrileaux and Advokat, 2009) that this psychological dependence stems from a differential attribution of agency. The individual attributes most of his academic or social success while on the drug to the medication instead of taking personal responsibility, and afterwards does not believe it is worth attempting to reproduce the work without aid of the stimulants. Therefore, within the context of this paper, psychological dependence will be operationally defined as a significantly diminished ability to work when the individual does not have access to the drugs as compared to baseline, pre-stimulant use levels. Although this test is impossible to run after the dependence is established, it is a useful way of grounding the abstract condition in a falsifiable prediction. Psychological dependence is an especially salient risk in competitive environments such as elite educational institutions where the pressure on students to perform at high levels is already intense. This paper will review the neurobiological substrates of ADHD medication, consider the range of possible cases of psychological dependence in college students who are prescribed ADHD medication and in those who use it illicitly, and offer some possible strategies for treatment in cases where there is an unhealthy attribution of agency.
Neural Mechanisms of ADHD Medications
As noted above, the most commonly prescribed stimulants fall into two classes. The drugs are typically either composed of methylphenidate compounds, which includes Ritalin and Concerta, or mixed amphetamine compounds, which includes Adderall and Dexedrine. These drugs seem to operate in an inverted U-shaped dose dependent manner, such that increasing the dose at low levels improves cognitive functioning but may prove detrimental at higher levels (Wolraich et al, 2005). Like virtually all known drugs of abuse, methylphenidate and amphetamine compounds both act on the dopaminergic motivation and reward system, which prominently includes the ventral tegmentum, the nucleus accumbens, and the prefrontal cortex (Sperlagh et al, 2009). The exact mechanism of action exerted by either of these classes of drugs is not completely known, but there are some promising lines of inquiry.
One such hypothesis is that methylphenidate increases the concentration of dopamine at the level of individual synapses by blocking dopamine transporters. Dopamine transporters clear the neurotransmitter from the synapse by transporting it back into the terminal button of the neuron. Volkow et al (1998) used PET scanning and carbon-11 cocaine as a radiotracer for imaging their dopamine transporter levels in seven healthy adults. They administered oral placebo pills as a baseline, and then administered methylphenidate as a test on the next day. Following methylphenidate intake, they found a weight-adjusted dose-dependent blockage of dopamine transporters in the striatum, a subcortical region which includes the nucleus accumbens. Crucially, the time required to reach the peak uptake of methylphenidate was 60 minutes, which corresponds to the amount of time it takes for peak behavioral effects to be seen following therapeutic doses of the drug. By increasing the concentration of dopamine in the synapse, this blockage of dopamine transporters is believed to amplify the reward signals elicited from environmental stimuli (Volkow et al, 2005). Thus, methylphenidate increases the saliency of otherwise commonplace stimuli, which boosts interest and attention.
Dopamine family-2 (D2) receptors also play a role in increasing the concentration of synaptic dopamine following methylphenidate intake, thus mediating its therapeutic and pleasurable effects. When Botly et al (2008) developed a rat model of Ritalin abuse, they found that drug naïve animals learn to self-administer the drug quickly, with similar dose infusions as seen in amphetamine or cocaine models. Injection of the D2 receptor antagonist eticlopride at a high dose significantly increased the number of self-infusions. This finding led the authors to speculate that D2 receptor antagonists block the reinforcing effects of methylphenidate. Volkow et al (1999) examined the behavioral effects of the drug on 23 males with self-reporting scales, as well as measuring their D2 receptor levels with PET scanning following injection of the D2 antagonist raclopride. Subjects who rated the effects of Ritalin as positive (n=12) had significantly lower levels of D2 receptors than those who described the effects as negative (n=9). This is additional evidence for a correlation between D2 receptor levels and the reinforcing effects of the drug, and it suggests one possible source of the observed individual variance in responses to the stimulants.
The mechanism of action for mixed amphetamine salts such as Adderall is not as clear cut, in part because amphetamines generally affect the dopamine, norepinephrine, and serotonin systems, and in part because many of them, such as Adderall, are made up of many different types of amphetamines. Moreover, amphetamines exert their action on a number of different neurotransmitter systems, mainly those of dopamine, norepinephrine, and serotonin. As in methylphenidate, the reinforcing effects of amphetamine are believed to be chiefly derived from its ability to elevate extracellular and synaptic dopamine levels (Wieczorek and Kruk, 1994). As evidence, brain imaging has demonstrated that amphetamines boost extracellular dopamine levels in the striatum (Cami and Ferre, 2003).
There is insight to be gained from a detailed study of the interplay between pharmacological agents and individual synapses. After this end, Schmitz et al (2001) investigated the mechanisms by which amphetamines distort dopamine release from vescicles in the neuron into the synapse. Injecting the D2 receptor antagonist sulpiride in mice led to a 47% reduction in the levels of vesicular dopamine, suggesting a role of the D2 receptor in the efficacy of the drug, similar to methylphenidate. Based on electrochemical data from rodent striatal brain slices, the authors determined that amphetamines also block the reuptake of dopamine from the synapse, which outweighs the inhibition of vescicular release, and leads to net overflow of synaptic dopamine that has a smaller amplitude but a longer duration. The multiple effects of amphetamine make it difficult to simplify its efficacy into a single model, especially because there is variance in the mechanism of action within different types of amphetamines. For example, MDMA and certain other “designer” amphetamines have an atypically large effect on the seritonergic system (Cami and Ferre, 2003).
In order to determine how amphetamines can increase sustained motivation and attention, Knutson et al (2004) examined eight healthy subjects using functional magnetic resonance imaging (fMRI) while completing the monetary incentive delay task, which is designed to provoke neural and emotional responses to quantified incentives. In two trials, the subjects were blindly given either amphetamines or placebo. Their fMRI time course analysis revealed that amphetamine treatment lowers the peak activation in the ventral striatum (i.e., the nucleus accumbens), but extends its overall duration during the anticipation of gains. Additionally, they found increased ventral striatum activity when amphetamine-treated subjects were anticipating the avoidance of future losses. The authors explain these findings in terms of an augmentation of positive arousal in the right nucleus accumbens, and a concomitant reframing of potential loss as potential gain. At the systems level, their model could explain why individuals who take mixed amphetamine salts such as Adderall are able to study longer, as they are physiologically more interested in the task at hand and thus are less likely to switch to a different one.
The interplay between the dopaminergic reward system and psychostimulant is further complicated when we consider the role of behavioral task. Volkow et al (2004) measured the subjective responses of sixteen healthy subjects following either a mathematical task that maintained an adjusted 80% success rate or a neutral task where subjects were shown scenic pictures and not asked to produce a behavioral response. Concurrently, they measured subject’s levels of D2 receptors in a PET scan using the D2 receptor ligand raclopride, and blindly administered either methylphenidate or placebo. They found that methylphenidate boosted extracellular dopamine in the striatum in a context-dependent manner, such that it did so during the challenging math task but had no effect during the tedious scenic task. Moreover, the subject’s self-reports of the math task as interesting, exciting, and motivating significantly increased when given methylphenidate, and there were significant correlations between the increase in extracellular dopamine release and changes in the ratings as interesting (r=0.67), exciting (r=0.52), and motivating (r=0.67). These results demonstrate the increased motivational saliency that methylphenidate use gives to a cognitive task. It also suggests that methylphenidate may be therapeutically effective in large part because it is able to make cognitive tasks such as homework more interesting, even in healthy individuals. This could help explain why the nonprescription use of ADHD medications has become so widespread.
Investigating the effects of these stimulants on the neural level is able to yield a number of insights. Both methylphenidate and mixed amphetamine salts perform the majority of their brain-related changes by acting on the dopaminergic reward and motivation system. As Volkow et al (1999) showed, there is some variance between individuals in the response to the same dose of methylphenidate that is related to the levels of D2 receptors, which suggests that not everyone will find the same dose of the prescription stimulants pleasurable, and some may not find them pleasurable at all. However, as Volkow et al (2004) showed, even healthy individuals can find their effects beneficial, as they make otherwise presumably boring cognitive tasks more interesting. Finally, since we do not fully understand the mechanism of action of either of these drugs, we should be wary of definitive claims about either their long-term efficacy or their health impacts in all of those whom use them. One of these potential adverse effects in the long run is psychological dependence, which is what this paper will consider next.
A Loss of Sense of Agency
The motives of college students in their use of prescription stimulants are predominantly to help with concentration, boost alertness, and to “get high” (Teter et al, 2005). They are particularly attractive to those seeking to boost their academic productivity, and it has been suggested that a more competitive college environment predicts increased stimulant use (Wilens et al, 2008). If students believe that the drugs will help them study, and they primarily use them for study purposes, it is easy to see how they might come to believe that their success in studying while on the drugs is mainly attributable to the effect of the drugs. Such a shift in agency attribution would be likely to lead to dependence. Indeed, this effect was postulated to occur in children when ADHD medications began to be used clinically. Amirkhan (1982) noted that the expectations of a child’s teacher can impact his academic achievement and classroom behavior. Drawing upon attribution theory, he argued that if a child’s teacher attributes a student’s achievement to an external cause, like the medication, instead of an internal cause, like hard work, then medicated ADHD children may develop low self-esteem. Finally, in a study of 15 teachers he found that they attributed any success of hyperactive students to their medication, showing that this may be a concern.
Milich et al (1989) took this one step further and argued that the children themselves might begin to attribute their academic success to the drug and regard their own efforts as playing only a minor role. They tested twenty-six boys with ADHD and a mean age of nine in the continuous performance test (CPT), a commonly used measure of sustained attention and/or impulsivity. On one trial they gave the children a standard dose of methylphenidate, and the other trial they were given a placebo pill, in a double blind design. As expected, the children performed significantly better while on medication, displaying significantly fewer errors of both omission and commission. Inconsistent with expectations, however, was the finding that their attributions of performance did not significantly vary between conditions. In fact, the results if anything trended towards the opposite direction as expected. Under both conditions, children attributed their success to effort and ability more so than to medication. Additionally, there was a correlation such that the better the boys did, the more likely they were to attribute their success to their inherent ability. These results show that children do not often attribute agency to the ADHD medications, and instead are quite willing to take personal credit for their success.
Subsequent studies have replicated these findings and placed them within the context of the self-serving bias, the tendency of individuals to attribute success to internal causes and failure to external causes. Although this tendency is present in the normal adult population at large, it is especially prominent in children with ADHD. For example, following a puzzle solving task, boys with ADHD are significantly less likely to attribute their own failings to a lack of effort, even though they are in reality more likely to quit early during the task (Hoza et al, 2001). In an elegant demonstration of this tendency, Pelham et al (2001) instructed ADHD children to convince a confederate peer to return to the summer camp the subsequent summer. The researchers manipulated the success of the children’s attempt by instructing the confederates to respond either positively or negatively to their case for returning. The researchers also manipulated the medication by either administering methylphenidate or placebo, and the reward expectancy by telling the subjects they would receive either a real or fake pill. Regardless of the medication and despite the fact that success was experimentally controlled, the boys consistently attributed success to internal reasons such as effort or ability and failure to external reasons such as task difficulty. Therefore, this study demonstrates once again that medication does not produce maladaptive patterns of attribution in children with ADHD, and suggests that the reason for the lack of a loss of agency is due to their self-serving bias.
However, the fact that the self-serving bias outweighs any tendency to attribute success to the drugs in children does not imply that it will necessarily do so in college-aged adults as well. At competitive colleges, the desires to improve intellectual performance and to be more efficient on academic assignments have been found to be the most common motivations among those using prescription stimulants non-medically (Low and Gendaszek, 2002). Unlike children, who take prescription drugs under superstition, prescription drugs in college age adults are administered independently and at their own discretion. It would require a tremendous leap of cognitive dissonance for the students to still attribute nearly all of their academic success to internal factors and ignore the effects of the drugs. There have been surprisingly few studies of ADHD in the college age group (Weyandt and DuPaul, 2008), but the few that have been performed suggest that the attribution of agency to the self instead of the drug may not be as consistent as it is in children.
In order to gain insight into prescription drug use, Meaux et al (2006) interviewed 15 college students with ADHD. They reported that the drugs were often misused by their peers, some of whom would “stay up for 4 days straight just on this medication studying for a test.” Many reported that after the initial diagnosis of ADHD, healthcare providers were rarely consulted about the use of medications, as individuals would simply call their mothers, who would then call to renew their prescriptions. Their vast amount of autonomy at college, coupled with a lack of guidance from physicians, often led them to procrastinate, and take over doses of stimulant medications to stay up all night and finish a paper. This type of behavior implies a type of psychological dependence. If one takes a pill at the last minute, it implies a form of “giving in” to the side effects in exchange for the immediate benefits. It implies a willingness to yield a degree of agency to the drug in the short run.
When DeSantis et al (2008) interviewed 1,811 students at a large southeastern university, they found that of the 34% of students that had used ADHD medications illegally, 63% of them first used the non-prescribed stimulants in college. On the basis of qualitative interviews, they found that much unlike every other illicitly used drug, prescription stimulants were used primarily in the pursuit of “getting good grades.” In addition to productivity, the stimulants often led to an enhanced ability to memorize, understand ideas, and recall information. One student remarked that “the stuff is like an academic anabolic steroid.” Although the authors did not report any data on psychological dependence, the overwhelmingly positive response to the drugs indicates that the students discriminate between their academic abilities while on stimulants and while not on stimulants. However, it may be the case that, as in children, these college students are able to explain away the effects of the drugs through their self-serving bias and thus retain their sense of agency.
In order to directly test whether adult college students with ADHD place more emphasis on medication as opposed to children, Barrilleaux and Advokat (2009) tested a group of 24 college students, around half of which had ADHD. They loosely adopted Milisch et al’s (1989) procedure, including the use of the continuous performance task, although their design was not placebo controlled. Non-medicated control subjects showed no difference from session one to session two, but ADHD subjects showed a significant increase in perception of self-performance and a significant decrease in commission errors when medicated. When the ADHD group was asked to attribute their success in the task, they reported that the most important factor was medication, then effort, then ability, and finally task difficulty. The researchers could not recreate a fully double-blind procedure because they did not want to interfere with the subject’s medication schedule, so these results can only be interpreted as preliminary. Further research should attempt to replicate this finding in college aged adults using the canonical double blind results, and it remains to be seen how this attribution of agency might affect their self-perceptions of success and failure.
Nevertheless, this is some evidence that a loss of sense of agency following prescription stimulant use, previously shown not to be a factor in children, may in fact adversely affect college age adults. Qualitatively, many students describing their symptoms on the internet note a psychological dependency on Adderall. For example, when one student was taken off medication, she began “wondering how I was going to get anything accomplished.” Another noted that “a friend of mine honestly can’t study unless she has an Adderall.” These qualitative trends suggest that college age adults may be particularly at risk of psychological dependence. The next section of this paper will consider that possibility more in-depth.
Who is at Risk for Dependence?
There are a number of factors that might predispose an individual to attribute agency to the drug instead of to him or herself following stimulant use. McCabe and Boyd (2005) reported that men, individuals whose families have higher incomes, Caucasians, people in fraternities or sororities, and students with lower GPAs are more likely to take the drugs than other samples. But just because certain groups are likely to take the stimulants does not mean that they are necessarily more likely to become dependent upon their use. Some studies have found that among those medically prescribed for ADHD stimulant use, overuse is almost twice as high for females (37%) and for males (20%; Arria et al, 2008), but their definition of overuse does not overlap with the definition of psychological dependence in this paper, and their sample size was not large for that cohort. Herman-Stahl et al (2007) find that high psychological distress is a significant risk factor for nonprescription stimulant use, but they too define abuse as any past year non-medical use of prescription stimulants, which also does not allow for discrimination between mere illicit use and psychological dependence. Without useful cross-sectional data on this key measure, the best we can do is to formulate some theoretical predictions.
The independence of college-age individuals, their ability to self-administer the drugs, and the widespread ubiquity of the drugs through peer to peer sharing all make college students especially likely to take prescription stimulants and be at risk for psychological dependence. If an outside agent such as one’s physician, parents, or school forces a child to take the drugs, then it might be possible for the child to rationalize the positive effects of the drugs as minimal and take credit for his actions while stimulated. However, as Meaux et al reported, this power structure shifts once the medicated individual enters adolescence and then college, at which point his or her autonomy in drug administration increases dramatically. This aspect of choice is especially pronounced in individuals who use the drugs without a prescription or even a diagnosis of ADHD, many of whom take the drugs solely to improve academic performance. These college-age individuals are in a sense selling their agency in exchange for improved academic performance and better grades. This exchange comes with the downside of a potential for psychological dependence, but this possibility is either ignored or, via hyperbolic discounting, the immediate rewards are perceived as being greater than the long term costs.
Another factor might be differential levels in the self-serving bias. Although the self-serving bias persists in some form across the lifespan, the effect sizes for this attributional bias are largest in children age 8-11, begin to attenuate during young adulthood, remain at a stable relative low during mid adulthood, and finally increases again in later adulthood at age 55 and above (Mexulis et al, 2004). If we accept the self-serving bias as the most parsimonious explanation for the lack of attributional agency to ADHD medication in children, then this trend has implications for predicting responses to prescription stimulants. In fact, we should expect that college age adults will be among the most likely individuals to attribute their success while taking ADHD medication to the drugs. In the only behavioral test to test this hypothesis directly (to the best of my knowledge), Barrilleaux and Advokat found tentative results in the affirmative. If their results can be replicated, then it can be concluded that the risk of individuals becoming psychologically dependent upon the drug and thus having diminished self-esteem in the college age cohort is high. Another group which seems especially at risk for psychological dependence following prescription stimulant use is individuals with depression, who show the lowest effect size of self-serving bias of any sample studied in Mexulis et al’s meta-review.
Although the extant data is limited, there are compelling arguments that college students will be particularly at risk for developing a psychological dependence on prescription stimulants. This paper will now address some possible treatments for this dependence.
Restoring a Sense of Agency
Many of the proposed treatments to the growing use of prescription stimulants in the literature suggest that institutions should limit availability of these drugs, educate students, or otherwise directly discourage their use among college students (i.e., see DeSantis et al, 2008). However, in the case of individuals that have already acquired psychological dependencies, limiting their availability may simply increase the levels of risk-taking behavior undertaken in order to acquire the stimulants. And although education might be useful in theory, large-scale drug intervention programs like DARE do not have a strong track record (Lynam et al, 1999). So it might be fruitful to consider some alternative treatments.
One possible treatment involves the characteristic of choice. As discussed above, individuals who explicitly choose to take the drugs for study purposes will have a harder a more difficult time rationalizing away their effects as minimal, and will likely begin to attribute agency to the drugs. So, in order to limit this autonomy, college age individuals with ADHD or ADHD-like symptoms could be pushed to take the drugs on a regular schedule instead of being allowed to pick and choose times. Following from this treatment, use of the stimulants would become a more regular phenomenon, and individual effort would be regarded as the more important factor in determining the outcome and quality of work. Thus, it might shift attributions of agency from the drug back to the individual. This treatment would come with the downside of increased negative side effects such as insomnia and reduced tolerance towards other recreational drugs, but it would likely be instrumental in preventing and reducing psychological dependence. Of course, this treatment brings up some ethical concerns regarding freedom and liberty. But perhaps one way out of this quandary is to stipulate that nobody will be forced to take the drugs, but if you do choose to do so, you must follow a physician’s guided schedule. In individuals at particularly high risk to developing psychological dependence, the benefits of such an intervention may be found to outweigh the costs.
Another way to decrease psychological dependence on prescription stimulants would be to emphasize the placebo effect of the drugs. Reward expectancies play a large role in many drugs, and may account for the majority of the effects sizes of certain prescription drugs such as antidepressants (Irving and Guy, 1998). Focusing on these effects following the use of stimulants might shift agency from the drug back to the user, with the effects of the drug serving to only unlock the user’s true potential. Volkow et al’s 2004 study showed, as described above, that the placebo effect cannot account for all and likely not even most of the effects of these prescription stimulants and indeed taking them does make cognitive tasks significantly more motivating and interesting even for healthy users. So these tactics might be seen as nefarious from a purely truth-seeking perspective. But then again, so is the self-serving bias, which is nevertheless classified by social psychologists as “healthy” behavior. Such a public relations ploy is a targeted way of addressing the problem, instead of vaguely suggesting increased education. Either of these treatments may help to specifically reduce or curb the growth of psychological dependence on the drug, if that is deemed by educational institutions to be a worthwhile goal. The next section will consider this issue of utility from a broader perspective.
Towards the Ethical Use of Psychostimulants
The non-medical use of prescription stimulants such as methylphenidate and mixed amphetamine salts is not likely to end anytime soon. In fact, some researchers have recently suggested that its nationwide use is on the rise (DeSantis et al, 2008). Given that psychological dependence following stimulant use is a possibility for many college students, identifying the risk factors predisposing students to a maladaptive attribution of agency and focusing on specific therapeutic treatments for this dependence would be of high utility. More broadly, as the use of neuroenhancers such as Adderall and Ritalin becomes more widespread and thus accepted, physicians, educators, and human resource professionals must address the issues they present head on.
In addition to concerns of psychological dependence, there are concerns over equity. Currently, students whose family income is above $250,000 are three times more likely to have used prescription stimulants non-medically in the past year than students whose family income is less than $50,000, a larger effect than that seen in other drug use (McCabe and Teter, 2007). Although in some samples 72% of students report that they can receive the stimulants for free (Arria et al, 2008), there may be implicit favor-sharing involved in which students of lower income would not be able to reciprocate. Moreover, most studies have found that individuals in fraternities and sororities have higher levels of non-medicated prescription stimulant use, even larger than we would expect based on an overall increase in drug use in those institutions (i.e., see McCabe and Teter, 2007). One parsimonious explanation of this finding is that these students have more access to these drugs because of their larger social network and increased likelihood of knowing somebody who has a prescription for the stimulants. A laissez-faire stance from authorities is likely to emphasize these inequities, which may or may not be justified by the benefits of such a stance.
Another way to approach the issue is to consider exactly who is using the prescription stimulants at a high rate. Given the high correlation between undiagnosed ADHD-like symptoms and self-administration of non-prescribed stimulants in students (Wilens et al, 2008), it may make sense to clinically evaluate these individuals. On the other hand, why must individuals be diagnosed with a medical illness in order to gain access to these drugs? From the perspective of the individual student, the fact that these drugs are prescribed to their peers probably destigmatizes their negative affects (Low and Gendaszek, 2002). And they have been shown to be effective in boosting cognitive performance in healthy as well as ADHD diagnosed individuals. A relationship is often discussed between steroid use in sports and “study steroid” use at competitive colleges and universities. As the argument goes, those who do not choose to use the drugs due to concerns about potential adverse long-term physiological or psychological consequences will be at an unfair competitive disadvantage. This is indeed analogous to the steroid problems in professional sports, which have been increasingly virulent and have even come under congressional purview as of late. However, the analogy only holds in so far as school work and education is a zero sum game. To the extent that improving education and research will benefit society as a whole, cognitive enhancement must be considered on its own merits.
In their recent paper on the use of neuroenhancers in society at large, Greely et al (2008) make a persuasive argument that we should welcome new technology to enhance brain function. Indeed, these prescription stimulants have the potential to benefit both individuals and society at large, by making useful but monotonous work more interesting and increasing attention spans. They call for a data-driven approach, emphasizing an understanding of the benefits and risks of cognitive enhancements. Up until now most of the research on the subject has focused on children, which makes less and less sense as the number of college aged adults taking the stimulants skyrockets. There are a number of important issues to tackle. For example, can we quantify the risk of psychological dependence on the drugs in adults? Do the stimulants stifle creativity or otherwise alter the mindset of the users? How pressured do third parties feel to take the drugs when they find that their peers are doing so? There are a number of possible approaches to regulating the use of these prescription stimulants both in educational institutions and in the workplace as well. A laissez-faire approach will leave the problem to undirected market forces, which is likely to lead to otherwise preventable inequity, and may or may not be worth the benefits. A tight regulatory stance will likely force users and especially individuals that are already psychologically dependent to go to “the street,” which also poses problems. The correct response will be somewhere in the middle, capitalizing on the benefits of the cognitive prescription stimulants while curtailing the downsides.
Schubiner H, Tzelepis A, Milberger S, Lockhart N, Kruger M, Kelley BJ, Schoener EP. 2000 Prevalence of attention-deficit/hyperactivity disorder and conduct disorder among substance abusers. Journal of Clinical Psychiatry 61: 244-251.
Wolraich ML, Wibbelsman CJ, Brown TE, Evans SW, Gotlieb EM, Knight JR, Ross EC, Shubiner HH, Wender EH, Wilens T. 2005 Attention-deficit/hyperactivity disorder among adolescents: A review of the diagnosis, treatment, and clinical implications. Pediatrics 115: 1734-1746.
Low KG, Gendaszek AE. 2002 Illicit use of psychostimulants among college students: a preliminary study. Psychology, Health and Medicine 7:283-287.
Sperlagh B, Windisch K, Ando RD, Vizi ES. 2009 Neurochemical evidence that stimulation of CB1 cannabinoid receptors on GABAergic nerve terminals activates the dopaminergic reward system by increasing dopamine release in the rat nucleus accumbens. Neurochemistry International 54: 452-457.
Wilens TE, Faraone SV, Biederman J, Gunawardene S. 2003 Does stimulant therapy of attention-deficit/hyperactivity disorder beget later substance abuse? A meta-analytic review of the literature. Pediatric 111: 179-185.
Arria AM, Caldeira KM, O’Grady EK, Vincent KB, Johnson EP, Wish ED. 2008 Nonmedical use of prescription stimulants among college students: Associations with attention-deficit-hyperactivity disorder and polydrug use. Pharmacotherapy 28: 156-169.
Esptein LA. 2007 Neuropsychiatric effects of prescription drug abuse. Neuropsychology review 17 363-380.
Faraone SV, Sergeant F, Gilberg C, Biederman J. 2003 The worldwide prevalence of ADHD: Is it an American condition? World Journal of Biological Psychiatry 2: 104-113.
Stolzer J. 2005 ADHD in America: A bioecological analysis. Ethical Human Psychology and Psychiatry 7: 65-76.
McCabe, SE, Teter CJ. 2007 Drug use related problems among nonmedical users of prescription stimulants: A web-based survey of college students from a Midwestern university. Drug and Alcohol Dependence 91: 69-76.
Herman-Stahl MA, Krebs CP, Kroutil LA, Heller DC. 2007 Risk and protective factors for methamphetamine use and nonmedical use of prescription stimulants among young adults aged 18 to 25. Addictive Behaviors 32: 1003-1015.
Teter CJ, McCabe SE, Cranford JA, Boyrd CJ, Guthrie SK. 2005 Prevalence and motives for illicit use of prescription stimulants in an undergraduate student sample. Journal of American College Health 53: 253-263.
Wilens TE, Adler LA, Adams J, Sgambati S, Rotrosen J, Sawtelle R, Utzinger L, Fusillo S. 2008 Misuse and diversion of stimulants prescribed for ADHD: A systematic review of the literature. Journal of the American Academy of Child and Adolescent Psychiatry 47: 21-31.
MTA Cooperative Group, National Institute of Health. 2004 National Institute of Mental Health Multimodal Treatment Study of ADHD Follow-up: Changes in Effectiveness and Growth After the End of Treatment. Pediatric 113: 762-769.
Amirkhan J. 1982 Expectancies and attributions for hyperactive and medicated hyperactive students. Journal of Abnormal Psychology 10: 265-276.
Milich R, Licht BG, Murphy DA, Pelham WE. 1989 Attention-deficit hyperactivity disordered boys’ evaluations of and attributions for task performance on medication versus placebo. Journal of Abnormal Psychology 98: 280-284.
Hoza B, Pelham WE, Waschbusch DA, Kipp H, Owens JS. 2001 Academic task persistence of normally achieving ADHD and control boys: Performance, self-evaluations, and attributions. Journal of Consulting and Clinical Psychology 69: 271-283.
Pelham WE, Hoza B, Waschbusch DA, Pillow DR, Gnagy EM. 2001 Effects of methylphenidate and expectancy on performance, self-evaluations, persistence, and attributions on a social task in boys with ADHD. Experimental and Clinical Psychopharmacology 9: 425-437.
Mexulis AH, Abramson LY, Hyde JS, Hankin BL. 2004 Is there a universal positivity bias in attributions? A meta-analytic review of individual, developmental, and cultural differences in the self-serving attributional bias. Psychological Bulletin 130: 711-747.
Volkow ND, Wang GJ, Folwer JS, Logan J, Gatley SJ, Giffod A, Hitzemann R, Ding YS, Pappas N. 1999 Prediction of reinforcing responses to psychostimulants in humans by brain Dopamine D2 receptor levels. American Journal of Psychiatry 156: 1440-1443.
Botly CP, Burton CL, Rizos Z, Fletcher PJ. 2008 Characterization of methylphenidate self-administration and reinstatement in the rat. Psychopharmacologia 199: 55-66.
Volkow ND, Wang GJ, Fowler JS, Ding YS. 2005 Imaging the Effects of Methylphenidate on Brain Dopamine: New Model on Its Therapeutic Actions for Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry 57: 1410-1415.
Volkow ND, Wang GJ, Fowler JS, Gatley SJ, Logan J, Ding YS, Hitzemann R, Pappas N. 1998 Dopamine Transporter Occupancies in the Human Brain Induced by Therapeutic Doses of Oral Methylphenidate. American Journal of Psychaitry 155: 1325-1331.
Menhard, Francha R. The Facts About Ritalin. Benchmark Books, NY, NY, 2006. p. 59.
DeSantis AD, Webb EM, Noar SM. 2008 Illicit use of prescription ADHD medications on a college campus: a multimethodological-approach. Journal of American College Health 57: 315-324.
Schmitz Y, Lee CJ, Schmauss C, Gonon F, Sulzer D. 2001 Amphetamine Distorts Stimulation-Dependent Dopamine Overflow: Effects on D2 Autoreceptors, Transporters, and Synaptic Vesicle Stores. The Journal of Neuroscience 21: 5916-5924.
Wieczorek WJ, Kruk ZL. 1994 Differential action of (+)-amphetamine on electrically evoked dopamine overflow in rat brain slices containing corpus striatum and nucleus accumbens. British Journal of Pharmacology 11: 829-936.
Lynam DR, Milich R, Zimmerman R, Novak SP, Logan TK, Martin C, Leukefeld C, Clayton R. 1999 Project DARE: No effects at 10-year follow-up. Journal of Consulting and Clinical Psychology 67: 590-593.
Volkow ND, Wang GJ, Fowler JS, Telang F, Maynard L, Logan J, Gatley SJ, Pappas N, Wong C, Vaska P, Zhu W, Swanson JM. 2004 Evidence that methylphenidate enhances the saliency of a mathematical task by increasing dopamine in the human brain. American Journal of Psychiatry 161: 1173-1180.
Greely H, Sahakian B, Harris J, Kessler RC, Gazzaniha M, Campbell P, Farah MJ. 2008 Towards responsible use of cognitive-enhancing drugs by the healthy. Nature 456: 702-705.
Kirsch I, Sapirstein G. 1998 Listening to Prozac but hearing placebo: A meta-analysis of antidepressant medication. Prevention and Treatment, 1: 002a.
Meaux JB, Hester C, Smith B, Shoptaw A. 2006 Stimulant medications: A trade-off? The lived experience of adolescents with ADHD. Journal for Specialists in Pediatric Nursing 11: 214-226.
McCabe SE, Boyd CJ. 2005 Sources of prescription drugs for illicit use. Addictive Behaviors 30: 1342-1350.
Barrilleaux C, Advokat K. 2009 Attribution and self-evaluation of continuous performance test task performance in medicated and unmedicated adults with ADHD. Journal of Attention Disorders 12: 291-298.
Weyandt LL, Dupaul GJ. 2008 ADHD in college students: Developmental findings. Developmental Disabilities Research Reviews 14: 311-319.
Caplan JP, Epstein LA, Quinn DK, Stevens JR, Stern TA. 2007 Neuropsychiatric effects of prescription drug use. Neuropsychology Review 17: 363-380.
Knutsonj B, Bjory JM, Fong GW, Hommer D, Mattay WS, Weinberger DR. 2004 Amphetamine Modulates Human Incentive Processing. Neuron 43: 261-269.
Cami J, Ferre M. 2003 Drug addiction. New England Journal of Medicine 349: 975-986.
 Some have noted that since this bias is merely a tendency to view events as less like reality than they really are, it should not be considered “healthy” behavior. But since its absence has been found to predict higher rates of depression, and since it is present in the majority of the population, the consensus of social psychologists is this that bias is healthy (Pelham et al, 2001).