Effects Of Smart Drugs On Academic Performance Among University Students - A Qualitative Study

Question:

Discuss about the Critical Evaluation of Evidence for Hyperactivity Disorder.

Evidence based practice is of utmost importance owing to the fact that current evidences related to health interventions are judiciously used to formulate best decisions that will help in providing a client-centred holistic care. The smart drugs mentioned in the case scenario are used to treat Attention deficit hyperactivity disorder, which is a neuro-developmental disorder. The common symptoms are less concentration and restless behaviour (Arnold, Hurt & Lofthouse, 2013). Wasim, a student has observed that all his university friends are talking about using smart drugs to improve their academic performance in examinations (Burgard et al., 2013). Although Wasim knows about the therapeutic benefits of the drugs on ADHD, he aims to discover their probable role in academic performance improvement, by thoroughly investigating 2 articles. The first article is a qualitative study that will show the association between examination performance psycho-stimulants and the second article will show the effects of smart drugs on executive functioning of university students.

Hildt, E., Lieb, K., & Franke, A. G. (2014). Life context of pharmacological academic performance enhancement among university students - a qualitative approach. BMC Medical Ethics, 15(1), 23-23. doi:10.1186/1472-6939-15-23

Authorship- the authors are well educated to carry out the research as Elisabeth Hildt works as a neuroethic expert. Klaus Lieb and Andreas Günter Franke belong to the Department of Psychiatry and Psychotherapy, University Medical Centre Mainz (Germany). Franke is a trainee under the guidance of the former.

Research Aims- The study aimed to investigate the effects of illicit and prescribed psycho-stimulants on academic performance. The effects of drugs such as, methylphenidate and amphetamine on examination performance were assessed. The student experiences were measured on administration of smart-drugs. Furthermore, influence of several factors such as academic and peer pressure on academic performance were also measured (Hildt, Lieb & Franke, 2014).

Design- Students were recruited from the University of Mainz campus, followed by conduction of semi-structured, face-to-face interviews. The questions focused on illicit or prescribed consumption of stimulants, individual perception of their effects on academics and any observable negative effects. After being transcribed verbatim, the responses were analysed systematically using a qualitative approach. The transcriptions were analysed by 2 raters who were blind to the study. The categories of responses were selected for final analysis on which both the raters showed agreement.

Findings- 18 out of 22 interviews were analysed. 4 students were reportedly under the use of prescribed stimulants. Rest were involved in illicit drug usage. The average age for the use of first stimulants was found to be 20.4 ± 2.88 years.The stimulants were used for facilitating exam preparation, gaining study time, and pursuing individual projects, out of academic domains (a career in music along with university study). Time pressure and performance affected the intake. Reports suggested increased in motivation and reduction in sleep time after drug usage (Farah et al., 2014). Thus, time maximisation and boosting motivation were the most important effects.

Research Aims

Strengths and weaknesses- One limitation was the relatively small number of interviews. Only 22 out of the 36,000 registered students were recruited. Drug related stigma resulted in low participation. Moreover, excluding willing participants with psychiatric disorders or under psychoactive medications, led to selection bias. Social desirability, time frame and behavioural aspects acted as major influencing factors. However, the strength lies in the fact that it acted as a starting point for further conduction of qualitative and quantitative studies on effects of stimulants on academic performance.

Munro, B. A., Weyandt, L. L., Marraccini, M. E., & Oster, D. R. (2017). The relationship between nonmedical use of prescription stimulants, executive functioning and academic outcomes. Addictive Behaviors, 65, 250-257. doi:https://dx.doi.org/10.1016/j.addbeh.2016.08.023

Authorship- Marisa E. Marraccini and Lisa L. Weyandt worked as Professors. Oster and Munro were Doctoral Research Assistants in the same university. Thus, the authors were well educated to conduct the study. Voluntary participant inclusion and generalization led to some discrepancies.

Research Aims- Executive functioning encompasses self regulation and cognitive flexibility and underlies academic performance. This study evaluated the association between non-prescribed psycho-stimulant use and executive functioning among college students (Munro et al., 2017).

Design- Eligible participants were selected from schools and public universities and had to complete 2 sets of questionnaire following informed consent. The questionnaire was based on gender, ethnicity, age, university names and membership status of sonority or fraternity.  Non-medical use of prescribed psycho stimulants was measured. Barkley Deficits in Executive Functioning Scale assessed adult executive functioning dimensions. An EF summary score was generated followed by t-test analysis.

Findings- This study identified for the first time, the relationship between non-medical use of psycho-stimulants and executive functioning of the brain. Majority of participants were found to be females. Higher SSQ score was found among students with EF deficits. 35.4% participants showed clinically significant EF scores. They were more likely to be associated with non medical psycho-stimulant use. In addition, a low grade point average was found among them. Furthermore, an increase was observed in the usage of NMUPS across the class years. Thus, procrastination and time-management difficulties were found to be related to NMUPS usage.

Strengths and weaknesses- The study determined association between brain EF and psycho-stimulants use. It also established academics to be the major reason for drug abuse. Therefore, it identified students who were at a risk of drug usage and could be used to design prevention policies. Presence of convenient sample and study generalization was a limitation. Selection bias occurred due to disproportionate number of females and Whites. Assessing psycho-stimulant effects on the brain were disturbed due to presence of 3 participants with <2 GPA score. Furthermore, voluntary participants might suitably represent the entire population.

Design

Barriers for the application of evidence in practice- Evidence-based practice (EBP) integrate best research evidences from well formulated studies. Some of the common barriers are inadequate knowledge, time management, low IT access and lack of motivation (Laska, Gurman & Wampold, 2014). Low English proficiency also creates major difficulties in EBP implementation (Sadeghi?Bazargani et al., 2014). Although, psycho-stimulant drugs treat ADHD symptoms, there was lack of adequate information on their role in academic performance and cognitive skill improvement. Further, inadequate access to large libraries and computer resources create hindrance in EBP implementation (Grant, Stuhlmacher & Bonte-Eley, 2012). Owing to the fact that EBP is a time consuming procedure, a major barrier exists in the form of time commitment (Kim et al., 2013).

Alignment with PICO elements- The 2 studies showed complete adherence to the PICO format (Cooke, Smith & Booth, 2012).

1. PICO structure (Munro et al., 2017):

Population- University students; Intervention- Nonmedical prescribed stimulant use; Comparison- Students with EF deficits compared to those without deficits; Outcome- Psycho-stimulant effects on executive brain functioning.

2. PICO structure (Hildt, Lieb & Franke, 2014):

Population- University student using psycho-stimulant; Intervention- Psycho-stimulant effect on academics; Comparison- Stimulant using students compared to placebo group; Outcome- Psycho-stimulant effect analysis. 

Conclusion

Thus, it can be concluded by analysing the two articles that psycho-stimulants demonstrate some potential side effects on people who use these drugs. The first research article is considered to be more successful because it provided direct evidences of the effects of smart drugs on improved academic outcomes. A thorough analysis helps in considering the first research study superior to the second research because the former study revealed that an enhancement of academic skills upon the administration of psycho-stimulant drugs is not an isolated phenomenon. Furthermore, the first research article also established that a multifaceted life context operates and controls the phenomenon of alertness and staying awake, in addition to the action of the smart drugs. To summarize, it was established that an improvement in cognitive skills led to better academic performance. Therefore, it can be stated that intake of smart drugs is not adequate for improving academic performance among Wasim’s university classmates.

References

Arnold, L. E., Hurt, E., & Lofthouse, N. (2013). Attention-deficit/hyperactivity disorder. Child and Adolescent Psychiatric Clinics, 22(3), 381-402.

Burgard, D. A., Fuller, R., Becker, B., Ferrell, R., & Dinglasan-Panlilio, M. J. (2013). Potential trends in Attention Deficit Hyperactivity Disorder (ADHD) drug use on a college campus: wastewater analysis of amphetamine and ritalinic acid. Science of the Total Environment, 450, 242-249.

Cooke, A., Smith, D., & Booth, A. (2012). Beyond PICO: the SPIDER tool for qualitative evidence synthesis. Qualitative Health Research, 22(10), 1435-1443.

Farah, M. J., Smith, M. E., Ilieva, I., & Hamilton, R. H. (2014). Cognitive enhancement. Wiley Interdisciplinary Reviews: Cognitive Science, 5(1), 95-103.

Grant, H. S., Stuhlmacher, A., & Bonte-Eley, S. (2012). Overcoming barriers to research utilization and evidence-based practice among staff nurses. Journal for Nurses in Professional Development, 28(4), 163-165.

Hildt, E., Lieb, K., & Franke, A. G. (2014). Life context of pharmacological academic performance enhancement among university students–a qualitative approach. BMC medical ethics, 15(1), 23.

Kim, S. C., Brown, C. E., Ecoff, L., Davidson, J. E., Gallo, A. M., Klimpel, K., & Wickline, M. A. (2013). Regional evidence-based practice fellowship program: Impact on evidence-based practice implementation and barriers. Clinical Nursing Research, 22(1), 51-69.

Laska, K. M., Gurman, A. S., & Wampold, B. E. (2014). Expanding the lens of evidence-based practice in psychotherapy: a common factors perspective. Psychotherapy, 51(4), 467.

Munro, B. A., Weyandt, L. L., Marraccini, M. E., & Oster, D. R. (2017). The relationship between nonmedical use of prescription stimulants, executive functioning and academic outcomes. Addictive behaviors, 65, 250-257.

Sadeghi?Bazargani, H., Tabrizi, J. S., & Azami?Aghdash, S. (2014). Barriers to evidence?based medicine: a systematic review. Journal of evaluation in clinical practice, 20(6), 793-802.