The research conducted by the investigators to test the efficiency of energy drinks in decreasing driver sleepiness presents various issues with threats to internal validity and experimental design. These issues may lead to concerns over the validity of their conclusion. This paper identifies several issues with this experiment.
Lack of Control Group
This experiment did not have a control group. It is challenging to attribute observed effects to the energy drink itself without a control group. For example, the observed decrease in lane drift and sleepiness among the learners could be because of other aspects besides the energy drink, like placebo effects and the novelty of the driving simulator. Also, the scholars who received the energy drink may have been extra attentive and alert during the second driving session because they were more excited or encouraged to participate in this research. However, the investigators cannot rule out these alternative explanations without a control group (Campbell & Stanley, 2015). This phenomenon threatens the internal validity of this study.
Small Sample Size
This research had a small sample size. For example, the study had only 20 undergraduate learners chosen from a single university. Still, the selected students originated from the investigators’ classes, resulting in sampling bias. The probable sampling bias, together with the small sample size, compromises this study’s external validity. Generally, the small sample size and its absence of representatives may limit the findings’ generalizability (Reichardt & Little, 2019). Thus, the research’s outcomes regarding the efficiency of energy drinks in decreasing driver sleepiness might not be generalizable to a more diverse and larger population. The investigation’s results may not be applicable to other circumstances. Choosing participants from one university might not offer adequate diversity to generalize the study’s findings.
The Absence of Experimental Control
This research utilized one beverage, Red Bull, representing all energy drinks. Red Bull may not be a representative sample of all energy drinks available. The investigators never gave a clear reason for choosing this drink. They also did not examine other energy drinks to ascertain whether there are variations in efficiency (Reichardt & Little, 2019). Thus, this absence of experimental control compromised the study’s internal validity. Still, the research never offered facts regarding whether the scholars had any prior experience with energy drinks, which may have affected their reaction to Red Bull.
Lack of Counterbalancing
The researchers never used counterbalancing to control for order effects. For example, learners drove for 15 minutes before taking Red Bull and for two hours after drinking it. Therefore, the order in which these scholars performed the tasks was never randomized. This phenomenon means that some learners might have driven more skillfully in the last session because they had become extra familiar with the simulator or had more experience, compromising the internal validity of this research. Counterbalancing would have permitted the investigators to alternate driving session orders for every scholar (Miller et al., 2020). This initiative would have decreased the possibility of order effects.
The research carried out by the investigators to examine the efficacy of energy drinks in decreasing driver sleepiness demonstrates several issues with threats to internal validity and experimental design. The issues compromise the validity of the investigators’ conclusions that taking energy drinks decreases driver sleepiness better than other standard techniques. This phenomenon underlines the essence of careful consideration of experimental control and design in conducting scientific studies. The researchers should carry out further investigation with more diverse and larger samples and extra robust experimental controls to determine the efficacy of energy drinks in decreasing driver sleepiness.
References
Campbell, D. T., & Stanley, J. C. (2015). Experimental and Quasi-Experimental Designs for Research. Ravenio Books.
Miller, C. J., Smith, S. N., & Pugatch, M. (2020). Experimental and quasi-experimental designs in implementation research. Psychiatry Research, 283(112452). https://doi.org/10.1016/j.psychres.2019.06.027
Reichardt, C. S., & Little, T. D. (2019). Quasi-experimentation: A guide to design and analysis. The Guilford Press.
write