Article summary & critique rubric = 30 total points available
- Turn in assignment on time, with appropriate length (minimum 600 words) = 4 points
- 1 day late: -2 points; >1 day late: -4 points
- Between 550-600 words: -1 point; between 500-549 words: -2 points, etc. No maximum length but try to be concise.
- Summarize the article in sufficient detail = 13 points
- Identify the research question that the study aimed to investigate
- Review the study methodology, including the participants used and the main procedures of the study. Identify hypothesis/hypotheses, if any.
- Summarize the main results/findings of the study and the authors’ interpretation of the results
- Critique and reflect on the article (identify limitations of the study, or things that could have been done better) = 13 points
- Include comments specific to flaws or suggested improvements in the experimental design, results, or interpretation of the data
- You may also provide commentary relating to personal relevance or real-world applied relevance of the article if you wish (but make sure to also address 3a.)
Your summary/critique will be submitted to CANVAS as a word or pdf file.
Example summary/critique
Insufficient sleep and its affects on risk-taking behavior: Summary and Critique
The authors of this study were interested in collecting data on how chronic sleep restriction and acute sleep deprivation, as compared to the suggested amount of sleep, may affect how a person functions cognitively and examining the underlying mechanisms of sleep restriction. It was hypothesized that subjects with less sleep would perform riskier behaviors than those who were well rested. The basis for this research question originated from the author’s belief that an insufficient amount of sleep is a concern due to its prevalence in today’s society, and is thought to have an adverse affect on health and community burden. To be able to objectively measure the affect on cognitive ability, the researchers chose to evaluate it in terms of risky decision-making, specifically financial decision-making.
Risk-taking behavior was assessed after seven uninterrupted nights of sleep restriction (as defined by the researchers as 5 hours of sleep per night) and one period of acute sleep deprivation (40 straight hours of no sleep). These were both compared to the control group (8 hours of sleep per night); participants receiving a regular sleep condition. The researchers strictly monitored the amount of sleep a participant was to receive and no naps, caffeine, alcohol, etc. were permitted in order to assure they wouldn’t be confounding variables. The independent variable for this experiment was the amount of sleep each participant received, while the dependent variable was how he or she performed the risk-taking behavior. The amount to which the participants behaved after the independent variable was implemented was measured twice a day by having the participants choose between a higher amount of money with a given probability that they will receive that money or a smaller, but assured, amount. The pairs of choices were shown four times per session in a random order. The subjects were given 8 seconds to decide which choice they preferred. After the session, they were asked to complete a survey that asked how often they thought they chose the riskier option.
Results of the study were then calculated and examined. The scores were given based on the calculation (EV – CE)/EV * 100, where EV represented the percent to which the value was expected and the CE (certainty equivalent) represented the amount of money the subject believed to be equivalent to the risky option. The answer was reported as a percentage. If the risk-taking behavior was approximately normal, the percentage could be expected to near 0%. For riskier behaviors the value was more negative, while the value was increasingly positive for aversion behaviors. From this, a distribution of the data was plotted.
A sleep study was conducted using a high-density EEG net, with a total of 128 electrodes. The slow waves during sleep were observed, as were the cortical areas of the brain. Multiple other calculations and assessments were performed to analyze results, including an analysis of variance (ANOVA), McNemar’s test, Pearson’s chi-square test, and a psychomotor vigilance test (PVT). It was concluded that lower slow wave sleep intensity around the right prefrontal cortex correlated with increased financial risk taking.
It was determined through the results that only the sleep restriction variable resulted in significantly higher risk-seeking behavior. Of the 14 participants, 11 of them showed an increase in risky behavior after the sleep restriction. In addition, 6 participants changed from risk-aversive to risky after having the sleep restriction. From this, it was determined that both categories of risky and risk-aversive increased their risky behavior after the sleep restriction. It was indicated through the results that the sleep restriction did significantly affect risk-preferences, but it did not affect the general behavior in terms of lapses in attention.
Overall, the researchers clearly operationally defined all the variables they were working with, making the study capable of being reproduced. Many tests were performed and multiple trials were repeated, along with the addition of a task validation group, to ensure all of the variables were accounted for. However, the generalizability of this study is practically nonexistent. The researchers specifically chose 14 healthy, male students as participants aged from 18-28 years. Men with sleep-related diseases, regular medication intake, history of seizure or traumatic brain injury, and drug or alcohol abuse were excluded from the study, among other variables. In addition, subjects could not study math, psychology, economics, physics, or computer science and participate in the experiment. Although these strict restrictions would not affect the accuracy of the results obtained, assuming there was a random sample of participants in each sleep variable, they would make the study unable to be generalized.
Furthermore, no women were allowed to participate in this study, so the results obtained here wouldn’t be able to be assumed as accurate for women (approximately half of the population). In addition, it is unclear if age would have an affect on this, so the study would need to be repeated to obtain results on older and younger populations. Anyone with any of the many restrictions (including field of study in school) would not be generalizable to, as their variable may have an effect on the results. Even men of similar age wouldn’t necessarily be able to be generalized to, as the men in this study were capable of going to college, and therefore would have a different socioeconomic status than many people, potentially affecting the results (i.e., poorer groups may be more stressed in general, potentially affecting the amount of sleep per night they receive). Although this study thoroughly addressed the research question proposed, the results would not pertain to most of the population, unless multiple other studies were to be conducted.
On a personal level, the main finding that sleep restriction leads to an increase in risk-taking behavior resonates with me, given that after being sleep deprived, I have sometimes found myself taking chances that I otherwise may not have – for example, speeding or other more erratic driving behavior. I also wonder what other increases in risky behavior I might be engaging in after sleep deprivation that I may not even be aware of. This research question has large real-world relevance, since in this day and age so many Americans, especially students, tend to be sleep-deprived. Given that this may result in putting ourselves at greater risk via higher risk-taking behavior, it seems that an important implication is to try to maintain an appropriate sleep schedule, in order to best protect ourselves from risk-taking behavior that could put us in danger.
