The Consequences of Sleep Deprivation Essay Example
As humans, we experience a natural phenomenon known as, sleep. Sleep occurs when our bodies are relaxed and we enter an altered state of mind that consists of unconsciousness, muscular inhibition, and induced interactions. Although we all experience sleep, majority of those experience another phenomenon known as sleep deprivation. Sleep deprivation is a condition in which people suffer from a lack of sleep. On average, an individual should get seven hours of sleep per night, however, statistically, 35% of humans are not getting the recommended seven hours (1 in 3 Adults Don’t Get Enough Sleep, 2016). Having the knowledge and experience of sleep deprivation, it is understandable of why these next three articles will be helpful when expressing the need for sleep. To continue, Gould and colleagues (2009), Aidman and colleagues (2018) and Talbot, McGlinchey, Kaplan, Dahl, and Harvey (2010) all explain what happens when humans do not get enough sleep; whether it is from real-world tasks that require long periods of wakefulness, driving performances, or the effects of behaviors between adolescents and adults. If humans experience lack of sleep, then it is apparent that negative consequences will occur to the human body.
As stated before, sleep deprivation affects the quality of peoples jobs and Gould and colleagues (2009) objective was to evaluate if total sleep deprivation (TSD) affected high-speed ship navigations. Along with their research, their hypotheses’ consisted of if participants were deprived of sleep then their execution of high-ship speed navigation would be hindered (Gould et. al, 2009). Another hypothesis is when using the electronic chart display and information system (ECDIS) people would experience extreme tiredness due to increased labor (Gould et. al, 2009). Electronic chart displays and information is used for navigational purposes which is an alternative for paper charts that tell the searchers their position, speed, and where the ship is headed (Gould et. al, 2009). Having the hypotheses involved is important because the first hypothesis involves how decreased speed and reaction time hinders their workload. Additionally, in the second hypothesis it navigates how the variables are switched, which explains the difference between workers who experienced enough sleep compared to those who did not (Gould et. al 2010). To continue, their independent variable was sleep deprivation whereas their dependent variable was those who were affected by sleep deprivation.
Once participants arrived at the laboratory, researchers insisted on no alcohol or caffeine consumption for 48 hours prior to the study (Gould et. al, 2009). Along with no alcohol or caffeine, their sleep schedule was also construed. Researchers directed each group to sleep between 11:00PM to 12:00AM and were advised to wake up between 7:00AM to 8:00AM (Gould et. al, 2009). The next morning, the study commenced. Each group was given thirty minutes to familiarize themselves with the navigation and the study took fifty-five minutes to complete (Gould et. al, 2009). While the study was happening, ten minute breaks were set and within those ten minutes, new roles were assigned so each participant could undergo the study (Gould et. al, 2009). Studies show that those who were falling asleep were woken up by an assistant. Once the study was complete, participants were driven home by a taxi (Gould et. al, 2009). The independent variable of sleep deprivation was operationalized by researchers changing when participants could sleep and wake up (Gould et. al, 2009). The dependent variable was operationalized because speed decreased when sleep deprived participants navigated the ship compared to when participants attained a full nights of sleep. (Gould et. al, 2009).
After the study was completed, researchers found that sleep deprivation did not affect the participants when navigating, however, their navigation skills increased when using the electronic displays and information system (Gould et. al, 2009). To continue, researchers assumed that participants would be unable to navigate when sleep deprived, however, their hypothesis was incorrect thus making it not consistent with their predictions. Also, the results indicated that navigation had to deal with teamwork abilities and lack of teamwork in one group construed their studies. Along with the ability to work together, disturbance of group members led to decline in mood and communication (Gould et. al, 2009).
Moreover, Adman’s and colleagues (2018), purpose is testing driving performances under different types of caffeine. Along with their research, their hypothesis consisted of, comparing the relationship between drowsiness and task performance and if caffeine was a key factor on how participants drove (Aidman et. al, 2018). The hypothesis involved is important to add because depending on how much caffeine the participants drink before this study, it could affect others more than the rest. Also, to test it on driving exceeds the theory because drowsiness and driving combined is a result of danger. To continue, the independent variable was how much caffeine was given over a period of time and how much participants slept whereas the dependent variable was the quality of participants’ drivers (Aidman et. al, 2018).
Prior to the actual study, when participants arrived at the driving performance, each party was assigned to sleep at least eight hours in bed for a week (Aidman et. al, 2018). Along with how many hours the participants received, caffeine was involved, and each group received 200mg of candy and received it every two hours (Aidman et. al, 2018). Also, the other group consisted of the placebo group, and were instructed to chew on non-caffeinated gum and both groups had to chew for five minutes to gain the full effect (Aidman et. al, 2018). The driving portion consisted of how sensitive it was when caffeine entered the body, and the driving test was the main part of the study at the site (Aidman et. al, 2018). Furthermore, the independent variable of sleep was operationalized by controlling the number of hours of sleep that the subjects received (Aidman et. al, 2018). Caffeine was operationalized because researchers were giving participants exactly 200mg of caffeine and taking it every two hours (Aidman et. al, 2018). The dependent variable was operationalized through the standard deviation of how well each group drove in the lanes and how fast each participant went (Aidman et. al, 2018). These standard deviations led up to finding the Johns Drowsiness Scores (Aidman et. al, 2018). The researchers were interested in the Johns Drowsiness Scores because scientists wanted to see how it corresponded with standard deviations (Aidman et. al, 2018).
After the completion of the study, researchers took into consideration of the driving data. To continue, when sleep loss occurred, speed was the first affect that happened and when caffeine came into the study, drowsiness was recorded.
Although, caffeine is a potential affect for sleep deprivation, Talbot, McGlinchey, Kaplan, Dahl, and Harvey (2010), explain that their target is what impact of sleep deprivation has on healthy participants aging from adolescence, mid-adolescence, and adulthood (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). Along with this, their hypothesis consisted of, if they are sleep deprived, then anxiety will increase along with extreme tiredness and participants’ potential to becoming more hostile (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). The hypothesis is important to understand because sleep deprivation is linked to mental disorders such as anxiety or depression. To test how participants are when they are sleep deprived will show how moods vary in research subjects. To continue, the independent variable is the number of hours of sleep they got, whereas the dependent variable is their level of anxiousness (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010).
Before the night at the laboratory, participants were asked to sleep for 6.5 hours at most. When they arrived at the laboratory, their first portion of the research was to complete the Stanford Sleep Scale (SSS), this was to measure how tired they felt after the first night (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). For the second night, all participants had to stay at the laboratory. All subjects were given options to do activities other than sleeping such as; watching television, eating, or talking to others (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). No caffeine or substances were added to alter how awake each contributor felt. After awaking from the second night, everyone had to take the SSS again. This was to see how the results compared from the first night (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). The independent variable was operationalized by the Stanford Sleep Scale (SSS) and how many hours’ participants received. To continue, the dependent variable was operationalized by how much caffeine researchers gave and how it affected each participants’ behavior.
After the completion of the study, researchers gathered the data that participants felt less positive behaviors, such as happiness, energetic, excitement, and active (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010) when sleep deprived, which makes their predictions consistent. To continue, researchers also predicted that increase of negative moods would occur when loss of sleep occurs, however, the opposite occurred, studies show that instead of negative behaviors, mental disorders such as anxiety increased (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). The correlation between anxiety and sleep deprivation was their second prediction and these two were consistent. To continue, anxiety increased when participants were sleep deprived and researchers believed that having a well-rested sleep is a method to reduce mental disorders such as anxiety or depression in adolescents (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010).
Although Gould and colleagues (2009), Aidmand and collegeues (2018), and Talbot, McGlinchey, Kaplan, Dahl, and Harvey (2010) are punctual about each of their articles, in my opinion, certain aspects of the independent variable could be changed. To continue, Gould and colleagues (2009) stated their independent variable was sleep deprivation, and this can be operationalized by researchers giving each participant how many hours each of them could sleep. In Aidman and colleagues (2018), their independent variable was caffeine intake and this can be operationalized by each group getting a different amount of caffeine. Moreover, Talbot, McGlinchey, Kaplan, Dahl, and Harvey’s (2010) independent variable was the number of hours’ participants received and this could be operationalized by letting participants sleep at times comfortable to themselves compared to setting an exact time that would affect their mood.
Each of the studies could have been misconstrued because it would affect how accurate the researchers’ findings were and if the participants actually participated in the study. To continue, if experimental participants joined the study, responses would have been similar because sleep deprivation was the study and there was a significant increase in loss of sleep when navigating the ships (Gould et. al, 2009). As for, if experimental participants joined the caffeine intake, their results would be different because certain participants could be immune to caffeine whereas others would be susceptible to caffeine. If experimental participants were involved with attitude, results would be different because changes in behavior would not be linked to previous emotions or affects from sleep deprivation (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010).
Additionally, a confound that would have affected the study would be the five participants that could not follow up the following week with the study (Gould et. al, 2009). This can cause a negative skew in the study because researchers can no longer compare when participants got a full nights of rest compared to when they did not. A confound in caffeine intake would consist of if participants are immune to caffeine or not. Being immune to caffeine would affect this study because the driving course would be easy for someone that intakes caffeine on a daily compared to those who do not. Therefore, a confound in attitude while sleep deprived would be blaming our negative attitudes on sleep when it reality, loss of sleep would not be a factor for some cases. The hypothesis seemed logical, however, the results showed that the ships ocean travel was not affected thus making an additional hypothesis needed (Gould et al, 2009). To continue, with the added hypothesis of ocean travel, results would have potentially been misconstrued.
The hypothesis of caffeine affecting others more or less is logical because as stated before, the confound of those who are heavily reliable on caffeine was not taken into consideration. Similar results could occur when viewing from different contexts because withdrawal tends to increase when participants become less dependent on caffeine. Lastly, the hypothesis for changes in moods is logical because mental disorders such as anxiety and or depression are possibilities of sleep deprivation. Different results could occur when dealing with different contexts because different mental disorders could already be attributed with the participant which results in the potential increase of developing more disorders. Furthermore, different results could happen because sleep deprivation could be genetic or inherited.
With the knowledge of how sleep deprivation affects periods of wakefulness, it is possible that my hypothesis is leading me to the right direction because speed was the only factor affected in the study (Gould et. al, 2009) and if being deprived of sleep affects how participants work, an increase of repercussions will occur. Moreover, the intake of caffeine and difference of attitudes could potentially play a role in my research because the more information that each of these authors bring up, the more possibilities of manipulation will occur to my independent and dependent variable.
These three articles have helped align my research ideas because in Gould and colleagues (2009) their goal was to test if sleep deprivation affects those that work for long periods of time and if sensitivity in sleep deprivation also affects their work. The correlation between sleep deprivation and sensitivity affects my research because when sleep becomes the least important in someone’s daily life, their performances on certain tasks become sensitive. Along with performances, Aidman and colleagues (2018) compares the differences between drowsiness and performance while driving. When driving becomes obstruct it usually happens when drowsiness occurs and humans’ reaction times are slower, speed could potentially increase or decrease, and it can result into falling asleep behind the wheel (Aidman and colleagues (2018). Moreover, not only will being sleep deprived affect driving, but individuals’ attitudes will also change.
Talbot, McGlinchey, Kaplan, Dahl, and Harvey (2010) explain the differences between adolescents and adults, two items were measured; loss of sleep and the amount of sleep received. This article helped with my research because positive and negative effects were explained when adolescents and adults would not get enough sleep; meaning their moods, energy, and anxiety would either increase or decrease due to the amount of sleep they loss (Talbot, McGlinchey, Kaplan, Dahl, and Harvey, 2010). With these three articles in mind, my independent variable will consist of sleep deprivation and irritability whereas my dependent variable will consist of negative consequences that occur when sleep is lost.
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