Sleep Study and Electronics Usage

Introduction
The purpose of this study was two-fold: 1) it aimed to identify relationships between sleep and other aspects of human functioning/performance; and 2) it sought to understand how sleep-wake patterns impact daytime functioning. The subject of this research was the researcher himself. The researcher kept a 4 week sleep diary with which to record information pertaining to sleep habits and daily life habits in order to test the conclusions of Bower, Bylsma, Morris and Rottenberg (2010) regarding their findings that poor reported sleep quality is predictive of low positive affects in daily life among persons of both healthy and disordered mindsets. Having a healthy mind, the researcher aimed to evaluate the extent to which sleep quality impacted his overall quality of life.
This topic is important because as Monk, Petrie, Hayes and Kupfer (1994) show, regularity in one’s daily life bears some relation to the development of the personality, one’s restfulness, sleep quality, and age. In order to better understand the relationship between sleep and how people operate when they are awake, this study examined one subject as a starting point for identifying how this relationship might appear in an up close and personal way.
This study aims to advance current research on sleep and human performance by focusing specifically on these distinct variables: 1) the number of caffeinated drinks consumed during the day, 2) the mood of the subject that day, 3) the energy level of the subject that day, 4) length of naps taken that day, and 5) whether electronics were used within one hour of sleep. These variables are all common factors in daily life, but it is not well known whether they are impactful on sleep quality. Fossum, Nordnes, Storemark, Bjorvatn and Pallesen (2014) have found that “computer usage for playing/surfing/reading was positively associated with insomnia, and negatively associated with morningness” (p. 343). In the researcher’s own life, he has not found electronic device usage so close to going to bed to be a noticeable factor in sleep quality and morningness—thus this study also aimed to test the findings of Fossum et al. (2014) in order to show how accurate the conclusions reached by these researchers were and whether they apply to all ethnicities. Considering that the subject of this study was an Hispanic male, the findings will add a degree of complexity currently missing from the study on sleep, electronics usage and mood relationship.
The research question for this study was: What is the relationship between mood during the day, electronics usage, hours slept and morningness for the researcher? While the sleep diary recorded other variables for study as well, the four identified in the research question received the main focus of analysis as they pertained the issue of testing the prior research on sleep, mood and electronics usage. The researcher hypothesized that there would be no clear relationship among these variables based upon a cursory reflection of the researcher’s own sense of sleep quality and daily life prior to keeping the sleep diary.
Methods
In order to obtain data for this study, a sleep diary was maintained for four weeks. Included in the sleep diary were the following data entry points: 1) a column for recording the day of the week; 2) a section for completing at the end of the day (just before going to bed); and 3) a section for completing at the start of the day (upon waking up in the morning). The end-of-day section contained five variable columns consisting of: a) number of caffeinated drinks consumed that day; b) the subject’s mood, ranked from 0 to 10 with 0 representing all negative and 10 representing all positive; c) the subject’s energy level that day, ranked from 0 to 10 with 0 representing no energy all day and 10 representing high energy all day; d) length of time spent napping that day; and e) electronics usage within 1 hour of going to be—electronic devices included in the checklist for this column included: TV, video games, computer, phone/PDA, iPad or tablet.
The complete-in-the-morning section consisted of six sleep-related data points: a) the time at which the subject went to bed at night; b) the time at which the subject got out of bed in the morning; c) the time it took to fall asleep at night; d) the number of times the subject woke up; e) the degree of morningness experienced by the subject—checklist items included: refreshed, somewhat refreshed, tired, and exhausted; and f) the total number of hours slept during the night.
The subject of the study was the researcher himself: he is a 23 year old, Hispanic male, in his senior year of college. He commutes to school daily.
The variables were measured over the course of 4 weeks total, beginning from January 29th, 2018 and lasting to April 8th, 2018.
The four main variables focused on for this study were two sleep-related variables and two daily-life related variables: the two sleep-related variables were: 1) total number of hours slept and 2) level of morningness felt upon waking up; the daily life variables focused on were: 3) mood and 4) electronic usage.
Results
Graph 1. Hours slept


The total number of hours slept over the course of the four weeks in which the sleep diary was maintained showed a range of sleep between 5 and 8 hours. 5 hours of sleep were obtained only twice during the four weeks. The majority of nights between 6 and 8 hours of sleep were obtained.

Graph 2. Level of Morningness


The level of morningness ranged from feeling tired to feeling refreshed. On only 6 of the 28 days did the subject experience feeling tired upon waking. The rest of mornings showed that the subject felt either somewhat refreshed refreshed.

Graph 3. Mood during the Day


The mood during the day ranged from 6 (just slightly above neutral) to 10 (all positive) during the course of the 4 weeks. The mood experienced never dipped into negative territory and the majority of the days showed that the subject felt positive mood during the day.

Graph 4. Electronics Usage

Electronics usage before bed was somewhat consistent with anywhere from 1 to 3 devices being used within one hour of going to bed every night of the 4 week study. The majority o the time at least one to two electronic devices were used before bed.

Discussion
The research question was: What is the relationship between mood during the day, electronics usage, hours slept and morningness for the researcher? The hypothesis was that there would show little to no strong correlation among the variables.
How Do Trends Within Graphs And Across Graphs Relate To One Another?
Trends within graphs and across graphs bear some relation to one another, indicating that correlation may indeed exist. However, the study’s weakness is that it only focused on four variables to analyze, when it appears that a number of extra variables could also be assessed in order to identify relationships.
Of the variables examined, the strongest correlation was between the number of hours slept and the level of morningness—i.e., if 6 or fewer hours were slept, the subject experienced feeling tired upon waking. The one outlier was during week 2 when the subject obtained only 5 hours of sleep on the first night of the week but still felt somewhat refreshed upon waking in the morning. That night only one electronic device was used before going to bed and the mood of the subject was all positive for the day with a perfect score of ten.
Another trend across graphs was that mood diminished as the number of hours slept during the night diminished. A few outliers existed but they were not strong outliers and the variance was slight (between 7 and 8 hours of sleep correlating with a mood variance of 1-2 points). Level of morningness across these two graphs also showed a consistency within feeling somewhat refreshed to refreshed. Electronics usage was not seen to have a significant impact on mood during the day, but sleep hours during the night definitely suggested a strong correlation as the trends lined up closely: the more sleep obtained, the better the mood on most days.
What Can We Conclude From These Relationships?
Because the sample size is so small it would be inappropriate to conclude anything significant from these relationships: however, examining the relationship in terms of the researcher’s own life shows that more focus should be given to electronics usage to see if the time spent using them prior to bed has anything to do with restfulness. It would also be worth looking into to see whether there is a sharp contrast among other ethnicities—comparing Hispanics with Europeans and Asians and Americans and Africa-Americans.
Do These Relationships Correspond With Findings From Previous Research? Why or Why Not?
These findings proved the hypothesis correct in the sense that electronics usage did not figure predominantly into level of morningness or mood felt during the day, so the studies by Fossum et al. (2014) and Bower et al. (2010) were not verified by this study’s findings. However, some explanation as to why this is could be provided. For example, the subject may have a high tolerance for electronics usage, especially as this is the Digital Age and young people are more accustomed to using electronic devices all day, every day—so the negative impact of these devices on young people of this generation may be significantly different from persons who reached adulthood prior to the onset of the Digital Age. This relationship should be examined in more detail using more subjects in a larger sample so as to compare relationships.
Are There Other Variables Not Measured In Your Study That Help To Explain Results?
Variables not measured in the study that might help to explain results are: 1) job during the day—this might impact mood and energy; 2) time spent recreating during the day—which might also impact mood and energy; 3) familiarity with electronics devices—as stated above, this could make a difference in the extent to which it impacts sleep for a younger generation accustomed to using these devices all day every day; and 4) hours of sleep the subject is accustomed to getting on average in the previous months prior to the study.
Conclusion
While there may be some important relationships between these variables, this study does not provide conclusive evidence either way. What needs to be studied more in depth is the matter of age (generation) and ethnicity to see if young persons of the Digital Age are more or less impacted by electronics usage before bed than are older persons of the pre-Digital Age. Familiarity with electronics devices may have a neutral impact on sleep quality. What this study did show was that the hours of sleep obtained each night made the biggest difference on the quality of mood and morningness for the subject in this study.


References
Bower, B., Bylsma, L. M., Morris, B. H., & Rottenberg, J. (2010). Poor reported sleep
quality predicts low positive affect in daily life among healthy and mood?disordered persons. Journal of Sleep Research, 19(2), 323-332.
Fossum, I. N., Nordnes, L. T., Storemark, S. S., Bjorvatn, B., & Pallesen, S. (2014). The
association between use of electronic media in bed before going to sleep and insomnia symptoms, daytime sleepiness, morningness, and chronotype. Behavioral Sleep Medicine, 12(5), 343-357.
Monk, T. H., Petrie, S. R., Hayes, A. J., & Kupfer, D. J. (1994). Regularity of daily life in
relation to personality, age, gender, sleep quality and circadian rhythms. Journal of Sleep Research, 3(4), 196-205.