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COVID-19 and HBCU Students

1. Birthday:

2. Age (circle one)

(1) 15-19 (2) 20-24

(3) 25-29 (4) 30–34

(5) 35+

 

2. Race (circle one)

African American White

Hispanic/Latino Asian

Other: ________

 

3. Employment Status (circle one)

(2) Employed

(1) Retired

(0) Unemployed

4. What HBCU do you attend

____________________________________

5. Did you receive Emergency Funding (College CARES Act, PPP, Stimulus, EBT) as a result of Covid-19? (circle one)

(2) Yes (2) No

6. Have You ever tested positive for COVID-19 (circle one)

(2) Yes (1) No (0) Unknown

7. How many days did you engage social distancing, quarantine or isolation as a result of testing positive for Covid-19? (Circle One)

(1) 0-5days (2) 5-7 days

(3) 7-10 days (4)10-14 days

Other ______

8. What were the COVID-19 restrictions that you experienced? (circle one)

a. stay-at-home order (1)

b. closing public places (2)

c. mask mandates (3)

d. travel restrictions (4)

e. all of the above (5)

f. none of the above (0)

9. Have recommendations for socially distancing caused stress for you? (circle one)

(3) A lot (2) Somewhat

(1) A little (0) Not at all

 

10. Have recommendations for socially distancing caused stress for your family and loved one? (circle one)

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

11. In the past two years have you experienced the following because of Covid-19: (Circle one)

(1) Not enough money to pay rent

(2) Not enough money to pay for gas

(3) Not enough money to pay for food

(4) Do not have a regular place to sleep or stay

(5) All The Above

 

12. In the past two years have your family or loved one experienced the following as a result of Covid-19:

(1) Not enough money to pay rent

(2) Not enough money to pay for gas

(3) Not enough money to pay for food

(4) Do not have a regular place to sleep or stay

(5) All The Above

 

13.Which aspect of Covid-19 affected you the most: (Select One)

(1) Socially Distancing

(2) Isolation & Quarantine

(3) Covid-19 Death of Immediate Family Member

(4) Covid-19 School Mandated Remote Learning

(5) Covid-19 Mandated Testing & Vaccinations

(6) Covid-19 Mandated Closings

14. To cope with your previous response, which action did you take most and how often? (Select one)

14A.Taking care of your body, such as deep breaths, stretching, or meditating

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

14B. Connecting with others, including talking with people you trust about your concerns

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

14C. Smoking more cigarettes or vaping more

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

14D. Using prescription drugs (like valium, etc.)

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

14E. Using non-prescription drugs

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

14F. Using cannabis or marijuana

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

14G. Drinking alcohol

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

14H. Eating high fat or sugary foods

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

14I.Cutting or self-injury

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

  

14J. Eating more food than usual

(3) A lot (2) Somewhat

(1) A little (0) Not at all 

 

 

15. Where did you get your information about COVID-19:

Friends Family

Social media News

Unknown

 

16. I believe that Covid-19 is a serious disease:

Yes No Unsure

 

17. How much information do you feel you know about Covid-19

A lot Some

A little Nothing

 

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Darielle Brooks

Department of Social Sciences, Allen University

Social Statistics

March 10, 2022

Covid-19 Mandates


Abstract 

​Covid-19 mandates, including face masking, testing, and vaccinations, have resulted in significant psychological implications among individuals. Among Historically Black Colleges and Universities (HBCU) students, psychological distress like stress, anxiety, frustration, and depression led to increased alcohol and other substance use, abuse, and addiction. This study sought to establish the relationship between Covid-19 mandates and increased alcohol and other substance use, abuse, and addiction among HBCU students. The hypothesis for the study entails that Covid-19 mandates increase the use of alcohol and other substance use, abuse, and addiction among HBCU students. The Self-Medication Theory comprised the primary application model to confirm this hypothesis. The study used a correlational research design, and data was collected using questionnaires. It also utilized simple random sampling and a sample size of 100 participants. Data was analyzed quantitatively using SPSS. The findings confirmed the hypothesis. It revealed that Covid-19 mandates result in psychological distress or mental health issues such as stress, anxiety, frustration, and depression among HBCU students. It showed a positive correlation between Covid-19 mandates and increase in alcohol and other substance use, abuse, and addiction among HBCU students. As the students became anxious, stressed, frustrated, and depressed because of the forced masking, testing, and vaccination, they resorted to drinking and substance abuse to address the negative emotions as per the self-medication theory. They did this to cope with the negative feelings. The study concluded that Covid-19 mandates result in psychological distress, which increases alcohol and other substance use, abuse, and addiction among HBCU students.   


Key Words: 

Covid-19, mandates, psychological distress, substance use, coping.

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Literature Review

Darielle Brooks

Department of Social Sciences, Allen University

Social Statistics

March 8,202

Psychological Distress

· Stress

· Anxiety

· Frustration

· Depression

Covid-19 Mandates

(Wearing of face masks, testing, and vaccinations)

Psychological Distress

· Stress

· Anxiety

· Frustration

· Depression

Theory: HBCU students are often mandated to wear face masks, get tested, or be vaccinated for Covid-19 while being on campus, which has resulted in significant adverse psychological responses such as stress, anxiety, frustration, and depression, leading to an increased usage of alcohol and other substances, abuse and addiction.

Question: With HBCU students being mandated or forced to wear face masks, get tested, or be vaccinated for Covid-19, it resulted in significant adverse psychological responses such as stress, anxiety, frustration, and depression leading to an increased usage of alcohol other substances, abuse, and addiction.

Supporting Theory: It is hypothesized that Covid-19 mandates (wearing face masks, testing, and vaccination) increase alcohol and other substance use, abuse, and addiction among HBCU students. It is anticipated that the Covid-19 mandates each respondent encounters will impact psychological distress, leading to an increase in alcohol and other substance use, abuse, and addiction. Specifically, the research will explore if Covid-19 mandates cause psychological distress like stress, anxiety, frustration, and depression that increase alcohol and other substance use, abuse, and addiction. The Self-Medication Theory will be used to support the hypothesis. The theory holds that individuals use alcohol and drugs to change an uncomfortable emotional state (Smith et al., 2017). The use develops as a coping strategy to specific types of emotional pain in the absence of appropriate solutions or meaningful social relationships, especially during a disaster.

Independent Variable: Covid-19 mandates ​

Dependent Variables: Psychological distress (Stress, Anxiety, frustration, depression)  Increased of alcohol and other substance use, abuse and addiction

As the Covid-19 pandemic ravaged the world, governments swung into action and implemented several containment measures to prevent the virus from spreading and reduce the infection rate, associated deaths, and other social and economic negative implications. Masking, testing, and vaccinations became the norm as the primary measures to addressing this global health crisis (French et al., 2020). The authorities mandated or forced individuals to wear face masks, test, and vaccinate against the Coronavirus in the United States and other parts of the world. However, these mandates led to a significant increase in alcohol and other substance use, abuse, and addiction among Americans, including HBCU students. This drew much interest from researchers, scholars, and experts to look into this subject. Several studies have been conducted to explain the relationship between Covid-19 mandates and increased alcohol and drug use, abuse, and addiction.

Essentially, previous studies have tried to demonstrate the link between the Covid-19 mandates and increase in alcohol and other substance use, abuse, and addiction using the adverse psychological consequences as the intervening variable and the Self-medication Theory to support their claims. According to research by Smith et al. (2017) that explored the association between substance use and mental health, the results showed a strong relationship between substance use and the psychological status of individuals. Persons suffering from mental health issues such as stress, anxiety, and depression are likely to use substance abuse as a coping strategy against these negative emotions. Smith and his colleagues used the Self-Medication Theory to back up this claim. 

According to Hawn et al. (2020), the Self-medication Theory posits that individuals experiencing adverse psychological distress like stress and anxiety, mainly because of a disaster, are likely to consume alcohol and other drugs to cope with the negative feelings. In other words, they drink or take drugs to satisfy an internal need. Smith and company’s arguments and the self-medication theory can be used to explain better why alcohol and other substance use, abuse, and addiction increased among HBCU students because of the Covid-19 pandemic. Typically, the mandates to wear face masks, test, and vaccinate during the health crisis resulted in adverse psychological effects such as stress, anxiety, depression, and frustration, influencing students to take alcohol and other drugs to cope with the damaging emotions.

A survey by Roberts et al. (2021) also brought out the link between the psychological status of individuals and an increase in alcohol intake and other substances during the Covid-19 pandemic. The researchers noted that alcohol and substance use grew massively during the Covid-19 crisis by 37% and 16%, respectively, because of the changes in the mental health status. As the government agencies like the Centers for Disease Control and Prevention (CDC) mandated people to wear face masks, stay-at-home, test, and vaccinate against the virus, anxiety, stress, and frustration grew, leading to many considering taking alcohol and other drugs as a coping strategy against these feelings. The authors added that the implications of a pandemic on the rise in alcohol and other drugs use had demonstrated similar trends even in the previous crises (Roberts et al., 2021). For example, alcohol intake and substance use, abuse, and addiction increased during the September 11 bombing attack in the United States in 2021. The mandates such as thorough security checks in airports following the incident frustrated and stressed many Americans who resorted to consuming alcohol and other drugs to wade away their worries and frustrations. 

Deacon et al. (2021) supported the findings of Roberts and colleagues. In their survey to establish the effects of parental homeschooling on parents during the Covid-19 pandemics, the scholars found that mandated homeschooling resulted in negative psychological consequences such as depression and anxiety, which increased alcohol and cannabis use among parents. The parents resorted to alcohol and substance abuse coping with the adverse psychological effects. In this sense, if the findings revealed that mandated homeschooling led to psychological distress on parents, influencing them to consume alcohol and other drugs, it would be fair to say that other Covid-19 mandates like masking, testing, and vaccination yield similar results.

For instance, forcing people to test and vaccinate against the virus made them worried about the test kits and vaccine contents, leading them to alcohol and other substance use, abuse, and addiction to suppress the negative feelings. Deacon and colleagues’ claims and findings also demonstrated the role the self-medication theory plays in explaining the link between mandates and an increase in alcohol and other substance use. Essentially, the parents decided to consume alcohol and other drugs to address their internal need to manage the negative feelings of stress, anxiety, and frustration associated with the homeschooling mandate. 

In another study by Van Hooijdonk et al. (2022) that examined the effects of Covid-19 mandates such as stay-at-home orders on alcohol and substance use among university students in the Netherlands, the results revealed that substances, particularly cannabis, increased by 8.9% during the lockdowns, while binge drinking decreased from 27.8% to 13.9%. They associated the increase in cannabis with mental health problems, including depression and frustration that resulted from the stay-at-home mandate. However, alcohol consumption reduction was influenced by financial constraints and its unavailability. In other words, students lacked the money to purchase alcohol. This finding aligned with the Alpers et al. (2021) survey, which revealed that alcohol intake and substance use reduced among university students during the Covid-19 because of the business closures and disrupted supply systems. Bars and shops students could access alcohol closed down due to the lockdowns and stay-at-home orders. Also, the pandemic led to financial challenges, and students lacked adequate money to purchase alcohol or drugs, leading to a massive decrease in usage.

Besides, research by Emery et al. (2021) supported Van Hooijdonk and the company’s findings on the increase in substance use during the Covid-19 pandemic, noting that Covid-19 influenced stress and mood disorders leading to substance abuse among youth and young adults. In a survey involving 670 young adults participants from Minneapolis, Emery and colleagues found that 84% experienced mood and stress changes, and 33% reported changes in their substance use. Typically, the authors established that the Covid-19 pandemic resulted in stress and mood disorders among young adults, which influenced some of them to resort to substance use as a coping strategy. The researchers utilized the Self-medication theory to support these claims (Emery et al., 2021). The youth and young adults in the survey resorted to substance use and abuse to cope with the negative emotions linked with stress and mood disorders. 

Furthermore, Moye et al. (2022) stated that the vaccine mandates during the Covid-19 pandemic affected the mental health status of HBCU students negatively. In an online survey involving HBCU students from the North Carolina campus, Moye and colleagues established that hesitancy level to vaccination was high among HBCU students as many worried about the safety of the vaccines. As a result, some of these students developed mental health problems such as stress and anxiety, leading them to resort to alcohol and substance use,abuse, and addiction. They did this to cope with the negative emotional responses. Previous findings had explained how mental health leads to alcohol and substance initiation, use, abuse, and addiction using the self-medication theory. Dr. Ed Khantzian developed the Self-medication theory in the 1980s (Hawn et al., 2020). As the model’s name suggests, individuals with mental concerns tend to “self-medicate” by indulging in alcohol and substance use to deal with the associated negative feelings. In this sense, HBCU students decided to take alcohol and other substances to address their adverse emotions of stress and anxiety.

French et al. (2020) also pointed out that the Covid-19 pandemic resulted in job losses and business closure, subjecting many Americans to several psychological distresses like anxiety, stress, and depression. Individuals became worried about their health, finance, and future, developing adverse emotional responses. Typically, people became concerned about getting the virus. The initial phases of masking, testing, and physical distancing measures also led to mental health problems among Americans (French et al., 2020). For instance, the mandate to wear face masks caused many individuals to develop psychological distress, leading many to consider taking alcohol and other substances as a coping approach. They wanted to suppress the negative emotions by consuming alcohol and abusing drugs.

References

Alpers, S. E., Skogen, J. C., Mæland, S., Pallesen, S., Rabben, Å. K., Lunde, L. H., & Fadnes, L. T. (2021). Alcohol consumption during a pandemic lockdown period and change in alcohol consumption related to worries and pandemic measures. International journal of environmental research and public health, 18(3), 1220.

Deacon, S. H., Rodriguez, L. M., Elgendi, M., King, F. E., Nogueira-Arjona, R., Sherry, S. B., & Stewart, S. H. (2021). Parenting through a pandemic: Mental health and substance use consequences of mandated homeschooling. Couple and Family Psychology: Research and Practice.

Emery, R. L., Johnson, S. T., Simone, M., Loth, K. A., Berge, J. M., & Neumark-Sztainer, D. (2021). Understanding the impact of the COVID-19 pandemic on stress, mood, and substance use among young adults in the greater Minneapolis-St. Paul area: Findings from project EAT. Social science & medicine, 276, 113826.

French, M. T., Mortensen, K., & Timming, A. R. (2020). Psychological distress and coronavirus fears during the initial phase of the covid-19 pandemic in the united states. The journal of mental health policy and economics, 23(3), 93-100.

Hawn, S. E., Bountress, K. E., Sheerin, C. M., Dick, D. M., & Amstadter, A. B. (2020). Trauma-related drinking to cope: A novel approach to the self-medication model. Psychology of addictive behaviors, 34(3), 465.

Moye, R., Skipper, A., Towns, T., & Rose, D. (2022). Attitudes toward vaccines during the COVID-19 pandemic: results from HBCU students. AIMS Public Health, 9(1), 155.

Roberts, A., Rogers, J., Mason, R., Siriwardena, A. N., Hogue, T., Whitley, G. A., &; Law, G. R. (2021). Alcohol and other substance use during the COVID-19 pandemic: A systematic review. Drug and alcohol dependence, 229, 109150.

Smith, L. L., Yan, F., Charles, M., Mohiuddin, K., Tyus, D., Adekeye, O., &; Holden, K. B. (2017). Exploring the link between substance use and mental health status: what can we learn from the self-medication theory?. Journal of health care for the poor and underserved, 28(2), 113-131.

Van Hooijdonk, K. J., Rubio, M., Simons, S. S., van Noorden, T. H., Luijten, M., Geurts, S. A., & Vink, J. M. (2022). Student-, Study-and COVID-19-Related Predictors of Students’ Smoking, Binge Drinking and Cannabis Use before and during the Initial COVID-19 Lockdown in The Netherlands. International journal of environmental research and public health, 19(2), 812.

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in

Q1. Birthdate Q2. Age Q3. Race Q4. Employment Status Q5. What HBCU do you attend Q6. Did you receive Emergency Funding (CollegeCARES Act, PPP, Stimulus, and EBT) because ofCovid-19? Q7. Have you ever tested positive for COVID-19 Q8. How many days did you engage social distancing, quarantine or isolation because of testing positive for Covid-19? ( Q9. What were the COVID-19 restrictions that you experienced? Q10. Have recommendations for socially distancing caused stress for you? Q11. Have recommendations for socially distancing caused stress for your family and loved one? Q12. In the past two years have you experienced the following because of Covid-19: 1=A, 2=B, 3=C, 4=D, 0=E Q13. In the past two years have your family or love done experienced the following as a result ofCovid-19: 1=A, 2=B, 3=C, 4=D, 0=E Q14. Which aspect of Covid-19 affected you the most: 1=A, 2=B, 3=C, 4=D, 5=E, 6=F Q15. To cope with your previous response, which action did you take most and how often? Q15A. Taking care of your body, such as deep breaths, stretching, or meditating Q15B. Connecting with others, including talking with people you trust about your concerns Q15C. Smoking more cigarettes or vaping more Q15D. Using prescription drugs (like valium, etc.) Q15E. Using non-prescription drugs Q15F. Using cannabis or marijuana Q15G. Drinking alcohol Q15H. Eating high fat or sugary foods Q15I. Cutting or self-injury Q15J. Eating more food than usual Q16. Where did you get your information about COVID-19: Q17. I believe that Covid-19 is a serious disease: Q18. How much information do you feel you know about Covid-19 Interviewer Initials
7311999 2 1 0 Allen University 2 1 1 0 0 1 0 0 1 3 2 0 0 2 2 2 1 0 1 4 2 3
8162000 2 1 0 Allen University 2 2 3 5 1 1 0 0 4 2 2 0 0 0 0 2 3 0 2 4 2 2
4162001 2 1 2 Allen University 2 2 2 5 1 2 1 1 1 2 3 0 0 0 0 1 2 0 0 2 0 3
1201996 3 1 2 Allen University 2 2 4 5 2 1 0 0 2 2 3 0 0 0 2 3 1 0 0 3 2 3
4231999 2 1 2 Allen University 2 1 1 1 0 0 1 4 3 1 0 0 0 0 0 0 0 1 4 0 2 LDR
192000 2 1 0 Allen University 1 2 3 5 2 2 0 0 4 1 3 2 0 1 3 1 3 2 2 4 2 2
3302000 2 1 0 Allen University 2 1 1 5 2 2 0 0 3 2 1 0 2 2 2 2 2 2 2 4 0 2 LDR
9172001 2 1 2 South Carolina State University 1 2 2 1 1 1 0 0 4 3 1 0 0 0 1 1 1 0 2 4 2 3
3101999 2 1 0 Allen University 2 1 1 6 2 3 0 1 3 1 2 0 0 0 3 1 1 0 2 3 2 3 DEB
8162000 2 1 0 Allen University 2 2 3 5 2 2 0 0 4 2 1 0 0 0 0 1 2 0 2 2 2 2
9161998 2 1 2 Allen University 2 2 3 5 2 2 1 1 5 2 2 0 0 0 0 3 1 0 1 3 0 3 LDR
171998 2 1 2 Allen University 2 1 1 5 1 1 0 0 4 0 0 2 0 2 3 3 3 0 1 2 1 2 DEB
12182000 2 1 2 Allen University 2 1 1 5 0 2 3 3 6 3 3 1 0 0 0 2 3 0 3 4 2 3
3142000 2 1 0 Allen University 2 1 4 5 3 3 0 0 2 3 3 0 0 0 0 0 3 2 1 3 2 2
2222000 2 1 2 Allen University 2 1 5 2 1 2 1 0 1 1 1 1 0 0 0 0 0 3 2 1
272001 2 1 0 Allen University 2 2 3 1 0 2 4 4 2 2 1 0 0 0 0 2 3 0 2 4 2 1
2222000 2 1 2 AU 2 1 1 5 2 0 0 0 5 1 3 0 0 1 1 2 2 0 1 4 2 2
272001 2 1 0 Allen University 2 1 1 5 0 1 3 3 4 2 3 1 0 0 1 3 1 0 1 2 0 3
3142000 2 1 0 A.L.S. 2 1 1 5 2 1 0 0 5 2 1 0 0 0 0 0 1 0 1 3 2 1
281999 2 1 0 Allen University and A.L.S 2 2 3 1 2 1 4 4 5 2 1 0 0 0 0 0 1 0 1 3 2 1
10142000 2 1 0 Claflin University 2 1 1 5 1 1 0 0 2 3 1 0 3 0 0 0 1 0 0 3 2 2 LDR
9272002 1 1 0 Allen University 1 2 3 1 3 3 0 0 3 3 1 0 0 0 0 1 2 2 0 4 2 2
5282001 2 1 2 Florida Agricultural & Mechanical University 2 2 3 5 2 3 2 2 2 2 2 0 0 2 3 3 3 0 0 4 2 3
12142000 2 1 0 Allen University 2 2 2 1 1 1 3 3 3 0 0 0 3 3 0 0 0 3 2 2 KW
12182000 2 1 2 Allen University (A.L.S) 2 1 1 2 0 1 3 3 6 3 2 2 0 0 0 1 3 0 3 4 2 3
4172002 1 1 0 Allen university 2 2 4 5 3 3 0 0 1 0 0 0 0 0 0 2 0
12212000 2 1 2 Allen University 2 0 1 1 2 2 4 1 3 2 3 3 3 3 3 3 3 3 3 1 2 3
7132000 2 1 2 Allen University 2 1 1 5 2 3 1 1 2 3 0 0 0 0 3 1 0 0 3 3 2 1 MO
3112000 2 1 0 Allen University (Mercedes) 2 1 1 5 M 2 1 1 5 3 3 2 0 0 3 1 1 0 1 4 2 2 MO
3242001 2 1 0 Allen University 2 1 1 5 0 2 0 6 2 0 0 0 3 0 2 0 0 3 0 2
6211997 2 1 2 Allen University 1 1 4 5 1 3 0 0 4 1 2 3 1 2 1 2 2 1 1 0 3
4192002 1 1 2 Allen university (Mercedes O.) 2 2 4 5 1 1 2 0 4 3 2 0 0 2 0 2 0 0 4 2 1
1112000 2 1 0 Allen 2 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 1
662001 2 1 2 Allen University 2 1 1 0 1 2 3 0 2 2 1 0 0 1 1 1 1 0 2 3 2 2 KW
9221999 2 1 2 Howard University 2 1 2 5 3 1 2 0 4 3 1 3 1 0 1 1 1 0 3 4 3 1 LDR
tc={0B7275FE-B462-9B4A-B141-68D1A5B7DE22}: [Threaded comment]

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LR

10182002 1 1 0 Jackson State University 2 1 1 0 0 0 0 0 6 2 1 0 0 0 0 1 1 0 3 4 2 3 LDR
6172000 2 1 Allen University 2 1 1 5 0 2 2 5 2 2 0 0 0 0 0 0 0 5 2 3
3252002 2 1 0 Allen University 2 1 1 1 1 3 0 0 2 0 3 1 0 0 3 3 3 0 3 4 2 2 MSH
242002 2 1 0 Allen University 2 2 2 1 3 0 0 0 2 2 2 0 0 1 0 0 1 0 2 4 0 3 MSH
11141996 3 1 2 Allen University 2 1 1 5 2 2 2 1 4 1 0 0 0 0 0 1 3 0 3 4 2 2 KW
7261994 3 1 2 Allen University 2 2 1 5 3 3 2 3 3 0 0 0 0 0 3 0 3 4 2 3 KW
1241997 3 1 2 Allen University 2 1 1 1,2,3 2 3 3 0 2 0 0 0 0 0 0 1, 2, 4 2 KW
4251999 2 1 0 Allen University (2020) 2 1 1 5 2 2 0 0 3 1 2 0 0 0 0 0 1 0 2 4 2 2 KW
12062000 2 1 2 Allen University 2 1 2 0 0 1 4 4 1 3 1 0 0 0 0 0 2 0 0 3,4 1 2 KW
4102000 2 1 0 Allen University 2 1 1 0 1 3 3 2 1 2 2 0 0 0 0 2 0 0 1 4 2 3 KW
1022000 2 1 2 Allen University 2 1 1 5 1 2 0 0 2 2 2 0 0 0 0 2 1 0 1 4 2 2 KW
2262000 2 1 2 Allen University 2 1 1 0 0 0 3 3 3 2 0 0 0 0 0 2 0 0 0 4 0 3 KW
11132002 2 1 2 Allen University 2 2 4 5 0 1 4 4 5 2 2 0 0 0 0 0 0 0 0 3 2 2 KW
12221997 2 1 2 Allen University 2 1 4 3 0 2 0 2 2 1 0 0 0 3 0 2 0 1 3 1 2 KW
1021997
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To Guest contributor can you please move down to number 50, So all of my data can be incorporated in one section please.

3 1 2 Allen University 2 1 1 5 0 0 4 3 2 3 3 3 2 1 DEB
9012000 2 1 2 Allen University 2 2 4 5 2 2 3 3 5 3 3 0 0 0 0 3 3 0 1 4 2 3 DEB
8242000 2 1 2 Allen University 2 1 1 5 2 1 3 0 2 2 2 2 1 2 2 2 2 DEB
4162001 2 1 2 Allen University 2 2 2 5 1 1 1 0 3 0 0 0 0 0 0 1 2 0 0 2 0 3 DEB
1201996 3 1 2 Allen University
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Who is guest contributor?

2 2 4 1 3 2 0 1 2 3 2 2 4 2 1 DEB
8111996
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51 please sorry and thank you


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Who is guest contributor?


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3 1 2 Allen University 2 2 2 1 2 0 6 1 2 0 0 0 0 0 0 0 0 4 2 3 DEB
328200 1 1 2 Allen University 2 1 5 0 2 3 5 2 2 0 0 0 0 0 0 0 0 1,2,3,4 2 2 DEB
1112002 2 1 South Carolina State University 2 1 1 5 1 1 0 2 4 3 0 0 0 0 0 0 3 0 0 3,4 2 1 DEB
4262003 1 1 0 Benedict College 2 2 3 1 3 1 4 3 3 2 1 2 2 3 1 1 DEB
10081999 2 1 2 Benedict College 2 2 2 1 3 3 2 2 3 0 0 1 1 1 1 0 0 3 2 3 DEB
8072001 2 1 2 Benedict College: Phone Survey 2 1 1 0 0 0 0 1 5 0 3 3 3 4 2 2 DEB
8232000 2 1 0 Benedict College 2 2 2 5 0 0 4 2 3 1 0 0 0 0 0 0 0 0 3 2 2 DEB
7202000 2 1 2 Benedict College 2 2 1 1 0 1 2 0 2 3 3 0 3 0 2 0 0 2 3 2 1 DEB
10231997 2 1 2 Benedict College 2 1 1 0 0 1 2 4 3 2 0 0 0 0 0 0 0 4 2 3 DEB
11241999 2 1 2 Claflin University 2 2 4 5 2 2 4 3 3 0 1 3 3 2 0 0 3 2 3 DEB
4252001 2 1 0 Allen University 2 1 4 5 0 0 3 3 3 2 0 0 0 0 1 1 0 0 3 2 3 MSH
8172001 2 1 0 Morris College 2 1 5 1 2 3 0 0 5 2 3 0 0 0 0 0 3 0 3 4 2 2 MSH
172000 2 1 2 Allen University 2 2 4 5 3 3 2 1 5 1 1 0 0 0 1 1 3 0 1 4 2 2 LDR
2252001 2 1 0 Claflin University 2 2 1 5 0 2 2 0 2 3 3 0 0 0 0 0 1 0 0 1,3,4 2 2 MSH
10302001 2 1 2 Allen University 2 2 4 5 0 0 0 0 5 0 1 0 0 0 0 0 0 0 0 4 2 2 LDR
912001 2 1 0 HAMPTON UNIVERSITTY 2 1 5 0 0 1 0 0 4 2 2 0 0 0 0 0 0 0 0 4 2 2 MSH
1162001 2 1 0 Allen University 2 1 5 6 2 2 4 4 2 3 3 0 0 0 0 0 1 0 0 4 2 2 LDR
291993 3 1 0 Southern University 2 1 1 5 1 1 0 0 5 2 0 0 0 0 3 3 3 0 3 4 1 1 AJN
242001 2 1 2 Allen University 2 1 1 3 0 0 0 0 2 0 2 0 0 0 0 2 0 0 0 3 1 2 MSH
3112001 2 1 0 Allen University 2 1 1 5 0 1 3 2 4 1 3 0 0 0 0 1 1 0 1 3 2 1 LDR
2132001 2 1 0 Allen University 2 1 1 5 0 0 0 3 3 0 0 0 0 0 0 0 2 0 2 4 2 3 LDR
1202000 2 1 0 Allen University 2 2 2 5 2 3 3 0 4 3 2 0 0 0 3 3 3 0 3 2,4 1 2 MSH
7172000 2 1 0 Allen University 2 2 4 5 2 2 0 0 5 2 0 0 0 0 0 2 2 0 2 2 2 2 MSH
1111999 2 1 0 Allen University 2 2 1 1 3 3 0 0 3 3 3 0 0 0 3 3 3 0 3 3 2 3 MSH
1242000 2 1 0 Grambing State 2 2 Other(32) 5 1 1 1 1 1 6 0 0 0 0 0 0 0 0 0 4 1 0 AJN
10132000 2 1 0 Benedict College 2 2 3 5 1 1 3 2 2 0 3 2 0 0 2 0 0 0 0 4 2 3 MSH
3121997 2 1 2 NCA&T 2 2 4 5 2 1 0 0 2 2 2 2 0 0 3 3 3 0 3 3,4 2 2 AJN
1121997 3 1 NCA&T 2 2 4 5 3 3 0 0 3 3 3 1 0 0 0 3 1

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1

A Basis For Grade Point Average:
A Study of the Relationship between a
student’s grade point average and the

number of hours sleep.

A research conducted by
Willie J. Thompson Jr.
December 2008

2

Introduction

In the university culture the grade point average is a key indicator of a successful

college career and vice versa. Most students would agree that in order to achieve the

highest grade point average, various conditions have to be met: a balanced course load,

consistent interaction with professors and staff, encouragement from a supporting family

or network and lastly, proper rest and relaxation. However many students have found

proper rest, or adequate sleep amounts to be a challenging area to conquer. This study

seeks to present findings about sleep hours as a key determinant of student’s grade point

average. In the preparation for the work force, a college student experiences could vary

from stressful situations, high campus involvement to depression, fear, and separation

anxiety. But does the lack of sleep can affect academic performance on any level?

Problem

Our question here is to understand the relationship between a student’s grade

point average and the number of hours sleep. The Grade point average (hereafter GPA) is

a number that represents the average of a student’s grades during his or her time at an

institution, and usually weighted by a number of credits given for the course. Most

colleges and universities in the US use a four-point system. And the GPA is sometimes

used as a determining factor of the student’s ability to engage further academic material

and the acquisition of graduate and post graduate degrees. However sleep is defined as

the innate state of bodily rest and is suggested by scientist as needed for survival.

Anderson A. Zagler, found that sleep deprivation affects the immune system and

metabolism (Zagler R504-R509.)i. Zagler’s study also shows numerous ways in which

sleep is related to memory processing, preservation, stating a person is most safe when

3

asleep. Engaging the above factors and comparing them to the experiences of the average

college student. This study has significance to the student who engages in a loaded course

of study and a sharp memory is needed during examination and testing seasons. This

study is scientifically significant for its uncommonness. Julian R. Betts and Darlene

Morell conducted a study the relative importance of family background, high school

resources and peer groups as determinant of GPA, but hours of sleep were not

considered. It causes this study to explore the hours of sleep a student gets, and its affect

on academic measuring systems such as GPA.

Hypothesis & Theory

It is hypothesized that the numbers of hours of sleep will have an inverse affect on

GPA. It is speculated that the hours sleep each respondent gets will affect the hours

engaged in rigorous academic work, therefore impacting the students GPA. As the

college student is in need of well rested functioning faculties’ to satisfy academic

requirements that are measured by the GPA.

Specifically, the study will explore: if the hours of study, hours working for an

employer, and if the respondent experiences trouble sleeping, all affect both the

respondents sleep hours and GPA; the on/off campus living situation can affect the

respondents sleep hours; and lastly the type of high school a student graduated from and

the respondents head(s) of household highest level of education can impact the GPA as

listed in Figure 1 below:

4

Figure I. Analytical Model of Relationships among Hours Sleep and Grade Point

Average and Other related Variables.

Methodology

The handed survey research design was chosen to gather data for this problem.

This process is where questionnaires were distributed by hand, completed by respondents

and returned to data collector by hand. This allows for a personal connection between

respondent and collector, is found to be cost efficient, and easily managed by the

collector. This also allows the data collected to be free of possible confidentiality

Hours of
Study

Hours Working
for an

Employer

Hours
Sleep

GPA
Residency

On/Off
Campus

High
School

Attended

Head(s) of
Household

Highest
level of

Education

Trouble
Sleeping

5

breaches, and destruction. The handed subtype does have drawbacks in which the

respondent might not feel comfortable sharing answers to certain questions with the

collector even though the questionnaire is anonymous and the respondent attitude, attire,

and presentation may be a factor in the distribution process.

Selection of the study participants were completed through two non-probability

processes called availability and quota sampling. The former sampling method is also

known as a haphazard, accidental, or convenience sample (Schutt 2006).ii This research

sampling consists of random number of freshmen, sophomores, juniors, seniors and

graduate students, both male and female. Data collectors went to certain buildings or

areas on the campus of Howard University and simply asked students who were available

to complete the survey, once all surveys were handed out and returned the sampling

process was over. The benefit of availability sampling it is convenient is easily

administered. The disadvantage to availability sampling is the prejudice the research staff

may have to the work/class schedules of respondents.

Quota sampling is intended to overcome the most obvious flaw of availability

sampling—that the sample will just consist of whoever or whatever is availability,

without any concern for its similarity to the population of interest (Schutt 154.)iii. This

research sampling consists of an equal number of freshmen, sophomores, juniors, seniors

and graduate students, both male and female. Data collectors went to certain buildings, or

areas on the campus of Howard University and simply asked students who fit the

characteristics to complete the survey, once the quota was reached the sampling process

was over. The benefit of quota sampling is the narrowed focus and is easily administered.

6

The disadvantage to quota sampling is the limited research the findings will provide. It is

not representative of the entire population, and it dispels random selection.

Table 1 below, presents the demographics of the respondents to the questionnaire:

61% of the respondents were female; 36% of the respondents were from homes whose

parent(s) held a bachelors degree; 162 respondents parents share a family income of less

than 40,000; and 502 of them grew up in suburban/rural areas.

Table 1
Demographic Characteristics of Sample

Demographic Characteristics Frequency Percent

Gender

Female 619 61.0
Male 367 36.2
Total 986 97.2

Education of Family Head

No college degree 310 31.7
Bachelors degree 373 36.8
Master’s degree or higher 295 29.1
Total 978 96.4

Annual Family Income
Less than $40,000 162 15.9
$40,000 to $59,999 156 15.4
$60,000 to $79,999 153 15.1
$80,000 to 99,999 138 13.6
$100,000 to 149,999 126 12.4
$150,000 or higher 95 9.4
Total 830 96.4
Median: $70,000

Type of Area Grew Up In
Urban 474 46.7
Suburban/Non Urban 502 49.7
Total 976 96.3

7

To collect data a questionnaire was designed by the fall 2008 Sociological

Methods class under the guidance of Dr. Johnny Daniel. A total of 8 questions were

asked to aid us in our understanding of the relationships among hours sleep and grade

point average and other related variables. Specifically: How many hours a week, on

average, do you spend studying, and measured on a scale ranged from less than 1 hour to

40 hours or more? Please indicate whether you experienced trouble sleeping during this

semester and asked to check if applicable? Was your high school public or private which

included the option of other? Do you live on-campus or off-campus, as a yes-on or no-off

measurement? How many hours of sleep do you get on an average night, and asked to

write in response? Which category best represents your overall grade point average,

measured on a scale ranging from 0= GPA not established to 12= 4.0? What is your

classification with choices ranging from freshmen to graduate or professional student?

And, what is the highest level of education the head(s) of your family household received

measure by a range from Elementary school diploma to Degree beyond the bachelor’s

degree?

The advantages to these questions were they were all closed ended and refined by

the professor. The questions maintained a consistent focus, and were not tedious, boring,

or lengthy. The disadvantages could have been the opened ended questions in which

respondents could not circle but have to give careless written responses.

To data was analyzed on an aggregate basis, in which all responses are combined

for the purpose of explanation, description or evaluation. This quantitative research uses

statistical procedures: univariate (frequency and percent distribution of grade point

8

average, (hereafter DV), bivariate (percent distribution of hours of sleep, (hereafter KIV),

variance, range, mean, mode, correlation, t-test, ANOVA, and regression checks.

Findings

The GPA of a student is simply a measuring rod of all the academic course work a

student has engaged in at an institution. In the administered questionnaire the Howard

University grading system ranged from GPA not yet established to 4.0, which is an A.

Students were asked to identify which category best represents their overall grade point

average this variable indicated here is the dependent variable.. The chart below describes

a percentage distribution of the respondents GPA.

In Table 2, the pattern of the distribution of GPA’s according to shows the modal

category for respondents is GPA category 2.6 to 2.9. The mean GPA for the respondents

is 3.1.

Table 2
Frequency Distribution and Percentage Distribution of

the Grade Point Average
GPA Frequency %

2.5 or less 73 8.3
2.6 to 2.9 181 20.6
3.0 to 3.1 147 16.7
3.2 to 3.3 151 17.2
3.4 to 3.5 131 14.9
3.6 to 3.7 101 11.5
3.8 to 4.0 96 10.9
Total 880 100
Mean 3.1

9

In Table 3 we find a cross tabulation between the respondents grade point average

and hours of sleep. This table shows that there is almost to no relationship between the

KIV and DV. The chi square test reads only a .099% of non-significance.

Table 3
Percentage Distribution of the GPA by the R Hours Sleep

Index of R

Hours Sleep

Index of GPA
– 5 hours 5 hours 6 hours 7 hrs 8 hrs 9 hrs +

2.5 or less 7.6 10 7.7 4.7 5.7 15.2
2.6 to 2.9 24.1 23.3 19.9 15.3 28.6 17.4
3.0 to 3.1 17.7 20.7 17.6 15.3 12.4 17.4
3.2 to 3.3 21.5 18 13.5 21.2 20 13
3.4 to 3.5 13.9 11.3 17.9 15.9 10.5 10.9
3.6 to 3.7 5.1 10 11.5 13.5 15.2 8.7
3.8 to 4.0 10.1 6.7 11.9 14.1 7.6 17.4
Total 100 100 100 100 100 100
Number 79 150 312 170 105 46

Chi-Square= 40.324^, df=30, p=.099

During the t-test the entire group of respondent is divided in two, by the number

of hours sleep. Group 1 (getting 5 to 6 hours of sleep) is 4.00 and the mean for group 2

group (getting 7 to 9 or more hours of sleep) is 3.58. The respondents hours of sleep in

either group does not encourage or discourage the respondents GPA. The other results

were; t-value=1.83, df=860, and p-value=0.67. The p-value of the t-test records no

significant relationship between group means.

Table 4 shows the mean GPA while comparing the results of the DV, and KIV

between groups which measures 0.011 represents a significant difference. The Scheffe

test shows there is a GPA difference between the people in Group 1 who get 5 hours of

sleep and those in Group 2 who get 7 hours of sleep.

10

Table 4
Results of the ANOVA Comparing Means of the Grade Point Average by

the R Hours Sleep

Sum of
Squares

df Mean
Square

F Sig.

Between
Groups 48.267 5 9.654 2.977 0.011

Within Groups 2775.817 856 3.243
Total 2824.08 861

Table 5 shows, the correlation to be statistically significant, yet inconsistent with

the hypothesis that the numbers of hours sleep has an inverse impact on the DV.

Variables that have significant yet small direct relationships with the DV is the

respondents: head(s) of household highest level of education, on/off campus living

situation, if respondent experienced trouble sleeping, and the number of hours the

respondent works per week.

Table 5
Matrix Correlation Coefficients Resulting from the

Intercorrelation of the Variables in Study

Variables

2

3

4

5

6

7

8

1 Grade Point Average .0587 -.0211 .1534 00263 -.0398 .1794 -.0218
2 Number of hours of sleep R gets on a
average night -.0249 .033 -.0074 -.1494 .0953 .0007

3 Type of high school R attended -.0427 .0253 .0088 -.0305 -.0015
4 Highest level of education of R’s family
household head -.0676 .0008 .0076 -.0243
5 Whether R live on-campus or off-
campus .0179 -.0641 -.2684

6 Trouble sleeping -.0821 -.0186
7 Number of hours per week studying -.0032
8 Number of hours per week working
for an employer

*Coefficients that are statistically significant are in bold. Range in Number of cases: 2 to 8.

11

Table 6 shows, the coefficient are statistically significant but inconsistent with the

hypothesis. . This table reveals respondents; hours of study, hours of work, trouble

sleeping and the head of household highest level of education have significant effects on

the DV and the type of high school, and number hours of sleep don’t, this also helps to

understand the multiple R and R square relations. In comparing the standardized

coefficients, if they were to be ordered the KIV would be the very last determinant of the

DV.

Table 6
Results of the Regressions of Grade Point Average

on a Model Composed of Sleep Hours, High School, Family Education, Residency,
Trouble Sleeping, Study Hours, and Work Hours

Variables In Model
Unstandardized

Coefficients
Standardized
Coefficients

Number of hours per week studying 0.342 0.176
Number of hours per week working for an employer -0.014 -0.011
Trouble sleeping -0.069 -0.018
Type of high school R attended -0.084 -0.019
Whether R live on-campus or off-campus 0.212 0.058
Highest level of education of R’s family household
head 0.420 0.181

Number of hours of sleep R gets on a average night 0.008 0.005
(Constant) 2.062
Multiple R 0.626
Multiple R Square .392
Number 734

*Coefficients that are statistically significant are in bold.

Notes: Predictors (constant) number hours of sleep R gets on an average night.

Conclusions

The findings presented under the six statistical procedures all reject the

hypothesis. The variables are not related to each other in the 2008 fall study conducted on

12

the campus of Howard University. While a student’s GPA may be affected by several

factors however in this case the hours of sleep one engages is not a significant factor. In

this case the respondent’s classification, parents education, residency, trouble sleeping,

hours of study, and high school privatization were all considered and yet the table shows

the hypothesis to be overthrown. This implies it is not necessary for people to focus on

the hours of sleep they get but on the hours of study they engage in at an academic

institution of high learning.

13

REFERENCES

i Zager, A., Andersen, M. L., Ruiz, F. S., Antunes, I. B., & Tufik, S. (2007). Effects of acute and chronic
sleep loss on immune modulation of rats [Electronic version]. Regulatory, Integrative and Comparative
Physiology, 293, R504-R509.
ii Schutt, Russell K. Investigating the social world: the process and practice of research. 5th ed. P. 152
iii Schutt, Russell K. Investigating the social world: the process and practice of research. 5th ed. P. 154

2 much

Mandates Topic

Demographic Table: 5 Variables

· Age

· Drinking Alcohol

· Caused stress for you

· What aspect of Covid affected you the most

· Connecting with others

Methodology: what you doing throughout the whole data set

Graphs to be used in Covid 19 deaths is

1. Demographics table (frequency distribution)

2. Independent variable (frequency distribution)

3. Dependent Variable ( IV on DV percentile)

4. IV/DV Table ( IV on DV percentile)

5. Anova table

6. Correlation Coefficient IV/DV: (Pearson’s)

7. Other Independent variables (3)

In completing this assignment we are gathering information within putting information into our graphs that is being needed for each paper. Summarizing the paper and putting it to a completion. I have provided the final data that we took for our surveys and all together we had 130 to receive a feedback but of all my people they are initialed with my name initials which is DEB in the satay set in the last column so that you can provide feed back for my paper and initial research of my responses.