The aim of this project was to survey the emotional health of different individuals before and during the pandemic.The data is taken from a survey constructed by the team. We asked respondents in out Bay Area community for their gender, symptoms of depression they have developed, and their average mental health before and during the pandemic on a scale of 1 to 10 where 10 is amazing and 1 is awful.
We expected for there to be a wide variety of different symptoms respondents to experience and a decrease in scores of mental health. The specific ones that we expected there to be the most responses are depressed mood for more than 2 weeks, easily agitated, and decreased interest in activites.
We had a total of 226 responses. This graph shows the symptoms people experienced during the pandemic. This data is organized by the number of people who chose that certain symptom, from all women, men, and non-binary.
As a result, a total of 35 people have expressed they are experiencing other types of symptoms. A total of 120 people expressed a symptom of depression they have developed would be that they have become easily agitated.
The second graph displays how the 226 respondents' mental health has been before and during the pandemic. The results of the survey shows a majority of people rating their mental health with an 8 from a scale of 1 to 10 before the pandemic and with a 3 during the pandemic. The darker the dots on the graph mean multiple people had the same before and during COVID-19 mental health scores. The line drawn through the graph is a y=x line where the slope is equal to 1. This lines shows the boarder between respondents' mental health improving during COVID-19 and mental health scroes decreasing over COVID-19. All the points on the line show respondents with no change in mental health scores over COVID-19. As shown in the graph, there are significantly more dots under the line than over the line, indicating that more people's mental health scores decreased than increased during COVID-19.
The graph above shows dots chosen randomly from the data we have recieved from the survey. The points are made of (x,y) points where x = mental health score before COVID-19 and y = mental health during COVID-19. The line running through it is the least squares regression line (LSRL, A.K.A the line of best fit) and it's equation is ŷ = 1.13504 + 0.6533x where ŷ = predicted mental score during COVID-19 and x= mental health score before COVID-19.
The fourth graph shows the residuals from the thrid graph, making this graph a residual plot. A residual is the difference between the actual y value minus the predicted y value from the LSRL for that x value. The residual plot is used to see if the data is linear or non-linear.
The dotplot above shows how many times each residual value shows up. This graph will later be used to prove that the data is from an approximately normal distrabution because the graph shows no major skews or outliers.
Below is the process for calculating if the true slope, represented by B, of the LSRL for the population surveyed.
Null hypothesis: B = 1
Alternative hypothesis: B > 1
Significance value: 0.05
Method: 1 sample t test
Linear: pass since the residual plot shows no pattern and the scatter plot for the random data points does not show a non-linear pattern.
Independent: 20(10)= 200 which is less than the 226 data points we recieved. Pass because it passes the 10% rule.
Normal: pass since residual dot plot does not show any major skews or outliers.
Equal Standard Deviations: pass since residuals are equal across x values (shown by residual plot not having a sideways christmas tree pattern).
Random: pass since data points chosen were randomly selected by a random number generator.
t = (slope of LSRL of data set - Null hypothesis)/Standard Error of slopes = (0.6533 - 1)/0.2169154681 = -1.598
tcdf(Lower: -1000, Upper: -1.598, Degrees of freedom: 18) = 0.016611039
P-value: 0.016611039
Since the p-value of 0.017 is less than the significance value of 0.05, we reject the null and have convincng evidencd that the true slope for a graph showing the relationship between mental health scores before COVID-19 and mental health scores during COVID-19 is less than 1. Since the true slope is less than 1, it shows that many people have had a decrease in menatl health scores during COVID-19 comapred to before COVID-19
This study can only show a correlation of decrease in mental health scores in people in the Bay Area since a study cannot prove causation. Since the mental health scores were self reported, there are chances of bias so we have to take the results we get with a grain of salt since the mental health scores submited are self reported.
If you or anyone you know are dealing with depression, related to COVID-19 or not, below are some local resources that can help.
National Suidcide Prevention Hotline: 1(800)-273-8255
Calhope Connect is a program that offers cultrually appropriate, safe, and secure emotional support for all Californians who may need help because of COVID-19. You can connect with through their website chat line or at (833)137-HOPE(4673).
Huckleberry Youth Program have many free or cheap theapy and educational programs to help youth around San Francisco and Marin County.
Mental Health Association of San Francisco provides it's own support line at (855)845-7415. They also have many support groups and peer counseling programs to help those with many differenct psychological negatives like hoarding, anxiety, autism, and depression.