library(haven) 

mydata <- read_sav("C:/Users/Monte Richardson/Desktop/Indep St/IV/Quant Data Files/SPSS_Data_V1.1.sav")
library(ggplot2)

Mass Shootings in the United States

513 people died and 494 were injured in 62 mass shootings in the United States between 1982 and 2012.

library(png)

library(grid)

img <- readPNG("US Mass Shootings 1982-2017.png") 

grid.raster(img)

Isla Vista Tragedy of 2014

In 2014, 6 people were murdered by a 22 year-old man who wanted to punish women for, *“rejecting him, as well as men he envied for being sexually active.*

He is not the first US male to commit a mass shooting.

library(png)
library(grid)
img2 <- readPNG("US Mass Shootings.png") 
grid.raster(img2)

Data source: Motherjones.com

The Data

4 years later, 170 survivors were asked to reflect on how the Isla Vista tragedy impacted their lives. We focused on posttraumatic growth, the psychological concept that people can grow and become more resilient after experiencing trauma. This is the distribution of posttraumatic growth (PTG) scores of the survey respondents.

library(haven)


ggplot(mydata, 
       aes(x = PTGISF_Total)) + 
  geom_histogram(fill = "navy")

The distribution of PTG scores is mostly normal, with most participants falling somewhere in the mid-range. (~30).

We also focused on Centrality of Events

the psychological concept that people who experience a traumatic event view it as central to their life story. This is the distribution of Centrality of Events (CES) scores of the survey respondents.

library(haven)


ggplot(mydata, 
       aes(x = CESSF_Total))+
  geom_bar(fill = "hotpink4")+
xlab("Centrality of Events Score")

The distribution of CES scores is different than PTG, with most participants obtainig scores in the mid to high range (~30-45).

Gender and Posttraumatic Growth

Given that the nature of the violence was based in misogyny, we wanted to know if men experienced more or less posttraumatic growth than women. The following score distribution was found by gender (1=Female, 2=Male).

plot(mydata$PTGISF_Total, # x variable
     mydata$Gender_Identity, # y variable
main = "Does PTG score vary by gender?", 
xlab = "Posttraumatic Growth Score", # x label
ylab = "Gender", # y label
pch = 19, 
col = "darkgreen")

Of the men who responded, most of their PTG scores fell in the mid to low range. Of the women who responded, most of their CES scores fell in the mid range, with more reporting higher scores. Could this be because of the gendered nature of the violence?

Gender and Centrality of Events

Since it seems true that in this sample, women report higher PTG scores then men, We then wanted to see if the same would be true for CES. ### The chart shows CES, PTG, and Gender as they relate. Of the men who reported higher PTG scores, they also reported the highest CES scores. The same is not true for women with the highest PTG scores. Women’s CES and PTG scores fall in the mid range. The scores of men vary from highest to lowest.

``` There is a connection between high PTG scores and high CES scores. People who have spent less time engaged in healing activities report lower PTG and CES scores.

The connection between time and PTG score is not the same as the number of healing activities pursued.

The pie chart represents the total number of healing activities and PTG score. People with mediuam-range PTG scores engaged in the largest amount of healing activities. From this comparison, there is a discrepancy between engaging in a certain number of healing activities, and engaging in these activities over different periods of time.

The bar chart also shows a lack of relationship between time spent in therapy and PTG score.

People with medium-range PTG scores spent the most time in therapy. People with high scores spent less time in therapy. This could mean that therapy is not the most important predictor of PTG for this sample.