How do the experiences and identities of respondents impact their PTG Score?

From a dataset of survivors of the Isla Vista Shooting of 2014, I attempt to see the relationship between their Posttraumatic Growth Score and other aspects of their experiences and identity.

This rmarkdown will show:

  1. Distribution of posttraumatic growth scores in the sample (n=168)
  2. List of the variables in this study.
  3. Distribution of PTG scores based on age x decision to leave or stay in California.
  4. Distribution of PTG and Centrality of Events Scores (CES) based on age.
  5. A 3-D Graph! of participant’s ages, PTG and CES scores, and decision to stay or leave CA.

SPSS_Data_V1_1

Distribution of PTG Scores

I think that the x-axis is the number of participants in the sample (n=168), and the y-axis is the range of Posttraumatic Growth scores

Here is a list of all the variables in this dataset.

##  [1] "StartDate"                       "EndDate"                        
##  [3] "Status"                          "Subject_No"                     
##  [5] "Progress"                        "Duration__in_seconds_"          
##  [7] "Finished"                        "RecordedDate"                   
##  [9] "ResponseId"                      "RecipientLastName"              
## [11] "RecipientFirstName"              "RecipientEmail"                 
## [13] "ExternalReference"               "LocationLatitude"               
## [15] "LocationLongitude"               "DistributionChannel"            
## [17] "UserLanguage"                    "IC"                             
## [19] "Q1"                              "Q2"                             
## [21] "Q3"                              "Q4"                             
## [23] "Age_Shooting"                    "Emp_Ed_Shooting"                
## [25] "No_memsrviv"                     "No_commorgiv"                   
## [27] "No_gunpolicy"                    "No_commadvoc"                   
## [29] "No_therapy"                      "No_commevent"                   
## [31] "No_leaveiv"                      "No_stayiv"                      
## [33] "No_art"                          "Time_memsrviv"                  
## [35] "Time_commorgiv"                  "Time_gunpolicy"                 
## [37] "Time_commadvoc"                  "Time_therapy"                   
## [39] "Time_commevent"                  "Time_leaveiv"                   
## [41] "Time_stayiv"                     "Time_art"                       
## [43] "Other_healing"                   "CESSF_1"                        
## [45] "CESSF_2"                         "CESSF_3"                        
## [47] "CESSF_4"                         "CESSF_5"                        
## [49] "CESSF_6"                         "CESSF_7"                        
## [51] "PTGISF_1"                        "PTGISF_2"                       
## [53] "PTGISF_3"                        "PTGISF_4"                       
## [55] "PTGISF_5"                        "PTGISF_6"                       
## [57] "PTGISF_7"                        "PTGISF_8"                       
## [59] "PTGISF_9"                        "PTGISF_10"                      
## [61] "Change_career"                   "Change_gohome"                  
## [63] "Change_leavejob"                 "Change_go2school"               
## [65] "Change_leaveca"                  "Change_stayca"                  
## [67] "Change_leaveschool"              "Change_delaygrad"               
## [69] "Change_leaveiv"                  "Change_stayiv"                  
## [71] "Change_timeoffwork"              "Change_noreturnschool"          
## [73] "Change_notreturnjob"             "Commevent_enoughmemorials"      
## [75] "Commevent_able2attend"           "Commevent_persbenefit_memorials"
## [77] "Commevent_want2lead_memorial"    "Commevent_goodthings_after"     
## [79] "Commevent_hard2heal_events"      "Commevent_commbenefit_events"   
## [81] "Commevent_hard2heal_comminvolve" "Q15"                            
## [83] "Q16"                             "Q17"                            
## [85] "Q18"                             "Q19"                            
## [87] "Q_language"                      "Q_TotalDuration"                
## [89] "Q_URL"                           "CESSF_Total"                    
## [91] "PTGISF_Total"                    "No_Healing_Total"               
## [93] "PTGISF_Scoring"                  "PTGISF_hilo"

This is a newer dataset, so new composite variables are still being developed, which is exciting!

Age of participants during the shooting, their decision to leave California, and their PTG score.

#Still struggling to create labels here. #This scatterplot shows that the majority of participants are in the first age bracket: 18-22 People who didn’t leave California have higher PTG scores, especially those who are older.

Another look at participant age and its relationship with PTG/CES Scores

#I’m loving these Wes Anderson colors

People with high PTG scores also usually had higher CES scores.

There is a slight connection between age during the shooting and PTG Scores. People who were younger during the shooting have lower PTG scores. People who were older during the shooting have higher PTG scores. There is variance in the CES scores, and they do not seem to be associated with age.

And Now for the Big one: Age During Shooting, Decision to Leave CA, and PTG?CES Scores

# There is a lot going on in this 3-D graph!

It’s a lot of information. I don’t know if I’d use this:

Hard to see everything at once.

Hard to see how things relate.

The relationship between PTG and CES scores seems clear: the higher the PTG score, the *higher the CES score.

In this sample, people who experienced a lot of posttraumatic growth also feel that the shooting has become central to their life story

So, that’s something!