setwd(“C:/Work Files/Collaboration/Jennifer Gomez/JSI manuscript”)

library(haven)
JSI_Data <-read_sav("Covid_Questions_Wave1.sav")

Descriptives for PROMIS-Depression Scale T-scores.

According to:

Kroenke K, Stump TE, Chen CX, et al. Minimally important differences and severity thresholds are estimated for the PROMIS depression scales from three randomized clinical trials [published online January 23, 2020]. J Affect Disord. doi:10.1016/j.jad.2020.01.101.

the cutoff values for different levels of depression are: 55 (mild), 60 (moderate), 65 (moderately severe), and 70+ (severe depression).

I assume that is how these were calculated, but these scores had already been generated when I got the dataset. Below are tables of the T-score distribution and the dichotomous depression cutoff: 0=not depressed, 1=depressed. Although we used the continuous raw scores for the analysis because we were more interested in depressive symptomology rather than clinical depression categories.

library(tidyverse)
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## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(knitr)
library(kableExtra)
## 
## Attaching package: 'kableExtra'
## 
## The following object is masked from 'package:dplyr':
## 
##     group_rows
table(JSI_Data$Promis_depressionT)%>%
  knitr::kable(digits = 3, format="html", booktabs=TRUE, caption="Table 1. Promis Depression T-Scores")%>%
  kable_classic(full_width = F, html_font = "Cambria")
Table 1. Promis Depression T-Scores
Var1 Freq
38.2 41
44.7 3
47.5 13
49.4 3
50.9 5
52.1 9
53.2 10
54.1 6
55.1 8
55.9 5
56.8 5
57.7 8
58.5 6
59.4 4
60.3 7
61.2 6
62.1 11
63.9 2
64.9 3
65.8 2
66.8 1
67.7 2
68.7 1
69.7 2
72.8 1
73.9 1
75 1
76.4 1
81.3 2 
table(JSI_Data$Prom_depresClinCut)%>%
  knitr::kable(digits = 3, format="html", booktabs=TRUE, caption="Table 1. Promis Depression Clinical Cutoff: 0=no, 1=yes")%>%
  kable_classic(full_width = F, html_font = "Cambria")
Table 1. Promis Depression Clinical Cutoff: 0=no, 1=yes
Var1 Freq
0 126
1 43