The SASS is a 21-item instrument for the evaluation of patient social motivation and behaviour in depression. Each answer is scored from 0 (minimal adjustment) to 3 (maximal adjustment), with a total score range of 0 to 60. [...] Questions 1 and 2 are preceded by a specification on the existence of an occupation; these questions were considered mutually exclusive, but pooled into a single answer/item (Q1/2, work interest) in the analysis. After pooling question 1A an 1B into question 1, 20 items must be used for calculating the score. Items 16, 17, and 19 must either be coded or scored reversely.

scoring_sass(
  data,
  items = 1:20,
  keep = TRUE,
  nvalid = 16,
  digits = NULL,
  reverse = c(16, 17, 19)
)

Arguments

data

a data.frame containing the SASS items orderd from 1 to 20

items

A character vector with the SASS item names ordered from 1 to 10, or a numeric vector indicating the column numbers of the SASS items in data.

keep

Logical, whether to keep the single items and whether to return variables containing the number of non-missing items on each scale for each respondent. The default is TRUE.

nvalid

A numeric value indicating the number of non-missing items required for score calculations. The default is 16.

digits

Integer of length one: value to round to. No rounding by default.

reverse

items to be scored reversely. These items can be specified either by name or by index. Default: 16, 17, 19

Value

The function returns 2 variables:

  • nvalid.sass: Number of valid values (MAX=20)

  • score.sass: SASS Total Score

Details

  • Number of items: 21 (20 for score calculation)

  • Item range: 0 to 3

  • Reverse items: 16, 17, 19

  • Score range: 0 to 60

  • Cut-off-values: none

  • Minimal clinically important difference: none

  • Treatment of missing values: Questionnaires with up to four missing values are scored, replacing any missing values with the average score of the completed items.

References

Bosc et al. 1997 (https://dx.doi.org/10.1016/S0924-977X(97)00420-3)

Examples

if (FALSE) { library(dplyr) items.sass <- paste0("SASS_", seq(1, 20, 1)) scoring_sass(mydata, items = items.sass, reverse = c(16, 17, 19)) }