K6 scoring

K6 scoring

Usage

k6_score(
  data,
  col_map = list(),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  impute = c("none", "mean"),
  prefix = "K6",
  cutoff = 13,
  verbose = TRUE
)

Arguments

data

Data frame containing questionnaire item columns.

col_map

Named list mapping canonical item IDs to column names; defaults assume items are already named.

na_action

How to handle rows with missing items: keep, omit, or error.

missing_prop_max

Maximum allowed proportion of missing items per row before the score is set to NA.

impute

Imputation strategy for missing items when under the threshold: none or mean (row-wise mean).

prefix

Prefix for output column names.

cutoff

Threshold for the K6 case flag.

verbose

Logical; if TRUE, emits informational messages about column resolution and scoring progress via hm_inform().

Value

A tibble of score columns only: K6_total and K6_case. Input columns are not included.

References

Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand ST, Walters EE, Zaslavsky AM (2002). “Short screening scales to monitor population prevalences and trends in non-specific psychological distress.” Psychological Medicine, 32(6), 959–976. doi:10.1017/S0033291702006074 . Prochaska JJ, Sung H, Max W, Shi Y, Ong M (2012). “Validity Study of the K6 Scale as a Measure of Moderate Mental Distress Based on Mental Health Treatment Need and Utilization.” International Journal of Methods in Psychiatric Research, 21(2), 88–97. doi:10.1002/mpr.1349 . (validation study)

Examples

df <- data.frame(k6_01 = 0, k6_02 = 1, k6_03 = 2, k6_04 = 1, k6_05 = 0, k6_06 = 1)
k6_score(df)
#> # A tibble: 1 × 2
#>   K6_total K6_case
#>      <dbl> <lgl>  
#> 1        5 FALSE