K10 scoring — k10_score • HealthMarkers

K10 scoring

Usage

k10_score(
  data,
  col_map = list(),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  impute = c("none", "mean"),
  prefix = "K10",
  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.
verbose: Logical; if TRUE, emits informational messages about column resolution and scoring progress via hm_inform().

Value

A tibble of score columns only: K10_total. Input columns are not included.

Note

K10 items are summed as provided. The original scale uses 1–5 coding (total 10–50); some implementations subtract 1 (0–4, total 0–40). The function accepts either coding, as no reverse-scored items are involved and min_val/max_val only affect reversal.

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 .

Examples

df <- data.frame(k10_01 = 0, k10_02 = 1, k10_03 = 2, k10_04 = 1, k10_05 = 0,
                 k10_06 = 1, k10_07 = 2, k10_08 = 1, k10_09 = 0, k10_10 = 1)
k10_score(df)
#> # A tibble: 1 × 1
#>   K10_total
#>       <dbl>
#> 1         9