WHO-5 scoring — who5_score • HealthMarkers

WHO-5 scoring

Usage

who5_score(
  data,
  col_map = list(),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  impute = c("none", "mean"),
  prefix = "WHO5",
  low_cutoff_percent = 50,
  verbose = FALSE
)

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.
low_cutoff_percent: Percentage threshold for low well-being flag.
verbose: Logical flag for verbose messaging (reserved).

Value

A tibble of score columns only: WHO5_raw, WHO5_percent, WHO5_low_wellbeing. Input columns are not included.

References

Topp CW, Østergaard SrD, Sø ndergaard S, Bech P (2015). “The WHO-5 Well-Being Index: A Systematic Review of the Literature.” Psychotherapy and Psychosomatics, 84(3), 167–176. doi:10.1159/000376585 .

Examples

df <- data.frame(who5_01 = 0, who5_02 = 1, who5_03 = 2, who5_04 = 3, who5_05 = 4)
who5_score(df)
#> # A tibble: 1 × 3
#>   WHO5_raw WHO5_percent WHO5_low_wellbeing
#>      <dbl>        <dbl> <lgl>             
#> 1       10           40 TRUE