PHQ-9 / PHQ-8 scoring

Usage

phq9_score(
  data,
  col_map = list(),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  impute = c("none", "mean"),
  variant = c("PHQ9", "PHQ8"),
  prefix = "PHQ9",
  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).
variant: Choose PHQ9 (9 items) or PHQ8 (drops suicidal ideation item).
prefix: Prefix for output column names.
verbose: Logical flag for verbose messaging (reserved).

Value

A tibble of score columns only: PHQ9_total and PHQ9_severity (factor). Input columns are not included.

References

Kroenke K, Spitzer RL, Williams JBW (2001). “The PHQ-9: Validity of a Brief Depression Severity Measure.” Journal of General Internal Medicine, 16(9), 606–613. doi:10.1046/j.1525-1497.2001.016009606.x .

Examples

df <- data.frame(phq9_01 = 0, phq9_02 = 1, phq9_03 = 2, phq9_04 = 1,
                 phq9_05 = 0, phq9_06 = 1, phq9_07 = 2, phq9_08 = 1,
                 phq9_09 = 0)
phq9_score(df)
#> # A tibble: 1 × 2
#>   PHQ9_total PHQ9_severity
#>        <dbl> <fct>        
#> 1          8 mild