Mood Disorder Questionnaire scoring

Usage

mdq_score(
  data,
  col_map = list(),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  prefix = "MDQ",
  symptom_cutoff = 7,
  require_clustering = TRUE,
  require_impairment = TRUE,
  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.
prefix: Prefix for output column names.
symptom_cutoff: Minimum symptom count for a positive screen.
require_clustering: Require clustering item == 1 to be positive.
require_impairment: Require impairment item == 1 to be positive.
verbose: Logical flag for verbose messaging (reserved).

Value

A tibble of score columns only: MDQ_symptom_count, MDQ_clustering, MDQ_impairment, MDQ_positive_screen. Input columns are not included.

References

Hirschfeld RMA, Williams JBW, Spitzer RL, Calabrese JR, Flynn L, Keck PE, Lewis L, McElroy SL, Post RM, Rapport DJ, Russell JM, Sachs GS, Zajecka J (2000). “Development and Validation of a Screening Instrument for Bipolar Spectrum Disorder: The Mood Disorder Questionnaire.” American Journal of Psychiatry, 157(11), 1873–1875. doi:10.1176/appi.ajp.157.11.1873 .

Examples

df <- data.frame(matrix(0, nrow = 1, ncol = 13))
names(df) <- sprintf("mdq_%02d", 1:13)
df$mdq_cluster <- 1; df$mdq_impair <- 1
mdq_score(df)
#> # A tibble: 1 × 4
#>   MDQ_symptom_count MDQ_clustering MDQ_impairment MDQ_positive_screen
#>               <dbl> <lgl>          <lgl>          <lgl>              
#> 1                 0 TRUE           TRUE           FALSE