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Determine PTSD diagnosis based on DSM-5 criteria using binarized scores

Source: R/helping_functions.R
create_ptsd_diagnosis_binarized.Rd

Determines whether DSM-5 diagnostic criteria for PTSD are met using binarized symptom scores (0/1) for PCL-5 items. This is an alternative to determine_ptsd_diagnosis() that works with pre-binarized data.

Usage

create_ptsd_diagnosis_binarized(data)

Arguments

data

A dataframe containing exactly 20 columns of PCL-5 item scores (output of rename_ptsd_columns) named symptom_1 to symptom_20. Each symptom should be scored on a 0-4 scale where:

  • 0 = Not at all

  • 1 = A little bit

  • 2 = Moderately

  • 3 = Quite a bit

  • 4 = Extremely

Note: This function should only be used with raw symptom scores (output of rename_ptsd_columns) and not with data containing a total score column, as the internal binarization process would invalidate the total score.

Value

A dataframe with a single column "PTSD_orig" containing TRUE/FALSE values indicating whether DSM-5 diagnostic criteria are met based on binarized scores

Details

The function applies the DSM-5 diagnostic criteria for PTSD using binary indicators of symptom presence:

  • Criterion B (Intrusion): At least 1 present symptom from items 1-5

  • Criterion C (Avoidance): At least 1 present symptom from items 6-7

  • Criterion D (Negative alterations in cognitions and mood): At least 2 present symptoms from items 8-14

  • Criterion E (Alterations in arousal and reactivity): At least 2 present symptoms from items 15-20

Examples

# Create sample data
sample_data <- data.frame(
  matrix(sample(0:4, 20 * 10, replace = TRUE),
         nrow = 10,
         ncol = 20)
)
colnames(sample_data) <- paste0("symptom_", 1:20)

# Get diagnosis using binarized approach
diagnosis_results <- create_ptsd_diagnosis_binarized(sample_data)
diagnosis_results$PTSD_orig
#>  [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE