Obsessive-Compulsive Inventory-Revised:
Scoring and Interpretation

The OCI-R records the distress associated with obsessive-compulsive symptom dimensions. Foa and colleagues (2002) revised the longer Obsessive-Compulsive Inventory into six succinct three-item domains: washing, checking, ordering, obsessing, hoarding and neutralizing.

It is used in clinical psychology studies, obsessive-compulsive disorder assessment research and evaluations of therapeutic interventions, and its dimensional profile lets researchers examine symptom types instead of relying only on an overall total. A higher score indicates more distress from OCD-related experiences, but it does not establish an OCD diagnosis. A frequent misreading is to quote one cut score for every comparison, and another is to treat subscale scores as separate diagnoses.

• Items: 18, each scored 0 to 4, with no reverse-scored items in the standard total.
• Subscales: six domains of three items each: hoarding (items 1, 7, 13), checking (2, 8, 14), ordering (3, 9, 15), neutralizing (4, 10, 16), washing (5, 11, 17) and obsessing (6, 12, 18).
• Total: one summed score from 0 to 72, with six subscale sums that each range from 0 to 12.
• Recall period: the past month in common standard administration.
• Local platforms: do not mistake instrument-specific summary means in a local platform for the original three-item subscale sums.

1. Verify that oci1 to oci18 correspond to the standard item order and contain scored responses from 0 to 4.
2. Sum all 18 items for oci_total (0 to 72). Calculate each of the six domain scores by summing its three named item numbers (0 to 12).
3. No reversal is required. The code below needs complete data for all 18 items in the total and all three items in each subscale. The cited abstract sets no single prorating policy, so document any alternative.

COMPUTE oci_total=SUM.18(oci1, oci2, oci3, oci4, oci5, oci6, oci7, oci8, oci9, oci10, oci11, oci12, oci13, oci14, oci15, oci16, oci17, oci18).
COMPUTE oci_hoarding=SUM.3(oci1,oci7,oci13).
COMPUTE oci_checking=SUM.3(oci2,oci8,oci14).
COMPUTE oci_ordering=SUM.3(oci3,oci9,oci15).
COMPUTE oci_neutralizing=SUM.3(oci4,oci10,oci16).
COMPUTE oci_washing=SUM.3(oci5,oci11,oci17).
COMPUTE oci_obsessing=SUM.3(oci6,oci12,oci18).
EXECUTE.

data$oci_total <- rowSums(data[paste0("oci",1:18)],na.rm=FALSE)
subscales <- list(hoarding=c(1,7,13),checking=c(2,8,14),
                  ordering=c(3,9,15),neutralizing=c(4,10,16),
                  washing=c(5,11,17),obsessing=c(6,12,18))
for (s in names(subscales)) {
  data[[paste0("oci_",s)]] <- rowSums(
    data[paste0("oci",subscales[[s]])],na.rm=FALSE)
}

Higher scores indicate more OCD-related distress. The original Foa et al. (2002) study identified different optimal screening cut scores depending on the comparison group: 21 when distinguishing OCD from nonanxious controls (sensitivity 65.6%, specificity 63.9%), and 18 when distinguishing OCD from other anxiety-disorder patients (sensitivity 74.0%, specificity 75.2%). These reflect distinct settings and do not constitute a universal clinical threshold.

Model OCI-R total severity and, where theoretically justified, the six domains separately, with control for multiple comparisons when several subscales are tested. Change during therapy can be estimated with Linear Mixed Models (Multilevel Modeling). Domain scores support the exploration of symptom profiles, though a patient’s diagnosis should not be inferred from subscale scores alone.

For psychometric validation, estimate reliability for each domain and for the full scale in the current sample, using Reliability Analysis (Cronbach’s Alpha) alongside ordinal omega, because three-item subscales may need careful interpretation of alpha. To test the six-domain structure, Confirmatory Factor Analysis (CFA) is the usual route, and Measurement Invariance should be tested when comparing populations or language versions. No universally applicable minimal clinically important difference was established in the primary paper.