# The Validation of the Persian Version of the ID-Migraine Questionnaire

## TL;DR

This study translated and validated the ID-Migraine questionnaire in Persian to help diagnose migraines more effectively in primary care.

## Contribution

The study provides a culturally adapted Persian version of the ID-Migraine questionnaire with evaluated diagnostic accuracy.

## Key findings

- The Persian ID-Migraine questionnaire showed high sensitivity (96%) and positive predictive value (86%).
- It had low specificity (46%) and a misclassification error of 14.9%.
- The questionnaire's Kappa coefficient was 0.78, indicating substantial agreement.

## Abstract

Background: Migraine is often not diagnosed or treated properly, despite being a common condition. The ID-migraine is a brief, self-administered test developed as a valuable tool for screening and diagnosing migraine in primary care settings. The objective of the present study was to produce a Persian translation of the original ID-migraine, perform cultural adaptation, and evaluate its validity. Methods: Consecutive patients who attended two neurology clinics for headache were enrolled in the study. Diagnoses were established by headache specialists and were compared with the Persian ID-migraine results. Results: Among the 657 participants included, 470 (71.5%) were clinically diagnosed with migraine, 120 (18.2%) with tension-type headache, and 40 (6.1%) with cluster headache. The validity attributes of the Persian ID-migraine were as follows: sensitivity, 0.96 (95% CI, 0.93–0.98); specificity, 0.46 (95% CI, 0.35–0.56); positive predictive value, 0.86 (95% CI, 0.82–0.89); negative predictive value, 0.76 (95% CI, 0.63–0.87), and a misclassification error of 14.9%. The questionnaire’s Kappa coefficient was 0.78. Conclusions: The Persian version of the ID-migraine questionnaire exhibited sufficient sensitivity and positive predictive value, along with an acceptable misclassification error. However, it demonstrated a deficient level of specificity and a considerably reduced negative predictive value.