The validation of the Hungarian version of the ID-migraine questionnaire

• Main Authors: Éva Csépány, Marianna Tóth, Tamás Gyüre, Máté Magyar, György Bozsik, Dániel Bereczki, Gabriella Juhász, Csaba Ertsey
• Format: Article
• Language: English
• Published: BMC 2018-11-01
• Series: The Journal of Headache and Pain
• Subjects: ID-migraine questionnaire; Hungarian version; Validity features; Migraine
• Online Access: http://link.springer.com/article/10.1186/s10194-018-0938-z

Abstract Background Despite its high prevalence, migraine remains underdiagnosed and undertreated. ID-Migraine is a short, self-administrated questionnaire, originally developed in English by Lipton et al. and later validated in several languages. Our goal was to validate the Hungarian version of the ID-Migraine Questionnaire. Methods Patients visiting two headache specialty services were enrolled. Diagnoses were made by headache specialists according to the ICHD-3beta diagnostic criteria. There were 309 clinically diagnosed migraineurs among the 380 patients. Among the 309 migraineurs, 190 patients had only migraine, and 119 patients had other headache beside migraine, namely: 111 patients had tension type headache, 3 patients had cluster headache, 4 patients had medication overuse headache and one patient had headache associated with sexual activity also. Among the 380 patients, 257 had only a single type headache whereas 123 patients had multiple types of headache. Test-retest reliability of the ID-Migraine Questionnaire was studied in 40 patients. Results The validity features of the Hungarian version of the ID-Migraine questionnaire were the following: sensitivity 0.95 (95% CI, 0.92–0.97), specificity 0.42 (95% CI, 0.31–0.55), positive predictive value 0.88 (95% CI, 0.84–0.91), negative predictive value 0.65 (95% CI, 0.5–0.78), missclassification error 0.15 (95% CI, 0.12–0.19). The kappa coefficient of the questionnaire was 0.77. Conclusion The Hungarian version of the ID-Migraine Questionnaire had adequate sensitivity, positive predictive value and misclassification error, but a low specificity and somewhat low negative predictive value.