Italian version of the Headache Disability Inventory: Cross-cultural adaptation, validity, and reliability.

Abstract

Listen

Translate article

To translate and cross-culturally adapt the Headache Disability Inventory (HDI) into Italian and study its reliability and validity. A total of 132 participants with primary and secondary headaches were included. The translation was performed following international guidelines with forward and back translation procedures. Structural validity, internal consistency, test-retest reliability, measurement error, and construct validity were studied. Test-retest reliability and measurement error were tested on a subsample of 32 participants. The cross-cultural adaptation into Italian was performed without issues. Confirmatory factor analysis supports the structural validity partially (comparative fit index = 0.963; Tucker-Lewis index = 0.959; root mean square error of approximation = 0.051; standardized root mean square residual = 0.084), showing a two-factor structure (i.e., emotional and functional). Each subscale presented high internal consistency (α = 0.87 and 0.87 for the emotional and functional subscales, respectively), excellent and good test-retest reliability (intraclass correlation coefficient = 0.93 and 0.88 for the emotional and functional subscales, respectively), and acceptable measurement error (standard error of the measurement [SEM] = 3.6 points, minimal detectable change [MDC] = 10.0 points for the emotional subscale; SEM = 3.8 points, MDC = 10.7 points for the functional subscale). Construct validity was satisfactory for the emotional subscale and moderate for the functional subscale, as 85.7% (6/7) and 57.1% (4/7) of a priori hypotheses were met, respectively. The HDI was successfully translated into Italian and has acceptable psychometric properties. The Italian version of the HDI can be used in daily clinical practice and research to assess the functional and emotional impact of primary and secondary headaches. Further research should study other psychometric properties (i.e., content validity, responsiveness, and reliability in a larger sample).