Design of a questionnaire for detecting contact lens discomfort: the Contact Lens Discomfort Index

Background: The objective of this study was to design a new questionnaire for identifying CLD, based on the currently established CLD definition considered in the Tear Film and Ocular Surface CLD Workshop. Methods: A survey to characterise CL wearers was created and administered. Some items of the survey were selected by a focus group and analysed using a Rasch model to develop a questionnaire to identify CLD. Unidimensionality was checked applying principal components analysis. To build a plausible CLD classification (symptomatic vs asymptomatic), an unsupervised cluster analysis was used. Gower's general similarity coefficient, the partitioning around medoids algorithm, and the silhouette width were calculated. The reliability of the questionnaire was assessed using the intraclass correlation coefficient and Cohen's kappa coefficient. A study was performed to compare this questionnaire with the Contact Lens Dry Eye Questionnaire (CLDEQ)-8. Results: The 31-item survey was completed by 1104 volunteers, and the posterior analysis resulted in a 9-item questionnaire, the Contact Lens Discomfort Index (CLDI). It showed a good fit with the model (mean square infit and outfit values range was 0.76-1.10), and good unidimensionality (eigenvalues <= 1.3). The CLDI score range was 0-18 and the cut-off score for identifying CLD was 8. The intraclass correlation coefficient was 0.88 (95% confidence interval, 0.75-0.94), and kappa was 0.67 (95% confidence interval, 0.41-0.93). Comparison of the CLDI with the CLDEQ-8 in a sample of 58 CL wearers showed that 70.7% were classified equally by both questionnaires. Conclusions: The CLDI is a well-structured instrument, with acceptable psychometric properties, making it a valid and reliable tool to measure CL-related symptoms.