Translation and Validation of the Low Luminance Questionnaire in the Chinese Population
Abstract
Purpose: To translate and validate a Chinese version of the Low Luminance Questionnaire (LLQ). Methods: The original LLQ was translated into Chinese by two ophthalmologists and back-translated by a professional translator. Between 2022 and 2023, participants with visual impairment were recruited from Zhongshan Ophthalmic Center. The method of successive dichotomizations (MSD) was used to assess the separation index, reliability, item misfit, and differential item functioning (DIF) of the questionnaire; principal component analysis was also used to assess unidimensionality. Linear regression analyzed the relationship between participant demographics and MSD person measures based on the Chinese LLQ. Results: A total of 173 participants (67.05% female) with an average age of 65.73 years were included, and all completed the Chinese version of the LLQ. After taking into account item fit, content validity, targeting, and cultural adaptation to the Chinese context, eight items were removed, yielding a final 24-item Chinese LLQ (LLQ-24). This version showed good separation (person, 3.47; item, 7.61) and reliability (person, 0.92; item, 0.98), although person-item targeting was suboptimal, with person measures averaging 1.63 logits higher than item measures. A few items showed DIF across age and gender. Participants with worse visual acuity and those with cataract had lower scores on the LLQ-24. Conclusions: The 24-item Chinese LLQ provides a useful tool with fair validity and reliability to assess low luminance visual difficulties in the Chinese population. Translational Relevance: The Chinese LLQ enables eyecare professionals to more accurately assess and manage vision-related conditions in low-light environments.
Fields of Study & Subjects
Ophthalmology and Visual Impairment Studies
Psychometric Methodologies and Testing
Health Education and Validation
Publication details
- Journal / source
- Translational Vision Science & Technology
- Volume
- 15
- Issue
- 1
- Pages
- 35–35
- Publication date
- 27 January 2026
- Language
- EN