Purpose: To evaluate the psychometric properties of glaucoma-specific quality of life (QoL) item banks (GlauCAT) and assess their performance using computerized adaptive testing (CAT) simulations.
Methods: In this cross-sectional study, 293 participants with glaucoma (mean age ± SD, 70.7 ± 13.2 years; 45% female) answered 342 items in 12 QoL item banks (IBs): Activity Limitation (AL); Driving (DV); Convenience (CV); Economic (EC); Emotional (EM); General Symptoms (GS); Health Concerns (HC); Lighting (LT); Mobility (MB); Ocular Surface Symptoms (OS); Social (SC); and Visual Symptoms (VS). These IBs were assessed using Rasch analysis, and CAT simulations with 1000 simulated respondents were utilized to determine the average number of items to be administered to achieve moderate and high precision levels.
Results: The AL, DV, EM, HC, LT, MB, EC, OS, SC, and VS IBs required relatively minor amendments to achieve satisfactory psychometric fit. To resolve multidimensionality, we split CV into Treatment Convenience (TCV) and General Convenience (GCV). Due to poor measurement precision, the GS IB was not pursued further. This resulted in 12 total IBs. In CAT simulations, an average of 3.7 and 7.3 items per IB were required to attain measurement at moderate and high precision, respectively.
Conclusions: Following rigorous psychometric assessment, we developed 12 valid glaucoma-specific QoL domains that can obtain highly precise person measure estimates using a small number of items.
Translational relevance: GlauCAT will enable researchers and clinicians to quickly and comprehensively assess the impact of glaucoma and its associated interventions across a range of QoL domains.