Dataset Information

Psychometric Evaluation of Glaucoma Quality of Life Item Banks (GlauCAT) and Initial Assessment Using Computerized Adaptive Testing.

ABSTRACT:

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.

SUBMITTER: Man REK

PROVIDER: S-EPMC9187937 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Psychometric Evaluation of Glaucoma Quality of Life Item Banks (GlauCAT) and Initial Assessment Using Computerized Adaptive Testing.

Man Ryan Eyn Kidd REK Fenwick Eva K EK Khadka Jyoti J Wu ZhiChao Z Skalicky Simon S Pesudovs Konrad K Lamoureux Ecosse L EL

Translational vision science & technology 20220601 6

<h4>Purpose</h4>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.<h4>Methods</h4>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 Concer ...[more]

PMID: 35679035

Similar Datasets

Project description:PurposeTo assess the psychometric properties of glaucoma-specific health-related quality of life (HRQoL) item banks (IBs), and explore their efficiency using computerized adaptive testing (CAT) simulations.MethodsIn this cross-sectional, clinical study, 300 Asian glaucoma patients answered 221 items within seven IBs: Ocular Comfort Symptoms (OS); Activity Limitation (AL); Lighting (LT); Mobility (MB); Glaucoma Management (GM); Psychosocial (PSY); and Work (WK). Rasch analysis was conducted to assess each IB's psychometric properties (e.g., item "fit" to the construct; unidimensionality) and a set of analytic performance criteria guiding decision making relating to retaining or dropping domains and items was employed. CAT simulations determined the mean number of items for 'high' and 'moderate' measurement precision (stopping rule: SEM 0.3 and 0.387, respectively).ResultsParticipants' mean age was 67.2 ± 9.2 years (62% male; 87% Chinese). LT, MB, and GM displayed good psychometric properties overall. To optimize AL's psychometric properties, 16 items were deleted due to poor "fit", high missing data, item bias, low discrimination and/or a low clinical/patient importance rating. To resolve multidimensionality in PSY, we rehomed 16 items into a "Concern (CN)" domain. PSY and CN required further amendment, including collapsing of response categories, and removal of poorly functioning items (N = 7). Due to poor measurement precision, low applicability and high ceiling effect, low test information indices, and low item separation index the WK IB was not considered further. In CAT simulations on the final seven IBs (n = 182 items total), an average of 12.1 and 15.7 items per IB were required for moderate and high precision measurement, respectively.ConclusionsAfter reengineering our seven IBs, they displayed robust psychometric properties and good efficiency in CAT simulations. Once finalized, GlauCAT™-Asian may enable comprehensive assessment of the HRQoL impact of glaucoma and associated treatments.

Project description:BackgroundA glaucoma-specific health-related quality of life (HRQoL) item bank (IB) and computerized adaptive testing (CAT) system relevant to Asian populations is not currently available. We aimed to develop content for an IB focusing on HRQoL domains important to Asian people with glaucoma; and to compare the content coverage of our new instrument with established glaucoma-specific instruments.MethodsIn this qualitative study of glaucoma patients recruited from the Singapore National Eye Centre (November 2018-November 2019), items/domains were generated from: (1) glaucoma-specific questionnaires; (2) published articles; (3) focus groups/semi-structured interviews with glaucoma patients (n = 27); and (4) feedback from glaucoma experts. Data were analyzed using the constant comparative method. Items were systematically refined to a concise set, and pre-tested using cognitive interviews with 27 additional glaucoma patients.ResultsOf the 54 patients (mean ± standard deviation [SD] age 66.9 ± 9.8; 53.7% male), 67 (62.0%), 30 (27.8%), and 11 (10.2%) eyes had primary open angle glaucoma, angle closure glaucoma, and no glaucoma respectively. Eighteen (33.3%), 11 (20.4%), 8 (14.8%), 12 (22.2%), and 5 (9.3%) patients had no, mild, moderate, severe, or advanced/end-stage glaucoma (better eye), respectively. Initially, 311 items within nine HRQoL domains were identified: Visual Symptoms, Ocular Comfort Symptoms, Activity Limitation, Driving, Lighting, Mobility, Psychosocial, Glaucoma management, and Work; however, Driving and Visual Symptoms were subsequently removed during the refinement process. During cognitive interviews, 12, 23 and 10 items were added, dropped and modified, respectively.ConclusionFollowing a rigorous process, we developed a 221-item, 7-domain Asian glaucoma-specific IB. Once operationalised using CAT, this new instrument will enable precise, rapid, and comprehensive assessment of the HRQoL impact of glaucoma and associated treatment efficacy.

Dataset Information

Psychometric Evaluation of Glaucoma Quality of Life Item Banks (GlauCAT) and Initial Assessment Using Computerized Adaptive Testing.

Purpose

Methods

Results

Conclusions

Translational relevance

Publications

Psychometric Evaluation of Glaucoma Quality of Life Item Banks (GlauCAT) and Initial Assessment Using Computerized Adaptive Testing.

Similar Datasets

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