Age-Related Macular Degeneration (AMD) is the leading cause of central vision loss among older adults worldwide. Patients with AMD often require frequent monitoring of visual function and disease progression, typically through multiple follow-up visits involving optical coherence tomography (OCT), visual acuity testing (VA), and clinical consultations. While digital self-monitoring tools have emerged as promising solutions to reduce the burden of in-clinic visits, many elderly patients face challenges in engaging with these platforms due to visual impairment, limited digital literacy, and poorly optimised user interfaces. These barriers may reduce patient willingness to adopt such systems and undermine their long-term effectiveness. To address this gap, the study team has developed the web-based AVIGA (Automated Vision Impairment Gaze-tracking Analysis) system, which is a portable, self-administered, home-based digital monitoring system designed to minimise cognitive load and maximise usability for elderly AMD patients. The platform integrates patient-centred design principles such as simplified navigation, optimised text, and multimodal feedback (visual and audio) to empower users to independently track their visual health. A prospective, single-site usability trial to evaluate the AVIGA platform using validated human factors measures: the System Usability Scale (SUS), the Technology Acceptance Model (TAM) will be conducted. By examining the relationship between usability, cognitive load, and perceived empowerment, this study aims to identify critical user interface and user experience (UI/UX) design factors that influence willingness to adopt and sustain use of digital health tools among elderly AMD patients.
Study Type
OBSERVATIONAL
Enrollment
30
Tan Tock Seng Hospital
Singapore, Singapore
Assess System Usability
Measure and evaluate overall system usability across three checkpoints (Baseline, Mid-point, and End-point) using the System Usability Scale (SUS), a 10-item questionnaire rated on a 5-point Likert scale.
Time frame: Baseline, Mid-point (6 months from baseline ±3 months), End-point (12 months from baseline ±3 months)
Assess System Acceptance
Measure and evaluate overall acceptance towards system adoption across three checkpoints (Baseline, Mid-point, and End-point) using 8 items from the Technology Acceptance Model (TAM), rated on a 5-point Likert scale.
Time frame: Baseline, Mid-point (6 months from baseline ±3 months), End-point (12 months from baseline ±3 months)
Track Change Over Time
Compare the changes in expectation (Baseline) versus lived experience (Mid-point, End-point) scores taken from the combined SUS and TAM to identify how usability perceptions and adoption intentions evolve with continued use.
Time frame: Baseline, Mid-point (6 months from baseline ±3 months), End-point (12 months from baseline ±3 months)
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