SightConnect: Mobile App Validation Data for Digital Vision Testing in Primary Eye Care

1,481 individuals were assessed for visual acuity using the SightConnect mobile application at the LV Prasad Eye Institute. The dataset likely contains measurements comparing the app's near and distance acuity results against standard clinical assessments, with a mean difference of 0.08-0.09 logMAR. Authored by Payal Sangani and last updated in May 2026, this research supports the use of digital tools for remote eye care triage.

Use Cases

• Validate mobile-based vision testing algorithms based on comparison data with standard clinical measurements.
• Train or benchmark classification models for visual impairment severity (mild, moderate, severe) based on the described grading module.
• Analyze agreement metrics (like ICCs of 0.74 and 0.67) for digital versus in-clinic diagnostic tools.
• Study referral urgency prediction (routine, early, urgent) based on vision status classifications.

Strengths

• Includes data from 1,481 individuals, providing a substantial sample for validation studies.
• Reports specific performance metrics: mean differences of 0.08-0.09 logMAR and intraclass correlation coefficients (ICCs) of 0.74 and 0.67.
• The visual acuity grading module achieved 78 to 90% accuracy for referral urgency classification.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic or institutional bias inherent to a single eye institute study.

Provenance

Source

LV Prasad Eye Institute

Collection Method

Consecutive recruitment of individuals visiting for ophthalmic consultation; visual acuity assessed by trained optometrists and technicians.

Time Range

null

Freshness

Last updated 2026-05-08 05:52:16; freshness should be verified.

Geography

Likely India (based on the institute name), but not explicitly stated.