Related Experiment Video
Updated: Sep 30, 2025

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment
Published on: March 24, 2020
Reaching Target Communities in a Community Preschool Vision Screening Program
Insights
This study developed a scoring system and used geoinformatics mapping to identify preschools needing vision screenings most. This method efficiently targets resources to underserved communities, improving pediatric vision health outreach.
Area of Science:
- Public Health
- Geoinformatics
- Pediatric Ophthalmology
Background:
- Vision screening is crucial for early detection of pediatric eye conditions.
- Identifying underserved populations for vision screening presents logistical challenges.
- Existing methods may not efficiently allocate resources to areas of greatest need.
Purpose of the Study:
- To develop a method for identifying preschools with the greatest need for vision screening.
- To investigate correlations between socioeconomic status, preschool capacity, and screening rates.
- To utilize geoinformatics mapping to visualize areas requiring targeted vision screening efforts.
Main Methods:
- Collected vision screening, child care facility, and U.S. Census income data.
- Utilized ArcGIS software for data consolidation (ZIP code level) and geoinformatics mapping.
- Applied Kolmogorov-Smirnov analysis and developed a scoring system for facilities based on socioeconomic status and capacity.
Main Results:
- A positive correlation was found between child care facility capacity and median household income (P = .005).
- A scoring system prioritized larger facilities in lower-income communities.
- Geographic Information System (GIS) software mapped facilities by their cumulative score.
Conclusions:
- Under-served communities face challenges in vision screening due to facility limitations.
- A scoring system combined with mapping software optimizes resource allocation for vision screening programs.
- This approach enhances the efficiency of reaching more children in need of vision screenings.
Purpose:
To develop a method to identify preschools with the greatest need for vision screening, correlations between socioeconomic status, preschool capacity, and rates of pediatric vision screenings performed by a community vision screening program were investigated. Geoinformatics mapping software was used to visually display the areas of greatest need.
Methods:
Vision screening data from a community vision screening program, child care facility data from California Department of Social Services, and income data from the U.S. Census Bureau through ArcGIS software (Esri) were collected. When possible, data were consolidated at the ZIP code level. Kolmogorov-Smirnov analysis was used to determine correlations between data elements. Licensed child care facilities were scored on a scale (from 1 to 5) based on the socioeconomic status of the ZIP code and the facility capacity. The scoring system prioritized larger facilities in lower income communities to most efficiently use vision screening program resources.
Results:
There was a positive correlation between the capacity of the child care facility and the median household income (P = .005). Second, we found a positive correlation between child care capacity and the median household income (P = .005). Licensed child care facilities were mapped and colored using GIS software according to their cumulative score.
Conclusions:
Challenges to vision screening in under-served communities include the lack of child care facilities and smaller facility size. The use of a scoring system and mapping software can direct vision screening programs to reach a greater number of children with the most efficient use of resources. [.
Related Concept Videos
Community Based Intervention
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Vision

