Evidence map›Paper›PMID 41822926›Full record

ArticleFrontiers in public health2026

A holistic approach for quantifying the value of public health programs: social return on investment (SROI) analysis of a mobile clinic as an example.

Shubha Kumar, Aaron Mallett, Sara Olsen, Anne Coleman

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shubha KumarDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States.
Aaron MallettSVT Group, Milpitas, CA, United States.
Sara OlsenSVT Group, Milpitas, CA, United States.
Anne ColemanJules Stein Eye Institute, University of California, Los Angeles, Los Angeles, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Public health programs often face challenges in demonstrating their full impact through traditional evaluation methods or economic approaches such as cost-benefit analysis or cost-effectiveness analysis. Methods: Using a social return on investment (SROI) analysis approach, we evaluated the broad social and economic impact and value created by UCLA Mobile Eye Clinic's Pre-School Vision Program. This program screened 90,000 pre-school children in underserved areas of Los Angeles County between 2012 and 2017, providing glasses and referrals as needed. The evaluation study employed mixed methods consistent with the process of SROI analysis. Results: Results indicate the strong positive impact and value of the program, generating approximately $40 of value in the community for every $1 invested. Various outcomes were identified by key stakeholders, with the most valuable being improved quality of life for pre-school children who received glasses. Other highly valued outcomes included increased confidence and self-esteem of the children, their decreased dependency on others, and their increased responsibility. Discussion: These findings suggest that increased provision of mobile clinics for communities including children living in underserved areas could produce significant value. Findings also demonstrate the relevance of SROI for evaluating and quantifying the impacts of public health programs more broadly.

Indexed as

Mobile Health UnitsProgram EvaluationPublic HealthChild, PreschoolCost-Benefit AnalysisFemaleHumansLos AngelesMaleeconomic evaluationimpactmobile clinicpublic health programssocial return on investment

Identifiers

PMID41822926
PMCPMC12975873

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.