Evidence mapPaperPMID 42390968Full record

ArticlePreventing chronic disease2026

Predictors of Voucher Redemption in Produce Prescription Programs in a Primarily Low-Income Population With Type 2 Diabetes.

Tolulope V Adebile, Kayla Rutt, Christina Scartozzi, William A Calo, Jennifer L Kraschnewski, Kelseanna Hollis-Hansen, Susan Veldheer

Abstract read
In one paragraph

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

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Tolulope V AdebileDepartment of Public Health Sciences, Pennsylvania State College of Medicine, Hershey, Pennsylvania.
Kayla RuttDepartment of Family and Community Medicine, Pennsylvania State College of Medicine, Hershey, Pennsylvania.
Christina ScartozziDepartment of Family and Community Medicine, Pennsylvania State College of Medicine, Hershey, Pennsylvania.
William A CaloDepartment of Public Health Sciences, Pennsylvania State College of Medicine, Hershey, Pennsylvania.
Jennifer L KraschnewskiDepartment of Public Health Sciences, Pennsylvania State College of Medicine, Hershey, Pennsylvania.
Kelseanna Hollis-HansenFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts.
Susan VeldheerDepartment of Public Health Sciences, Pennsylvania State College of Medicine, Hershey, Pennsylvania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Food as Medicine initiatives, including produce prescription (PRx) programs, provide incentives (ie, vouchers) for participants to purchase free or reduced-cost produce. Voucher redemption is central to PRx effectiveness, yet predictors of redemption are poorly characterized. Prior evaluations often excluded nonusers, potentially overestimating effects. We applied an intent-to-treat (ITT) approach to examine the association between baseline characteristics and voucher redemption rates (VRRs) in a PRx program among primarily low-income Hispanic/Latino adults with type 2 diabetes. Methods: In this single-arm, pre-post study, 154 participants were enrolled in a 7-month PRx program offering up to $90 in fruit and vegetable vouchers for attending monthly nutrition education sessions. Binomial logistic regression assessed predictors of ITT-VRRs, including transportation access, baseline fruit and vegetable intake, and knowledge of produce preparation. Results: The sample was majority female (66.2%), Hispanic/Latino (83.1%), and low income (using public health insurance [88.9%] or food insecure [76.0%]). Most participants shared purchased produce with others in the household (61.2%). The ITT-VRR was 65.8%, versus 84.3% in per-protocol analysis. Higher odds of ITT-VRR were associated with transportation access (personal car [odds ratio, 2.28; 95% CI, 1.94-2.67]), while little/no self-reported knowledge of how to prepare fruit and vegetables was associated with lower odds (odds ratio, 0.58; 95% CI, 0.52-0.63). Conclusion: Transportation access and baseline knowledge of how to prepare fruit and vegetables were associated with voucher redemption, suggesting vouchers alone may not sustain engagement or dietary change. To enhance program equity and effectiveness, future PRx programs may consider pairing vouchers with strategies addressing transportation challenges and supporting fruit and vegetable preparation-related capability.

Indexed as

Diabetes Mellitus, Type 2Food AssistanceFruitHealth PromotionPovertyVegetablesFemaleHispanic or LatinoHumansMaleMiddle Aged

Identifiers

PMID42390968
PMCPMC13334710

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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 Socratic graph.