ArticlePrevention science : the official journal of the Society for Prevention Research2021
Red, Yellow, and Green Light Changes: Adaptations to Extension Health Promotion Programs.
Article in Prevention science : the official journal of the Society for Prevention Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Cultural adaptations and cultural factors in EBI implementation with Latinx communities.Frontiers in public health · 2023Pooled it
- Implementation Strategies Applied in Communities Matching Process (ISAC Match): Expanded Guidance and Case Study.Implementation science : IS · 2025Article
- Healthy eating and active living policy, systems, and environmental changes in rural Louisiana: a contextual inquiry to inform implementation strategies.The international journal of behavioral nutrition and physical activity · 2023Article
- Racial and Ethnic Representation in Preventive Intervention Research: a Methodological Study.Prevention science : the official journal of the Society for Prevention Research · 2023Article
- Influence of Classroom-Level Factors on Implementation Fidelity During Scale-up of Evidence-Based Interventions.Prevention science : the official journal of the Society for Prevention Research · 2022Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Extension professionals have high autonomy to adapt the programs they deliver. However, fidelity is typically not reported, so it is unknown what adaptations are made. It is also unknown whether agents have the necessary training to adapt programs while maintaining fidelity to the core components. The purpose of this study was to determine (1) adaptations that Extension agents and specialists are making to programs they deliver, (2) the reasons for making these adaptations, (3) timing of adaptations, and (4) Extension agents' and specialists' understanding of the adaptation process. Extension agents and specialists nationwide were invited to complete a survey which queried about adaptations based on the traffic light model, adaptome, and adaptation taxonomy. Specifically, the traffic light model assigns a color for adaptations: tailoring language or pictures (green), adding/substituting activities or session sequence (yellow), or deleting lessons and decreasing timeline or session length (red). Responses were received from 98 agents and 24 specialists. Most agents and specialists reported making green (85% and 79%, respectively), yellow (89% and 75%), and red light changes (81% and 58%). Agents were significantly more likely than specialists to change the age appropriateness of lessons or activities, respond to individual client needs, substitute activities, delete lessons or activities, decrease the length and/or number of sessions, and shorten the program timeline. Within green light changes, each of those that could increase cultural appropriateness (tailoring language, scenarios, and pictures) were reported by less than 50% of agents and specialists. Of the most common adaptations reported, the primary reasons for these decisions were difficulty retaining or engaging participants and lack of time/competing demands on time. Most adaptations were made before the program was delivered. Agents rated their confidence level in the program adaptation process as somewhat confident to confident. Dissemination and implementation strategies to improve program adaptation within Extension are needed, including participatory approaches, training on the adaptation process, bi-directional evidence-based program repositories, and organizational-level changes.
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Registered trials
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.