Home
Magna Scientia Advanced Research and Reviews
Peer-Reviewed • ISSN: 2582-9394 • Fast-Track Publishing • Impact Factor 8.5 • Low Publication Charges • Crossref DOI Linking

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

Research and review articles are invited for publication in September - October 2026 (Volume 18, Issue 1) Submit manuscript

FRAMEWORKS FOR DATA-DRIVEN EVALUATION OF COMMUNITY-BASED CHRONIC DISEASE INTERVENTIONS: A NARRATIVE REVIEW AND PROPOSED ANALYTICAL ROADMAP

Breadcrumb

  • Home
  • FRAMEWORKS FOR DATA-DRIVEN EVALUATION OF COMMUNITY-BASED CHRONIC DISEASE INTERVENTIONS: A NARRATIVE REVIEW AND PROPOSED ANALYTICAL ROADMAP

Chidi Okafor *

Central Michigan University.
* Corresponding Author

Review Article
 
Magna Scientia Advanced Research and Review, 2026, 18(01), 042–052
Article DOI: 10.30574/msarr.2026.18.1.0178
DOI url: https://doi.org/10.30574/msarr.2026.18.1.0178

Received on 25 July 2026; revised on 02 September 2026; accepted on 05 September 2026

Community-based chronic disease prevention programs operate in complex, multi-component environments where robust evaluation is critical yet, their integration into a coherent, data-driven, equity-centered analytical approach remains underdeveloped, particularly in United States community and safety-net settings. This narrative review synthesizes the published literature on evaluation frameworks and data-driven methodologies applied to community-based chronic disease intervention programs. Drawing on peer-reviewed literature, grey literature from public health agencies, and implementation science frameworks published between 2020 and 2026, sources were identified through searches of PubMed, Scopus, and Google Scholar using terms spanning chronic disease evaluation, community-based intervention frameworks, implementation science, data-driven evaluation, and health equity. Five major framework categories were identified: logic model and theory-of-change approaches; health service quality models including the Donabedian structure-process-outcome framework; chronic disease management frameworks led by the Chronic Care Model; implementation science frameworks centered on RE-AIM; and equity-centered participatory evaluation models designed for vulnerable and indigenous populations. Across frameworks, common evaluation elements included inputs and context, process fidelity, outputs and reach, and short- and long-term outcomes. Persistent gaps included inconsistent use of standardized indicators, limited economic evaluation, underinvestment in sustainment and scale-up assessment, and inadequate representation of equity dimensions in analytical design. No single existing framework fully addresses the analytical needs of data-driven community chronic disease prevention evaluation in diverse United States settings. An integrated roadmap combining theory-based frameworks, mixed-methods designs, equity-centered indicators, and explicit sustainment assessment is needed, and is proposed here to strengthen the evidence base for community chronic disease prevention and inform national policy decisions.

Community-Based Intervention, Chronic Disease Prevention, Evaluation Frameworks, Implementation Science, Health Equity

https://msarr.magnascientiapub.com/sites/default/files/fulltext_pdf/MSARR-2026-…

Preview Article PDF

Chidi Okafor. FRAMEWORKS FOR DATA-DRIVEN EVALUATION OF COMMUNITY-BASED CHRONIC DISEASE INTERVENTIONS: A NARRATIVE REVIEW AND PROPOSED ANALYTICAL ROADMAP. Magna Scientia Advanced Research and Review, 2026, 18(01), 042–052. Article DOI: https://doi.org/10.30574/msarr.2026.18.1.0178

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 Magna Scientia Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution