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Background: The Consolidated Framework for Implementation Research (CFIR) is a determinant framework that includes constructs from many implementation theories, models, and frameworks; it is used to predict or explain barriers and facilitators to implementation success. CFIR is among the most widely applied implementation science frameworks, and after 15 years of use in the field, the framework was updated based on user feedback obtained via literature review and survey. Dissemination of the updated CFIR and accompanying outcomes addendum resulted in hundreds of requests from users for further guidance in applying the framework. In addition, observations of potential and actual misuse of CFIR in grant reviews and published manuscripts were the catalyst for the development of this user guide. As a result, the objective of this article is to provide a user guide and essential tools and templates for using CFIR in implementation research.
Methods: This user guide was generated from the combined wisdom and experience of the CFIR Leadership Team, which includes the lead developers of the original and updated CFIR (LJD, CMR), and has collectively used CFIR in more than 50 projects. The five steps as well as the tools and templates were finalized via consensus discussions.
Results: The five steps below guide users through an entire research project using CFIR and include 1) Study Design; 2) Data Collection; 3) Data Analysis; 4) Data Interpretation; and 5) Knowledge Dissemination. In addition, the article provides a Frequently Asked Questions (FAQs) section based on user queries and six tools and templates: 1) CFIR Construct Example Questions; 2) CFIR Construct Coding Guidelines; 3) Inner Setting Memo Template; 4) CFIR Construct Rating Guidelines; 5) CFIR Construct x Inner Setting Matrix Template; and 6) CFIR Implementation Research Worksheet.
Conclusion: This user guide details how to use CFIR in implementation research, from the design of the study through dissemination of findings, answers frequently asked questions, and offers essential tools and templates. We hope this guidance will facilitate appropriate and consistent application of the framework as well as generate feedback and critique to advance the field.
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http://dx.doi.org/10.1186/s13012-025-01450-7 | DOI Listing |
Comput Biol Med
September 2025
INSIGNEO Institute for in silico medicine, University of Sheffield, UK; School of Mechanical, Aerospace and Civil Engineering, University of Sheffield, UK. Electronic address:
Modelling cardiovascular disease is at the forefront of efforts to use computational tools to assist in the analysis and forecasting of an individual's state of health. To build trust in such tools, it is crucial to understand how different approaches perform when applied to a nominally identical scenario, both singularly and across a population. To examine such differences, we have studied the flow in aneurysms located on the internal carotid artery and middle cerebral artery using the commercial solver Ansys CFX and the open-source code HemeLB.
View Article and Find Full Text PDFPLoS Negl Trop Dis
September 2025
Universitat Oberta de Catalunya, Barcelona, Spain.
Background: Originally adapted from a paper-based guide for skin-related neglected tropical diseases (NTDs), version 3.0.0 of the World Health Organization (WHO) SkinNTDs app aims to strengthen disease surveillance and frontline health worker capacity in NTD-endemic settings.
View Article and Find Full Text PDFBioinformatics
September 2025
Biocomputation and Complex Systems Physics Institute (BIFI)-Joint Unit GBsC-CSIC, University of Zaragoza, Zaragoza, 50018, Spain.
Motivation: The stability of protein interfaces influences protein dynamics and unfolding cooperativity. Although in some cases the dynamics of proteins can be deduced from their topology, much of the stability of an interface is related to the complementarity of the interacting parts. It is also important to note that proteins that display non-cooperative unfolding cannot be rationally stabilized unless the regions that unfold first are known.
View Article and Find Full Text PDFJMIR Hum Factors
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York City, NY, United States.
Background: As information and communication technologies and artificial intelligence (AI) become deeply integrated into daily life, the focus on users' digital well-being has grown across academic and industrial fields. However, fragmented perspectives and approaches to digital well-being in AI-powered systems hinder a holistic understanding, leaving researchers and practitioners struggling to design truly human-centered AI systems.
Objective: This paper aims to address the fragmentation by synthesizing diverse perspectives and approaches to digital well-being through a systematic literature review.
ACS Electrochem
September 2025
Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Kemigården 4, Gothenburg 412 96, Sweden.
Carbon fiber nanotip electrodes (CFNEs) are crucial for electrochemical recordings of neurotransmission release in confined spaces, such as synapses and intracellular measurements. However, fabricating CFNEs with small surface area to minimize noise remains challenging due to inconsistent tip size control, low reproducibility, and low fabrication success rate. Here, we present a reliable, user-friendly method with high reproducibility and success rate for precise CFNE fabrication using microscopy-guided electrochemical etching of cylindrical carbon fiber microelectrodes in a potassium hydroxide droplet.
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