Resources
This page presents resources that are open access and ready to use. These include methods papers, the protocols of our studies, and other related materials.
Searchable and continuously updated, built from the lab's umbrella review that identified more than 700 theories, models and frameworks. Each entry will carry its purposes, its core attributes and the evidence on its use, so that teams can choose the right one with the SELECT-IT meta-framework.
Also in preparation: AIM-IS framework, toolkit and reporting standard · Guidance on selecting and using theories, models and frameworks.
SELECT-IT meta-framework
Implementation science has hundreds of theories, models and frameworks (TMFs), and they are often chosen by habit or convenience rather than fit. Our scoping review of how researchers select them produced SELECT-IT, a four-step meta-framework: be clear about the purpose a TMF must serve, shortlist candidates, judge them against defined attributes, and check that they fit the project and the team. Work through the steps below.
Definition. Purposes are the primary goals and functions that theories, models and frameworks serve in implementation practice and research.
Task. Identify the goal(s) or function(s) you need the TMF to achieve, and make sure they align with your project objectives. Tick the purposes that apply to your project.
No purpose selected yet. Most projects need two or three.
Definition. A shortlist of candidate theories, models and frameworks that appear to fit the purpose(s) and the context.
Task. Search for TMFs commonly used in similar contexts, populations or interventions, using reviews of TMFs, online tools and database searches. Then create a shortlist that aligns with your purpose and context.
Definition. Attributes are the distinctive characteristics of TMFs that help define how they operate, explain phenomena or support implementation efforts.
Task. Evaluate each short-listed TMF against the attributes in the five domains below.
Clarity of constructs, clarity of the relationships between constructs, parsimony, and related attributes.
Evidence base, generalizability, predictive and explanatory power, and related attributes.
Practicality, measurability, availability of support, adaptability, and related attributes.
Equity focus, structural interplay, cultural safety, respect and trust.
Inclusion of multiple analytical levels, cross-sectoral collaboration, and related attributes.
Definition. Practical considerations are project- and team-specific factors that can affect the selection and application of a TMF.
Task. Assess each TMF's fit with the project context, data, goals, population and interventions, and whether the team has the knowledge, skills and resources to apply it.
Fit with the project context, population, intervention and outcomes, among others.
Sufficient funding, personnel, tools and time to use the TMF.
Knowledge and skills to apply the TMF, and its acceptability to the team.
Lab-authored papers and protocols come first, followed by recordings and courses. Use the filters to narrow the list to methods, to material for health services, or to learning.
What the field is, the concepts you need, and how to plan a first project. Drawn from ten foundational papers, with a roadmap, a glossary and practical notes. Web page and PDF, in English and French.
A scoping review of how researchers select theories, models and frameworks, and a meta-framework to guide the choice.
How the framework, toolkit and reporting standard for responsible AI use are being developed.
A secondary analysis of 204 implementation trials using the TIDieR checklist and the AACTT framework, with implications for specifying strategies.
A systematic review and meta-analysis of strategies used to change nursing practice.
The methods behind the national study: process mapping, multilevel interviews, co-design and evaluation of point-of-care hepatitis C testing.
Recorded sessions with Jeremy Grimshaw, Byron Powell, France Légaré, Natalie Taylor, Rachel Shelton, Ian Graham, Justin Presseau, Susan Michie, Annie LeBlanc and Elvin Geng.
Rigorous, responsible use of artificial intelligence in implementation research and practice, drawing on the lab's AIM-IS program.
A four-day course directed by Dr. Fontaine with an international faculty: core concepts, practical tools and methods.
The papers above are open access under their journals' licences and may be reused with citation. Please cite the article, not this page.
