5.A. Scientific session: From theory to action - Applying the Medical Research Council framework on complex interventions
Bibliographic record
Abstract
Abstract The reasons for the workshop: Globally, public health problems such as obesity, poor mental health, and social inequality in health are on the rise. Tackling these significant challenges requires well-designed complex interventions. Interventions rarely follow linear sequences from intervention design toward large-scale implementation. Rather, they take non-linear trajectories by constantly adapting the intervention design according to the context. This thinking is outlined in the British Medical Research Council’s (MRC) 2021 framework for developing and evaluating complex interventions. This workshop encompasses four case projects, each corresponding to one of the four phases in the framework: i) development, ii) feasibility, iii) implementation, and iv) evaluation. However, recognising the deliberately generic nature of this framework, our workshop also encompasses co-creation, process evaluation, and implementation theories and methodology. Combining these methodologies presents challenges that necessitate clear argumentation and critical reflection. In this workshop, we will share the challenges encountered when applying the MRC 2021 framework and hopefully inspire future innovative opportunities in intervention research. Specifically, this workshop aims to: i) exchange challenges from intervention research methods and theories drawing on presenters’ experiences across four public health case projects. Presenters will critically reflect on the key concepts from the MRC framework including context, programme theory, engagement of stakeholders, uncertainties, and refinement of interventions. ii) discuss opportunities for future complex intervention research and outline best practices for using the MRC 2021 framework for complex interventions. The added value of organising the workshop: The audience attending this workshop will reflect on multiple on-the-ground experiences of applying methodology and principles from the MRC 2021 framework as well as methods and theories relevant to intervention research: co-creation, qualitative (e.g., ethnography, interviews) and quantitative (e.g. experimental, observational) methods applied to all core phases of complex interventions. At the end of the workshop, the audience will be invited to participate in an open, plenary discussion facilitated by the workshop’s chairs: two international experts on complex interventions, Reader Rhiannon Evans and Prof. Helle Terkildsen Maindal. The experts will encourage the presenters and audience to reflect critically on the case projects and ways forward for complex intervention research. Coherence between the presentations in relation to the workshop topic: The four case projects are guided by the MRC 2021 framework for complex interventions and involve public health interventions at the individual, interpersonal, and structural levels in Denmark and Canada. Key messages • Tackling public health challenges demands innovative and well-designed complex interventions combining research traditions, principles from health promotion, and cutting-edge best-practice frameworks. • The symposium will create a platform for cross-disciplinary knowledge exchange through case projects and expert-led joint discussions on how to apply the MRC 2021 framework for complex interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.182 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.008 | 0.017 |
| Research integrity | 0.018 | 0.028 |
| Insufficient payload (model declined to judge) | 0.030 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".