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Record W4403825549 · doi:10.1093/eurpub/ckae144.271

5.A. Scientific session: From theory to action - Applying the Medical Research Council framework on complex interventions

2024· article· en· W4403825549 on OpenAlexaboutno aff

Bibliographic record

VenueEuropean Journal of Public Health · 2024
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)Psychological interventionAction researchAction (physics)Medical researchPsychologyPolitical scienceManagement scienceEngineering ethicsMedical educationComputer scienceMedicineEngineeringMathematics educationPsychiatryWorld Wide WebPhysics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.182
metaresearch head score (Gemma)0.143
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.182
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1820.143
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.002
Science and technology studies0.0100.021
Scholarly communication0.0240.019
Open science0.0080.017
Research integrity0.0180.028
Insufficient payload (model declined to judge)0.0300.008

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.

Opus teacher head0.826
GPT teacher head0.593
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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