Framework for design and evaluation of complex interventions to improve health
Bibliographic record
Abstract
Randomised controlled trials are widely accepted as the most reliable method of determining effectiveness, but most trials have evaluated the effects of a single intervention such as a drug. Recognition is increasing that other, non-pharmacological interventions should also be rigorously evaluated.1-3 This paper examines the design and execution of research required to address the additional problems resulting from evaluation of complex interventions—that is, those “made up of various interconnecting parts.”4 The issues dealt with are discussed in a longer Medical Research Council paper (www.mrc.ac.uk/complex_packages.html). We focus on randomised trials but believe that this approach could be adapted to other designs when they are more appropriate. #### Summary points Complex interventions are those that include several components The evaluation of complex interventions is difficult because of problems of developing, identifying, documenting, and reproducing the intervention A phased approach to the development and evaluation of complex interventions is proposed to help researchers define clearly where they are in the research process Evaluation of complex interventions requires use of qualitative and quantitative evidence There are specific difficulties in defining, developing, documenting, and reproducing complex interventions that are subject to more variation than a drug. A typical example would be the design of a trial to evaluate the benefits of specialist stroke units. Such a trial would have to consider the expertise of various health professionals as well as investigations, drugs, treatment guidelines, and arrangements for discharge and follow up. Stroke units may also vary in terms of organisation, management, and skill mix. The active components of the stroke unit may be difficult to specify, making it difficult to replicate the intervention. The box gives other examples of complex interventions. #### Examples of complex interventions Service delivery and organisation: Stroke units Hospital at home Interventions directed at health professionals' behaviour: Strategies for implementing guidelines Computerised decision support Community interventions: Community …
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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 | 0.328 | 0.210 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.013 | 0.010 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.028 | 0.007 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".