Implications of a complexity perspective for systematic reviews and guideline development in health decision making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is growing interest in the potential for complex systems perspectives in evaluation. This reflects a move away from interest in linear chains of cause-and-effect, towards considering health as an outcome of interlinked elements within a connected whole. Although systems-based approaches have a long history, their concrete implications for health decisions are still being assessed. Similarly, the implications of systems perspectives for the conduct of systematic reviews require further consideration. Such reviews underpin decisions about the implementation of effective interventions, and are a crucial part of the development of guidelines. Although they are tried and tested as a means of synthesising evidence on the effectiveness of interventions, their applicability to the synthesis of evidence about complex interventions and complex systems requires further investigation. This paper, one of a series of papers commissioned by the WHO, sets out the concrete methodological implications of a complexity perspective for the conduct of systematic reviews. It focuses on how review questions can be framed within a complexity perspective, and on the implications for the evidence that is reviewed. It proposes criteria which can be used to determine whether or not a complexity perspective will add value to a review or an evidence-based guideline, and describes how to operationalise key aspects of complexity as concrete research questions. Finally, it shows how these questions map onto specific types of evidence, with a focus on the role of qualitative and quantitative evidence, and other types of information.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it