Current practice in systematic reviews including the ‘PICO for each synthesis’ and methods other than meta-analysis: protocol for a cross-sectional study
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
<ns3:p> <ns3:bold>Introduction</ns3:bold> : Systematic reviews are used to synthesise research and inform decision making by clinicians, consumers and policy makers. The synthesis component of systematic reviews is often narrowly considered as the use of statistical methods to combine the results of studies, primarily meta-analysis. However, synthesis can be considered more broadly as a process beginning with: (i) defining the groupings of populations, interventions and outcomes to be compared (the ‘PICO for each synthesis’); (ii) examining the characteristics of the available studies; and (iii) applying synthesis methods from among multiple options. To date, there has been limited examination of approaches used in reviews to define and group PICO characteristics and synthesis methods other than meta-analysis. </ns3:p> <ns3:p> <ns3:bold>Objectives</ns3:bold> : To identify and describe current practice in systematic reviews in relation to structuring the PICO for each synthesis and methods for synthesis when meta-analysis is not used. </ns3:p> <ns3:p> <ns3:bold>Methods</ns3:bold> : We will randomly sample 100 systematic reviews of the effects of public health and health systems interventions published in 2018 and indexed in the <ns3:italic>Health Evidence</ns3:italic> and <ns3:italic>Health Systems Evidence</ns3:italic> databases. Two authors will independently screen studies for eligibility. One author will extract data on approaches to grouping and defining populations, interventions and outcomes, and the rationale for the chosen groups; and the presentation and synthesis methods used (e.g. tabulation, visual displays, statistical synthesis methods such as combining P values, vote counting based on direction of effect). A second author will undertake independent data extraction for a subsample of reviews. Descriptive statistics will be used to summarise the findings. Specifically, we will compare approaches to grouping in reviews that primarily use meta-analysis versus those that do not. </ns3:p> <ns3:p> <ns3:bold>Conclusion</ns3:bold> : This study will provide an understanding of current practice in two important aspects of the synthesis process, enabling future research to test the feasibility and impact of different methodological approaches. </ns3:p>
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 | 0.672 | 0.541 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.012 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.000 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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