Adding value to core outcome set development using multimethod systematic reviews
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
Trials evaluating the same interventions rarely measure or report identical outcomes. This limits the possibility of aggregating effect sizes across studies to generate high-quality evidence through systematic reviews and meta-analyses. To address this problem, core outcome sets (COS) establish agreed sets of outcomes to be used in all future trials. When developing COS, potential outcome domains are identified by systematically reviewing the outcomes of trials, and increasingly, through primary qualitative research exploring the experiences of key stakeholders, with relevant outcome domains subsequently determined through transdisciplinary consensus development. However, the primary qualitative component can be time consuming with unclear impact. We aimed to examine the potential added value of a qualitative systematic review alongside a quantitative systematic review of trial outcomes to inform COS development in neonatal care using case analysis methods. We compared the methods and findings of a scoping review of neonatal trial outcomes and a scoping review of qualitative research on parents', patients', and professional caregivers' perspectives of neonatal care. Together, these identified a wider range and greater depth of health and social outcome domains, some unique to each review, which were incorporated into the subsequent Delphi process and informed the final set of core outcome domains. Qualitative scoping reviews of participant perspectives research, used in conjunction with quantitative scoping reviews of trials, could identify more outcome domains for consideration and could provide greater depth of understanding to inform stakeholder group discussion in COS development. This is an innovation in the application of research synthesis methods.
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 | 0.233 | 0.168 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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