Improving the quality of evidence production in rehabilitation. Results of the 5th Cochrane Rehabilitation Methodological Meeting
Bibliographic record
Abstract
The paper introduces the Special Sections of the European Journal of Physical and Rehabilitation Medicine dedicated to the 5th Methodological Meeting of Cochrane Rehabilitation. It introduces Cochrane Rehabilitation; its vision, mission and goals; discusses why the Methodological Meetings were created; and reports on their organisation and previous outcomes. The core content of this editorial is the 5th Methodological Meeting held in Milan in September 2023. The original title for this meeting was “The Rehabilitation Evidence Ecosystem: useful study designs.” The focus of the Milan meeting was informed by the lessons learned by Cochrane Rehabilitation in the past few years, by the new rehabilitation definition for research purposes, by the collaboration with the World Health Organization (WHO), and by the REH-COVER (Rehabilitation COVID-19 Evidence-Based Response) action. During the Meeting, participants discussed the current methodological evidence on the following: RCTs in rehabilitation coming from meta-epidemiological studies; observational study designs - specifically the IDEAL Framework (Idea, Development, Exploration, Assessment, Long-term study) and its potential implementation in rehabilitation and the Target Trial Emulation framework: Single Case Experimental Designs; complex intervention studies: health services research studies, and studies using qualitative approaches. The Meeting culminated in the development of a first version of a “road map” to navigate the evidence production in rehabilitation according to the previous discussions. The Special Sections’ papers present all topics discussed at the meeting, and a methodological paper about choosing the right research question, presenting final results and the “road map” for evidence production in rehabilitation.
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 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 | 0.614 | 0.804 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.035 | 0.024 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.030 | 0.021 |
| Open science | 0.006 | 0.024 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".