2015 Updated Method Guideline for Systematic Reviews in the Cochrane Back and Neck Group
Bibliographic record
Abstract
STUDY DESIGN: Method guideline for systematic reviews of trials of interventions for neck and back pain, and related spinal disorders. OBJECTIVE: To help authors design, conduct, and report systematic reviews of trials in this field. SUMMARY OF BACKGROUND DATA: In 1997, the Cochrane Back Review Group editorial board published the Method Guideline for Systematic Reviews, which was updated in 2003 and in 2009. Since then, new methodological evidence has emerged and standards have changed, therefore it was clear that revisions were needed to the 2009 guideline. In May 2015 the group changed its name to Cochrane Back and Neck. METHODS: The editorial board met in September 2014 to review the relevant new methodological evidence and determine how it should be incorporated. Members of the advisory board were consulted. Based on the feedback received, an updated method guideline was prepared and approved by the editorial board. RESULTS: We have updated recommendations in 7 categories: objectives, literature search, selection criteria, risk of bias assessment, data extraction, data analysis, and reporting of results and conclusions. Each category is classified into minimum criteria (mandatory) and further guidance (optional). This update also includes some new guidance for preparation of summary of finding tables and for conducting nonintervention reviews. CONCLUSION: Citations of previous versions of the method guideline in published scientific articles (1193 in total) suggest that others may find this guideline useful to plan, conduct, or evaluate systematic reviews in the field of back and neck pain, and spinal disorders. LEVEL OF EVIDENCE: N/A.
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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 | 0.171 | 0.418 |
| Meta-epidemiology (narrow) | 0.006 | 0.009 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.021 | 0.022 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.014 | 0.008 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.030 | 0.020 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".