Methodological developments in searching for studies for systematic reviews: past, present and future?
Bibliographic record
Abstract
The Cochrane Collaboration was established in 1993, following the opening of the UK Cochrane Centre in 1992, at a time when searching for studies for inclusion in systematic reviews was not well-developed. Review authors largely conducted their own searches or depended on medical librarians, who often possessed limited awareness and experience of systematic reviews. Guidance on the conduct and reporting of searches was limited. When work began to identify reports of randomized controlled trials (RCTs) for inclusion in Cochrane Reviews in 1992, there were only approximately 20,000 reports indexed as RCTs in MEDLINE and none indexed as RCTs in Embase. No search filters had been developed with the aim of identifying all RCTs in MEDLINE or other major databases. This presented The Cochrane Collaboration with a considerable challenge in identifying relevant studies.Over time, the number of studies indexed as RCTs in the major databases has grown considerably and the Cochrane Central Register of Controlled Trials (CENTRAL) has become the best single source of published controlled trials, with approximately 700,000 records, including records identified by the Collaboration from Embase and MEDLINE. Search filters for various study types, including systematic reviews and the Cochrane Highly Sensitive Search Strategies for RCTs, have been developed. There have been considerable advances in the evidence base for methodological aspects of information retrieval. The Cochrane Handbook for Systematic Reviews of Interventions now provides detailed guidance on the conduct and reporting of searches. Initiatives across The Cochrane Collaboration to improve the quality inter alia of information retrieval include: the recently introduced Methodological Expectations for Cochrane Intervention Reviews (MECIR) programme, which stipulates 'mandatory' and 'highly desirable' standards for various aspects of review conduct and reporting including searching, the development of Standard Training Materials for Cochrane Reviews and work on peer review of electronic search strategies. Almost all Cochrane Review Groups and some Cochrane Centres and Fields now have a Trials Search Co-ordinator responsible for study identification and medical librarians and other information specialists are increasingly experienced in searching for studies for systematic reviews.Prospective registration of clinical trials is increasing and searching trials registers is now mandatory for Cochrane Reviews, where relevant. Portals such as the WHO International Clinical Trials Registry Platform (ICTRP) are likely to become increasingly attractive, given concerns about the number of trials which may not be registered and/or published. The importance of access to information from regulatory and reimbursement agencies is likely to increase. Cross-database searching, gateways or portals and improved access to full-text databases will impact on how searches are conducted and reported, as will services such as Google Scholar, Scopus and Web of Science. Technologies such as textual analysis, semantic analysis, text mining and data linkage will have a major impact on the search process but efficient and effective updating of reviews may remain a challenge.In twenty years' time, we envisage that the impact of universal social networking, as well as national and international legislation, will mean that all trials involving humans will be registered at inception and detailed trial results will be routinely available to all. Challenges will remain, however, to ensure the discoverability of relevant information in diverse and often complex sources and the availability of metadata to provide the most efficient access to information. We envisage an ongoing role for information professionals as experts in identifying new resources, researching efficient ways to link or mine them for relevant data and managing their content for the efficient production of systematic reviews.
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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 | 0.689 | 0.765 |
| Meta-epidemiology (narrow) | 0.005 | 0.009 |
| Meta-epidemiology (broad) | 0.017 | 0.011 |
| Bibliometrics | 0.055 | 0.078 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.039 | 0.073 |
| Open science | 0.017 | 0.016 |
| Research integrity | 0.026 | 0.037 |
| Insufficient payload (model declined to judge) | 0.010 | 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".