The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta‐analysis, and clinical practice guideline: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the methodological assessment tools for pre-clinical and clinical studies, systematic review and meta-analysis, and clinical practice guideline. METHODS: We searched PubMed, the Cochrane Handbook for Systematic Reviews of Interventions, Joanna Briggs Institute (JBI) Reviewers Manual, Centre for Reviews and Dissemination, Critical Appraisal Skills Programme (CASP), Scottish Intercollegiate Guidelines Network (SIGN), and the National Institute for Clinical Excellence (NICE) up to May 20th, 2014. Two authors selected studies and extracted data; quantitative analysis was performed to summarize the characteristics of included tools. RESULTS: We included a total of 21 assessment tools for analysis. A number of tools were developed by academic organizations, and some were developed by only a small group of researchers. The JBI developed the highest number of methodological assessment tools, with CASP coming second. Tools for assessing the methodological quality of randomized controlled studies were most abundant. The Cochrane Collaboration's tool for assessing risk of bias is the best available tool for assessing RCTs. For cohort and case-control studies, we recommend the use of the Newcastle-Ottawa Scale. The Methodological Index for Non-Randomized Studies (MINORS) is an excellent tool for assessing non-randomized interventional studies, and the Agency for Healthcare Research and Quality (ARHQ) methodology checklist is applicable for cross-sectional studies. For diagnostic accuracy test studies, the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool is recommended; the SYstematic Review Centre for Laboratory animal Experimentation (SYRCLE) risk of bias tool is available for assessing animal studies; Assessment of Multiple Systematic Reviews (AMSTAR) is a measurement tool for systematic reviews/meta-analyses; an 18-item tool has been developed for appraising case series studies, and the Appraisal of Guidelines, Research and Evaluation (AGREE)-II instrument is widely used to evaluate clinical practice guidelines. CONCLUSIONS: We have successfully identified a variety of methodological assessment tools for different types of study design. However, further efforts in the development of critical appraisal tools are warranted since there is currently a lack of such tools for other fields, e.g. genetic studies, and some existing tools (nested case-control studies and case reports, for example) are in need of updating to be in line with current research practice and rigor. In addition, it is very important that all critical appraisal tools remain subjective and performance bias is effectively avoided.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.403 | 0.632 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.040 | 0.032 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".