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Record W4391354425 · doi:10.11124/jbies-23-00268

The revised JBI critical appraisal tool for the assessment of risk of bias for quasi-experimental studies

2024· review· en· W4391354425 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJBI Evidence Synthesis · 2024
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsQueen's University
Fundersnot available
KeywordsCritical appraisalSystematic reviewPsychological interventionInternal validityExternal validityClinical study designResearch designRisk analysis (engineering)Management scienceRandomized controlled trialComputer sciencePsychologyMedicineMEDLINEClinical trialAlternative medicineEngineeringSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Systematic reviews of effectiveness offer a rigorous synthesis of the best evidence available regarding the effects of interventions or treatments. Randomized controlled trials are considered the optimal study design for evaluating the effectiveness of interventions and are the ideal study design for inclusion in a systematic review of effectiveness. In the absence of randomized controlled trials, quasi-experimental studies may be relied on to provide information on treatment or intervention effectiveness. However, such studies are subject to unique considerations regarding their internal validity and, consequently, the assessment of the risk of bias of these studies needs to consider these features of design and conduct. The JBI Effectiveness Methodology Group has recently commenced updating the suite of JBI critical appraisal tools for quantitative study designs to align with the latest advancements in risk of bias assessment. This paper presents the revised critical appraisal tool for risk of bias assessment of quasi-experimental studies; offers practical guidance for its use; provides examples for interpreting the results of risk of bias assessment; and discusses major changes from the previous version, along with the justifications for those changes.

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.

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 armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.231
metaresearch head score (Gemma)0.721
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2310.721
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.014
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0050.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.714
GPT teacher head0.645
Teacher spread0.069 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it