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Record W4366597924 · doi:10.1136/bmjopen-2022-069906

Strategies used to manage overlap of primary study data by exercise-related overviews: protocol for a systematic methodological review

2023· article· en· W4366597924 on OpenAlexaff
Ruvistay Gutiérrez-Arias, Dawid Pieper, Carole Lunny, Rodrigo Torres‐Castro, Raúl Aguilera-Eguía, Pamela Serón

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsPublic Health OntarioUniversity of TorontoInstitute of Health Services and Policy Research
FundersUniversitat Autònoma de BarcelonaUniversitat de Barcelona
KeywordsMedicineSystematic reviewMEDLINEPsychological interventionCochrane LibraryProtocol (science)Grey literatureAlternative medicinePathologyNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: One of the most conflicting methodological issues when conducting an overview is the overlap of primary studies across systematic reviews (SRs). Overlap in the pooled effect estimates across SRs may lead to overly precise effect estimates in the overview. SRs that focus on exercise-related interventions are often included in overviews aimed at grouping and determining the effectiveness of various interventions for managing specific health conditions. The aim of this systematic methodological review is to describe the strategies used by authors of overviews focusing on exercise-related interventions to manage the overlap of primary studies. METHODS AND ANALYSIS: A comprehensive search strategy has been developed for different databases and their platforms. The databases to be consulted will be MEDLINE (Ovid), Embase (Ovid), The Cochrane Database of Systematic Reviews (Cochrane Library) and Epistemonikos. Two reviewers will independently screen the records identified through the search strategy and extract the information from the included overviews. The frequency and the type of overlap management strategies of the primary studies included in the SRs will be considered as the main outcome. In addition, the recognition of the lack of use of any overlap management strategy and the congruence between planning and conducting the overview focusing on overlap management strategies will be assessed. A subgroup analysis will be carried out according to the journal impact factor, year of publication and compliance with the Preferred Reporting Items for Overviews of Reviews statement. ETHICS AND DISSEMINATION: This study will not involve human subjects and therefore does not require ethics committee approval. However, the conduct and reporting of the findings of this review will be conducted in a rigorous, systematic and transparent manner, which relates to research ethics.The findings of this review will be presented at scientific conferences and published as one or more studies in peer-review scientific journals related to rehabilitation or research methods.

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

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: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearchMeta-epidemiology (broad)
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
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)0.432
metaresearch head score (Gemma)0.061
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4320.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0110.001
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0110.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.972
GPT teacher head0.726
Teacher spread0.246 · 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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

MetaresearchMeta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
DomainMethods
GenreProtocol

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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