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Record W3115985147 · doi:10.1136/bmjopen-2020-042975

Practicability of lower extremity functional performance tests and their measurement properties in elite athletes: protocol for a systematic review

2020· review· en· W3115985147 on OpenAlexaff
Rosalyn Cooke, Alison Rushton, James Martín, Lee Herrington, Nicola R Heneghan

Bibliographic record

VenueBMJ Open · 2020
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsWestern University
Fundersnot available
KeywordsData extractionMedicineInterpretabilityProtocol (science)AthletesSports medicineMeta-analysisReliability (semiconductor)MEDLINESystematic reviewApplied psychologyPhysical medicine and rehabilitationPhysical therapyArtificial intelligenceComputer scienceAlternative medicinePsychologyPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Lower extremity injury (LEI) is highly prevalent and its occurrence increases the risk of future injury in athletic populations. Identifying athletes at risk of injury is the key to target injury-prevention programmes. Functional performance tests (FPT) assess an athlete's ability to produce and accept forces during movement tasks reflective of those experienced in sport, and are used to identify deficits in physical qualities or neuromuscular control. This review aims to identify FPT which have potential to predict LEI and assess their measurement properties associated with reliability, validity, responsiveness and practicability (interpretability and feasibility). METHODS/ANALYSIS: This protocol will be reported using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol and the COnsensus-based Standards for the selection of health Measurement INstruments Methodology. The search strategy has two stages: stage 1 will identify lower limb FPT used in athletic populations; and stage 2 will assess the measurement properties of the identified FPT. A sensitive search strategy will use MEDLINE, EMBASE, CINHAL and SPORTdiscus databases; from inception to June 2020. Hand searching reference lists, key journals and grey literature will be completed. One reviewer will complete search 1 and data extraction. Two reviewers will complete the search, data extraction and risk-of-bias assessment for search 2. Evidence will be pooled or summarised by individual measurement property by each individual study and grouped by FPT. Meta-analysis using a random effects model with subgroup analysis will be performed where possible. Pooled or summarised results for each FPT in relation to each measurement property will be rated against the criteria for good measurement properties. Two reviewers will assess the overall body of evidence per measurement property per FPT using the modified Grading of Recommendations, Assessment, Development and Evaluation guidelines. This review will enable clinicians to make an informed choice when selecting FPT. ETHICS AND DISSEMINATION: No ethical approval is required for this review and the results will be disseminated through peer-reviewed publications and submitted for conference presentation. PROSPERO REGISTRATION NUMBER: CRD42020188932.

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

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.091
metaresearch head score (Gemma)0.146
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.091
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.146
Meta-epidemiology (narrow)0.0080.006
Meta-epidemiology (broad)0.0240.023
Bibliometrics0.0130.012
Science and technology studies0.0040.006
Scholarly communication0.0090.009
Open science0.0050.006
Research integrity0.0110.008
Insufficient payload (model declined to judge)0.0660.009

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 head0.392
GPT teacher head0.462
Teacher spread0.070 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
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

Citations7
Published2020
Admission routes1
Has abstractyes

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