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Record W7036179669

Barriers and Facilitators to Children Wearing a Sports Mouthguard: A Systematic Review

2022· dissertation· en· W7036179669 on OpenAlexaboutno aff

Bibliographic record

VenueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2022
Typedissertation
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsSystematic reviewData extractionContext (archaeology)Scale (ratio)Identification (biology)Data collection
DOInot available

Abstract

fetched live from OpenAlex

A systematic review on the identification of the barriers and facilitators of wearing a sports mouthguard among children. For this, A systematic search was done from different databases following PRISMA guidelines. The six different databases including (Ovid MEDLINE, Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Embase, Embase Classic, Web of Science, and Scopus) were searched, including the search terms related to the topic. 1470 records were identified, 36 studies were included in this systematic review. The data was collected using a modified data extraction form. The barriers and facilitators found were put into five sociological levels of influence based on the Theoretical Domains Framework domains (individual, interpersonal, organisational, community, and public policy). The Newcastle-Ottawa Scale was used to measure the risk of bias in the included studies. The discovered barriers and facilitators were classified into seven TDF domains, including knowledge, beliefs about consequences, intentions, memory, attention and decision process, environmental context and resources, social influence, and emotions.

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)0.015
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.194
Teacher spread0.183 · 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.

Study designSystematic review
Domainnot available
GenreEmpirical

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)Same topicShakespeare, Adaptation, and Literary CriticismFrench-language works237,207