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Record W4387730361 · doi:10.1371/journal.pone.0293118

Overview of oral health status and associated risk factors in maritime settings: An updated systematic review

2023· review· en· W4387730361 on OpenAlexaff
Tuan Nguyen, Sanju Gautam, Sweta Mahato, Olaf Chresten Jensen, Arezoo Haghighian Roudsari, Fereshteh Baygi

Bibliographic record

VenuePLoS ONE · 2023
Typereview
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMEDLINEMedicineEnvironmental healthBioinformaticsData scienceBiologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this study is to provide an updated overview of the oral health status and associated risk factors in maritime settings. METHODS: We systematically searched PubMed, Ovid Embase, Web of Science, CINAHL and SCOPUS from January 2010 to April 2023. Two independent reviewers extracted the data. The quality of included studies was assessed using relevant assessment tools. RESULTS: A total of 260 records were found in the initial search; 24 articles met the inclusion criteria. Most studies had descriptive design, and only two randomized controlled trials were found. The main oral health issues noted are oral cancer, dental caries, periodontal diseases, oral mucosal lesions, and dental emergency. Male seafarers have higher risk of oral cancers in the tongue, lips, and oral cavity while oral mucosal lesions are more prevalent among fishermen. CONCLUSIONS: Dental caries and periodontal diseases are prevalent in both seafarers and fishermen. The consumption of tobacco, alcohol, fermentable carbohydrate, and poor oral hygiene are risk factors that affect the oral health status at sea. The occurrence of oral diseases in maritime setting requires more attention of researchers and authorities to develop strategies to tackle these issues. TRIAL REGISTRATION: Systematic review registration number in PROSPERO: CRD42020168692.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.107
GPT teacher head0.328
Teacher spread0.221 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

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