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Record W2768928076 · doi:10.12973/ejmste/80723

Paediatricians’ Knowledge, Attitude and Practice towards Children’s Oral Health in North Cyprus

2017· article· en· W2768928076 on OpenAlexaboutno aff
Ozkem Azmi Oge, Serap Çetiner

Bibliographic record

VenueEurasia Journal of Mathematics Science and Technology Education · 2017
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOral healthFamily medicineFeelingOral health careEarly childhood cariesHealth careQuarter (Canadian coin)Health educationPublic healthNursingPsychology

Abstract

fetched live from OpenAlex

The frequent one-to-one contact offers an ideal opportunity for paediatricians to perform oral health risk assessment and educate families on preventive oral health care at early stages. The aim of this research is to assess paediatricians’ knowledge, attitude and practice regarding children’s oral health. A cross-sectional survey was sent to all paediatricians currently practicing in the North Cyprus. Data was analysed using statistical package for social sciences for descriptive and univariate analysis. Response rate was 92%. Almost all of the paediatricians stated that oral health advice should be included in their routine health supervision. However, many of them reported not feeling confident enough to take active role in preventive oral health care. Less than quarter of the total paediatricians reported that they had received oral health education previously. Previous oral health education/training was associated with improved oral health knowledge, confidence in entering oral health discussions with caregivers and identifying oral health pathologies. The results of our study support the need for paediatricians to receive further oral health training/education.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.027
GPT teacher head0.389
Teacher spread0.362 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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Same venueEurasia Journal of Mathematics Science and Technology EducationSame topicDental Health and Care UtilizationFrench-language works237,207