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Record W3017022795 · doi:10.4103/jispcd.jispcd_438_19

Oral Health Status of Schoolchildren Living in Remote Rural Andean Communities: A Cross-Sectional Study

2020· article· en· W3017022795 on OpenAlexaff
Dave A. Bergeron, Lise R. Talbot, Isabelle Gaboury

Bibliographic record

VenueJournal of International Society of Preventive and Community Dentistry · 2020
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversité du Québec à RimouskiUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineInterquartile rangeConfidence intervalPsychological interventionCross-sectional studyEnvironmental healthRural areaOral healthRural healthDemographyDentistryNursing

Abstract

fetched live from OpenAlex

A BSTRACT Objective: Oral health promotion (OHP) was introduced in Peruvian primary schools in 2013, and no evaluation has been undertaken in rural areas since then. To measure OHP outcomes, this cross-sectional study aimed to assess the oral health (OH) status of schoolchildren living in a remote rural area of the Cusco region. Materials and methods: Sixty-six children were recruited in three remote rural communities and in a rural district capital. Six dimensions of OH (knowledge, attitudes, behaviors, dental plaque, dental caries, and quality of life related to OH) were measured using self-administered questionnaires and dental examinations. Wilcoxon–Mann–Whitney tests were conducted to compare outcomes between two types of settings (remote rural community and district capital). Multiple linear regression models were fit to identify which variables can explain the variance observed in the decayed, missing, and filled teeth (DMFT) index. Results: The median percentage of dental plaque in remote rural communities was 78.7+ (interquartile range [IQR] 71.5–82.8) and 78.6+ (IQR 72.7–82.2) in the district capital ( P = 0.90). The prevalence of dental caries was estimated to be 94.1+ (95+ confidence interval [CI] 71.1–>99.9) in the district capital and 98.0+ (95+ CI 88.3–>99.9) in remote rural communities ( P = 0.43). Conclusion: These results suggested that OHP interventions had not reached their full potential. Identifying different factors that influence the reported outcomes would provide a more comprehensive understanding and help to tailor OHP interventions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.051
GPT teacher head0.389
Teacher spread0.338 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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