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Record W1567178231 · doi:10.1111/adj.12321

Exploring child dental service use among migrant families in metropolitan Melbourne, Australia

2015· article· en· W1567178231 on OpenAlex
Bradley Christian, Dana Young, Lisa Gibbs, Andrea de Silva, Lisa Gold, Elisha Riggs, Hanny Calache, Maryanne Tadic, Martin T. Hall, Laurence Moore, Elizabeth Waters

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralian Dental Journal · 2015
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsRichmond Hospital
FundersAustralian Research CouncilMedical Research Council
KeywordsSnowball samplingMedicineOutreachPopulationFamily medicineEarly childhood cariesContext (archaeology)Oral healthEnvironmental healthGeography

Abstract

fetched live from OpenAlex

BACKGROUND: This study describes and explores factors related to dental service use among migrant children. METHODS: A cross-sectional analysis of baseline data from Teeth Tales, an exploratory trial implementing a community based child oral health promotion intervention. The sample size and target population was 600 families with 1-4 year old children from Iraqi, Lebanese and Pakistani backgrounds residing in metropolitan Melbourne. Participants were recruited into the study using purposive and snowball sampling techniques. RESULTS: Most (88%; 550/625) children had never visited the dentist (mean (SD) age 3.06 years (1.11)). In the fully adjusted model the variable most significantly associated with child dental visiting was parent reported 'no reason for child to visit the dentist' (OR = 0.07, p < 0.001). Of those children whose parents reported their child had no reason to visit the dentist, 22% (37/165) experienced dental caries with 8% (13/165) at the level of cavitation. CONCLUSIONS: Dental service use by migrant preschool children was very low. The relationship between perceived dental need and dental service use is currently not aligned. One in 10 children of select migrant background had visited a dentist, which is in the context of 1 in 3 with dental caries. To improve utilization, health services should consider organizational cultural competence, outreach and increased engagement with the migrant community.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.157
GPT teacher head0.343
Teacher spread0.185 · 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