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Record W2903843273 · doi:10.1111/cdoe.12440

Beliefs about managing dental problems among older people and dental professionals in Southern Brazil

2018· article· en· W2903843273 on OpenAlexafffund
Mariél de Aquino Goulart, Renato José De Marchi, Dalva Maria Pereira Padilha, Mario Brondani, Michael I. MacEntee

Bibliographic record

VenueCommunity Dentistry And Oral Epidemiology · 2018
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
FundersMinistério da EducaçãoCanadian Bureau for International Education
KeywordsDenturesMedicineThematic analysisFocus groupContext (archaeology)DentistryAnxietyDental careFamily medicineQualitative researchPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: To explore the sociocultural context in which patients and dentists in urban and rural communities in Southern Brazil interpret dental problems. METHOD: Beliefs and experiences related to dental problems were explored in eight focus groups involving a total of 41 older patients, and in direct interviews with two dentists and two dental assistants. The interactions were audio recorded and transcribed for thematic analysis. RESULTS: The beliefs and experiences of the participants focused on four main themes: cultural beliefs; dental services; decisions to extract teeth; and expectations for change. A culture of pre-nuptial tooth loss and complete dentures was considered beneficial to young women. Although dental services at the time were scarce in the region, demands for relief of pain were extensive despite the fear and anxiety of the participants. Extraction of teeth and fabrication of complete dentures were the usual dental treatments available, although some participants felt that dentists withheld other treatment options. Participants were hopeful that dental services would improve for their children. CONCLUSIONS: Patients and dental professionals in urban and rural communities of Southern Brazil managed dental problems within a culture of limited access and availability of services that favoured dental extractions and complete dentures.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.041
GPT teacher head0.375
Teacher spread0.334 · 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 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

Citations12
Published2018
Admission routes2
Has abstractyes

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