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Record W4312118035 · doi:10.2196/39685

Maximizing Oral Health Outcomes of Aboriginal and Torres Strait Islander People With End-stage Kidney Disease Through Culturally Secure Partnerships: Protocol for a Mixed Methods Study

2022· article· en· W4312118035 on OpenAlexvenueno aff
Sneha Sethi, Brianna Poirier, Joanne Hedges, Zell Dodd, Priscilla Larkins, Cindy Zbierski, Stephen P. McDonald, Shilpanjali Jesudason, Lisa Jamieson

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilFaculty of Health and Medical Sciences, University of Western Australia
KeywordsMedicineIndigenousIntervention (counseling)Pacific islandersNursingHealth careFamily medicineGerontologyEnvironmental healthPopulationPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Dialysis for end-stage kidney disease (ESKD) is the leading cause of hospitalization among Aboriginal and Torres Strait Islander individuals in Australia. Poor oral health is commonly the only obstacle preventing Aboriginal and Torres Strait Islander people with ESKD in Australia from receiving kidney transplant. OBJECTIVE: This study aims to improve access, provision, and delivery of culturally secure dental care for Aboriginal and Torres Strait Islander individuals with ESKD in South Australia through the following objectives: investigate the facilitators of and barriers to providing oral health care to Aboriginal and Torres Strait Islander patients with ESKD in South Australia; investigate the facilitators of and barriers to maintaining oral health among Aboriginal and Torres Strait Islander people with ESKD in South Australia; facilitate access to and completion of culturally secure dental care for Aboriginal and Torres Strait Islander individuals with ESKD and their families; provide oral health promotion training for Aboriginal health workers (AHWs) at each of the participating Aboriginal Community Controlled Health Services, with a specific emphasis on oral health needs of patients with ESKD; generate co-designed strategies to better facilitate access to and provision of culturally secure dental services for Aboriginal and Torres Strait Islander people living with ESKD; and evaluate participant progress and AHW oral health training program. METHODS: This collaborative study is divided into 3 phases: exploratory phase (baseline), intervention phase (baseline), and evaluation phase (after 6 months). The exploratory phase will involve collaboration with stakeholders in different sectors to identify barriers to providing oral health care; the intervention phase will involve patient yarns, patient oral health journey mapping, clinical examinations, culturally secure dental care provision, and strategy implementation workshops; and the evaluation phase will involve 6-month follow-up clinical examinations, participant evaluations of dental care provision, and AHW evaluation of oral health training. RESULTS: Stakeholder interviews were initiated in November 2021, and participant recruitment commenced in February 2022. The first results are expected to be submitted for publication in December 2022. CONCLUSIONS: Expected outcomes will identify the burden of oral disease experienced by Aboriginal and Torres Strait Islander people with ESKD in South Australia. Qualitative outcomes are expected to develop a deeper appreciation of the unique challenges regarding oral health for individuals with ESKD. Through stakeholder engagement, responsive strategies and policies will be co-designed to address participant-identified and stakeholder-identified challenges to ensure accessibility to culturally secure dental services for Aboriginal and Torres Strait Islander individuals with ESKD. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/39685.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.066
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.066
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.038
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0030.004
Science and technology studies0.0060.003
Scholarly communication0.0040.003
Open science0.0050.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0530.008

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 head0.290
GPT teacher head0.618
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations5
Published2022
Admission routes1
Has abstractyes

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