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Record W4393436511 · doi:10.1177/22925503241241088

First Nations Patients’ Experience Receiving Care for Cleft Lip and Palate in a Multidisciplinary Clinic Setting

2024· article· en· W4393436511 on OpenAlexaffabout
Haley Shade, A. Robertson Harrop, Donald F Mcphalen, Pamela Roach

Bibliographic record

VenuePlastic Surgery · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultidisciplinary approachMedicineDentistryOrthodonticsFamily medicineSociology

Abstract

fetched live from OpenAlex

Purpose: Our small-scale qualitative study sought to explore the experiences of Indigenous patients receiving care for cleft lip and/or palate at a multidisciplinary clinic. There currently are no published studies that demonstrate the experiences of cleft lip and/or palate patients receiving care in multidisciplinary clinics in Canada. This work is foundational to informing future care in a way that is reflective and cognizant of Indigenous ways of life and lived experiences. Method: Participants were recruited via purposive and snowball sampling through community networks and public advertising in relevant healthcare spaces. Semi-structured interviews were completed; transcribed verbatim and descriptive codes were generated using Indigenist research methodologies through the Blackfoot medicine wheel. Results: Five participants that included patients, parents of patients with cleft lip and/or palate, and Indigenous health liasions were interviewed. Participants indicated a lack of spiritual health, the physical demands of having a cleft lip and/or palate on a patient and their families, the fear and unknown associated with a new cleft lip and/or palate diagnosis, and lack of cultural support, awareness and racism may negatively impact mental health. Conclusion: Indigenous patients must receive cleft lip and/or palate care that is cognizant of both their cultural needs identified in our study but also reflective of the ways in which health may be conceptualized for Indigenous patients. The following models of care suggested in our study must also seek to address historic mandates that include UNDRIP and the Truth and Reconciliation Commission's Calls to Action.

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)0.000
metaresearch head score (Gemma)0.004
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 score0.014
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
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 science0.0000.000
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 head0.023
GPT teacher head0.310
Teacher spread0.287 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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