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Record W2103291025 · doi:10.25011/cim.v36i2.19567

Dismantling Sociocultural Barriers to Eye Care with Tele-Ophthalmology: Lessons from an Alberta Cree Community

2013· article· en· W2103291025 on OpenAlexaffvenueabout
Sourabh Arora, Ayaz Kurji, Matthew Tennant

Bibliographic record

VenueClinical and investigative medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsQueen's UniversityUniversity of AlbertaRoyal Alexandra Hospital
Fundersnot available
KeywordsAttendanceMedicineCulturally sensitiveCulturally appropriateInclusion (mineral)Family medicineHealth careNursingCultural competencePsychologyPolitical science

Abstract

fetched live from OpenAlex

PURPOSE: There are significant disparities in access to health care amongst Aboriginal Canadians. The purpose of this study was to determine whether tele-ophthalmology services, provided to Aboriginal Canadians in a culturally-sensitive community-based clinic, could overcome social and cultural barriers in ways that would be difficult in the traditional hospital-based setting. METHODS: The Aboriginal Diabetes Wellness Program of Alberta incorporates culturally-sensitive health-related activities and rituals as a component of a diabetic retinopathy tele-ophthalmology screening program. Metrics of program attendance were collected while stakeholders participated in a survey to identify barriers to healthcare delivery. RESULTS: Aboriginal patients, cultural liaison, nurses and program administrators revealed economic, geographic, social and cultural barriers to healthcare faced by Aboriginal people. It was found that the introduction of culturally-sensitive programs led to increased appointment attendance; from 25% to 85%. Involvement of Aboriginal nurses, inclusion of culturally-sensitive activities and participation in spiritual ceremonies led to qualitative accounts of increased patient satisfaction, trust towards the healthcare team and communication amongst participants. CONCLUSIONS: A culturally-sensitive model of healthcare delivery in a community-based health clinic improved access to tele-ophthalmology services. This was demonstrated by increased attendance at appointments and increased satisfaction amongst patients.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.004
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.155
GPT teacher head0.412
Teacher spread0.257 · 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 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

Citations68
Published2013
Admission routes3
Has abstractyes

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