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Record W3193135925 · doi:10.35680/2372-0247.1566

A patient’s narrative of engaging HIV care: Lessons learned to harness resources and improve access to care

2021· article· en· W3193135925 on OpenAlexaffabout
David Lessard, Serge Vicente, Patrick Keeler, Bertrand Lebouché

Bibliographic record

VenuePatient Experience Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité de MontréalMcGill University Health Centre
Fundersnot available
KeywordsNarrativeHealth carePseudonymEmpowermentNursingPatient experienceStigma (botany)Human immunodeficiency virus (HIV)Government (linguistics)Public relationsSociologyMedicinePsychologyPolitical scienceFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

In Canada and the USA, about 30% of people with HIV are uninsured or not covered by government-subsidized health insurance. This paper presents a patient’s narrative of his experience being diagnosed with HIV and accessing care in the midst of his process of immigrating to and studying in Canada. The narrative explores how Vincent Croft (pseudonym) has coped with the chronicity of the infection and its associated social stigma, and the temporary solutions he found to access treatment. Engaging with healthcare providers, researchers, and other people living with HIV has allowed Croft to share his experience, including the barriers he encountered and the solutions he envisioned or attempted, resulting in self-empowerment and reinterpretations of Croft’s own trajectory. Patrick Keeler, a community-based intervener, reflects on Croft’s narrative as symptomatic of systemic issues in access to care of people living with HIV in Canada. He also illustrates how the experiential knowledge of people with similar lived experiences can trigger simple, innovative, and cost-efficient initiatives with Le Cercle Orange, which connects and mobilizes existing resources for people with HIV with no or limited access to care and treatment. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.050
GPT teacher head0.394
Teacher spread0.344 · 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 designQualitative
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

Citations1
Published2021
Admission routes2
Has abstractyes

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