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Record W1979009166 · doi:10.1111/nin.12075

Counselling about <scp>HIV</scp> serological status disclosure: nursing practice or law enforcement? a Foucauldian reflection

2014· article· en· W1979009166 on OpenAlexaff
Patrick O’Byrne, Dave Holmes, Marie Roy

Bibliographic record

VenueNursing Inquiry · 2014
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSerostatusEmpirical researchQualitative researchPsychologyNursingEmpirical evidenceMedicineSocial psychologyHuman immunodeficiency virus (HIV)SociologyFamily medicine

Abstract

fetched live from OpenAlex

Recently, focus groups and qualitative interviews with nurses who provide frontline care for persons living with HIV highlighted the contentiousness surrounding the seemingly innocuous activity of counselling clients about HIV-status disclosure, hereafter disclosure counselling. These empirical studies highlighted that while some nurses felt they should instruct clients to disclose their HIV-positive status if HIV transmission were possible, other nurses were equally adamant that such counselling was outside the nursing scope of practice. A review of these opposing perceptions about disclosure counselling, including an examination of the empirical evidence which supports each point, revealed that the dichotomous arguments needed to be nuanced. The empirical evidence about serostatus disclosure neither supported nor refuted either of these assertions; rather, it substantiated parts of each. To create this understanding, both empirical and theoretical works are used. First, the results of empirical studies about serostatus disclosure, or lack thereof and HIV transmission is presented; as part of this, Marks and Crepaz's HIV disclosure and exposure framework is examined. Second, the work of Michel Foucault on disciplinary and pastoral power is drawn from. The outcome is a nuanced understanding about the interrelationships between disclosure counselling and nursing practice and a final interpretation about what this understanding means for public health practice.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.077
GPT teacher head0.419
Teacher spread0.342 · 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 designNot applicable
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

Citations9
Published2014
Admission routes1
Has abstractyes

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