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Record W3082500236 · doi:10.18192/aporia.v12i1.4832

Freins à l’observance au traitement antirétroviral en milieu rural de la République Démocratique du Congo et regard sur l’Alliance thérapeutique dans le circuit de soins

2020· article· fr· W3082500236 on OpenAlexvenueno aff
Simon-Decap Mabakutuvangilanga Ntela, Jean‐Manuel Morvillers, Nathalie Goutté, Cyril Crozet, Mathieu Ahouah, Marie-Claire Omanyondo-Ohambe, Bernard Ntoto-Kunzi, Félicien Tshimungu Kandolo, Monique Rothan‐Tondeur

Bibliographic record

VenueAporia · 2020
Typearticle
Languagefr
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesAllianceHuman immunodeficiency virus (HIV)Political scienceAntiretroviral therapyMedicineArtViral loadFamily medicine

Abstract

fetched live from OpenAlex

Cette étude vise à comprendre les freins à l’observance au traitement antirétroviral et à porter un regard critique sur la qualité d’alliance thérapeutique Infirmier-patient. Il s’agit d’une étude qualitative phénoménologique réalisée dans deux hôpitaux ruraux de la province du Kongo-central en République Démocratique du Congo (RDC). Des entretiens semi-directifs ont été réalisés auprès de patients. Deux grands groupes de freins ont été relevés :
 L’un lié au patient (manque de nourriture, le ressenti (peur, doute)) et l’autre en rapport avec son environnement (rupture des antirétroviraux, influence des médias, des religieux et autres croyances traditionnelles…). Ces freins généraient des forces antagonistes influençant négativement l’observance au traitement antirétroviral.
 Cette étude met en évidence l’existence des écarts sur la qualité d’alliance thérapeutique dans le circuit de soins. Ainsi, surmonter les forces négatives, renforcer les capacités infirmières et revisiter les programmes de formation Infirmière sur les questions du VIH semblent une nécessité.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.313
Teacher spread0.286 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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