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Record W2073432479 · doi:10.1258/095646207782212243

Inadequate adherence to antiretroviral treatment and prevention in hospital and community sites in Burkina Faso and Mali: a study by the ATARAO group

2007· article· en· W2073432479 on OpenAlexafffund
S. Ag Aboubacrine, Pascal Niamba, Cathérine Boileau, Marı́a Victoria Zunzunegui, Nimâ Machouf, Vinh‐Kim Nguyen, S. Rashed

Bibliographic record

VenueInternational Journal of STD & AIDS · 2007
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité de MontréalMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsMedicineHousewifeLogistic regressionAntiretroviral therapyAntiretroviral treatmentCross-sectional studyDemographyHuman immunodeficiency virus (HIV)Environmental healthPediatricsFamily medicineInternal medicineViral load

Abstract

fetched live from OpenAlex

Our objective was to determine the prevalence and identify the factors that influence antiretroviral therapy (ART) adherence among patients in Bamako and Ouagadougou. A cross-sectional study was conducted among 94 men and 176 women receiving ART. Data were collected through questionnaires and chart reviews. Logistic regressions were performed to isolate determinants of adherence. Overall, 58% of the patients were adherent, but there were differences in the levels of adherence according to country and treatment site. Sociodemographic factors were not associated with adherence. However, social characteristics such as having children, in Ouagadougou, or being a housewife and not planning to have a child in the next year, in Bamako were associated with adherence. Time on ART was negatively associated with adherence in both countries with decline occurring later in Bamako. Levels of adherence are inadequate particularly among more experienced patients. Further adherence research and monitoring using longitudinal designs are warranted to assess the extent to which adherence is declining with time on treatment.

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)0.000
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 score0.182
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.033
GPT teacher head0.375
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 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

Citations17
Published2007
Admission routes2
Has abstractyes

Explore more

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