MétaCan
Menu
Back to cohort
Record W2269763004 · doi:10.1016/j.jana.2016.02.005

Preliminary Findings on the Association Between Symptoms of Depression and Adherence to Antiretroviral Therapy in Individuals Born Inside Versus Outside of Canada

2016· article· en· W2269763004 on OpenAlexafffundabout
Elena Ivanova, Adina Coroiu, Amrita Ahluwalia, Eugene Alexandrov, Kathryn D. Lafreniere

Bibliographic record

VenueJournal of the Association of Nurses in AIDS Care · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsConcordia UniversityFife HouseMcGill University
FundersCanadian Institutes of Health ResearchUniversity of Windsor
KeywordsDepression (economics)Antiretroviral therapyMedicineAffect (linguistics)Human immunodeficiency virus (HIV)Confidence intervalAssociation (psychology)DemographyPsychiatryInternal medicinePsychologyFamily medicineViral loadPsychotherapist

Abstract

fetched live from OpenAlex

For optimal health, people living with HIV (PLWH) need to adhere to antiretroviral therapy (ART). We explored the relationship between symptoms of depression and ART adherence for PLWH born inside versus outside of Canada. PLWH taking ART (N = 57) completed self-assessments of depression and adherence to ART. Adherence rates did not differ significantly for PLWH who were born outside (66.7% were ≥95% adherent) versus inside Canada (51.6% were ≥95% adherent), but the relationship between symptoms of depression and ART adherence depended on the country of birth: for individuals born in Canada, depression was associated with lower ART adherence (β = -.21, p = .005, 95% confidence interval -.35 to -.07); for PLWH born outside of Canada there was no association between symptoms of depression and ART adherence. Symptoms of depression may not universally affect ART adherence; country of birth may be one critical variable impacting this relationship.

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)0.001
metaresearch head score (Gemma)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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

Citations2
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueJournal of the Association of Nurses in AIDS CareSame topicHIV/AIDS Research and InterventionsFrench-language works237,207