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Record W2792669626 · doi:10.1177/2325958218759208

HIV-Positive Patients’ Perceptions of Antiretroviral Therapy Adherence in Relation to Subjective Time: Imprinting, Domino Effects, and Future Shadowing

2018· article· en· W2792669626 on OpenAlexafffund
David Lessard, Isabelle Toupin, Kim Engler, Andràs Lènàrt

Bibliographic record

VenueJournal of the International Association of Providers of AIDS Care (JIAPAC) · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health ResearchCanadian HIV Trials Network, Canadian Institutes of Health Research
KeywordsTemporalityMedicineFocus groupPerceptionPsychological interventionHuman immunodeficiency virus (HIV)Imprinting (psychology)Antiretroviral therapyTemporalitiesAntiretroviral treatmentClinical psychologyPsychologyFamily medicineNursingViral load

Abstract

fetched live from OpenAlex

Antiretroviral treatment adherence barriers are major concerns in HIV care. They are multiple and change over time. Considering temporality in patients' perceptions of adherence barriers could improve adherence management. We explored how temporality manifests itself in patients' perceptions of adherence barriers. We conducted 2 semi-structured focus groups on adherence barriers with 12 adults with HIV which were analyzed with grounded theory. A third focus group served to validate the results obtained. Three temporal categories were manifest in HIV-positive patients' perceptions of barriers: (1) imprinting (events with lasting impacts on patients), (2) domino effects (chain of life events), and (3) future shadowing (apprehension about long-term adherence). An overarching theme, weathering (gradual erosion of abilities to adhere), traversed these categories. These temporalities explain how similar barriers may be perceived differently by patients. They could be useful to providers for adapting their interventions and improving understanding of patients' subjective experience of adherence.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.331

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 studies0.0000.000
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 head0.005
GPT teacher head0.275
Teacher spread0.270 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

Explore more

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