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Record W4393408763 · doi:10.1097/jnc.0000000000000460

A Systematic Review of Oral Pre-exposure Prophylaxis HIV Adherence Interventions

2024· review· en· W4393408763 on OpenAlexafffund
Marlene Haines, Amanda Vandyk, Becky Skidmore, Lauren Orser, Patrick O’Byrne

Bibliographic record

VenueJournal of the Association of Nurses in AIDS Care · 2024
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsVictorian Order of NursesOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicinePsychological interventionPre-exposure prophylaxisIntervention (counseling)Human immunodeficiency virus (HIV)Systematic reviewClinical trialMedication adherenceAlternative medicineFamily medicineMEDLINEIntensive care medicineInternal medicineNursingMen who have sex with menPathology

Abstract

fetched live from OpenAlex

ABSTRACT: Clinical trials of pre-exposure prophylaxis (PrEP) to prevent HIV infection have established its efficacy as upwards of 99%. Despite this, the effectiveness of this medication has been shown to be diminished by individual factors, such as medication adherence. We completed a systematic review to identify and describe interventions to improve oral PrEP adherence. Overall, 16 articles were located. Two of the articles reported on results from the same trial and were collapsed for analysis, bringing the total to 15 studies. Twelve unique PrEP adherence interventions were tested, with the most common intervention being the use of mobile phone technology, which was used in 7 (46%) of the studies. Ten (67%) studies found that medication adherence improved when participants received an intervention to support adherence. Adherence intervention strategies effectively improved PrEP adherence. Further research into PrEP adherence interventions is warranted, particularly among diverse groups.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.041
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.036
GPT teacher head0.424
Teacher spread0.388 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations7
Published2024
Admission routes2
Has abstractyes

Explore more

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