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Record W4224920905 · doi:10.1097/jnc.0000000000000335

Invalid Results in the GetaKit Study in Ottawa: A Real-World Observation of the INSTI® HIV Self-test Among Persons At Risk for HIV

2022· article· en· W4224920905 on OpenAlexaffabout
Patrick O’Byrne, Alexandra Musten, Lauren Orser, Cynthia Horvath

Bibliographic record

VenueJournal of the Association of Nurses in AIDS Care · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Test (biology)Hiv testPsychologyMedicineGerontologyClinical psychologyVirologyEnvironmental healthHealth servicesPopulation

Abstract

fetched live from OpenAlex

ABSTRACT: HIV self-testing corresponds with more frequent testing, better user satisfaction, and higher positivity rates compared with clinic-based testing. We implemented an open cohort prospective observational study, which provided a website through which persons could do online HIV self-assessments and, if eligible, receive a free HIV self-test. We implemented this project on July 20, 2021 and used the bioLytical INSTI® test. Herein, we describe the number of tests participants reported as invalid, which started at a rate of one fifth of all ordered tests and decreased to 8% after we provided more instructions on completing the test. Our data suggest that a high rate of invalids occur with self-testing in the real-world. Although this has cost implications, we feel this rate is acceptable, considering that 25% of our cohort reported no previous HIV testing. Our take-away message is that HIV self-testing requires additional supports and resources to function as an effective testing intervention.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.023
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.339
Teacher spread0.311 · 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

Citations9
Published2022
Admission routes2
Has abstractyes

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