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Record W4310784810 · doi:10.1016/s2352-3018(22)00266-1

Free HIV self-test for identification and linkage to care of previously undetected HIV infection in men who have sex with men in England and Wales (SELPHI): an open-label, internet-based, randomised controlled trial

2022· article· en· W4310784810 on OpenAlexaff
Alison Rodger, Leanne McCabe, Andrew Phillips, Fiona Lampe, Fiona Burns, Denise Ward, Valérie Delpech, Peter Weatherburn, T. Charles Witzel, Richard Pebody, Peter Kirwan, Michelle M. Gabriel, Jameel Khawam, Michael Brady, Kevin Fenton, Roy Trevelion, Yolanda Collaço‐Moraes, Sheena McCormack, David Dunn

Bibliographic record

VenueThe Lancet HIV · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsHealth Care Foundation
FundersMedical Research CouncilNational Institute for Health and Care ResearchNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsMedicineMen who have sex with menFamily medicineDemographyIncidence (geometry)Human immunodeficiency virus (HIV)Pediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: High levels of HIV testing in men who have sex with men remain key to reducing the incidence of HIV. We aimed to assess whether the offer of a single, free HIV self-testing kit led to increased HIV diagnoses with linkage to care. METHODS: SELPHI was an internet-based, open-label, randomised controlled trial that recruited participants via sexual and social networking sites. Eligibility criteria included being a man or trans woman (although trans women are reported separately); being resident in England or Wales, UK; being aged 16 years or older; having had anal intercourse with a man; not having a positive HIV diagnosis; and being willing to provide name, email address, date of birth, and consent to link to national HIV databases. Participants were randomly allocated (3:2) by computer-generated number sequence to receive a free HIV self-test kit (BT group) or to not receive this free kit (nBT group). Online surveys collected data at baseline, 2 weeks after enrolment (BT group only), 3 months after enrolment, and at the end of the study. The primary outcome was confirmed (linked to care) new HIV diagnosis within 3 months of enrolment, analysed by intention to treat. Those assessing the primary outcome were masked to allocation. This study is registered with the ISRCTN Clinical Trials Register, number ISRCTN20312003. FINDINGS: 10 111 participants (6049 in BT group and 4062 in nBT group) enrolled between Feb 16, 2017, and March 1, 2018. The median age of participants was 33 years (IQR 26-44 years); 9000 (89%) participants were White; 8118 (80%) participants were born in the UK; 81 (1%) participants were transgender men; 4706 (47%) participants were university educated; 1537 (15%) participants had never been tested for HIV; and 389 (4%) participants were taking pre-exposure prophylaxis. At enrolment, 7282 (72%) participants reported condomless anal sex with at least one male partner in the previous 3 months. In the BT group, of the 4511 participants for whom HIV testing information was available, 4263 (95%) reported having used the free HIV self-test kit within 3 months.Within 3 months of enrolment there were 19 confirmed new HIV diagnoses (0·31%) in 6049 participants in the BT group and 15 (0·37%) of 4062 in the nBT group (p=0·64). INTERPRETATION: The offer of a single, free HIV self-test did not lead to increased rates of new HIV diagnoses, which could reflect decreasing HIV incidence rates in the UK. Nonetheless, the offer of a free HIV self-testing kit resulted in high HIV testing rates, indicating that self-testing is an attractive testing option for a large group of men who have sex with men. FUNDING: UK National Institute for Health and Care Research.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0150.001

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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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 designRandomized trial
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

Citations34
Published2022
Admission routes1
Has abstractyes

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