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Record W4404310123 · doi:10.2196/62801

Preferences for Starting Daily, On-Demand, and Long-Acting Injectable HIV Preexposure Prophylaxis Among Men Who Have Sex With Men in the United States (2021-2022): Nationwide Online Cross-Sectional Study

2024· article· en· W4404310123 on OpenAlexvenueno aff
Duygu İşlek, Travis Sanchez, Jennifer L. Glick, Jeb Jones, Keith Rawlings, Supriya Sarkar, Patrick S. Sullivan, Vani Vannappagari

Bibliographic record

VenueJMIR Public Health and Surveillance · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious Diseases
KeywordsPre-exposure prophylaxisMen who have sex with menMedicineFamily medicineHuman immunodeficiency virus (HIV)Demography

Abstract

fetched live from OpenAlex

BACKGROUND: Long-acting (LA) injectable preexposure prophylaxis (PrEP) and on-demand PrEP may improve overall PrEP uptake among men who have sex with men (MSM), but little is understood about the PrEP option preferences of MSM in practical scenarios where they may choose between various PrEP options. OBJECTIVE: This study aims to examine the preferences for starting various PrEP options among a US nationwide online convenience sample of MSM from September 2021 to February 2022. METHODS: Participants reporting no prior HIV diagnosis were provided brief descriptions of each PrEP option and were asked, "If [PrEP option] were available from your local doctor and you could access it for free, would you go to your doctor in the next month to start [PrEP option]?" Those who said "yes" to multiple options were asked to rank them in order of preference. MSM currently taking daily oral (DO) PrEP were asked whether they would switch to on-demand or LA PrEP options. Log binomial models were created to examine the association between willingness to start or switch to on-demand and LA PrEP with various sociodemographic and behavioral factors. RESULTS: In the analytic sample (N=7760), among the participants who did not use any PrEP in the past 12 months (n=5108, 66%), 54% (n=2445) reported willingness to start at least 1 PrEP option and 41% (n=1845) of participants showed interest in starting multiple PrEP options. Overall, the highest willingness was reported for on-demand PrEP (n=2235, 44%), followed by DO PrEP (n=2174, 43%) and LA PrEP (n=1482, 29%). LA PrEP was ranked first among those interested in multiple options. Characteristics associated with ranking LA PrEP as a first option to start PrEP versus DO or on-demand PrEP were region of residence (residing in the West vs Northeast), report of sexually transmitted infection diagnosis in the past year, report of illicit drug use other than marijuana in the past year, and prior awareness of LA PrEP. Among current DO PrEP users (n=2379, 31%), 58% (n=1386) were willing to switch to on-demand or LA PrEP, and LA PrEP was ranked first among participants who were open to switching to both options. Willingness to switch to LA PrEP was higher among those who used illicit drugs other than marijuana in the past year, who heard of LA PrEP prior to the survey, and those who took 15 or less doses of oral PrEP in the last 30 days. CONCLUSIONS: LA PrEP was the highest-ranked option among most MSM who were willing to try multiple options or switch from DO PrEP. These findings highlight that LA PrEP might fill coverage gaps among MSM who use illicit drugs, have had a recent sexually transmitted infection diagnosis, and have less than optimal DO PrEP 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 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)0.002
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.040
GPT teacher head0.368
Teacher spread0.328 · 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

Citations12
Published2024
Admission routes1
Has abstractyes

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