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Record W3022697548 · doi:10.1016/j.pmedr.2020.101100

Barriers to post exposure prophylaxis use among men who have sex with men in sub-Saharan Africa: An online cross-sectional survey

2020· article· en· W3022697548 on OpenAlexaff
Sandra Isano, Rex Wong, Jenae Logan, Soha El-Halabi, Ziad El‐Khatib

Bibliographic record

VenuePreventive Medicine Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsMen who have sex with menDemographyCross-sectional studyLogistic regressionPre-exposure prophylaxisTransgenderMedicinePsychological interventionDescriptive statisticsOddsHuman immunodeficiency virus (HIV)Environmental healthPsychologyFamily medicineSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Curbing new HIV infections among MSM in SSA remains problematic, due to cultural beliefs, norms that oppose same-sex acts, and criminalization of same-sex acts. No study focused on barriers to PEP use in SSA region has been conducted. Our study focused on identifying barriers to Post-Exposure Prophylaxis (PEP) use among MSM in sub-Saharan Africa (SSA). METHODS: An online cross-sectional survey was sent out to members of 14 Lesbian, Gay, Transgender, Bisexual, Queer (LGBTQ) associations in SSA, to identify barriers to PEP utilization in MSM. A total of 207 MSM from 22 countries in SSA completed the survey between 8 January 2019 and 23 February 2019. Descriptive statistics were generated, chi-square and backward stepwise logistic regression analysis were performed to evaluate the association between the outcome "PEP use" and other variables. RESULTS: Most of the MSM were aged 18 to 30, and the majority (220, 74.6%) described themselves as gay. Rwanda had the highest number of respondents (117, 39.7% of the total), followed by Nigeria, Ghana and South-Africa.The majority of respondents reported having heard about PEP (234, 80.7%), and the average PEP correct knowledge level was 59%.Five characteristics were associated with increased odds of using PEP: Age, having vocational education, having heard of PEP, knowledge of where to get PEP, and having been refused housing. CONCLUSION: There is a need for a collaborative effort between policy makers, key players in HIV prevention, and MSM associations in SSA to remove barriers to PEP uptake to promote optimal PEP utilization amongst MSM.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.338
Teacher spread0.287 · 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 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

Citations23
Published2020
Admission routes1
Has abstractyes

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