Back

HIV Risk and Intention to use PrEP among Sexually Active Female University Students in Zambia: A Cross-Sectional Survey to Understand Influential Factors

Hampanda, K.; Bolt, M.; Nayame, L.; Hamoonga, T.; Sehrt, M.; Thorne, J.; Harrison, M.; Pintye, J.; Amstutz, A.; Abuogi, L.; Mweemba, O.

2024-12-13 hiv aids
10.1101/2024.12.12.24318948 medRxiv
Show abstract

BackgroundLimited research exists on pre-exposure prophylaxis (PrEP) interest or use among female university students in high HIV-prevalence African settings. This study sought to establish the relationship between epidemiologic and perceived HIV risk and PrEP intention among Zambian female university students. MethodsWe recruited female students at an urban university to complete a survey on intention to use PrEP in the next year (primary outcome); other PrEP knowledge, attitudes, and behaviors; demographics; epidemiologic HIV risk and risk perception. Descriptive statistics, regression and mediation analyses were used. ResultsOf the 454 sexually active participants, 118 (26%) reported PrEP intention. Actual PrEP use was rare (< 5%). The odds of PrEP intention increased for those with perceived high HIV risk (aOR 3.08; 95% CI 1.71-5.55) and with each year at university (aOR 1.47; 95% CI 1.21-1.80) but decreased with higher PrEP stigma (aOR 0.91; 95% CI 0.86-0.96) and more negative PrEP perceptions (aOR 0.91; 95% CI 0.85-0.97). More epidemiologic risk factors were originally associated with PrEP intention (OR 1.24; 95% CI 1.01-1.53 for each risk factor), though this relationship weakened after adjustment for perceived HIV risk, which mediated 69% of the relationship between epidemiologic HIV risk and PrEP intention. Only 29% of high-risk participants recognized their high epidemiological HIV risk (3+ risk factors). ConclusionsAlong with PrEP education and stigma reduction, there is a need for approaches that help female university students in Zambia accurately identify their HIV risk to make informed PrEP decisions.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.