The research team, led by Mary Aku Ogum and including Thomas Hormenu and Edward Wilson Ansah, set out to quantify both the prevalence of risky sexual behaviours and the social and demographic factors that predict them among unmarried, regular undergraduate students. Their motivation was straightforward: university students in Ghana, as in many countries, represent a large, mobile, and socially transitional population. They are typically living away from parental oversight for the first time, navigating new peer environments, and encountering the freedoms and pressures of early adulthood. Studies from universities in multiple countries have shown that this group is more likely to be sexually active and to engage in behaviours with negative consequences for health and academic achievement, making them a priority population for prevention efforts.

Methodologically, the study was ambitious in scale. The researchers conducted a quantitative cross-sectional survey using a multistage sampling procedure to recruit 10,896 undergraduate students, split evenly between 5,448 males and 5,448 females. Data were collected with an adapted questionnaire drawn from the Core Expanded Questions of the Global School-based Student Health Survey, a standardized instrument designed to allow comparison across settings and countries. The team then analyzed responses using frequencies, percentages, and binary logistic regression, a statistical technique that estimates how strongly each candidate factor predicts a binary outcome, in this case whether a student engaged in risky sexual behaviour. The study received ethical approval from the Institutional Review Board of the University of Cape Coast, and every participating student signed an informed consent form before taking part.

The headline numbers are sobering. Of the 10,896 students surveyed, 38.3 percent, or 4,176 individuals, reported being sexually active. Within that sexually active group, the researchers documented a cluster of behaviours that epidemiologists consider high-risk. The most common was condom non-use: 63.7 percent of sexually active students, amounting to 2,661 individuals, reported not using condoms. Nearly half, 45.7 percent or 1,654 students, reported having multiple sexual partners, a pattern that multiplies the number of potential transmission pathways for HIV and other sexually transmitted infections. A substantial 37.2 percent, or 1,552 students, reported using alcohol or drugs in connection with sex, a behaviour known to impair judgment, reduce condom negotiation, and increase the likelihood of unprotected encounters.

Two further findings rounded out the risk profile. Some 16.3 percent of sexually active students, or 682 individuals, reported engaging in anal sex, a practice associated with a heightened biological risk of HIV transmission compared with vaginal intercourse because of the fragility of rectal mucosal tissue. Meanwhile, 12.4 percent, or 520 students, reported an early onset of sexual activity, defined in the study context as first intercourse at a young age. Taken together, these behaviours produced an overall magnitude of risky sexual behaviour of 78.8 percent among sexually active students, meaning 3,291 of the 4,176 sexually experienced respondents reported at least one behaviour placing them at elevated risk. The authors frame this figure as a clear signal that the burden of sexual risk in this population is not confined to a small minority but is a mainstream campus health issue.

Beyond the raw prevalence figures, the study’s regression analysis identified which characteristics predicted risky behaviour. Chronological age emerged as a significant factor, with risk profiles shifting as students moved through their undergraduate years. Religious affiliation also played a measurable role, consistent with a body of literature suggesting that religious identity can shape sexual norms, expectations, and disclosure behaviour among young adults in Ghana. Perhaps most tellingly, the age at first sexual intercourse and the circumstances influencing that first experience predicted later risk-taking, suggesting that early sexual trajectories cast a long shadow over subsequent behaviour during university years.

Living arrangements and family communication completed the predictive picture. The researchers found that who students lived with during their studies influenced their likelihood of engaging in risky behaviour, an intuitive but important result given that residence type shapes supervision, privacy, and peer exposure. Equally significant was the difficulty students reported in discussing sexual issues with their parents. Where parent-child communication about sexuality was strained or absent, students were more likely to engage in risky practices. This finding resonates with a broader public health consensus that open, accurate family communication about sexuality acts as a protective factor, delaying sexual debut and increasing protective behaviours such as condom use when sexual activity does begin.

The implications for intervention are spelled out clearly in the study’s conclusion. The authors argue that public health programmes should incorporate campus-based counselling and peer education, with a particular focus on students who are already sexually experienced. Peer education, in which trained students deliver health information and norm-change messages within their own social networks, has a long track record in HIV prevention because it leverages trust and shared language in ways that top-down messaging often cannot. Counselling services, meanwhile, can address the individual-level drivers of risk, including alcohol use, relationship pressures, and gaps in knowledge about transmission and contraception. The finding that parental communication difficulties predict risk suggests that interventions may also need to reach beyond the campus gates, supporting families in sustaining conversations about sexual health into late adolescence and early adulthood.

The study also situates itself within global health frameworks. The rising prevalence of HIV/AIDS and unintended pregnancies is widely attributed to exactly the behaviours this survey measured: non-use of condoms, alcohol intake before sex, multiple sexual partnerships, early sexual debut, and survival sex. Because university students represent an educated cohort whose health behaviours today shape the health of families and communities tomorrow, the authors argue that securing their well-being is crucial for the overall health and development of society, in line with the United Nations Sustainable Development Goals. In Ghana, where young people constitute a large share of the population, the stakes of translating these findings into policy are considerable.

Caveats are worth noting, as with any cross-sectional survey. The design captures behaviour at a single point in time and cannot establish cause and effect; it shows that age, religious affiliation, early sexual debut, living situation, and parental communication are associated with risky behaviour, not that one directly produces the other. Self-reported data on sexual behaviour are also vulnerable to social desirability bias, particularly on sensitive topics, although the large sample size and use of a validated international instrument strengthen confidence in the overall patterns. The study was conducted at a single public university, so generalization to other institutions or countries should be made cautiously. The authors received no specific funding for the research and declare no competing interests. Even with these limitations, the sheer scale of the survey, nearly eleven thousand respondents balanced by sex, makes it one of the most detailed portraits to date of sexual risk among Ghanaian undergraduates, and its central message is hard to ignore: condom use, partner reduction, and substance-related risk remain stubbornly high on campus, and the levers of change run through families, faith communities, and student peer networks as much as through clinics and lecture halls.

Subject of Research: Prevalence and predictors of risky sexual behaviours among undergraduate university students in Ghana

Article Title: Prevalence and factors influencing risky sexual behaviours among university students in Ghana

Article References: Ogum, M. A., Mintah, J. K., Ogum, P. N., Hormenu, T., & Ansah, E. W. (2026). Prevalence and factors influencing risky sexual behaviours among university students in Ghana. BMC Public Health. https://doi.org/10.1186/s12889-026-29715-w

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29715-w

Keywords: risky sexual behaviour, university students, Ghana, HIV/AIDS, condom non-use, multiple sexual partners, sexually transmitted infections, unintended pregnancy, cross-sectional survey, peer education, parental communication, public health

The methodological core of the study is what statisticians call multilevel latent class analysis, or MLCA. Traditional variable-centered approaches ask how single factors, such as partner age or substance use, relate to outcomes like condomless sex. Person-centered mixture models instead search for hidden subgroups within a population, defined by co-occurring patterns across many indicator variables simultaneously. The multilevel extension is crucial for sexual network data, because each participant, or ego, nominated multiple partners, or alters, creating a nested structure in which partnerships are clustered within individuals. Ignoring this nesting can distort estimates and obscure the fact that a single man may move fluidly between very different kinds of sexual encounters. The researchers modeled both levels at once: lower-level classes describing types of individual partnerships, and upper-level groups describing the overall composition of each man’s sexual network.

Data collection relied on an egocentric social network approach implemented through the Network Canvas platform, with participants recruited through a modified respondent-driven sampling strategy led by a community-based sexual health clinic. Each participant named the people with whom he had anal or vaginal sex in the past six months and reported detailed characteristics of each relationship: whether the partner was a main or casual partner, whether condoms were always used, which sexual positions involved condomless contact, whether the partner disclosed an HIV status, and how emotionally close the respondent felt to that person. Covariates included alcohol and other substance use when the dyad met to have sex, the respondent’s current PrEP use, country of nativity, and total sexual network size. Participants averaged 34.5 years of age, 88 percent were born outside the United States, and 57 percent reported currently using PrEP.

The analysis converged on a three-class, two-group solution. At the partnership level, three distinct sexual partner typologies emerged. The first, accounting for 37 percent of partnership contexts, was an elevated-risk context with a main sexual partner: seroconcordant dyads in which both partners disclosed being HIV-negative, marked by high emotional closeness, main partnership status, and a high probability of versatile condomless sex. The second class, 35 percent of contexts, was labeled selective and close casual partnerships, in which men reported condomless sex in only one position, such as insertive or receptive anal sex exclusively, alongside moderate emotional closeness. The third class, 27 percent, comprised low-exposure casual partnerships with little condomless sex, variable closeness, and a high probability that the partner’s HIV status was simply unknown. At the network level, two groups emerged: one dominated by casual partnerships, accounting for 54 percent of sexual partnerships, and one centered on a main sexual partner, accounting for 46 percent.

Perhaps the most striking finding concerns what these typologies reveal about trust. Consistent with the dyadic framework for HIV prevention developed by Karney and colleagues, the study found that risk behaviors clustered within emotionally close relationships rather than anonymous encounters. Condomless sex was most prevalent in main partnerships, where intimacy and trust may paradoxically substitute for barrier protection, and lowest in casual partnerships where serostatus was undisclosed. Partners in the low-exposure casual class frequently had unknown HIV seroconcordance, which may itself have prompted greater caution. Meanwhile, classes with higher perceived closeness involved partners who disclosed being HIV-negative, more versatile condomless practices, and more substance use when the dyad met for sex. This inversion of the intuitive risk hierarchy, in which the most trusted relationships carry the most condomless exposure, has been documented in prior research among Latino men and now receives a rigorous person-centered confirmation.

The multinomial logistic regression results sharpened the picture of who occupies which network context. Respondents currently using PrEP had 1.60 times greater odds of belonging to the group whose networks were composed primarily of main partnerships with elevated risk contexts, relative to the casual-network group. Latino men born outside the United States had 43 percent lower odds of having elevated-risk main-partner contexts compared to those born in the country. Network size mattered as well: every additional partner reduced the odds of belonging to the main-partnership group by 29 percent. Substance use when the dyad met to have sex was independently associated with roughly threefold higher odds of condomless sex in a random intercept model, and within the multilevel model, substance use sharply reduced the odds of membership in low-exposure casual classes relative to elevated-risk main-partner contexts.

These associations carry important caveats that the authors themselves emphasize. The data are cross-sectional, so the temporal direction of the PrEP finding remains unresolved: men may adopt PrEP because they are in higher-exposure partnerships, or their partnerships may take a particular shape because PrEP has reduced their perceived need for condoms. PrEP, when taken as directed, is extremely effective against HIV acquisition but does not prevent other sexually transmitted infections, and systematic reviews have documented elevated STI diagnosis rates among PrEP users, potentially reflecting both reduced condom use and increased testing frequency. The study also captured only the daily-pill form of PrEP, predating wider availability of long-acting injectable options, and the reporting window overlapped with the COVID-19 pandemic, when social distancing measures may have altered sexual network patterns in ways that differ from pre- and post-pandemic behavior.

Cultural and structural context adds further layers of complexity. Miami-Dade is a distinctive setting in which 69 percent of residents identify as Latino, more than half were born outside the United States, and 68 percent of adults speak Spanish. Approximately one-third of foreign-born participants had lived in the country for a year or less, a period that may be insufficient to establish close, serious partnerships and during which navigating new social and sexual environments can shape partner selection, communication, and trust. Prior research suggests that cultural values such as collectivism and familismo can support condom use, while acculturative processes, language barriers between partners, and hypermasculine norms may complicate safer-sex negotiation. The authors argue that future work should move beyond a simple US-born versus foreign-born dichotomy and apply syndemic theory or intersectional perspectives to capture how immigration experiences, stigma, substance use, and cultural values interact to shape vulnerability.

The practical implications point toward interventions designed at the level of the dyad and the network rather than the isolated individual. Couples-based programs can facilitate conversations about relationship agreements, the increasing openness of sexual partnerships, and the role of substances in sexual decision-making, while network interventions that engage opinion leaders can diffuse prevention messaging through the social structures the study has now characterized in detail. The researchers also propose expanding clinic screening tools to include brief egocentric sexual network modules, allowing providers to tailor recommendations, whether PrEP, doxycycline post-exposure prophylaxis, routine testing, or negotiated safety agreements, to the specific partnership typologies a patient actually experiences. By replacing blunt risk categories with empirically derived partnership profiles, the study offers a template for precision HIV and STI prevention that respects the fluid, context-dependent reality of Latino men’s sexual lives in one of America’s hardest-hit communities.

Subject of Research: Sexual partnership typologies and HIV/STI risk contexts among Latino men in Miami analyzed with multilevel latent class analysis of egocentric sexual network data

Article Title: Sexual Partner Typologies Among Latino Men Living in Miami, Florida: A Multilevel Latent Class Analysis

Article References: Despres, L., Rodriguez, E., Johnson, A. L., Bravo, A., Vilchez, L., Doblecki-Lewis, S., Fallon, S., & Kanamori, M. (2026). Sexual Partner Typologies Among Latino Men Living in Miami, Florida: A Multilevel Latent Class Analysis. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-026-03441-1

Image Credits: AI Generated

DOI: 10.1007/s10508-026-03441-1

Keywords: HIV, sexually transmitted infections, Latino men, Miami-Dade County, multilevel latent class analysis, sexual networks, PrEP, condomless sex, substance use, dyadic prevention, immigration and acculturation, syndemic theory

The New Innovator Award occupies a distinctive niche in the NIH funding landscape. Rather than requiring preliminary data or a conventional track record, the program seeks out scientists whose ideas are considered transformative precisely because they depart from established approaches. Daniela Friedman, the Arnold School’s associate dean for research and leadership development, described the recognition as extremely well deserved, noting that since joining the school Shi has built an outstanding research program and distinguished herself as an innovative investigator whose work has the potential to reshape her field. For a researcher who has been on the faculty for only a short time, the award signals both the ambition of the science and the confidence the institute has placed in it.

Shi’s path to this project began far from South Carolina. She studied preventive medicine at Shanghai Jiao Tong University in China, where her involvement in tobacco control and other public health research projects led her to a realization that would define her career: improving health requires addressing not only diseases themselves but also the social and behavioral factors that shape how people live. That conviction deepened during an intervention project for people living with HIV in China. Although antiretroviral therapy has transformed HIV from a fatal diagnosis into a manageable chronic condition, Shi observed firsthand how many patients continued to struggle with stigma, fear of disclosure, and discrimination. Even individuals who were effectively controlling the virus medically tended to isolate themselves from family and friends, a pattern that convinced her that biomedical advances alone are not enough and that social and structural barriers must be confronted alongside them.

That experience brought her to the Arnold School, where she enrolled in the doctoral program in health promotion, education, and behavior and later completed a postdoctoral fellowship with the department and the South Carolina SmartState Center for Healthcare Quality. During that period she worked closely with faculty members Xiaoming Li and Xueying Yang, whom she credits as exceptional mentors who encouraged her to ask meaningful research questions, think creatively, and pursue innovative approaches that combine big data and artificial intelligence to advance HIV prevention and care. She has said their guidance was instrumental in her development as an independent researcher, fostering an environment of collaboration, curiosity, and innovation while emphasizing that research should ultimately improve people’s lives. It is also the community she built there, she explains, that drew her to remain at the Arnold School as a faculty member.

The new project brings together the threads of that training into a single, data-intensive research program. Shi and her team will draw on the NIH’s All of Us Research Program, one of the largest and most diverse health data resources ever assembled, which offers researchers access to longitudinal health information from hundreds of thousands of participants across the United States. Using advanced computational techniques, including machine-learning tools, the team will analyze how patterns of sexually transmitted infections relate to HIV risk and to HIV treatment outcomes over time. The analytical challenge is considerable: STI diagnoses arrive in clinical systems as scattered events, and connecting them to downstream HIV outcomes requires models that can capture multilevel social, structural, and clinical determinants of health simultaneously.

The scientific rationale for the project rests on a well-documented but underexploited relationship. Sexually transmitted infections are known to biologically increase the risk of acquiring HIV, and they may also signal lapses in engagement with HIV care among people already living with the virus. Yet, as Shi points out, STI data remains markedly underutilized by healthcare systems and researchers when it comes to predicting who may be at higher risk of HIV infection or adverse HIV-related health outcomes. In most clinical settings, an STI diagnosis is treated as a discrete event to be treated and closed, rather than as a signal that could trigger risk stratification, intensified prevention counseling, pre-exposure prophylaxis evaluation, or re-engagement efforts. Her project aims to close that gap by turning routinely collected clinical data into actionable predictive insight.

The stakes of better prediction are substantial. Of the roughly 1.1 million Americans living with HIV, an estimated 13 percent are unaware of their status, 25 percent do not receive care, and 35 percent are not virally suppressed. Each of those gaps represents a point at which the care continuum fails both the individual and public health, since unsuppressed viral load sustains transmission risk while untreated infection progresses. The extraordinary advances of the past three decades in HIV treatment, including reduced transmission achieved through careful management and modern prevention measures, mean that these numbers do not have to be what they are. What is missing, Shi argues, is a systematic way for clinicians to identify which patients need additional support and when. Her findings are intended to help clinicians do exactly that, and to give other scientists and healthcare providers a foundation for developing more effective strategies for HIV prevention and care.

Technically, the project sits at the intersection of infectious disease epidemiology, behavioral science, and data science. By training machine-learning models on the rich, longitudinal All of Us dataset, the team hopes to detect combinations of STI histories, demographic characteristics, social determinants, and clinical indicators that reliably precede HIV acquisition or poor treatment outcomes. Such models, if validated, could eventually be embedded in electronic health record systems as risk-stratification tools, flagging patients who warrant proactive outreach. The guidelines Shi’s team plans to develop for healthcare providers will translate these statistical findings into concrete clinical workflows, addressing the persistent divide between what population data can reveal and what individual practitioners can act upon during a routine visit.

Beyond its immediate clinical aims, the project reflects a broader vision of prevention that Shi has carried since her early days in preventive medicine: one in which social context, stigma, and structural barriers are treated as measurable, modifiable components of risk rather than as background noise. Her own trajectory, from studying preventive medicine in China to leading federally funded research at a major American research university, is one she hopes will encourage other early-career researchers and international scholars to pursue ambitious ideas with the potential for meaningful public health impact. The award, by its design, rewards exactly that kind of trajectory, betting on investigators whose careers are just taking shape and whose questions are still unconventional.

Looking ahead, Shi describes the Arnold School and the Center for Healthcare Quality as a unique environment where expertise in public health, clinical research, and data science converge. She intends to use the New Innovator Award to build an independent research program that leverages large-scale data and artificial intelligence to improve HIV prevention and care, while eventually extending her methods to other infectious diseases and health disparities. She also plans to invest in the next generation of the field, mentoring students and collaborating across disciplines to translate research findings into real-world impact. For a scientist whose formative insight was that data alone is never enough, the project she has now begun represents an attempt to prove the converse as well: that when large-scale data is joined to an understanding of human behavior and social barriers, prediction can become prevention.

Subject of Research: Use of large-scale health data and artificial intelligence to identify sexually transmitted infection patterns that predict HIV infection risk and treatment outcomes in at-risk populations

Article Title: New faculty member Fanghui Shi awarded NIH grant to protect at-risk populations from contracting HIV

Article References: New faculty member Fanghui Shi awarded NIH grant to protect at-risk populations from contracting HIV. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: HIV, NIH Director's New Innovator Award, Fanghui Shi, sexually transmitted infections, machine learning, All of Us Research Program, HIV prevention, public health, health disparities, University of South Carolina, Arnold School of Public Health, data science