HPV Prevalence Research Will Separate Identity From Behavior in Cisgender Bisexual Women
Research on human papillomavirus in cisgender bisexual women has been split by a problem that sounds semantic but changes the meaning of the data. Some studies define bisexuality by identity, capturing women who self-identify as bisexual. Others define it by behavior, including women with sexual contact with more than one sex or gender. Those two approaches may identify overlapping groups, but they are not interchangeable, and the resulting HPV estimates can point in different directions. This protocol for a systematic review and meta-analysis is built around that fault line.
HPV remains the most common sexually transmitted infection in the United States and a direct causal driver of cervical cancer, especially through high-risk types 16 and 18. Vaccination has already changed the epidemiology of precancer, with large declines in cervical intraepithelial neoplasia reported among young adults after vaccine introduction. Yet vaccine coverage among adolescents still falls short of the Healthy People 2030 target, leaving many people without the protection that could prevent infection years later. In bisexual women, where sexual network patterns and health care experiences may differ from those of other sexual minority women, the gap between risk and prevention deserves a cleaner measurement framework.
A single sentence captures the central problem: not all bisexuality measures describe the same population.
Why the Definition of Bisexuality Changes the HPV Estimate
The protocol addresses a longstanding limitation in LGBTQ+ health research. Sexual minority women are often grouped together, and bisexual women are frequently combined with lesbian women to improve statistical power. That approach can erase meaningful differences in exposure, screening behavior, care access, and perceived susceptibility to cervical cancer. It also blurs whether a study is measuring identity-based risk, behavior-based risk, or some mixture of both.
That distinction matters for HPV because transmission is tied to sexual contact, but prevention behavior is shaped by identity, stigma, and how patients interact with the health system. A woman who identifies as bisexual may have different screening experiences than a woman classified as bisexual because of behavior alone. Identity can influence disclosure to clinicians, willingness to seek vaccination, and continuity of gynecologic care. Behavior can capture exposure histories that identity-based surveys miss. When a meta-analysis pools both without separation, the estimate may become internally consistent yet clinically misleading.
The planned review will ask whether reported HPV prevalence and vaccination rates differ depending on how bisexuality is defined. That question is narrow, but it has practical implications for cervical cancer prevention research and for the design of future observational studies.
A Registered Protocol Built for a Cleaner Comparison
The study is registered in PROSPERO under CRD420251252015 and follows PRISMA-P guidance. The investigators plan a systematic review with random-effects meta-analyses to estimate pooled HPV prevalence and HPV vaccination rates, stratified by definition type. That design is appropriate for a literature base expected to be heterogeneous, since studies in this field often vary in sampling frame, geography, age distribution, and how sexual identity or behavior is recorded.
By using random-effects models, the analysis can account for real between-study variation instead of pretending all cohorts are drawn from the same underlying population. That is especially important here, because the biological endpoint is simple but the social definition is not. HPV positivity can be measured in similar ways across studies, yet the population being tested may shift substantially depending on whether bisexuality is operationalized by self-identification or by behavior.
The protocol also draws attention to vaccine uptake as a separate outcome. Vaccination is not just a proxy for access; it is shaped by age cohort, clinical counseling, prior engagement with preventive care, and the broader sexual health environment in which patients receive recommendations. A lower vaccination rate in one definition group could reflect structural barriers rather than biological susceptibility, which is exactly why separating the groups is analytically useful.
Cervical Cancer Prevention Depends on Better Measurement
Cervical cancer remains one of the most preventable malignancies in the United States, yet it still carries a substantial burden. Bisexual women are increasingly visible in population estimates, and the public health relevance of this group is growing with them. If current research is mixing identity-based and behavior-based definitions, the field risks generating averages that conceal actionable differences.
This protocol is not claiming an outcome; it is trying to make the next set of outcomes interpretable. If HPV prevalence appears higher in one definition category, the reason could lie in patterns of sexual exposure, in screening behavior, or in how studies recruited participants. If vaccination appears lower, the explanation may involve age structure, access, or differences in disclosure and clinical recommendation. The planned synthesis is designed to sort those possibilities rather than flatten them into one pooled estimate.
A second hard reality follows from the design itself: the literature may be too sparse or too inconsistent to yield stable subgroup estimates. Even a rigorous meta-analysis can only be as informative as the studies available to pool.
What This Review Can Clarify, and What It Cannot Yet Solve
The strongest value of this protocol is methodological. It forces the field to treat bisexuality as a construct with multiple operational meanings, not a single fixed category. That is a necessary step if researchers want to understand HPV prevalence and vaccination patterns in cisgender bisexual women with enough precision to guide cervical cancer prevention efforts.
The review will not directly measure cervical cancer incidence, and it cannot by itself explain why any prevalence or vaccination difference exists. It also depends on the quality of the underlying studies, which may differ in recruitment methods, biomarker testing, recall of vaccination history, and the exact wording used to define sexual identity or behavior. Those constraints will shape how far the meta-analysis can go. Even so, the protocol sets up a more defensible comparison than the field has had so far, and it does so around a question that has been obscured by inconsistent definitions for years.