Developing a digital interactive tool to enhance cervical cancer awareness and health literacy in Croatia: a community case study

Background: Cervical cancer is highly preventable but remains a major public health problem due to limited health literacy and suboptimal uptake of HPV vaccination and screening. Digital health tools are increasingly used to provide risk communication and prevention information. Objective: To describe the development, implementation, and early use of a free web-based tool for cervical cancer risk self-assessment in Croatia and to report initial usage metrics from this community-based initiative. Methods: An interdisciplinary team translated published evidence on cervical cancer risk factors into a decision-tree-based scoring system embedded in an online questionnaire featuring conditional logic and tailored feedback. Risk categories and thresholds were derived from literature-informed estimates and expert consensus and have not yet been empirically validated against clinical outcomes. The tool was deployed on the national "Neću rak" ("I Don't Want Cancer") platform of the Croatian Institute of Public Health. Aggregated, anonymized usage data from February 2023 to February 2025 were analysed descriptively. Results: The questionnaire (10-14 items, depending on branching logic) categorises users into four qualitative risk levels (no, low, moderate, high). In the first two years, the tool was accessed almost 9,000 times, with about 8,000 completed questionnaires, indicating a high completion rate. Most respondents (around 60%) were aged 34-54 years. Self-reported HPV vaccination (13%) and smoking history (30%) reflect aggregated responses from voluntary users and do not represent the general population. Conclusion: This national web-based risk calculator demonstrates the feasibility of integrating evidence-informed scoring framework and tailored educational content within a public health platform. Such digital tools may contribute to awareness and support existing screening and vaccination programmes. However, formal evaluation of algorithm performance, usability, and potential behavioural impact is required before effectiveness can be determined.