Cross-national survey on cancer prevention knowledge and behaviors methdology
The survey was administered across all seven 4P-CAN consortium countries — Romania, Bulgaria, Italy, Portugal, Republic of Moldova, Montenegro, and North Macedonia — using a standardised instrument designed to enable direct cross-country comparison. For non-EU countries, a slightly adapted version of the survey was used to reflect the absence of EU-specific frameworks and indicators, such as the Eurobarometer and EU Cancer Profiles.
Comprising over 30 questions, the survey is organised into five thematic sections: (1) demographic profile, (2) cancer prevention literacy, (3) knowledge of the European Code Against Cancer (ECAC), (4) communication preferences and trust, and (5) the impact of COVID-19 on institutional trust. The instrument captures both knowledge and behavioural dimensions of cancer prevention, alongside attitudes toward institutional communication and public health guidance.
All responses were collected using a consistent data collection approach across countries and analysed using harmonised procedures to ensure cross-national comparability and methodological coherence.
The survey constitutes the primary behavioural dataset integrated into the platform and provides the empirical foundation for the country profile visualisations.
Comprising over 30 questions, the survey is organised into five thematic sections: (1) demographic profile, (2) cancer prevention literacy, (3) knowledge of the European Code Against Cancer (ECAC), (4) communication preferences and trust, and (5) the impact of COVID-19 on institutional trust. The instrument captures both knowledge and behavioural dimensions of cancer prevention, alongside attitudes toward institutional communication and public health guidance.
All responses were collected using a consistent data collection approach across countries and analysed using harmonised procedures to ensure cross-national comparability and methodological coherence.
The survey constitutes the primary behavioural dataset integrated into the platform and provides the empirical foundation for the country profile visualisations.
| Country | EU Status | Sample Size (n) |
|---|---|---|
| Bulgaria | EU | 1,058 |
| Italy | EU | 1,059 |
| Portugal | EU | 1,056 |
| Romania | EU | 1,057 |
| Republic of Moldova | Non-EU | 606 |
| Montenegro | Non-EU | 600 |
| North Macedonia | Non-EU | 1,059 |
| Total | 6,495 |
Multi-level Assessment of Cancer Risk Factors Preventive Legislation
D2.3 - Tobacco Regulation
The tobacco analysis was conducted through a scoping review following PRISMA-ScR guidelines, combining systematic database searches of Medline and Embase (indexed to January 2024) with grey literature from tobacco-specific repositories and in-depth interviews with national stakeholders. Data was extracted by two independent reviewers using a standardised form, covering documents published in English or native languages within the last 15 years. The analysis maps implementation of the WHO Framework Convention on Tobacco Control (FCTC), the EU Tobacco Products Directive, and related regulatory instruments across 11 countries, tracking key performance indicators including smoking prevalence, Tobacco Control Scale rankings, MPOWER scores, and excise taxation levels.
D2.4 — Alcohol, Food, and Sugar-Sweetened Beverage Regulations
Three parallel scoping reviews were conducted following PRISMA-ScR guidelines, covering alcohol, food and nutrition, and sugar-sweetened beverage (SSB) policies respectively.
Database searches spanned PubMed and Scopus (January 2008 to January 2024), supplemented by grey literature, institutional websites, and targeted Google searches. Research questions were formulated using the PCC (Population–Concept–Context) framework. Screening was conducted by two independent reviewers at title/abstract and full-text stages, with conflicts resolved by a third reviewer. Data was extracted and classified according to WHO Global Health Observatory policy categories, with Rayyan used for duplicate management. The analysis covers all 27 EU member states plus the four non-EU consortium partners.
Database searches spanned PubMed and Scopus (January 2008 to January 2024), supplemented by grey literature, institutional websites, and targeted Google searches. Research questions were formulated using the PCC (Population–Concept–Context) framework. Screening was conducted by two independent reviewers at title/abstract and full-text stages, with conflicts resolved by a third reviewer. Data was extracted and classified according to WHO Global Health Observatory policy categories, with Rayyan used for duplicate management. The analysis covers all 27 EU member states plus the four non-EU consortium partners.
D2.5 — Physical Activity Policies
The analysis follows the indicator framework established in D2.1, which identified 150 physical activity indicators across five domains including population behaviour, policy and legislation, knowledge and awareness, monitoring systems, and health outcomes. The methodology combines a review of policy documents from the WHO, European Commission (EUR-Lex), and national institutions with analysis of three consecutive Eurobarometer surveys on Sport and Physical Activity (2014, 2018, and 2022). Country-level assessments were conducted for all 11 consortium countries, covering national policies and strategies, Eurobarometer trend data, monitoring capacity, and public awareness activities. The Eurobarometer data provides the primary quantitative source for cross-country behavioural comparison on the platform.
D2.6 — HPV and HBV Vaccination Policies
The vaccination analysis drew on searches of PubMed, Cochrane Library, and Google Scholar, covering publications from 2010 to 2024 with earlier studies included where relevant. Grey literature was sourced from WHO, ECDC, OECD, the European Commission, and national Ministries of Health, with a snowballing approach used to identify additional sources. Screening was conducted in three stages (title, abstract, full text) and reviewed by an external reviewer, yielding 127 included sources. Epidemiological data was sourced from GLOBOCAN/WHO Global Cancer Observatory (2022), with vaccination coverage data drawn from WHO immunization records, ECDC immunization schedules, and the HPV Policy Atlas. The analysis produced standardised country profiles covering cancer epidemiology, vaccination policy, coverage rates, financing models, and best practice case studies for all 11 consortium countries.
Socio-economic and informational determinants of cancer prevention
D3.1 — Direct Cost Analysis
The direct cost analysis combines three methodological components. First, a systematic bibliometric review of 1,200 documents from Scopus (1919–2024) mapped the state of cancer cost research globally, using co-occurrence analysis in VoSViewer to identify key research clusters and methodological approaches. Second, an analysis of EU Member States' healthcare expenditure data — drawn from Eurostat, WHO, OECD, and World Bank — examined financing structures, out-of-pocket spending patterns, and the statistical relationships between preventive expenditure and cancer mortality outcomes. Third, the team developed the Cancer Risk Factors Index (CRFI), a novel composite indicator built from five categories — obesity tendency, alcohol and tobacco consumption, physical activity, socio-economic conditions, and pollution — using Min-Max normalisation on a 0–100 scale with data from Eurostat (2019–2022). For non-EU consortium countries where standardised data is unavailable, dedicated country case studies were produced drawing on national statistical institutes, national health strategies, and cancer registry data.
D3.2 — Indirect Cost Analysis
The indirect cost analysis applies the Human Capital Approach (HCA) to quantify economic losses attributable to cancer-related premature mortality in the working-age population (ages 20–64) across eight consortium countries over the period 2015–2023. The HCA estimates productivity losses by calculating the potential future earnings foregone due to premature death, using average hourly labour productivity and annual working hours as the primary productivity proxy, with data sourced from national statistical institutes, IARC, Eurostat, ILOSTAT, and OECD. Fiscal costs — comprising uncollected social contributions, personal income tax, and VAT — are calculated separately and summed with productivity losses to produce a total indirect cost figure per country per year. Compound Annual Growth Rates (CAGR) are applied to model workforce and productivity dynamics over time. The analysis is complemented by panel data regression models (fixed effects) estimating income and price elasticities for alcohol and tobacco consumption across five countries (2012–2024), and by forward-looking intervention scenarios projecting the economic returns of comprehensive, screening-focused, and treatment-only cancer control strategies for the period 2026–2028.
