Three ways networks are contributing to public health research

Public health challenges, especially in cancer prevention, rarely stem from biology alone. They are shaped by relationships: between people, between communities, and between institutions. Over the past years, our team has explored how networks can become powerful tools for understanding health behaviors, governance systems, and the lived realities of rural populations. These explorations have been performed under the framework of the research project 4P-CAN (HORIZON EUROPE project led by the Center of Innovation in Medicine).

In our most recent three preprints, we show how network science, qualitative methods, and participatory approaches can contribute to the public health tools. Together, these papers brings forth a relational approach to prevention: one that listens to communities, maps the hidden structures of power, and builds interventions from the ground up.

1. Following People Through Time: Personal Networks in a Rural Community

In Adapting Longitudinal Personal Network Research through Participation: Reflections from a Rural Study (*click here for the manuscript), we take on a major challenge in public health research: how to study people’s personal networks over time* in rural contexts that are mobile, underserved, and historically skeptical of outside research (Image 1).

Image 1. Panel personal network design. Sursa: https://www.researchsquare.com/article/rs-8064502/v1

Rather than imposing a standardized research design, we embedded ourselves in the community of Lerești, Romania. Over three waves of data collection (face-to-face, participatory, and supported by interactive digital tools) we worked alongside residents to co-create a network study that fit their reality.

Several aspects of our work may be considered as innovative: Link-tracing recruitment, where participants introduce others in their network, building trust and continuity. Participatory design of tools (including free-choice name generators and visual elicitation). Community involvement through a citizens’ jury, acting as an advisory body. Culturally adapted fieldwork rhythms, synchronizing with agricultural seasons, migration patterns, and local events.

The result? One of the first multi-wave personal network panels in a rural Eastern European living lab, showing not only how networks change but how to collect such data ethically and sustainably.

2 Mapping Power: An End-to-End Demonstration of Net-Map for Health Governance

While the first paper focuses on people’s personal ties, the second, From stakeholder mapping to statistical modeling: An illustrative demonstration of end-to-end Net-Map methodology (click here for the manuscript), zooms out to the institutional level and asks: Who actually shapes cancer prevention policy? And how do influence, authority, and funding flow between them? (Image 2)

Image 2. Multi-level organizations involved in primary cancer prevention. Source: https://www.researchsquare.com/article/rs-7837431/v1

Using the Net-Map participatory method, we worked with a national NGO expert panel to: identify 128 organizations involved in primary cancer prevention, map their relationships across local, national, and European levels, and analyze these ties using exponential random graph models (ERGMs). Our findings reveal a governance landscape where: EU actors are the most active funders, connecting broadly across levels. Influence matters far more than formal authority for predicting funding. Cross-level coordination dominates, yet national–local connections remain weaker than expected.

Importantly, this paper demonstrates the full methodological cycle: from stakeholder mapping to statistical modeling, showing how qualitative participatory tools can be systematically integrated with quantitative network analysis. In a system as complex as cancer prevention, understanding who talks to whom is as critical as understanding the science.

3. Normalization of overweight and obesity in family relations: a personal network analysis study

This research (*click here for the manuscript*) investigates how people perceive the weight status of those in their social circles, revealing as a pattern that family members tend to underestimate each other’s weight, while accurate assessments occur more often with non-family contacts. In other words, when family relationships are involved, people are significantly more likely to underestimate family members’ BMI categories compared to being accurate when evaluating non-family members. Thus, people who perceive fewer overweight individuals in their broader social networks are more likely to underestimate others’ weight categories, a phenomenon explained by visual normalization theory.

Image 3. Evaluations of BMI in personal networks. Source: https://www.researchsquare.com/article/rs-8059527/v1

As additional factors, we may refer to the fact that younger study participants tend to overestimate weight in others, males’ weight is more likely to be overestimated compared to females, and income levels influence perception patterns.

In plain English, we may claim that our closest relationships may inadvertently normalize excess weight, potentially delaying interventions and reducing support for healthy lifestyle changes. These results may support the idea that weight control interventions should address not only individual self-perception but also network influences, as underestimation biases within family relationships may persist into adulthood and limit social support for weight management and health-related behaviors. This study was conducted on 444 evaluator-evaluated dyads using personal network analysis methodology, combining self-reported data with visual assessment tools.