Latent trait models for perceived risk assessment using a Covid-19 data survey

Area of Science:

• Risk perception analysis
• Public health
• Environmental hazards

Background:

• Assessing public perception of risks is crucial for effective hazard management.
• COVID-19 (Coronavirus Disease 2019) presented a novel global health challenge.
• Understanding comparative risk perception aids in public health communication and policy.

Purpose of the Study:

• To analyze perceived personal and social risk of COVID-19 compared to other major hazards.
• To identify factors influencing the perceived risk of COVID-19.
• To examine individual characteristics affecting COVID-19 risk perception.

Main Methods:

• Comparative risk analysis using survey data from the first Italian COVID-19 lockdown.
• Item response theory (IRT) model for polytomous items to position COVID-19 risk.
• Latent regression analysis to explore individual factors influencing perceived risk.

Main Results:

• COVID-19's perceived risk is influenced by knowledge of its dangers, media coverage, and peer-induced fear.
• Specific individual characteristics were found to play a role in shaping COVID-19 risk perception.
• The study identified key attributes differentiating COVID-19 from other assessed hazards.

Conclusions:

• Perceived risk is a complex construct influenced by hazard-specific attributes and individual factors.
• Findings inform the adequacy of current control measures and public interest in new media strategies for health communication.
• This research provides insights into public responses to multifaceted risks.