Communication Strategies to Reduce Alcohol Consumption

This project examines how message framing influences perceived risk severity and alcohol consumption behaviour. Recent research shows that subtle linguistic differences in health communication—particularly how agency is assigned in a sentence (e.g., “Alcohol increases the risk of cancer” vs. “You increase your risk of cancer by drinking alcohol”)—can influence how people perceive health risks and choose to act. Our previous work demonstrates that alcohol-agency framing (i.e., “Alcohol increases the risk of cancer”) can increase intentions to
reduce drinking compared with human-agency framing (“You increase your risk of cancer by drinking alcohol”). However, we still do not fully understand why this agency effect occurs.

The current project aims to test whether the persuasive effect of message framing is driven by differences in perceived threat and/or psychological reactance (i.e., how defensive or resistant people feel when being told what to do). The project will involve designing and conducting randomized experiments across multiple languages and cultural settings (e.g., Chinese, English, German, Italian, Greek) to test the cross-cultural robustness of this communication strategy in promoting reduced alcohol consumption.

Essential and Preferred Skills:

Essential (or strong willingness to learn):
▪ Interest in behavioural science, health communication, or decision-making
▪ Clear written communication skills, especially for preparing experiment instructions and materials
▪ Attention to detail, especially when checking survey logic, translations, or data files
▪ Ability to work independently while updating the research team regularly
▪ Interest in quantitative data analysis and experimental methods
▪ Careful and reliable approach to research work
▪ Fluent spoken and written English

Preferred (but not required):
▪ Experience programming surveys/experiments (e.g., Qualtrics, Gorilla)
▪ Experience recruiting participants online (e.g., Prolific, CloudResearch)
▪ Experience with data analysis (e.g., R, SPSS, Stata, Python)
▪ Fluency in Chinese, German, Italian, or Greek (for cross-language stimulus testing)