I am broadly interested in applying psychological research to create social change, using open and reproducible practices. I am a big proponent of team science and collaborating with others to effectively answer good research questions. I am currently a member of the MIWATEX consortium, working on understanding consumer attitudes towards recycled textiles, and changing behaviour to redirect clothing from a linear to circular pathway.
I am interested in how descriptions of changing norms can influence people to change their attitudes and behaviours, even when these attitudes and behaviours involve going against the grain. Some of the questions I have been trying to answer in my own research include: How can we effectively communicate dynamic norm information to influence engagement in sustainable behaviours? What design choices are most suitable for testing the effect of dynamic norms? Relatedly, I am interested in the factors influencing the diffusion of positive and negative counternormative behaviour.
The replication crisis cast doubt on many findings in the social and behavioural sciences published in the last few decades. The fact that many effects do not replicate - or even reverse - could be due to many reasons beyond the theoretical existence/validity of the effect. In addition to testing the robustness of published effects, I am very interested in the factors influencing failures to replicate, as well as factors resulting in false positive/negative findings. This includes investigating effects of design choices (e.g., control conditions used, analytical decisions), data characteristics, etc.
I am broadly interested in mainstreaming and facilitating adoption of transparent and effective open practices such as Registered Reports and data sharing. I am involved in several projects at the Framework of Open and Reproducible Research Training (FORRT) including the open science glossary, lesson plans for open scholarship, and the collation of replications and reversals in the social sciences.
I am a strong advocate for using Bayesian methods to make inferences about our research questions.