Using smartphone-based experience sampling to assess interventions for dietary change

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There is growing concern about the sustainability of current meat consumption rates. The UnitedNations Food and Agriculture Organization and the Intergovernmental Panel on Climate Changeidentify meat production as one of the leading causes of climate change and deforestation (ChathamHouse Report, 2015). The livestock sector accounts for 14-14.5% of total global greenhouse gasemissions, as much as the transportation sector. Meat production also wastes resources, as waterand energy is lost in the conversion from plant to animal protein (Hoekstra, 2012). Diets rich in redmeat and dairy have also been linked to health problems such as cancer and cardiovascular disease(Pan et al., 2012).Since global population is expected to increase by 36% by 2050, promoting diets less dependent onanimal products is of critical importance to promote global health, sustainable food production, andreduce global warming (Tilman & Clark, 2014). To achieve more sustainable levels of consumption,we need a better understanding of the types of interventions that are likely to lead to real change indietary practices. What messages are likely to motivate consumers to reduce their meatconsumption, and how do we know when consumers are likely to act on their reported intentions tomake a behavioural change?Meat avoiders make up a small minority of the population in most countries, yet positive attitudestowards plant-based eating are on the rise, particularly in Europe (The Vegan Society, 2018).Consumers tend to report personal health, animal welfare, and environmental concern as reasons toavoid meat (Faunalytics, 2014). In the present project, we consider whether some reasons forreducing meat may be more motivating than others, particularly in the early stages of behaviouralchange.It is unclear whether current global consumption patterns reflect a lack of awareness around thenegative effects of meat production on health, the environment and animal welfare, or a failure toact upon this knowledge (Wellesley et al., 2015). Furthermore, most research to date has reliedheavily on self-reports of consumer's eating habits and/or intentions-reports which are susceptibleto social desirability and memory bias. More research is needed that engages methodologies thatcan more reliably track consumer patterns over time and closer to the point of consumption.