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Theory of Change Template | Miro
Theory of Change Workbook: A Step-by-Step Process for Developing or Strengthening Theories of Change | Eval Forward
View of The Development of Effective and Tailored Digital Behavior Change Interventions: An introduction to the Multiphase Optimization Strategy (MOST)
Learning from Behavioural Changes That Fail: Trends in Cognitive Sciences
The behavioural change enterprise disproportionately focuses on promoting successes at the expense of examining the failures of behavioural change interventions. We review the literature across different fields through a causal explanatory approach to identify structural relations that impede (or promote) the success of interventions. Based on this analysis we present a taxonomy of failures of behavioural change that catalogues different types of failures and backfiring effects. Our analyses and classification offer guidance for practitioners and researchers alike, and provide critical insights for establishing a more robust foundation for evidence-based policy. Behavioural change techniques are currently used by many global organisations and public institutions. The amassing evidence base is used to answer practical and scientific questions regarding what cognitive, affective, and environment factors lead to successful behavioural change in the laboratory and in the field. In this piece we show that there is also value to examining interventions that inadvertently fail in achieving their desired behavioural change (e.g., backfiring effects). We identify the underlying causal pathways that characterise different types of failure, and show how a taxonomy of causal interactions that result in failure exposes new insights that can advance theory and practice.
Study identifies the best healthy eating nudges | EurekAlert! Science News
In a meta-analysis of real-life experiments drawn from food science, nutrition, health economics, marketing and psychology, the authors find that behavioural nudges - facilitating action rather than providing knowledge or inducing feelings - can reduce daily energy intake by up to 209 kcal, the same number of calories as in 21 cubes of sugar.
Understanding how and why people change - Journal of Marketing Management
We applied a Hidden Markov Model* (see Figure 1) to examine how and why behaviours did or did not change. The longitudinal repeated measure design meant we knew about food waste behaviour at two points (the amount of food wasted before and after the program), changes in the amount of food wasted reported over time for each household (more or less food wasted) and other factors (e.g. self-efficacy). By using a new method we could extend our understanding beyond the overall effect (households in the Waste Not Want Not program group wasted less food after participating when compared to the control group).