Does Information Change Behavior?

This paper reviews and synthesizes the theory of information economics and empirical evidence on how information changes the behavior of consumers, households and firms. I show that consumers respond to new information in food experiments but perhaps not in retirement account management. Some seeming perverse consumer/investor decision making may be a result of a complex decision with a low expected payoff.moral hazard; information economics; consumer behavior; behavioral economics; adverse selection

Government Incentives to Change Employer Behavior

Through various incentive mechanisms, the U.S. government has sought to shape and change the ways in which American businesses operate in a wide range of industries. This fact sheet discuss a few examples of the ways the government can incentivize employer behavior through recognition and awards programs, and through government financing

Physical activity behaviour change driven from engagement with an incentive-based app : evaluating the impact of Sweatcoin

Background Now the fourth leading cause of death, physical inactivity is a primary element of non-communicable diseases. Despite a great number of attempts, there is still a lack of effective approaches that can motivate sedentary populations to increase their levels of physical activity over a sustained period. Financial and non-financial incentives for exercise can provide an immediate reward for increasing activity levels, but due to limited funding to provide rewards, previous programmes using this approach have only shown short-term changes in behaviour. Sweatcoin, a UK-based technology company, has developed a digital platform that tracks and verifies physical movement to convert it into virtual currency. The currency can subsequently be exchanged for goods and services on their marketplace, providing a continuous incentive to be active. This study investigates the physical activity behaviour change observed in Sweatcoin users over a 6-month period of app usage. Objective To investigate the change in physical activity (measured using daily step-count) of Sweatcoin users following registration with the app, the longevity of the change and whether this change can be predicted through and driven by demographic and other lifestyle variables. Methods Activity data from a sample of 5,406 Sweatcoin users was used to analyse daily step count. Activity change was measured in terms of the percentage change in average daily step count for each month after registration, relative to that in the 3 months prior to the app being used. A subset of over 800 users completed a questionnaire capturing demographic and activity information. Change in activity behaviour following app download was calculated and users were grouped according to having no/negative, moderate or high activity change. Differences between groups in terms of activity and demographic status were investigated using regression analyses. Seasonal effects were also investigated and accounted for. Results Analyses show an overall average increase in daily step count of 19.5% over the 6-months following registration, in comparison to 3-months prior to registration (P<.001). Of the questionnaire respondents, 678 were valid responses. Of those, 34% were identified to have shown high levels of behaviour change following app registration. The logistic regression identified the key drivers of high activity behaviour change. There was an obvious impact of seasonality, with those registering the app in winter (OR, 6.89, p<.001) or spring (OR, 5.87, p=.002) were more likely to show high activity behaviour change than those registering in summer. More striking were the results identifying those classified as overweight (measured through body mass index (BMI); OR, 2.22, p=.014) and less active (based on self-report scale of physical activity; OR, 0.85, p=.037), being most likely to show high levels of physical activity change following registration with app. Conclusions The results highlight that an incentives-based app can induce significant sustainable physical activity behaviour change. Importantly, the results suggest that those typically lacking motivation to exercise (sedentary and high BMI) are most likely to be incentivised to increase their activity levels

7th Annual Behavior, Energy and Climate Change Conference

Conference Note

Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science

Stages of health behavior change and factors associated with physical activity in patients with intermittent claudication

OBJECTIVE: To analyze, in people with intermittent claudication, the frequency of individuals who are in each of stages of health behavior change to practice physical activity, and analyze the association of these stages with the walking capacity. METHODS: We recruited 150 patients with intermittent claudication treated at a tertiary center, being included those > 30-year-old-individuals and who had ankle-arm index < 0.90. We obtained socio-demographic information, presence of comorbidities and cardiovascular risk factors and stages of health behavior change to practice physical activity through a questionnaire, they being pre-contemplation, contemplation, preparation, action and maintenance. Moreover, the walking capacity was measured in a treadmill test (Gardner protocol). RESULTS: Most individuals were in the maintenance stage (42.7%), however, when the stages of health behavior change were categorized into active (action and maintenance) and inactive (pre-contemplation, contemplation and preparation), 51.3% of the individuals were classified as inactive behavior. There was no association between stages of health behavior change, sociodemographic factors and cardiovascular risk factors. However, patients with intermittent claudication who had lower total walking distance were three times more likely to have inactive behavior. CONCLUSION: Most patients with intermittent claudication showed an inactive behavior and, in this population, lower walking capacity was associated with this behavior

Social norms and farm animal protection

Social change is slow and difficult. Social change for animals is formidably slow and difficult. Advocates and scholars alike have long tried to change attitudes and convince the public that eating animals is wrong. The topic of norms and social change for animals has been neglected, which explains in part the relative failure of the animal protection movement to secure robust support reflected in social and legal norms. Moreover, animal ethics has suffered from a disproportionate focus on individual attitudes and behavior at the expense of collective behavior, social change, and empirical psychology. If what we want to change is behavior on a large scale, norms are important tools. This article reviews an account of social norms that provides insights into the possibility and limitations of social change for animals, approaching animal protection as a problem of reverse social engineering. It highlights avenues for future work from this neglected perspective

Effectiveness of interventions using self-monitoring to reduce sedentary behavior in adults : a systematic review and meta-analysis

Background: Sedentary behavior occurs largely subconsciously, and thus specific behavior change techniques are needed to increase conscious awareness of sedentary behavior. Chief amongst these behavior change techniques is self-monitoring of sedentary behavior. The aim of this systematic review and meta-analysis was to evaluate the short-term effectiveness of existing interventions using self-monitoring to reduce sedentary behavior in adults. Methods: Four electronic databases (PubMed, Embase, Web of Science, and The Cochrane Library) and grey literature (Google Scholar and the International Clinical Trials Registry Platform) were searched to identify appropriate intervention studies. Only (cluster-)randomized controlled trials that 1) assessed the short-term effectiveness of an intervention aimed at the reduction of sedentary behavior, 2) used self-monitoring as a behavior change technique, and 3) were conducted in a sample of adults with an average age >= 18 years, were eligible for inclusion. Relevant data were extracted, and Hedge's g was used as the measure of effect sizes. Random effects models were performed to conduct the meta-analysis. Results: Nineteen intervention studies with a total of 2800 participants met the inclusion criteria. Results of the meta-analyses showed that interventions using self-monitoring significantly reduced total sedentary time (Hedges g = 0,32; 95% CI = 0,14 - 0,50; p = 0,001) and occupational sedentary time (Hedge's g = 0,56; 95% CI = 0,07 - 0,90; p = 0,02) on the short term. Subgroup analyses showed that significant intervention effects were only found if objective self-monitoring tools were used (g = 0,40; 95% CI = 0,19 - 0,60; p < 0,001), and if the intervention only targeted sedentary behavior (g = 0,45; 95% CI = 0,15-0,75; p = 0,004). No significant intervention effects were found on the number of breaks in sedentary behavior. Conclusions: Despite the small sample sizes, and the large heterogeneity, results of the current meta-analysis suggested that interventions using self-monitoring as a behavior change technique have the potential to reduce sedentary behavior in adults. If future - preferably large-scale studies - can prove that the reductions in sedentary behavior are attributable to self-monitoring and can confirm the sustainability of this behavior change, multi-level interventions including self-monitoring may impact public health by reducing sedentary behavior