Modelling population responses to workplace minimum dietary standards introduced as workers return after social lockdowns.

BACKGROUND: Diet norms are the shared social behaviours and beliefs about diets. In many societies, including the UK, these norms are typically linked to unhealthy diets and impede efforts to improve food choices. Social interactions that could influence one another's food choices, were highly disrupted during the lockdowns in response to the COVID-19 pandemic. A return to workplaces and re-establishment of eating networks may present an opportunity to influence dietary norms by introducing minimum dietary standards to in workplaces, which could then spread through wider home and workplace networks. METHODS: An agent-based model was constructed to simulate a society reflecting the structure of a city population (1000 households) to explore changes in personal and social diet-related norms. The model tracked individual meal choices as agents interact in home, work or school settings and recorded changes in diet quality (range 1 to 100). Scenarios were run to compare individuals' diet quality with the introduction of minimum dietary standards with degrees of working from home. RESULTS: The more people mixed at work the greater the impact of minimum standards on improving diet norms. Socially isolated households remained unaffected by minimum standards, whereas household members exposed directly, in workplaces or schools, or indirectly, influenced by others in the household, had a large and linear increase in diet quality in relation to minimum standards (0.48 [95% CI 0.34, 0.62] per unit increase in minimum standards). Since individuals regressed to the new population mean, a small proportion of diets decreased toward lower population norms. The degree of return to work influenced the rate and magnitude of change cross the population (-2.4 points [-2.40, -2.34] in mean diet quality per 20% of workers isolating). CONCLUSIONS: These model results illustrate the qualitative impact social connectivity could have on changing diets through interventions. Norms can be changed more in a more connected population, and social interactions spread norms between contexts and amplified the influence of, for example, workplace minimum standards beyond those directly exposed. However, implementation of minimum standards in a single type of setting would not reach the whole population and in some cases may decrease diet quality. Any non-zero standard could yield improvements beyond the immediate adult workforce and this could spill between social contexts, but would be contingent on population connectivity.

Effect of different food groups on energy intake within and between individuals.

PURPOSE: Energy intake varies day-to-day because we select different foods, and different amounts of these foods. Energy balance is not tightly regulated over the short-term, and the variability in diet results in an energy surplus or deficit. The aim of this study was to explore how consuming more, or less, than usual amounts of foods contributed towards balancing of total energy intake (TEI) within a day. METHODS: Four-day food records came from 6155 adult participants of the National Diet and Nutrition Survey to study these effects. Within-individual regression models of the energy from 60 food groups on TEI were calculated. Energy intake variation within-individuals was regressed separately on the variation in amounts of each food group. Regression models were also fitted to individual four day means. RESULTS: Within-individual coefficients ranged from about 0 for high-fibre breakfast cereals to 1.7 for sugar preserves and spreads. Three food groups (e.g. low-calorie soft drinks) tended to reduce TEI, and 13 food groups (e.g. margarine and other spreads, and alcoholic drinks) tended to elevate TEI above the energy content of the food group when more than usual amounts were consumed. Foods groups of higher energy densities, or lower fibre content (e.g. typical "snack" foods, low-fibre bread, and processed meat) tended to promote greater TEI more so than did food groups of lower energy densities (e.g. meat, fish, high-fibre foods, and potatoes). CONCLUSION: Different food groups vary considerably in the extent to which they affect TEI in free-living adults. The associations between consuming more, or less, than usual amounts of foods and the effects on TEI are consistent with those found in laboratory studies. Importantly, the present study found similar associations, but using a different methodology and in observational data, providing novel information on energy intake compensation.

Testing a norm-based policy for waste management: An agent-based modeling simulation on nudging recycling behavior.

The present study uses agent-based modeling (ABM) to examine the effectiveness of a nudge policy for improving recycling behavior. In our simulation, agents' recycling behavior is computed by components of the Theory of Planned Behaviour (i.e., attitudes, perceived behavioral control, social norms) and influenced by other agents as well as their surrounding (i.e., amount of waste in the area). The simulation, based on real data from a Taiwan community district, confirms realistic recycling trends and demonstrates the usefulness and reliability of ABM as a method to examine the effectiveness of waste management policies. An additional step in our simulation was to manipulate the amount of waste in the community to test the effect of a nudge policy based on social norms. Results showed that the policy increases recycling activity, but predominantly in low waste scenarios. This suggests that nudges, in the form of norm-based policies, can be an effective solution to enhancing people's recycling behavior under specific circumstances.

Theories for Computing Prosocial Behavior.

Most relevant theories of prosocial behavior aim at exploring and understanding helping motivations from an evolutionary perspective. This article summarizes findings from research on prosocial behavior from both a socio-economic and psychological perspective. Building on literature exploring the basic processes and determinant variables of helping, we propose a stochastic and dynamic model to simulate prosocial behaviors over time and recreate evolutionary processes of helping behaviors. Such a mathematical model formalizes a procedure for dynamic simulations, including agent-based modeling, which implies non-linear dynamics of prosocial processes underlying helping motivations. Practical implications for organizations and societies are addressed.

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

Predicting organic food consumption: A meta-analytic structural equation model based on the theory of planned behavior.

During the last decade, the purchase of organic food within a sustainable consumption context has gained momentum. Consequently, the amount of research in the field has increased, leading in some cases to discrepancies regarding both methods and results. The present review examines those works that applied the theory of planned behavior (TPB; Ajzen, 1991) as a theoretical framework in order to understand and predict consumers' motivation to buy organic food. A meta-analysis has been conducted to assess the strength of the relationships between attitude, subjective norms, perceived behavioral control, and intention, as well as between intention and behavior. Results confirm the major role played by individual attitude in shaping buying intention, followed by subjective norms and perceived behavioral control. Intention-behavior shows a large effect size, few studies however explicitly reported such an association. Furthermore, starting from a pooled correlation matrix, a meta-analytic structural equation model has been applied to jointly evaluate the strength of the relationships among the factors of the original model. Results suggest the robustness of the TPB model. In addition, mediation analysis indicates a potential direct effect from subjective norms to individual attitude in the present context. Finally, some issues regarding methodological aspects of the application of the TPB within the context of organic food are discussed for further research developments.