Social networks and the theory of planned behavior: How networks matter for healthy eating and meat consumption

Social-cognitive theories, such as the Theory of Planned Behavior (TPB), define social norms as the generalized behavioral expectations and observed behavior of important others. Social network measures capture social context more directly, offering an alternative way to examine how others' attitudes and behaviors enable or constrain action. We integrate both approaches to study the social context of healthy eating and meat consumption.

2083 German adults completed an online survey (January-March 2024) that measured TPB variables (attitudes, perceived behavioral control, injunctive and descriptive norms, intention, behavior). Egocentric social network data were collected, including the perceived eating behavior and attitudes of network partners toward healthy eating and meat consumption. Bayesian multilevel path analysis was applied.

Social network partners' perceived behavior accounted for variation in healthy eating (BF₁₀=992.5) and meat consumption frequency (BF₁₀>1000) beyond TPB norms. Social network partners' perceived attitudes accounted for variation in meat consumption and healthy eating through their association with attitudes, norms and perceived behavioral control. Neither behavior nor attitudes of social network partners were associated with intentions to eat healthily or intention to reduce meat consumption beyond their association with the TPB's antecedents of intention.

Social network behavior accounts for additional variance in eating behavior beyond TPB norms and may help illuminate the intention behavior gap in healthy eating and meat consumption. Public Significance Statement: This study bridges a traditional psychological theory and social network science to understand healthy eating and meat consumption. We found that people's real-life social environments, especially the behaviors of the people close to them, are associated with their dietary choices beyond a standard psychological model. Considering social network dynamics may therefore improve strategies for supporting healthy and sustainable eating behaviors.