5.3: Predicting Sedentary Behavior
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Ecological models help to provide a framework that shows multiple levels of influence on behavior. They are useful to highlight specific contexts or situations in which factors may be most likely to influence human behavior. Ecological models typically organize the levels along intrapersonal, interpersonal, contextual, environmental, and policy levels. Each level has distinct factors that predict sedentary behavior. For example, attitudes, beliefs, and perceptions fit within the intrapersonal level. The interpersonal level includes factors that capture social influence such as a friend suggesting going for a walk or watching a movie. The contextual level includes factors within the immediate surroundings that are likely to influence behavior such as school, work, or home. The environmental level includes factors like the attributes of the built-environment, such as suburban compared to a metropolis, that may influence daily patterns of behavior. These levels are usually nested within each other and when considered together can interact and explain human behavior.
The ecological model of four domains of sedentary behavior (Owen et al., 2011) focuses on factors associated with sedentary behavior among domestic (i.e., household), occupation (i.e., work/school), transport (i.e., walk ability, biking, commuting; Figure 5.2), and leisure (i.e., neighborhood and recreational environments). Sedentary behavior may be unavoidable for some individuals as using a private automobile or seated public transport may be the only way to get to their occupation whereas others may be able to walk or bike to work. Moreover, sitting in school or at work is considered a social norm. Identifying the contexts where sedentary behavior is likely to occur and accumulate in time can help guide intervention efforts to break up extended periods of sedentary behavior.
Manini and colleagues (2015) recommend several notable considerations for intervening on sedentary behavior. Sedentary behavior is likely a product of both conscious decision making and automatic responses to environmental cues (e.g., dual-process models). Recommendations include computer-based prompts to stand or move (e.g., smart watches), active workstations such as treadmill desks, allowing employees regular desk breaks, and standing meetings. The efficacy of such interventions to reduce sedentary behavior provides a positive outlook as interventions demonstrate short-term and medium-to-long-term reductions in sedentary behavior (Blackburn, 2020).
Figure 5.2: Neighborhoods with Sidewalks, Bicycle Lanes, Adequate Lighting, and Speed Bumps Can be More Conducive to Transportation-Related Physical Activity
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