Abstract

Decision-making contributes to what and how much we consume, and deficits in decision-making have been associated with increased weight status in children. Nevertheless, the relationships between cognitive and affective processes underlying decision-making (i.e., decision-making processes) and laboratory food intake are unclear. We used data from a four-session, within-subjects laboratory study to investigate the relationships between decision-making processes, food intake, and weight status in 70 children 7-to-11-years-old. Decision-making was assessed with the Hungry Donkey Task (HDT), a child-friendly task where children make selections with unknown reward outcomes. Food intake was measured with three paradigms: (1) a standard ad libitum meal, (2) an eating in the absence of hunger (EAH) protocol, and (3) a palatable buffet meal. Individual differences related to decision-making processes during the HDT were quantified with a reinforcement learning model. Path analyses were used to test whether decision-making processes that contribute to children’s (a) expected value of a choice and (b) tendency to perseverate (i.e., repeatedly make the same choice) were indirectly associated with weight status through their effects on intake (kcal). Results revealed that increases in the tendency to perseverate after a gain outcome were positively associated with intake at all three paradigms and indirectly associated with higher weight status through intake at both the standard and buffet meals. Increases in the tendency to perseverate after a loss outcome were positively associated with EAH, but only in children whose tendency to perseverate persistedacross trials. Results suggest that decision-making processes that shape children’s tendencies to repeat a behavior (i.e., perseverate) are related to laboratory energy intake across multiple eating paradigms. Children who are more likely to repeat a choice after a positive outcome have a tendency to eat more at laboratory meals. If this generalizes to contexts outside the laboratory, these children may be susceptible to obesity. By using a reinforcement learning model not previously applied to the study of eating behaviors, this study elucidated potential determinants of excess energy intake in children, which may be useful for the development of childhood obesity interventions.

Highlights

  • 18% of children in the United States have obesity, and an additional 16% meet the criteria for overweight (Skinner et al, 2018)

  • Pre-standard meal fullness was negatively associated with standard meal intake [r(68) = −0.24, p < 0.05], pre-eating in the absence of hunger (EAH) and pre-buffet meal fullness were not associated with EAH [r(68) = 0.06, p = 0.62] or buffet meal intake [r(67) = −0.02, p = 0.86], respectively

  • This study showed that decision-making processes related to perseveration were associated with energy intake in children across a variety of eating contexts

Read more

Summary

Introduction

18% of children in the United States have obesity, and an additional 16% meet the criteria for overweight (Skinner et al, 2018). Behavioral interventions to reduce energy intake can produce beneficial weight-loss results (Jelalian, 1999; Epstein et al, 2001), they are not effective for all children and lack long-term efficacy (Mead et al, 2017) One reason for this may be a lack of understanding of food-related decision-making in middle childhood (i.e., 6-to-12 years-old), a period where children gain autonomy over foodrelated decisions (Ogden and Roy-Stanley, 2020). While research has examined the decision-making mechanisms underlying what foods children select (Lim et al, 2016; van Meer et al, 2017; Ha et al, 2020; Ogden and Roy-Stanley, 2020; Pearce et al, 2020), the mechanisms underlying how much children consume are unclear To close this gap, this study aims to identify decision-making processes that are associated with increased energy intake and weight status in middle childhood

Objectives
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call