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Decision-Making Processes Related to Perseveration Are Indirectly Associated With Weight Status in Children Through
Bari A Fuchs1, Nicole J Roberts2, Shana Adise3
1Metabolic Kitchen and Children's Eating Behavior Laboratory, Department of Nutritional Sciences, State College, The Pennsylvania State University, University Park, PA, United States.
Frontiers in Psychology
|September 7, 2021
Summary
Children
Area of Science:
- Neuroscience and Behavior
- Developmental Psychology
- Pediatric Obesity Research
Background:
- Decision-making processes influence food consumption and are linked to childhood weight status.
- The precise relationship between decision-making processes and laboratory food intake in children remains unclear.
Purpose of the Study:
- To investigate how decision-making processes relate to food intake and weight status in children aged 7-11.
- To identify specific decision-making characteristics associated with higher energy intake and weight status.
Main Methods:
- Utilized a within-subjects laboratory study with 70 children (7-11 years old).
- Assessed decision-making using the Hungry Donkey Task (HDT) and quantified individual differences with a reinforcement learning model.
- Measured food intake via standard ad libitum meal, eating in the absence of hunger (EAH) protocol, and a palatable buffet meal.
Main Results:
- Increased tendency to perseverate after a positive outcome was linked to higher intake across all eating paradigms and indirectly to higher weight status.
- Perseveration after a negative outcome was associated with eating in the absence of hunger, particularly in children who consistently perseverated.
- Decision-making processes, specifically perseveration, are associated with laboratory energy intake in children.
Conclusions:
- Decision-making processes, particularly the tendency to repeat choices after positive outcomes, are related to increased food intake in children.
- These findings suggest a potential pathway linking specific decision-making behaviors to childhood obesity.
- The study highlights the utility of reinforcement learning models in understanding eating behaviors and developing interventions for childhood obesity.
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