While the Diabetes Prevention Program demonstrated that relatively small changes in diet and physical activity could substantially reduce the incidence of diabetes among high risk adults, few programs have influenced obesity or diabetes risks among children. With the increasing rates of child obesity and diabetes, innovative programs are needed that capture children's attention and permit behavior change messages to get through. Serious video games with their immersive stories offer one such promising alternative. "Escape from Diab" and "Nanoswarm: Invasion from Inner Space" are two video games guided in their design by four behavior change theories that were targeted at increasing fruit, vegetable and water intakes, and lowering sedentary behaviors, and have been shown to change these children's diet and physical activity practices in a pilot study with a relatively low risk sample. In light of this preliminary success, it is important to test the efficacy of these interventions on diabetes risks (i.e. fasting insulin) with higher risk children (which should increase the effect) and with a larger sample to learn how the games change behaviors using mediating variable analyses. A study with 444 high risk (85 percentile Fruit, vegetable, and water consumption and physical activity are still substantially below minimum recommendations, indicating increased risks for diabetes and obesity. Serious video games hold promise for promoting increases in these behaviors. The proposed research represents the next step in determining whether behavioral designed video games influence risks and behaviors in a high risk sample.
Public Health Relevance
Fruit, vegetable, and water consumption and physical activity are still substantially below minimum recommendations, indicating increased risks for diabetes and obesity. Serious video games hold promise for promoting increases in these behaviors. The proposed research represents the next step in determining whether behavioral designed video games influence risks and behaviors in a high risk sample.
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