エージェントベースのモデリングを使用して,職場の食事介入を超えた転移効果を探求する
Yinjie Zhu1,2, Marga C Ocké2,3, Emely de Vet1
1Consumption and Healthy Lifestyles chair group, Wageningen University & Research, Hollandseweg 1, 6706 KN, Wageningen, the Netherlands.
Public health nutrition
|February 12, 2026
まとめ
エージェントベースのモデリング (ABM) は,食事の介入が家庭での植物性タンパク質の消費に肯定的な影響を与える可能性があることを示しました. 職場での介入により,夕食時に植物性食事が多くなり,転移効果が示されました.
科学分野:
- コンピューティング社会科学
- 栄養科学とは,栄養科学である.
- 行動科学は,行動科学である.
背景:
- ダイエット介入は,しばしば直接的な影響に焦点を当てています.
- 他の食事や状況への転移効果を理解することは,公衆衛生にとって極めて重要です.
- エージェントベースのモデリング (ABM) は,複雑な行動ダイナミクスを研究するための新しいアプローチを提供します.
研究 の 目的:
- ABMを用いて,直接的な範囲を超えた食事介入の転移効果を調査する.
- 職場での食生活の変化が家庭での食生活に影響する程度を定量化するために.
- これらの効果を媒介する食事のアイデンティティやソーシャルネットワークなどの要因の役割を探求する.
主な方法:
- オランダの成人の昼食と夕食の食事習慣をシミュレートするエージェントベースのモデル (ABM) を開発しました.
- 職場の食堂での介入をシミュレートし,昼食に植物性タンパク質を推奨しました.
- 夕食時の植物性タンパク質の消費に対する転移効果を評価し,直接介入効果の大きさを変化させた.
主要な成果:
- シミュレーションにより,人口レベルでのプラスの転移効果が示され,3年間にわたって夕食時に植物性タンパク質の消費量が増加しました.
- 夕食時の植物性タンパク質の摂取量は線形的に増加し,直接介入効果のサイズは0.5.5まで増加しました.
- 溢出効果は,0.5の効果サイズを超えて停滞し,収益の減少を示した.
結論:
- ABMは,職場での食事の介入が家庭での食事習慣にプラスの転移効果を生むことができると成功裏に実証しました.
- このモデリングアプローチは,食事の行動の変化を研究するための伝統的な方法を補完することができます.
- 研究結果は,ABMが持続可能な食習慣を促進する可能性を裏付けています.
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