Starke Alain D, Dierkes Jutta, Lied Gülen Arslan, Kasangu Gloria A B, Trattner Christoph
Amsterdam School of Communication Research, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, the Netherlands.
MediaFutures, Department of Information Science and Media Studies, University of Bergen, Norway.
PEC Innov. 2025 Jan 10;6:100372. doi: 10.1016/j.pecinn.2025.100372. eCollection 2025 Jun.
To develop a research agenda to investigate the effectiveness of AI-tailored advice to support healthier home cooking. It aims to support healthier food choice in the context of hypertension, allergies, and sustainable diets.
We describe an agenda that has been formed between 2019 and 2022, through multiple rejected grant applications to the Research Council of Norway. We focus on the case of tailored recipe advice for individuals, formulating research questions and methods for three topics: "Acceptance of Personalized Food Advice", "Algorithm and Interface AI: App Development", and "Nutrition Modeling & Clinical Trials". The overall methodology focuses on mitigating health issues among individuals with hypertension.
The design of AI to support healthier home cooking should tap into computational principles, as well as (psychological) theories of behavioral change. The effectiveness of an AI-driven home cooking app can be evaluated in a clinical trial akin to 'regular' dietary intervention studies.
The development of a research agenda requires an integrated effort between scientists from different domains, during both the development and writeup of ideas. The proposed project is innovative, as most food technology and AI approaches have yet to be tested in proper trials on changes in eating habits.
制定一项研究议程，以调查人工智能定制建议对支持更健康家庭烹饪的有效性。其旨在在高血压、过敏和可持续饮食的背景下支持更健康的食物选择。
我们描述了一个在2019年至2022年期间形成的议程，该议程通过多次向挪威研究理事会提交被拒的资助申请而产生。我们专注于为个人提供定制食谱建议的案例，为三个主题制定研究问题和方法：“个性化饮食建议的接受度”、“算法与界面人工智能：应用程序开发”以及“营养建模与临床试验”。总体方法侧重于缓解高血压患者的健康问题。
支持更健康家庭烹饪的人工智能设计应借鉴计算原理以及行为改变的（心理学）理论。人工智能驱动的家庭烹饪应用程序的有效性可以在类似于“常规”饮食干预研究的临床试验中进行评估。
研究议程的制定需要不同领域的科学家在想法的开发和撰写过程中进行综合努力。所提议的项目具有创新性，因为大多数食品技术和人工智能方法尚未在关于饮食习惯变化的适当试验中得到检验。
