ArticlePEC innovation2025
Supporting healthier food choices through AI-tailored advice: A research agenda.
Article in PEC innovation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Trial
- Understanding Graduate Students' Perspectives on Food Apps to Inform User-Centered Design: Explanatory Sequential Mixed Methods Survey Study.JMIR formative research · 2026Article
- Article
- Learning from brilliant failures.PEC innovation · 2025Article
- Artificial intelligence in personalized nutrition and food manufacturing: a comprehensive review of methods, applications, and future directions.Frontiers in nutrition · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: 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. Methods: 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. Conclusion: 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. Innovation: 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.