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Record W4406703975 · doi:10.1093/ecco-jcc/jjae190.0779

P0605 Nutritional Therapy for IBD: a new non-profit organization that offers trusted, evidence-based information and novel resources on diet and nutritional therapies in IBD

2025· article· en· W4406703975 on OpenAlexaffabout
Agustina Prados, Rotem Sigall Boneh, Stephanie Gold, Natasha Haskey, Andrew S. Day, K Beall

Bibliographic record

VenueJournal of Crohn s and Colitis · 2025
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMedicineMedical nutrition therapyIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Background There is a well-described need for credible resources on the role of diet in IBD, with many Internet and social media sources found to be unbalanced and misaligned with the evidence1,2. Nutritional Therapy for IBD (https://www.nutritionaltherapyforibd.org/) was founded in 2019 to enhance the well-being and health outcomes of children and adults with IBD by optimizing medical care through adjunctive evidence-based nutritional therapy. An overview of the characteristics of this organization’s online resources, web traffic, and user impressions are described. Methods Website performance metrics were collected via Google Analytics from Oct 31, 2023, to Oct 31, 2024, and an online survey was conducted for two weeks in Oct 24. Results The website fosters training and dissemination of knowledge of the role of diet and nutritional therapies in IBD and includes four main sections: dietary options for IBD, research database, information for patients and families, and tools for healthcare professionals. Over the study period, there were 453,103 visits and 151,588 active users from 10 countries, with an average of 3 visits per user. The top-engaged countries were the United States, United Kingdom, Canada, South Africa, and Australia (Figure 1). The most visited website sections included 1) Recipes, 2) The Crohn’s Disease Exclusion Diet, and 3) The low FODMAP diet for non-inflammatory symptoms (Figure 2). Of 81 users completing the survey, 80.2% were female, 35.8% were patients with IBD, 29.5% were healthcare professionals, and 13.6% were family members. Among healthcare professionals, 30.3% were registered dietitians, 21.2% IBD-specialized registered dietitians, and 12.1% IBD gastroenterologists. 91.4% of responders indicated the content was useful, with high scientific rigor (82.7%), and stated the content influenced how they viewed nutrition as part of IBD care (74.1%). The most valuable resources were research summaries (80.0%), resources for implementing nutritional therapies in daily life (73.8%), and detailed information on specific nutritional therapies (68.8%). Conclusion Internet users are clearly interested in and find it useful to have access to evidence-based information about dietary interventions for IBD. Scientific rigor combined with accessible language are distinctive features of Nutritional Therapy for IBD, developed to help healthcare professionals use the best available evidence to inform their practice and help patients make informed choices about nutrition. References 1.Fusco, S., Briese, K., Keller, R., et al. (2024). Are Internet information sources helpful for adult Crohn’s disease patients regarding nutritional advice? J Clin Med, 13(10), 2834. https://doi.org/10.3390/jcm13102834 2.Gkikas, K., Wan, M., Svolos, V., et al. (2024). YouTube as a source of information for food, diet-related items, and advisory comments for the management of inflammatory bowel disease. Inflamm Bowel Dis, 30(3), 347-356. https://doi.org/10.1093/ibd/izad076

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.126
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1260.050

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.293
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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