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S1419 Following a Stricter Diet Is Associated With Higher Confidence in Managing IBD But Also a Higher Perceived Diet Burden

2024· article· en· W4403722288 on OpenAlexaboutno aff
Jamie Horrigan, Jessica K. Salwen‐Deremer, Corey A. Siegel

Bibliographic record

VenueThe American Journal of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConfidence intervalEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Many patients with inflammatory bowel disease (IBD) use diet to manage symptoms and potentially improve inflammation. Our aims were to define a spectrum in patients’ dietary preferences or “dietypes” and to understand how a stricter diet may be associated with other factors. Methods: We ran 4 focus groups of 5-6 participants with IBD to learn about their dietary preferences and aimed to develop either specific “dietype” categories or a spectrum of “dietypes.” Focus groups were repeated until thematic saturation was achieved. We then developed a questionnaire targeting adults with IBD on social media to learn more about their dietary preferences and the burden of these preferences. Results: Demographics of participants are shown in Table 1. 60% reported currently following a special diet, 34% previously followed a special diet, and 6% had never tried a special diet to help manage their IBD. 80% believe that diet has an impact on their IBD. The most common current special diets include avoiding trigger foods (47.3%), gluten and dairy free (12.6%), gluten free (12.6%), dairy free (9%), low fiber/low residue (7.6%), and Mediterranean diet (5.1%) . Other diets including Specific Carbohydrate Diet, low fermentable oligosaccharides, disaccharides, monosaccharides, and polyols; paleo, and ketogenic diets had < 5% following each (n=277). There was wide variation in perceived strictness of current diets. Most viewed their diets as not a major burden and were confident that their diet improves their symptoms but unsure if diet was helping to heal their bowel (Figure 1). Increased strictness of current diet positively correlated with confidence in control and management of health problems related to IBD (r=0.20, P =0.04). There was also a positive relationship between perceived strictness of current diet and burden of current diet (r=0.38, P < 0.001). Higher PHQ4 (measuring anxious and depressive symptoms) scores correlated with increased perceived burden of current diet (r=0.32, P < 0.001). Similarly, increased perceived burden of diet correlated with increasing severity of avoidant/restrictive food intake disorder symptoms (ARFID) (r= 0.43, P < 0.001). Conclusion: Most respondents use dietary therapy to help manage their IBD. While following a stricter diet is associated with having more control over their disease, it is also associated with a higher perceived burden, and higher burden is associated with increased symptoms of anxiety, depression, and ARFID. It is important to help patients find a dietype that improves their confidence in managing their disease without creating psychosocial consequences.Figure 1.: Patients with inflammatory bowel disease (IBD) were asked to place the slider on a scale from 0 to 100 where it best represented their (A) approach to diet as related to having IBD from “0” “I do not follow any particular diet” to “100” “I follow a strict restrictive diet” (n=228), (B) burden of their current diet from “0” “No burden at all, it is easy for me” to “100” “Significant burden, it is very difficult for me” (n=228), (C) confidence their current diet improves their IBD symptoms from “0” “Not confident at all, I do not think the diet I am currently following improves my IBD symptoms” to “100” “Fully confident, I strongly believe the diet I am currently following improves my IBD symptoms” (n=227), and (D) confidence their current diet heals their bowel from “0” “Not confident at all, I do not think the diet I am currently following helps heal my bowel due to my IBD” to “100” “Fully confident, I strongly believe the diet I am currently following helps heal my bowel due to my IBD” (n=227). Table 1. - Demographics of Participants Characteristics Gender Identity Woman 90.3%Man 9.7% (n-277) Current Age Average: 36.7 years (range 19-75 years) (n=272) Hispanic, Latino, or Spanish Origin Yes 5%No 95% (n=277) Self-Description of Ethnicity American Indian or Alaska Native 0%Asian 4%Black or African American 2.9%Native Hawaiian or Other Pacific Islander 0% White 93.5% (n=277) Total Annual Household Income Less than $24,999 5.4%$25,000 to $49,999 4.3%$50,000 to $99,999 22.7%$100,000 to $199,999 10.5%$200,000 to $299,999 10.5%Greater than $300,000 11.9%Prefer not to say 12.6% (n=277) Country of Residence United States 84.5%Canada 7.9%*< 3% from each of the following: Belgium, Finland, Germany, Greece, India, Ireland, Malaysia, Mexico, Poland, Slovakia, South Africa, United Kingdom (n=277) Disease Type Crohn's Disease 70.4%Ulcerative Colitis 29.6% (n=277) Average Age at Diagnosis 23.9 years (range 1-72 years) (n=272) IBD-Specific Medication None 11.6%Prednisone 3.6%5-ASA 18.1%Immunomodulators 10.1%Biologic 77.2%Other/Clinical Trial 2.9% (n=276) Prior or Current Crohn's Disease Complications Stricture 42.6%Fistula 27.2%Perianal Disease 26.2%None 45.1% (n=190) Current J-pouch 5.5% (15 out of 272) Current Stoma 5.1% (14 out of 272) Nine Item Avoidant/Restrictive Food Intake Disorder Screen (NAIS) Picky Eating Subscale Positive Screen 14.8%Appetite Subscale Positive Screen 18.1%Fear Subscale Positive Screen 28%Positive Screen on 1 or More Subscales 39.9%*Positive screen defined as a subscale score of ≥10 for picky eating, ≥9 for appetite (lack of interest in eating/food, ≥10 for fear (fear of adverse consequences of eating) (n=243) PHQ-4 Score (anxious and depressive symptoms) Moderate to Severe (score 6-12) 25.3% (n=233)

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0410.002

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 head0.013
GPT teacher head0.267
Teacher spread0.255 · 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 designObservational
Domainnot available
GenreEmpirical

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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Published2024
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