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Enregistrement W4403722288 · doi:10.14309/01.ajg.0001035044.63132.11

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

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

Notice bibliographique

RevueThe American Journal of Gastroenterology · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueEosinophilic Esophagitis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineConfidence intervalEnvironmental healthInternal medicine

Résumé

récupéré en direct d'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)

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,041
Score d'incertitude au seuil0,137

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,014
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0410,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,267
Écart entre enseignants0,255 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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