Non-pharmacological therapies for inflammatory bowel disease: Recommendations for self-care and physician guidance
Bibliographic record
Abstract
We performed a scoping review on sought-after complementary therapies for patients with inflammatory bowel disease (IBD), specifically diet, physical activity and exercise (PA/E), and psychotherapy.We aim to update patients with IBD on therapies for self-care and provide physicians with guidance on how to direct their patients for the management of IBD.A search of MEDLINE, EMBASE, and PUBMED was completed in Sept 2016.Studies on diet, PA/E, or psychotherapy in patients with IBD were included.Medical Subject Heading terms and Boolean operators were used.The search was limited to full-text English articles describing an adult population.This review included 67 studies: Diet (n = 19); PA/E (n = 19); and psychotherapy (n = 29).We have made the following recommendations: (1) Diet: Consumption of diets rich in vegetables, fruit and soluble fiber may be beneficial in IBD.A trial of a low FODMAP diet can be considered in those patients with functional gastrointestinal symptoms.Restrictive diets are lacking in evidence and should be avoided; (2) PA/E: Regular lowmoderate intensity activity, including cardiovascular and resistance exercise, has been shown to improve quality
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".