Factors Associated With Social Participation in Persons Living With Inflammatory Bowel Disease
Bibliographic record
Abstract
Abstract Background Inflammatory bowel disease (IBD) including Crohn’s disease (CD) and ulcerative colitis (UC) imposes a significant burden on health-related quality of life, particularly in social domains. We sought to investigate the factors that limit social participation in patients with IBD. Methods We assessed a cohort of 239 Manitobans with IBD. We collected sociodemographic information, medical comorbidities, disease phenotype, symptom activity and psychiatric comorbidity (using the Structured Clinical Interview for DSM-IV). Participants completed the eight-item Ability to Participate in Social Roles and Activities (APSRA) questionnaire, which assesses participation restriction, including problems experienced in social interaction, employment, transportation, community, social and civic life. Results Poorer social participation scores were associated with earning less than $50,000 CAD income annually (P < 0.001), actively smoking (P = 0.006), higher symptom scores (P < 0.001 for CD, P = 0.004 for UC), and having an increasing number of chronic medical conditions (R = −0.30). History of depression (P < 0.001) and anxiety (P = 0.001) and having active depression (P < 0.001) and anxiety (P = 0.001) all predicted poor social participation scores. IBD phenotype or disease duration was not predictive. Based on multivariable linear regression analysis, significant predictors of variability in social participation were medical comorbidity, psychiatric comorbidity, psychiatric symptoms and IBD-related symptoms. Conclusions The factors that predict social participation by IBD patients include income, smoking, medical comorbidities, IBD symptom burden, and psychiatric comorbidities. Multivariable linear regression suggests that the most relevant factors are medical comorbidity, psychiatric comorbidity, psychiatric symptoms and IBD symptoms.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".