Predictors of Impaired Mental Health and Support Seeking in Adults With Inflammatory Bowel Disease
Bibliographic record
Abstract
This study explored the possible factors associated with psychological distress in adults with inflammatory bowel disease (IBD) and also engagement in mental health services (MHS) in those reporting distress in a large Australian cohort. Participants with IBD completed an online survey assessing perceived IBD activity (Manitoba Index; MI), mental health status (K10), demographic details, and engagement with MHS for IBD-associated issues. Of 336 participants, 76.5% perceived themselves as having active disease over the past 6 months, and on K10 scores, 51.8% had a mental health issue. Of participants with a mental health issue, only 21.3% were currently receiving mental health support. A stepwise logistic regression analysis correctly classified 78.7% of the status of receiving mental health support, with lower income (<$60,000 per annum) the only significant predictor. Paradoxically, the degree of psychological distress did not correlate with seeking mental health support. The data show that in individuals with ongoing symptoms attributed to active IBD, mental health issues are highly prevalent, with older age and higher income being additional drivers of mental health issues. The greater challenge, however, seems not to be identifying mental health issues, but in getting those in need to engage in MHS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".