The Prevalence and Risk Factors of Undiagnosed Depression and Anxiety Disorders Among Patients With Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) is associated with a high prevalence of comorbid depressive and anxiety disorders. A significant proportion of IBD patients with comorbid psychiatric disorders remain undiagnosed and untreated, but factors associated with diagnosis are unknown. We evaluated the prevalence of undiagnosed depression and anxiety in an IBD cohort, along with the associated demographic and clinical characteristics. METHODS: We obtained data from the enrollment visit of a cohort study of psychiatric comorbidity in immune-mediated diseases including IBD. Each participant underwent a Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID) to identify participants who met lifetime criteria for a diagnosis of depression or anxiety. Those with a SCID-based diagnosis were classified as diagnosed or undiagnosed based on participant report of a physician diagnosis. RESULTS: Of 242 eligible participants, 97 (40.1%) met SCID criteria for depression, and 74 (30.6%) met criteria for anxiety. One-third of participants with depression and two-thirds with anxiety were undiagnosed. Males were more likely to have an undiagnosed depressive disorder (odds ratio [OR], 3.36; 95% confidence interval [CI], 1.28-8.85). Nonwhite participants were less likely to have an undiagnosed anxiety disorder (OR, 0.17; 95% CI, 0.042-0.72). CONCLUSION: Our findings highlight the importance of screening for depression and anxiety in patients with IBD, with particular attention to those of male sex and with a lower education level.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".