How Did COVID-19 Affect Mental Health and Access to Care in Persons With Inflammatory Bowel Disease
Bibliographic record
Abstract
The coronavirus disease pandemic globally affected public health and the world economy, leading to an increase in mental health symptoms, thought to be due in part to periods of quarantining, restrictions, and other interventions used to curb ongoing transmission of the virus. It is well established that persons with inflammatory bowel disease (IBD) have significantly higher rates of depression and anxiety than the general population and that mental health symptoms can exacerbate disease severity. For persons with IBD, psychological distress was correlated with challenges in accessing medical care. In the early stages of the pandemic, endoscopy suites were closed, leading to fewer colonoscopies, although this rebounded the following year. This likely led to fewer diagnoses of IBD initially as people avoided the health care system, and also a reduction in IBD-related dysplasia being detected during colonoscopy. Many hospitals and health care clinics adjusted by delivering telemedicine for ambulatory care. Persons with IBD had increased stress about accessing both their health care provider and gastroenterologist during the pandemic, although many had increased satisfaction with the level of care they received virtually. Telemedicine is now being used in most clinics in conjunction with in-person care, to help deliver care, and can be cost-effective. Additional research is needed to assess whether heightened levels of mental health symptoms have led to worsening disease activity, and further, if a delay in health care access including colonoscopies and surgeries, or the perceived decreased access to health care professionals for some will have detrimentally affected the disease course for persons with IBD.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".