The Relationship Between Adverse Childhood Experiences and Health Care Use in the Manitoba IBD Cohort Study
Bibliographic record
Abstract
BACKGROUND: We aimed to determine the prevalence of adverse childhood experiences (ACEs) in persons with inflammatory bowel disease (IBD) and whether having ACEs was associated with health care utilization post-IBD diagnosis. METHOD: Three hundred forty-five participants from the population-based Manitoba IBD Cohort Study self-reported ACEs (ie, physical abuse, sexual abuse, death of a very close friend or family member, severe illness or injury, upheaval between parents, and any other experience thought to significantly impacts one's life or personality) at a median of 5.3 years following IBD diagnosis. Cohort study data were linked to administrative health databases that captured use of hospitals, physician visits, and prescription drugs; use was classified as IBD-related and non-IBD-related. Mean annual estimates of health care use were produced for the 60-month period following the ACE report. Generalized linear models (GLMs) with generalized estimating equations (GEEs) with and without covariate adjustment were fit to the data. RESULTS: The prevalence of at least 1 ACE was 74.2%. There was no statistically significant association between having experienced an ACE and health care use. However, unadjusted mean annual non-IBD-related general practitioner visits were significantly higher for participants exposed to physical and sexual abuse than those not exposed. Selected adjusted rates of IBD-related health care use were lower for participants who reported exposure to an upheaval between parents and high perceived trauma from ACEs. CONCLUSION: The estimated prevalence of at least 1 self-reported ACE in persons with diagnosed IBD was high. Health care use among those who experienced ACEs may reflect the impacts of ACE on health care anxiety.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".