Adverse childhood experiences and psychiatric comorbidity in multiple sclerosis, inflammatory bowel disease, and rheumatoid arthritis in the Canadian longitudinal study on aging
Bibliographic record
Abstract
OBJECTIVES: Adverse childhood experiences (ACE) are associated with immune-mediated inflammatory diseases (IMID). We evaluated whether: (i) ACE associate with psychiatric comorbidity among individuals with IMID, including rheumatoid arthritis (RA), multiple sclerosis (MS), and inflammatory bowel disease (IBD); (ii) whether psychiatric disorders mediate the relationship between ACE and IMID; and (iii) whether these findings differ from those in individuals with other chronic physical disorders. METHODS: Using data from the Canadian Longitudinal Study on Aging (CLSA) we performed a retrospective case-control study of participants aged 45-85 years recruited between 2010 and 2015. ACE were queried using questions derived from the Childhood Experiences of Violence Questionnaire-Short Form and the National Longitudinal Study of Adolescent to Adult Health Wave III questionnaire. We used multivariable logistic regression and causal mediation analysis to address our objectives. RESULTS: We included 13,977 CLSA participants. Among the 31 % of IMID participants who reported a comorbid psychiatric disorder, 79 % reported a history of ACE. ACE associated with increased odds (OR [95 % CI]) of a psychiatric disorder (2.55 [1.02-6.35]) among participants with IMID; this did not differ across IMID. The total effect (OR [95 % CI]) of ACE on IMID was 1.11 (1.07-1.16), of which 10.60 % (8.04-17.47) was mediated by psychiatric disorders. We found similar associations among participants with other chronic physical disorders. CONCLUSION: Our findings suggest that psychiatric disorders partially mediate the association between ACE and IMID. Most participants with IMID and comorbid psychiatric disorders report a history of ACE and may benefit from trauma-informed mental health care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".