Attachment Insecurity Moderates the Relationship Between Disease Activity and Depressive Symptoms in Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND: Among people with ulcerative colitis, depression occurs more frequently when inflammation is active. We hypothesized that individual differences in interpersonal style affect the risk that active disease will be accompanied by depressive symptoms. METHODS: In this study, disease activity, depressive symptoms, and 2 dimensions of interpersonal style, attachment anxiety and attachment avoidance, were measured in 146 ulcerative colitis outpatients at time 1 and in 99 of these patients at a second time-point, 7 to 37 months later. Test-retest correlations of attachment anxiety (r = 0.83, P < 0.001) and attachment avoidance (r = 0.76, P < 0.001) confirmed that these dimensions are stable. RESULTS: There was a stepwise increase in the correlation between time 2 disease activity and depression from the lowest tercile of attachment anxiety (r = 0.00, P = 0.99), through the middle tercile (r = 0.36, P = 0.05), to the highest tercile (r = 0.52, P = 0.002). For attachment avoidance, disease activity and depression were only significantly correlated in the highest tercile (r = 0.49, P = 0.005). CONCLUSIONS: Attachment anxiety meets all tested criteria as a moderator of the relationship between disease activity and depressive symptoms. Further attention to interpersonal style as a moderator of depressive risk in ulcerative colitis is warranted.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".