P495 The interplay of biopsychosocial factors and quality of life in Inflammatory Bowel Diseases: a network analysis
Bibliographic record
Abstract
Abstract Background Quality of life (QoL) is one of the most relevant patient-reported outcomes in the treatment of patients with inflammatory bowel diseases (IBD), but does not only depend on disease activity. We aimed to investigate the interplay of biopsychosocial factors and their associations with QoL in patients IBD by using a network analytical approach (NA). Methods We measured QoL and anxiety, depression, illness identity, self-esteem, loneliness, childhood trauma, and visceral sensitivity with self-report questionnaires in two independent IBD-samples (sample 1: n=209, anonymous internet survey; sample 2: n=84, outpatients with active disease before the beginning of a biologic treatment). Additionally, fatigue, haemoglobin levels and response to biologic therapy (3–6 months after the first assessment) were assessed in sample 2. We estimated regularized partial correlation networks and conducted tests of accuracy and stability of the network parameters. Results In both samples, QoL had the strongest associations with visceral sensitivity and the illness identity dimension engulfment, a maladaptive integration of IBD into the ‘self’. QoL was uniquely associated with depressive symptoms and fatigue was an essential factor in this link (sample 2). Depression was the most central factor in the networks. Baseline depression scores were connected to response to biologic therapy in sample 2. Conclusion This is the first study using NA to assess the complex interplay between biopsychosocial factors and QoL in IBD. It reveals a comparable network structure in two independent samples emphasizing the importance of depression. Visceral sensitivity and engulfment connected most strongly to QoL. Beyond depression, visceral sensitivity and illness identity may be targetable characteristics to improve QoL in personalised holistic therapy in 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".