Defense mechanisms in immune-mediated diseases: a cross-sectional study focusing on Severe Allergic Asthma and Hymenoptera Venom Anaphylaxis patients
Bibliographic record
Abstract
Background: Chronic immune-mediated diseases, such as Severe Allergic Asthma (SAA) and Hymenoptera Venom Anaphylaxis (HVA), significantly impact quality of life. Defense mechanisms, as implicit emotion-regulation strategies, shape an individual's adaptation to chronic stressors. This cross-sectional study explored the relationship among defensive functioning, psychological symptoms, and perceived physical and mental health in patients with SAA and HVA. Methods: To explore the role of defensive functioning in perceived physical and mental health 34 patients with SAA and 32 with HVA were assessed with the Short-Form Health Survey, the Beck Depression Inventory, the Hamilton Anxiety Rating Scale, the Toronto Alexithymia Scale, and the Defense Mechanisms Rating Scales Self Report-30; between-group differences, and mediation analyses were performed. Results: Defensive functioning was positively associated with mental health and negatively related to depressive symptoms, anxiety and alexithymia. Males reported significantly higher physical and psychological health than females. Patients with SAA exhibited significantly higher defensive functioning but worse physical health than HVA patients. Mediation analysis revealed that defensive functioning correlated with disease type and physical health, accounting for 39% of the explained variances. Moreover, defensive functioning independently predicted mental health. Conclusion: This study highlights the influence of implicit emotional regulation on psychophysiological well-being in patients with chronic immune-mediated disorders. Despite reporting lower perceived physical health, patients with SAA exhibited higher defensive functioning, suggesting that chronic conditions may shape distinct psychological adaptation processes. These findings support the importance of defence mechanisms assessment to tailor psychological interventions promoting well-being in patients with chronic diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".