Affect Regulation Capabilities in Hypermobility Ehlers Danlos Syndrome: Exploring the Associations with Pain Perception and Psychophysical Health
Bibliographic record
Abstract
Background: Hypermobility Ehlers Danlos syndrome (hEDS) is a clinical condition characterized by hypermobility and tissue fragility and associated to chronic pain. The present study aimed to investigate the associations between affect regulation, pain perception and psychophysical dimensions. Methods: Twenty-five hEDS patients completed tests assessing pain experience, pain intensity, emotion regulation, alexithymia and quality of life. A regression analysis was performed on the total sample, in order to investigate the relationship between alexithymia, pain, emotional regulation and perception of quality of life. Results: A high percentage of alexithymia emerged. Negative significant associations emerged between quality-of-life scale and both emotion regulation scale and scales as well as with alexithymia scale and difficulties in identifying and describing feelings. Moreover, a relationship between hEDS and psychological variables concern the time of diagnosis appear. Discussion: Patients with hEDS seems to refer alexithymia; pain seems to interfere with practical aspects of daily life, and may reduce an individual's awareness of their emotional capabilities. Perception of heightened pain has a stronger impact on emotional resources when it interferes with affective life, rather than with practical life. Finally, delayed diagnoses of hEDS entail psychological consequence such as alexithymia. Conclusion: All these aspects may interfere with the possibility of patients to be understood for clinicians and a particular attention is needed also to define the rehabilitative approach.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".