Emotion Regulation, Coping, and Alexithymia in Adolescents With Obsessive–Compulsive Disorder: A Mediational Analysis
Bibliographic record
Abstract
BACKGROUND: Obsessive-compulsive disorder (OCD) is a debilitating mental health condition that impacts daily functioning. In addition to classical symptoms, emotion regulation (ER), alexithymia and maladaptive coping are thought to be involved in the symptomology and maintenance of the disorder. This study aims to investigate the relationship between ER, alexithymia and coping in adolescents with a sole diagnosis of OCD. METHODS: The study comprised of 93 participants with OCD and 92 healthy controls. Patients with any psychiatric disorder other than OCD were set as exclusion criteria. A sociodemographic form, Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children, Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS), Difficulties in Emotion Regulation Scale (DERS), Toronto Alexithymia Scale (TAS) and KidCOPE were applied. RESULTS: The TAS and DERS scores of participants with every subscale, except awareness in DERS, and the KIDCOPE-Avoidant Coping scores were significantly higher in the OCD group (p < 0.05). A positive and moderately significant relationship was identified between the CY-BOCS-Obsession, CY-BOCS-Compulsion and CY-BOCS-Total scores and the DERS-Total (p < 0.05). Linear regression analysis revealed that CY-BOCS-Total scores significantly predicted DERS-Total scores in a positive direction even when TAS-Total and KidCOPE scores were controlled (p = 0.001). Difficulties in ER mediated the relationship between OCD and the severity of negative coping (b = 0.064, 95% CI (0.036-0.097)). CONCLUSIONS: There is limited evidence regarding the specific contribution of OCD with emotion dysregulation, alexithymia and avoidant coping. Our study suggests a possible relationship with OCD and these parameters, highlighting the need to develop effective intervention techniques tailored to this population.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".