Regolazione affettiva e psicopatologia nei giovani adulti: una ricerca clinica
Bibliographic record
Abstract
ABSTRACT: Background: In recent years, clinical research has highlighted the importance of considering \nthe strategies of affect regulation and the quality of attachment. These are indeed key variables in determining \npossible psychological difficulties or even development of psychopathology in youth. Disorders \nof affect regulation, caused by insecure attachment patterns, frequently associated with an alexithymic functioning, \nmay represent significant risk factors for the development and long-term outcomes of psychopathology \nin adolescence, especially if in presence of disorganized states of mind. Objective: Assessing the quality \nof affect regulation in a sample of adolescents and young adults who refer to a service for mental distress \nin adolescence. Method: A sample of 204 late adolescents between 17 and 25 years old were assessed \nby clinicians according to the ICD-9 (World Health Organization, 1992). Overall mental functioning (VGF), \nsymptoms’ level (Symptom Checklist-90-R; Derogatis, 1977), attachment style (Attachment Style Questionnaire; \nFeeney et al., 1994), level of alexytimia (Toronto Alexytimia Scale-20; Bagby et al., 1994a, 1994b) were \nalso assessed. A subgroup of patients were administered the Adult Attachment Interview (George, Kaplan \ne Main, 1984) and the SWAP-200 (Shedler Westen Assessment Procedure-200, Westen, Shedler, Lingiardi, \n2003). Results: Results showed the existence of high correlations between self-report instruments that define \ntwo profiles of affect regulation: an anxious-symptomatic style, characterized by hyperactivation of the \nattachment system, high level of symptoms and difficulty in identifying emotional states; and an alexithymicavoidant \nstyle, characterized by deactivation of attachment system, low self-esteem, emotional distance and \ndifficulties to communicate internal states. These styles show significant correlations with some personality disorders and with disorganized attachment states of mind. Conclusions: The possibility to investigate these \nvariables in the initial consultation with adolescents who have a clinically significant distress allows a more \nthorough evaluation of their level of functioning with significant implications on treatment plan.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.005 | 0.001 |
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".