The Role of Alexithymia in Social Withdrawal during Adolescence: A Case–Control Study
Bibliographic record
Abstract
Although social withdrawal is becoming increasingly common among adolescents, there is still no consensus on its definition from the diagnostic and psychopathological standpoints. So far, research has focused mainly on social withdrawal as a symptom of specific diagnostic categories, such as depression, social phobia, or anxiety disorders, or in the setting of dependence or personality disorders. Few studies have dealt with social withdrawal in terms of its syndromic significance, also considering aspects of emotion control, such as alexithymia. The present case-control study aimed to further investigate the issue of social withdrawal, and try to clarify the part played by alexithymia in a sample of Italian adolescents diagnosed with psychological disorders (n = 80; Average Ageg = 15.2 years, SD = 1.49). Our patients with social withdrawal (cases) scored significantly higher than those without this type of behavior (controls) in every domain of alexithymia investigated, using the Toronto Alexithymia Scale (TAS-20) and with the scales in the Youth Self-Report (YSR) regarding internalizing problems, anxiety–depression, social problems, and total problems. Internalizing problems and total levels of alexithymia also emerged as predictors of social withdrawal. These variables may therefore precede and predispose adolescents to social withdrawal, while social problems may develop as a consequence of the latter.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".