The relationship between alexithymia and dissociation in an adolescent sample
Bibliographic record
Abstract
Objective: The relationship between alexithymia and dissociation has not been well researched and clarified in an adolescent population. Our study aims to test the hypothesized link between alexithymia and dissociation along with other possible predictors of dissociation in an adolescent population. \nMethod: The sample consisted of 145 adolescent high school students between the ages of 15 and 18. The subjects were assessed using the Dissociative Experiences Scale, the Toronto Alexithymia Scale, the Rosenberg Self-esteem Scale, the Beck Anxiety and Depression Scales, and a sociodemographic form. Multiple linear regression analyses were used to predict scores on the Dissociative Experiences Scale. \nResults: When anxiety was entered in the regression model, alexithymia was no longer associated with dissociation and anxiety became the sole significant predictor of the Dissociative Experiences Scale scores. This model accounted for 17% of the variance. This finding shows that alexithymia is not a predictor of dissociation in our adolescent population. \nConclusion: Alexithymia does not predict dissociative tendencies in adolescents. Anxiety emerges as a significant predictor but by itself can not explain the plentitude of factors determining dissociative tendencies. But because only 17% of the variance is explained in this model, it seems that many other factors involved in the development of dissociative processes need to be addressed. Including more variables in a regression equation could highlight the predictors of dissociation better
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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) | 0.000 | 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) | 0.002 | 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".