THE RELATIONSHIP BETWEEN IMPULSIVITY AND ALEXITHYMIA IN A SAMPLE OF STRONG NICOTINE ADDICTED. A PRELIMINARY STUDY
Bibliographic record
Abstract
Background and Aims:Given the correlation between tobacco addiction and impulsivity, this study means to evaluate the role of alexithymia in the relationship between impulsivity and tobacco addiction. Alexithymia is defined as a difficulty in the mental representation of emotions due to a loss of integration between physiological and cognitive component of emotions. Alexithymia can be characterized by an operative kind of thought, lacking in imagination, fantasy or oneiric activity that, according to the u201cHuman Birth Theoryu201d by Massimo Fagioli, are fundamental to ensure the possibility to mentally elaborate psychic and physical sensation. Consequently, a lack of psychophysical sensibility could prejudice the imaginative thinking process, mystifying our experience awearness (Atzori, 2017), and making emotional experience less comprehensible and intense.Methods:This preliminary study examines the correlation between the dimensions of impulsivity and alexithymia in a sample of 30 help-seekers related to a Service for Addictions, diagnosed with Tobacco Addiction, through the analysis of the results of a test battery distributed at the admission.Results:Test results suggest that alexithymia has a role in leading to impulsive action. The greatest correlation was found between alexithymia and the impulsivity sub-factor called
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".