ALEXITHYMIA FORMATION AS AN ADAPTATION TO EVERYDAY STRESS IS DETERMINED BY THE PROPERTIES OF THE NERVOUS SYSTEM
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to determine the psychological nature and mechanisms of alexithymia formation by way of the analysis of its relation to the properties of the nervous system, mental states, and characteristics of the emotional sphere of the personality. PATIENTS AND METHODS: Materials and methods: In the process of the study, for the diagnostics of alexithymia, we used the 26-item Toronto Alexithymia Scale (TAS-26) developed by G.J. Taylor and a block of psycho-diagnostic methods aimed at the diagnostics of properties of the nervous systems, the emotional sphere and mental states of respondents. The relationships were evaluated using Spearman's rank correlation coefficient and Pearson's correlation coefficient. RESULTS: Results: The main factors related to alexithymia were weak nervous system, low stress resistance and such characteristics of the emotional sphere as marked extraversion, high level of trait anxiety, neuroticism, indirect verbal aggression, low levels of aggressiveness. The emotional exhaustion and reduction of personal achievements, the Resistance Phase, chronic fatigue and depression were the most pronounced within the alexithymia group. The alexithymic personality type demonstrated less developed spatial anticipation. CONCLUSION: Conclusion: In accordance with our results, the weakness of the nervous system and high Trait Anxiety facilitate the adaption to stressful situations by avoiding and crowding out negative emotions, lead to the inability of verbal description and expression of emotions. A low level of stress resistance conduces to neurotization, chronic fatigue, and emotional burnout. The predominance of refractory and dysphoric reactions causes a negative vision of the situation and can provoke the development of psychosomatic disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".