ALEXITHYMIA AS RISK FACTOR OF THE DEVELOPMENT OF ADDICTIVE BEHAVIOR OF YOUNG PEOPLE IN THE REPUBLIC OF BELARUS
Bibliographic record
Abstract
A socio-psychological survey and clinical-psychological research were conducted (level of alexithymia; intensity of internet addiction; individual-characterological personality traits; individual style of coping strategies, behavioral patterns and resources of personality) in the cohort of 150 people at the age of 15-24, average age: 18.9±1.64, M:F= 87:63). As a result of the randomization of subjects, 3 groups were detected: themain group (people with traces of developing anaddiction from “new psychoactive substances” (NPS)) (MG, 50 people); a comparison group (people with “non-chemical” forms of addiction (internet addiction) (CG, 50 people) and a reference group (50 people, without addictions and deviant behavior). The research of coping behavior methods, in the category “Search for social support” groups MG and RG significantly differ statistically (probability of passing similarity p = 0.016, t =2.45, df = 147) has shown the significance of asocial network support as in the case of NPS addiction. The total score of the Toronto Alexithymia Scale-26-R showed that people from MG (average number 67.66±8.01) and RG (average number 58.92±8.36) statistically differ significantly, with a probability of passing similarity being p<0.001, t=5.3, df=147. Indicators of expressed alexithymia noticeably prevailed in MG and CG, in comparison with the RG. While researching internet addiction using a subject oriented scale, there was a statistically significant difference between CG and RG. The probability of a passing similarity is p = 0.006, t=2.82, df =147. The received and analyzed study materials are the basis for the development of acombined preventive and rehabilitation program for those with “NPS” addiction and “internet addiction” among teenagers and youth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".