Alexithymia in patients with an eating disorder
Bibliographic record
Abstract
To date, eating disorders (anorexia nervosa, bulimia) have become widespread among the population. Alexithymia is considered to be one of the main features of patients with an eating disorder. In this regard, the purpose of this study was to identify and register the components of alexithymia in patients with an eating disorder, conceptually reflecting the features of this phenomenon. The research methods included: the Toronto Alexithymic Scale (TAS-20), the Lyusin Emotional Intelligence Test, the Karpov Reflexivity Questionnaire, the Giessen Questionnaire of Somatic Complaints (GBB), the Method «Identification of essential features». The methods of data processing and analysis were carried out using the IBM SPSS Statistics 26 program, which used the Spearman rank correlation coefficient and the Mann-Whitney U-criterion. As a result, it was revealed that patients with an eating disorder are characterized by a general deficiency of emotional regulation, which reflects the inability to identify, understand and describe emotions. At the same time, patients diagnosed with anorexia nervosa demonstrated a reduced ability to reflect, and were also characterized by a predominance of a specific situational style of thinking over an abstract logical one. The revealed features of the phenomenon of alexithymia in patients with an eating disorder can later be used in an integrated approach to the preparation and implementation of psychotherapeutic interventions, thereby increasing the effectiveness of therapeutic measures.
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 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 | 0.002 |
| 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) | 0.001 | 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".