Comparison of Early Maladaptive Schemas and Defense Styles in Asthmatic, Alexithymic and Normal Subjects
Bibliographic record
Abstract
Objective: The aim of the present article was to study the relationship between early maladaptive schemas and the defense styles (mature, immature, and neurotic) in asthmatics, alexithymics and normal subjects. Methods: 216 asthmatic, alexithymic and normal subjects were selected and they completed Young Schema Questionnaire (short form), Defense Style Questionnaire and the Farsi version of the Toronto Alexithymia Scale. Descriptive and inferential statistics such as mean, standard deviation, MANOVA and multiple regressions analysis were used to analyze the research data. Results: Results indicated a significant difference (P<0.05) in all domains of early maladaptive schemas, except other-directedness between the mean scores of the groups of normal subjects and asthmatic patients as well as alexithymic patients. In mature and neurotic defense style, there was not a significant difference between the mean scores of the three groups, while the immature defense style scores of normal subjects and patients with asthma were significantly different (P<0.05) from those of alexithymic. Conclusion: Alexithymia is equivalent to difficulty in self-regulation. When emotional information could not be perceived and evaluated through cognitive processing, it results in the individual's emotional and cognitive confusion. This inability increases the possibility of the immature and neurotic defense styles in stressful situations. A B S T R A C T
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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 | 0.002 |
| 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".