The Relationship Between Alexithymia and Positive Beliefs to Rumination and Psychological Resilience
Bibliographic record
Abstract
The aim of this study is to examine the relationships between alexithymia, positive beliefs towards rumination and psychological decisiveness in alexithymic individuals. In addition to determining the relationships between the variables, the mediating role of alexithymia in the relationship between positive beliefs about rumination and resilience was evaluated. The research was carried out on university students. Alexithymic individuals were identified by a two-stage process. First of all, students were asked to evaluate the measurement tools based on the convenient sampling method without any discrimination. Then, the data obtained were analyzed and 144 university students were determined as alexithymic in line with the cut-off score determined. The Toronto Alexithymia Scale, Psychological Resilience Scale and Positive Rumination Scale were used as data collection tools. Research findings show that there is a positive and significant relationship between positive beliefs about alexithymia and rumination in alexithymic individuals. However, a significant negative correlation was determined between resilience and alexithymia. According to the mediation analysis findings, the mediating role of alexithymia in the relationship between positive belief in rumination and resilience is significant. As a result, a model to explain resilience was tested in line with the mediation theory and the interaction between two variables that could explain resilience was found. In particular, it is evaluated that research findings may be functional in the therapy phase in clinical studies to be conducted on psychological resilience.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 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".