Examining the Relationship Between Childhood Traumas, Alexithymia and Emotional Regulation Difficulties in University Students
Bibliographic record
Abstract
The aim of this study is to examine the relationship between childhood traumas, alexithymia, and difficulty in emotion regulation among university students. A relational screening approach was used in the research. A relational screening model was used in the research. The study sample group consists of 351 university students. 83.5% of the participants were women (n = 293) and 16.5% were men (n = 63). Informed Voluntary Consent Form, Sociodemographic Information Form, Childhood Trauma Scale, Toronto Alexithymia Scale and Emotion Regulation Scale Short Form were administered to the participants. Data collection was carried out online (Google Forms) through convenient sampling, examining the relationship and effect between nonparametric tests and sociodemographic characteristics, childhood traumas, alexithymia and emotion regulation difficulties by looking at normality curves in data analysis. As a result of the research findings, a significant and positive relationship was found between childhood traumas, alexithymia and emotion regulation difficulties of university students. In addition, it was determined that male individuals are more alexithymia than females, females are exposed to sexual abuse more than males, the 24–25 age group has more emotional dysregulation, and the rates of emotional dysregulation and alexithymia are low in the presence of a romantic relationship. It is thought that this study can contribute to the relevant literature.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".