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Record W4399321932 · doi:10.5772/intechopen.1005138

Examining the Relationship Between Childhood Traumas, Alexithymia and Emotional Regulation Difficulties in University Students

2024· book-chapter· en· W4399321932 on OpenAlexaboutno aff
Büşra Akpinar

Bibliographic record

VenueIntechOpen eBooks · 2024
Typebook-chapter
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyEmotional regulationDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.197
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.278
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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