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Record W4414072609 · doi:10.1002/brb3.70825

Effect of Childhood Trauma on Emotional Distress: A Chain‐Mediated Effects of Alexithymia and Psychological Flexibility

2025· article· en· W4414072609 on OpenAlexaboutno aff
Ning Wang, Guo Chen, Ziyue Wang, Wenjuan Wang

Bibliographic record

VenueBrain and Behavior · 2025
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaMediationFlexibility (engineering)Psychological traumaPsychological abuseChildhood abusePsychological resilience

Abstract

fetched live from OpenAlex

OBJECTIVE: The study aims to explore how emotional distress is affected by childhood trauma through pathways involving alexithymia and psychological flexibility, and to construct a complete model established on this foundation, which will be provided as a theoretical theory for interventions in college students' mental health. METHODS: Note that 1002 college students were assessed using Childhood Trauma Questionnaire (CTQ), The Depression Anxiety Stress Scale (DASS-21), the 20-item Toronto alexithymia scale (TAS-20), and Acceptance and Action Questionnaire-2nd Edition (AAQ-II). After removing some non-compliant questionnaires, the remaining 885 were used for data analysis. RESULTS: Scores on childhood trauma, alexithymia, and psychological flexibility exhibited notable correlation with depression, anxiety, and stress; childhood trauma had chain mediation effects on depression, anxiety, and stress through alexithymia and psychological flexibility. CONCLUSION: Among college students, childhood trauma is positively associated with depression, anxiety, and stress, and impacts the relationship between them through the single mediation and chain mediation of alexithymia and psychological flexibility.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.013
GPT teacher head0.320
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2025
Admission routes1
Has abstractyes

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