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Record W2377955476

Relationship among alexithymia,coping styles and the depression among undergraduates

2011· article· en· W2377955476 on OpenAlexaboutno aff
Shichang Yang

Bibliographic record

VenueChinese Journal of School Health · 2011
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaCoping (psychology)PsychologyTraitClinical psychologyToronto Alexithymia Scale
DOInot available

Abstract

fetched live from OpenAlex

ObjectiveTo explore the relationship of the alexithymia,coping styles and depression among undergraduates.MethodsA total of 733 undergraduates were surveyed by Toronto Alexithymia Scale(TAS),Trait Coping Style Questionnaire(TCSQ) and Center for Epidemiological Studies Depression Scale(CES-D).ResultsNo statistically significant difference by genders was found in the scores of depression of undergraduates.The scores of depression of undergraduates from rural area was significantly higher than those from urban area(P0.05).The undergraduates self-reported poor economic condition got significantly higher scores of depression than those self-reported good economic condition.A 38% variance of depression could be explained by alexithymia and coping styles after controlling the demographic variables.Alexithymia and coping styles had direct effects on depression,furthermore,alexithymia had indirect effects on depression through coping styles,and the proportions of indirect effects were respectively 19.7% and 27.9% of the total through positive and negative coping styles.ConclusionAlexithymia and coping styles might have direct effects on depression,moreover,coping styles can mediate the relationships between alexithymia and depression as a mediated variable.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.041
GPT teacher head0.316
Teacher spread0.275 · 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
Published2011
Admission routes1
Has abstractyes

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