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Record W2384984405

Mental Health State and Alexithymia of Wenchuan Earthquake Rescue Officers and Soldiers

2010· article· en· W2384984405 on OpenAlexaboutno aff
Qiuping Tang

Bibliographic record

VenueZhongguo linchuang xinlixue zazhi · 2010
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychoticismPsychologySymptom Checklist 90Mental healthClinical psychologyPsychiatryBig Five personality traitsPersonalitySomatizationExtraversion and introversionSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Objective:To explore the mental health state and its relationship with alexithymia of officers and soldiers who involved in Wenchuan earthquake rescue.Methods:A cross-sectional study was performed in 116 rescue soldiers and 144 soldiers who didn't have rescue mission.All the 280 soldiers were tested with Symptom Checklist-90(SCL-90),Posttraumatic Stress Disorder Symptoms Self-rating Scale and the 20-item Toronto Alexithymia Scale(TAS-20).Results:①The factorial scores of psychoticism,paranoid ideation of SCL-90 of the rescue team were significantly higher than those of the non-rescue team.The positive rate of SCL-90 of the rescue team(28.45%) were significantly higher than that of the non-rescue team(15.27%).②The positive rate of PTSD between the two groups was not significantly different,the re-experience factor of the rescue team was significantly higher than that of the non-rescue team.③The multiple linear regression result of SCL-90 and PTSD of the rescue team was found that,DDF and DIF entered the regression equation of SCL-90,and DIF and age entered the regression equation of PTSD.Conclusion:There is a certain degree of psychosomatic symptoms in rescue officers and soldiers after 3 months of earthquake.Their mental health state is moderately correlated with the factors of DDF and DIF.

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: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.269
Teacher spread0.260 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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