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Record W2359649357

Psychosomatic symptoms and alexithymia of the male patients with heroin dependence

2005· article· en· W2359649357 on OpenAlexaboutno aff
SU Zhong-hua

Bibliographic record

VenueZhonghua xingwei yixue yu naokexue zazhi · 2005
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScaleCravingPsychologyClinical psychologyAnxietyHeroinChecklistRating scaleHeroin dependenceDepression (economics)PsychiatrySymptom Checklist 90MedicineAddictionDrugSomatizationDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

ObjectiveTo understand the relationship between psychosomatic symptoms and alexithymia, and the contributing factors to psychosomatic symptoms in male patients with heroin dependence(MPHD). Methods218 MPHD (study group) from Hunan province were assessed employing a self-developed data-collecting form, Symptom Checklist 90 (SCL-90), Toronto Alexithymia Scale (TAS), Heroin Craving Questionnaire (HCQ), Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS), and there were 194 MPHD finished the test effectively. 107 healthy men were assessed employing SCL-90 and TAS. ResultsCompared with the control group, MPHD had significant higher total and factor scores of SCL-90 and TAS(P0.05 or P 0.01). The total score of SAS, factor of TAS, drug abuse craving, the number of previous acute toxicosis and educated years entered the regression equation of SCL-90 in turn. ConclusionMPHD had severe psychosomatic symptoms and alexithymia, and there were significant associations between them. Alexithymia may be one of core psychological characteristics for heroin dependence. The worse psychosomatic status was impacted by multiple factors.

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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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