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Record W2228007133

Prevalence of Psychiatric Disorders in Hepatitis B Virus Carriers in Iranian Charity for Hepatic Patients Support (December 2004-August 2005)

2008· article· en· W2228007133 on OpenAlexaff
N Ebrahimi Daryani, Mohammad Bashashati, M Karbalaeian, Mohammad Reza Keramati, Ebrahimi Daryani Narges, A A Shadman Yazdi

Bibliographic record

VenueHepatitis Monthly · 2008
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDepression (economics)PsychiatryAnxietyHepatitis B virusTransmission (telecommunications)KowsarHepatitis BInternal medicineVirusImmunology
DOInot available

Abstract

fetched live from OpenAlex

Background and Aims: More than 35% of Iranians have been exposed to hepatitis B virus (HBV) and almost 3% are chronic carriers. Knowledge of HBV-related diseases and its chronicity, and insufficient knowledge about the transmission routes are predisposing factors for occurrence of psychological disorders among these patients. Methods: Self-administered CHQ28 questionnaire was used to find the prevalence of psychiatric disorders among 100 HBV carriers. Results: We found depression in 30%, anxiety in 6%, functional impairment in 6%, and somatic abnormalities in 8% of HBV carriers. 36 patients had at least one psychiatric disorder. Conclusions: The prevalence of psychiatric disorders among HBV carriers is higher than that of community. Psychiatric consultation after screening along with continuous education of patients and their families may improve this condition. Physical, psychological, spiritual and social support to HBV carriers is therefore of paramount importance.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.285
Teacher spread0.266 · 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

Citations11
Published2008
Admission routes1
Has abstractyes

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