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Record W2409182361 · doi:10.1017/s1121189x00001172

Primary care and the early phases of schizophrenia in the Czech Republic

2010· article· en· W2409182361 on OpenAlexaboutno aff
David Holub, Barbora Wenigová, Daniel Umbricht, Andor E. Simon

Bibliographic record

VenueEpidemiologia e Psichiatria Sociale · 2010
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersUniversität ZürichSanofi
KeywordsCzechAnxietyPsychosisMental healthPsychiatryEarly psychosisGlobal Positioning SystemSchizophrenia (object-oriented programming)Primary careMedicineFamily medicinePsychology

Abstract

fetched live from OpenAlex

SUMMARY Aim – To explore knowledge, treatment setting, attitudes and needs associated with patients in early phases of psychosis among general practitioners (GPs) in Prague, andto compare results with GPs from 6 countries participating in the International GP Study (IGPS) on Early Psychosis (Canada, Australia, New Zealand, England, Norway,Austria). Methods – Survey questionnaires were mailed to 648 GPs in the city of Prague. Results – The response rate was 19.9%. Prague GPs showed significantly lower diagnostic knowledge of early phases of psychosis compared to their international colleagues. They frequently indicated depression/anxiety and somatic complaints as early warnings of psychosis. They more often considered their behaviour to be problematic and more commonly handed them over to specialists. The majority of Prague GPs wished specialized outpatient services for low-threshold referrals of such patients. Conclusions – Along the mental health reforms in the Czech Republic which emphasis the role of primary care, GPs' knowledge of the early warning signs of psychosis needs to be improved. Declaration of Interest: The study was supported by an unrestricted grant from Sanofi-Synthélabo SA, Switzerland, to the principal investigators of the IGPS (AES, DU). The authors have stated that there are none; all authors are independent from the funding body and the views expressed in this paper have not been influenced by the funding source.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.229
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.310
Teacher spread0.286 · 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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