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Agreement Between Self-Rated and Clinically Assessed Symptoms in Subjects With Psychosis

2004· article· en· W1997000327 on OpenAlexaboutno aff
F. Liraud, Tiphaine Droulout, Marie Parrot, Hélène Verdoux

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2004
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDelusionScale for the Assessment of Negative SymptomsPsychosisDepressive symptomsClinical psychologyDepression (economics)Schizophrenia (object-oriented programming)Negative symptomPsychiatryPsychologyPositive and Negative Syndrome ScaleGlobal Assessment of FunctioningMedicineAnxiety

Abstract

fetched live from OpenAlex

The aim of this study was to explore the capacity of acutely ill patients with psychosis (N = 40) to self-report their symptoms by comparing self-assessment and objective measures. Positive, negative, and depressive symptoms were rated using the Scale for the Assessment of Positive Symptoms, the Scale for the Assessment of Negative Symptoms, and the Calgary Depression Scale. Insight level was measured using the Scale to Assess Unawareness of Mental Disorder. Patients were asked to self-report positive, negative, and depressive symptoms using the Community Assessment of Psychic Experience. Patients presenting with acute psychotic disorders are able to assess fairly their positive, negative, and depressive symptoms. Significant associations were found between self-reported and objective measures of positive, negative, and depressive symptoms independently of insight level. Individual positive and negative symptoms were correctly self-assessed, except for persecutory delusion and alogia, respectively. These results suggest that self-report questionnaires can be used in educational programs to favor the patient's therapeutic adherence.

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 score0.022
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.313
Teacher spread0.296 · 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

Citations68
Published2004
Admission routes1
Has abstractyes

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