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A 12‐month outcome study of insight and symptom change in first‐episode psychosis

2010· article· en· W2098146344 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEarly Intervention in Psychiatry · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsGeePsychopathologyPsychologyPsychosisGeneralized estimating equationExacerbationClinical psychologyCohortStructural equation modelingLongitudinal studyPsychiatryLatent growth modelingSchizophrenia (object-oriented programming)Depressive symptomsCohort studyMedicineAnxietyDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

AIM: We first aimed to evaluate the progression of insight and psychopathology over the first year of treatment for a psychosis. We hypothesized that improvement in insight would associate with improvement in positive and negative symptoms, and depressive and anxious symptom exacerbation. Secondly, in an exploratory analysis, we aimed to identify quantitatively distinct insight trajectory groups, and to describe the impact of psychopathology over time on the different trajectory groups. METHODS: One-hundred and sixty-five patients were administered a comprehensive clinical evaluation, and insight was rated on the Scale for Assessment for Unawareness of Mental Disorder, item 1 (awareness of mental disorder), at admission and after 1, 2, 3, 6, 9 and 12 months. RESULTS: In a generalized estimating equation (GEE) model of change, insight improved concurrently with positive, negative and anxious symptoms between baseline and month 1 in the entire cohort. Latent group-based trajectory analysis revealed five insight groups: good, increasing, decreasing, moderate poor and very poor. GEE modelling revealed that the very poor and moderate poor insight groups displayed greater overall negative symptoms than patients with good and increasing insight trajectories. The good insight group showed significantly greater overall depressive symptoms than the diminished and very poor insight groups. CONCLUSIONS: The results suggest that specific longitudinal insight trajectories were driving the observed associations between insight and negative and depressive symptoms in the entire first-episode psychosis cohort. Persistently poor insight may be an important factor in negative symptom maintenance. Good or increasing course of insight may be early clinical indicators of a liability to depression.

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.

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 score0.692
Threshold uncertainty score0.988

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)0.0010.000

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 head0.042
GPT teacher head0.321
Teacher spread0.278 · 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