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Is there an association between neurocognitive performance and medication adherence in first episode psychosis?

2010· article· en· W1878400105 on OpenAlexafffund
Martín Lepage, Michael Bodnar, Ridha Joober, Ashok Malla

Bibliographic record

VenueEarly Intervention in Psychiatry · 2010
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsNeurocognitivePsychosisCognitionMedication adherenceAssociation (psychology)PsychiatrySchizophrenia (object-oriented programming)PsychologyClinical psychologyMedicineInternal medicinePsychotherapist

Abstract

fetched live from OpenAlex

AIM: Medication adherence is a determining factor for symptomatic remission and relapse prevention following a first episode of psychosis (FEP). Neurocognitive abilities have received only scant attention so far as a risk factor for poor adherence but significant impairments with memory and/or planning abilities could play a role. We examined early medication adherence following admission to a specialized clinical programme for FEP. METHOD: One hundred sixty FEP participants and 35 healthy controls completed an exhaustive neurocognitive assessment. FEP participants were categorized as a function of their medication adherence at 6 months into poor (n = 34), partial (n = 27) and full (n = 99) adherence, respectively. Domain-specific and global measures of cognitive ability were examined. RESULTS: No measure of neurocognition could significantly discriminate amongst the three medication adherence groups. CONCLUSION: These results suggest no strong associations between neurocognitive abilities and medication adherence in first episode of psychosis.

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 score0.024
Threshold uncertainty score0.997

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 integrity0.0000.001
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 head0.019
GPT teacher head0.328
Teacher spread0.309 · 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

Citations22
Published2010
Admission routes2
Has abstractyes

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