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Record W1975433526 · doi:10.1017/s0033291799002718

Continuous performance test differences among schizophrenic out-patients living in high and low expressed emotion environments

2000· article· en· W1975433526 on OpenAlexaff
Mike J. Dixon, Suzanne King, Émmanuel Stip, Hubert Cormier

Bibliographic record

VenuePsychological Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteUniversity of Waterloo
Fundersnot available
KeywordsPsychologyVigilance (psychology)StressorSchizophrenia (object-oriented programming)AudiologyClinical psychologyDevelopmental psychologyMedicinePsychiatryCognitive psychology

Abstract

fetched live from OpenAlex

BACKGROUND: High expressed emotion (EE) in families reliably predicts relapse in schizophrenia leading to the assumption that high EE stresses patients and is the cause of relapse. Attempts at validating the stressful properties of high EE using autonomic skin conductance measures have been inconclusive. Since memory loaded vigilance tasks are sensitive to stress, we used a memory loaded version of the Continuous Performance Test (CPT) to see if test performance would change in the presence and absence of high or low EE relatives. If high EE was stressful, performance should decline in their presence of high EE relatives. If low EE was protective against stress performance should improve in the presence of low EE relatives. METHODS: The CPT was administered to 41 schizophrenic and 51 normal control participants. CPT testing was conducted in the absence, then presence, then absence of high or low EE relatives. RESULTS: Control participants had significantly greater CPT scores than schizophrenic participants; there was no effect of the relative's presence or absence on CPT performance for either the high or low EE group. Schizophrenic participants from high EE homes demonstrated significantly better, rather than worse, CPT scores than those in low EE homes. CONCLUSIONS: These findings fail to support the notion of high EE as stressor, but show that high EE and low EE patient groups perform a vigilance task significantly differently. We propose that patients from low EE groups may be underaroused relative to their high EE counterparts and that this underarousal leads to less than optimal performance on the CPT.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.999

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)0.0020.000

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 head0.274
Teacher spread0.255 · 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.

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

Citations13
Published2000
Admission routes1
Has abstractyes

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