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Record W2128997249 · doi:10.1348/014466506x129862

Under what circumstances do patients with schizophrenia jump to conclusions? A liberal acceptance account

2006· article· en· W2128997249 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.

Bibliographic record

VenueBritish Journal of Clinical Psychology · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsRiverview HospitalSimon Fraser University
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyTask (project management)AmbiguityJumpCognitive psychologyConvergence (economics)Contrast (vision)PsychosisPsychiatryArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: A consistent body of studies suggests that schizophrenia patients are extremely hasty when making decisions, and generally opt for the strongest response alternative. This pattern of results is primarily based on studies conducted with the beads task, which requires participants to determine from which of two possible jars a series of beads has been drawn. We have recently proposed a liberal acceptance (LA) bias to account for decision-making biases in schizophrenia, which claims that under heightened ambiguity the jump to conclusions (JTC) bias is abolished in schizophrenia. METHODS: A total of 37 schizophrenia patients were compared with 37 healthy controls on different versions of the beads paradigm. For the first task, participants were required to rate the probability that a bead was being drawn from one of two jars, and had to evaluate after each bead whether the amount of presented information would justify a decision. The second task was a classical draws to decision experiment with two jars. The third task confronted participants with four possible jars. If JTC was ubiquitous in schizophrenia hasty convergence on one alternative would be predicted for all three tasks. In contrast, the LA account predicts an abolishment of the JTC effect in the final task. RESULTS: Tasks 1 and 2 provide further evidence for the well-replicated JTC pattern in schizophrenia patients. In accordance with the LA hypothesis, no group differences were detected for task 3. DISCUSSION: The present results confirm that JTC is not ubiquitous in schizophrenia: in line with the LA account a JTC bias in schizophrenia occurred under low but not high ambiguity. LA may partly explain the emergence of fixed, false beliefs.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.001
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 head0.146
GPT teacher head0.486
Teacher spread0.339 · 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