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Record W4394167333 · doi:10.6084/m9.figshare.20021515

Communicative behavior of individuals with a diagnosis of schizophrenia

2022· dataset· en· W4394167333 on OpenAlexaboutno aff
Ariana Elite dos Santos, Luiz Jorge Pedrão, Nelma Ellen Zamberlan-Amorim, Ana Maria Pimenta Carvalho, Alessandra Marino Bárbaro

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldPsychology
TopicStuttering Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyCognitive psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Purpose to describe the communicative behavior of individuals diagnosed with schizophrenia in psychosocial rehabilitation. Methods a descriptive and exploratory study with a convenience, cross-sectional sample. 50 individuals diagnosed with schizophrenia, of both sexes, aged between 19 and 75 years, users of a mental health unit in the interior of the state of São Paulo, Brasil participated in the study. Survey was conducted in the medical records for personal data and subtype of schizophrenia. To evaluate the communicative behavior, the instrument Montreal Battery of Evaluation of Communication (Drums MAC) was used, which is consisted of 14 tasks that assess discursive aspects: pragmatic-inferential, lexical-semantic and prosodic language. Results most participants were males, with low education, Catholics, with schizophrenia paranoid type. The assessment through Battery MAC showed changes in all tasks evaluated and most participants said they were aware of the difficulty related to communication. The biggest changes occurred in the tasks of lexical evocation with semantic criteria, indirect speech acts, conversational discourse and narrative discourse, and the smallest changes occurred in the prosodic components related to understanding, highlighting that the level of production related to linguistic and emotional aspects of prosody also showed considerable change. Conclusion all tasks evaluated presented changes. The most affected aspects were the discourse and pragmatics, which should not only be related to linguistic aspects, but also the characteristics of changes in thought and cognition, the affective blunting and social issues of this disorder.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.929
Threshold uncertainty score0.727

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9290.001

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 head0.083
GPT teacher head0.377
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations3
Published2022
Admission routes1
Has abstractyes

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