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Record W2131951724 · doi:10.1097/nmd.0b013e31815c1a1d

Hopelessness in Schizophrenia: The Impact of Symptoms and Beliefs About Illness

2007· article· en· W2131951724 on OpenAlexaboutno aff
Ross G. White, Muriel McCleery, Andrew Gumley, Ciaran Mulholland

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2007
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsBrief Psychiatric Rating ScaleBeck Hopelessness ScaleSchizophrenia (object-oriented programming)PsychologyClinical psychologyPsychiatryRating scaleDepression (economics)Mental illnessPsychometricsScale for the Assessment of Negative SymptomsPsychosisBeck Depression InventoryMental healthDevelopmental psychologyAnxiety

Abstract

fetched live from OpenAlex

Risk factors for the development of hopelessness in schizophrenia remain poorly understood. This study investigated how psychiatric symptom levels and beliefs about illness might be linked to hopelessness in 100 patients with DSM-IV schizophrenia. Participants were assessed on the Beck Hopelessness Scale (BHS), the Calgary Depression Scale for Schizophrenia (CDSS), the Personal Beliefs about Illness Questionnaire (PBIQ), the Brief Psychiatric Rating Scale (BPRS), and the Scale for the Assessment of Negative Symptoms (SANS). Severe levels of hopelessness were found in 25% of the sample. There were significant differences between the hopeless and nonhopeless participants on the PBIQ subscales, SANS and BPRS. Differences on the PBIQ subscales remained significant when depression scores were controlled for. The total CDSS score, the "humiliating need to be marginalized" PBIQ subscale, and total BPRS score contributed significantly to a model accounting for 60% of the variance in hopelessness scores. Processes potentially implicated in the emergence of hopelessness in schizophrenia are discussed.

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)0.001
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 score0.538
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.009
GPT teacher head0.304
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.

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

Citations47
Published2007
Admission routes1
Has abstractyes

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