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Record W1966296206 · doi:10.1017/s1352465800003027

CATASTROPHIZING ASSESSMENT OF WORRY AND THREAT SCHEMATA AMONG WORRIERS

2000· article· en· W1966296206 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBehavioural and Cognitive Psychotherapy · 2000
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsConcordia UniversityInstitut universitaire en santé mentale de MontréalUniversité Laval
FundersMedical Research Council CanadaJohns Hopkins University
KeywordsWorryPsychologyAnxietyCognitive psychologyDevelopmental psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Several authors have suggested that threat schemata of high worriers may differ from those of less worried individuals with regards to the manner with which information is structured in the Long Term Memory (LTM) or the content of the information stored in the LTM. The present study tested this hypothesis using the catastrophizing interview technique (c.f., Vasey & Borkovec, 1992). Results revealed that high worriers evaluated the likelihood of the occurrence of feared consequences generated for each worry as more likely to actually happen than low worriers did. Second, the ultimate outcome generated in the catastrophizing sequence for a given worry was more severe for high worriers. Finally, high worriers generated ultimate outcomes that were more similar in content, presumably reflecting tightly organized threat schemata. It is argued that activation of these threat schemata in the LTM contributes to the maintenance of worry and anxiety in anxious individuals.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.354
Teacher spread0.318 · 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