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Record W2044386237 · doi:10.1002/da.20031

Gender differences in anxiety-related traits in patients with panic disorder

2004· article· en· W2044386237 on OpenAlexaff
Meredith Foot, Diana Koszycki

Bibliographic record

VenueDepression and Anxiety · 2004
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
Fundersnot available
KeywordsPanic disorderAnxietyPanicPsychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study examined gender differences in anxiety-related personality traits in patients with panic disorder with or without agoraphobia (PD+/-AG). Outpatients (101 total) with SCID confirmed PD+/-AG completed the Anxiety Sensitivity Index (ASI), the Trait form of the State-Trait Anxiety Inventory (STAI-T), the NEO Personality Inventory Revised (NEO PI-R), and the Retrospective Self-Report of Inhibition (RSRI) as part of their assessment. Significant gender differences were not detected for the total ASI scores. Females scored significantly higher than males on the Physical Concerns subscale of the ASI, whereas males scored significantly higher than women on the Social Concerns subscale. Women scored higher than men on the Extraversion scale of the NEO PI-R as well as on certain subscales of this domain. Although a significant gender difference was not detected on the Neuroticism subscale, men scored higher on the angry hostility and depression facets of this trait. Significant gender differences were not found for the STAI-T or the RSRI. These findings suggest that gender differences exist among patients with PD+/-AG in the feared consequences of anxiety symptoms as well as in the personality characteristics of extraversion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), 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

Citations55
Published2004
Admission routes1
Has abstractyes

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