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Record W2145927709 · doi:10.1177/0145445507309302

The Exposure Hierarchy as a Measure of Progress and Efficacy in the Treatment of Social Anxiety Disorder

2008· article· en· W2145927709 on OpenAlexaff
Marina Katerelos, Lance L. Hawley, Martin M. Antony, Randi E. McCabe

Bibliographic record

VenueBehavior Modification · 2008
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare HamiltonToronto Metropolitan University
Fundersnot available
KeywordsPsychologyHierarchyDiscriminant validityPsychopathologyClinical psychologyConvergent validitySocial anxietyAnxietyPsychometricsMetric (unit)Developmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study explored the psychometric properties and utility of the exposure hierarchy as a measure of treatment outcome for social anxiety disorder (SAD). An exposure hierarchy was created for each of 103 individuals with a diagnosis of SAD who completed a course of cognitive behavioral group therapy. Exposure hierarchy ratings were collected on a weekly basis, and a series of self-report measures were collected before and after treatment. Results indicated that the exposure hierarchy demonstrated high test-retest reliability, as well as significant convergent validity, as participants' exposure hierarchy ratings correlated positively with scores on conceptually related measures. Hierarchy ratings were significantly associated with changes in SAD symptoms over time. However, exposure hierarchy ratings were correlated to general measures of psychopathology, suggesting limited discriminant validity. The study highlights the clinical and scientific utility of the exposure hierarchy.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.073
GPT teacher head0.373
Teacher spread0.300 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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