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Record W2075632693 · doi:10.1177/1534650103258977

Fearful Appraisals and Behavioral Responses of a Patient with an Implantable Cardioverter Defibrillator

2004· article· en· W2075632693 on OpenAlexaff
Steven M. Schwartz, Amy S. Janeck, Stephanie L. Deaner

Bibliographic record

VenueClinical Case Studies · 2004
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPanicLearned helplessnessImplantable cardioverter-defibrillatorPsychologyCognitionCognitive behavioral therapyDepression (economics)Clinical psychologyMedicinePsychiatryAnxietyCardiology

Abstract

fetched live from OpenAlex

The implantable cardioverter defibrillator (ICD) is an effective treatment device for potentially malignant arrhythmias, including those leading to sudden cardiac death. However, some patients develop a variety of adjustment problems to the ICD. Clinical behavioral scientists have conceptualized ICD adjustment problems using principles of classical conditioning (i.e., cardiophobia), the learned helplessness paradigm of depression, and cognitive-behavioral models of panic. This case study likens ICD adjustment problems to a cognitive-behavioral model of panic and chest pain illustrating the limits of thesemodels in terms of howType I/Type II threat appraisal by the patient serves as a significant barrier to full symptomresolution. This case study supports the need formodifications in suchmodels and related interventions as they relate to the presence of real comorbid risk factors.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.150
GPT teacher head0.490
Teacher spread0.340 · 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 designCase report
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

Citations4
Published2004
Admission routes1
Has abstractyes

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