Comparing Two Brief Psychological Interventions to Usual Care in Panic Disorder Patients Presenting to the Emergency Department with Chest Pain
Bibliographic record
Abstract
BACKGROUND: Panic disorder (PD) is a common, often unrecognized condition among patients presenting with chest pain to the emergency departments (ED). Nevertheless, psychological treatment is rarely initiated. We are unaware of studies that evaluated the efficacy of brief cognitive-behavioural therapy (CBT) for this population. AIM: Evaluate the efficacy of two brief CBT interventions in PD patients presenting to the ED with chest pain. METHOD: Fifty-eight PD patients were assigned to either a 1-session CBT-based panic management intervention (PMI) (n = 24), a 7-session CBT intervention (n = 19), or a usual-care control condition (n = 15). A structured diagnostic interview and self-reported questionnaires were administered at pre-test, post-test, 3- and 6-month follow-ups. RESULTS: Statistical analysis showed significant reduction in PD severity following both interventions compared to usual care control condition, but with neither showing superiority compared to the other. CONCLUSIONS: CBT-based interventions as brief as a single session initiated within 2 weeks after an ED visit for chest pain appear to be effective for PD. Given the high prevalence of PD in emergency care settings, greater efforts should be made to implement these interventions in the ED and/or primary care setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".