A Randomized Controlled Trial of Cognitive Behavior Therapy Tailored to Psychological Adaptation to an Implantable Cardioverter Defibrillator
Bibliographic record
Abstract
OBJECTIVES: To evaluate a eight-session cognitive behavior therapy (CBT) intervention tailored to adaptation in implantable cardioverter defibrillator (ICD) patients; and to test for treatment group by gender interaction effects. METHODS: Patients receiving their first ICD implant were randomized to CBT or usual cardiac care. Primary outcomes measured at baseline, 6-month, and 12-month follow-ups were symptoms of anxiety and depression (Hospital Anxiety and Depression Scale), posttraumatic stress disorder symptoms (Impact of Events Scale-Revised), and phobic anxiety (Crown-Crisp Experiential Index). Secondary outcomes were quality of life (Short Form-36 Physical Component Summary and Short Form-36 Mental Component Summary) and ICD shocks or antitachycardia pacing therapies. RESULTS: Of 292 eligible patients, 193 consented and were randomized to CBT (n = 96) or usual cardiac care (n = 97). Eighty percent were male; mean age was 64.4 years (standard deviation = 14.3); and 70% received an ICD for secondary prevention. No baseline differences were observed between the treatment conditions; however, women scored worse than men on all psychological and quality of life variables (p < .05). Eighty-three percent completed follow-up. Repeated-measures analyses of covariance revealed significantly greater improvement with CBT on posttraumatic stress disorder total and avoidance symptoms for men and women combined (p < .05) and significantly greater improvement in depressive symptoms and Short Form-36 Mental Component Summary only in women (p < .01). No differences were observed between treatment conditions on ICD therapies over follow-up. CONCLUSION: A CBT intervention to assist adaptation to an ICD enhanced psychological functioning over the first year post implant.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".