A PSYCHOLOGICAL FACTOR AFFECTING A CARDIAC CONDITION IN A PSYCHOTHERAPIST
Bibliographic record
Abstract
It has been established that intense emotions can affect the development and course of cardiac arrhythmias. This study sought to convey that a lack of expression of emotion can also have an effect on arrhythmias. A psychotherapist with Idiopathic Ventricular Fibrillation and an Implantable Cardioverter Defibrillator measured his rate of Premature Ventricular Contractions using a Holter monitor during three separate six-week periods and in three domains: A) work days vs. off days, B) a 27 hour work week vs. 22 hour work week, and C) in 5 different modalities including 1) Meeting with department head 2) Individual psychotherapy with patients 3) Group therapy with patients 4) Supervision of residents 5) Personal psychoanalysis. The results showed more than a 3-fold increase of arrhythmogenic activity during the 27-hour work week vs. 22 and a 5-fold increase in arrhythmogenic activity on work days compared to days off. Department Head meetings were found to be most arrhythmogenic and personal psychoanalysis was least. The data suggest that the psychiatrist’s lack of emotional expression in his clinical work has been demonstrated to markedly worsen his arrhythmia. The results also point to the potential ameliorating effects of the therapist’s own psychotherapy.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".