Narcissistic rage: The Achilles’ heel of the patient with chronic physical illness
Bibliographic record
Abstract
Thomas Hyphantis1, Augustina Almyroudi1, Vassiliki Paika1, Panagiota Goulia1, Konstantinos Arvanitakis2,31Department of Psychiatry, Medical School, University of Ioannina, Ioannina, Greece; 2Canadian Institute of Psychoanalysis, Mcgill University, Montreal, Canada; 3Departments of Philosophy and Psychiatry, Mcgill University Health Centre, Montreal, CanadaAbstract: Based on the psychoanalytic reading of Homer’s Iliad whose principal theme is “Achilles’ rage” (the semi-mortal hero invulnerable in all of his body except for his heel, hence “Achilles’ heel” has come to mean a person’s principal weakness), we aimed to assess whether “narcissistic rage” has an impact on several psychosocial variables in patients with severe physical illness across time. In 878 patients with cancer, rheumatological diseases, multiple sclerosis, inflammatory bowel disease, and glaucoma, we assessed psychological distress (SCL-90 and GHQ-28), quality of life (WHOQOL-BREF), interpersonal difficulties (IIP-40), hostility (HDHQ), and defense styles (DSQ). Narcissistic rage comprised DSQ “omnipotence” and HDHQ “extraverted hostility”. Hierarchical multiple regressions analyses were performed. We showed that, in patients with disease duration less than one year, narcissistic rage had a minor impact on psychosocial variables studied, indicating that the rage was rather part of a “normal” mourning process. On the contrary, in patients with longer disease duration, increased rates of narcissistic rage had a great impact on all outcome variables, and the opposite was true for patients with low rates of narcissistic rage, indicating that narcissistic rage constitutes actually an “Achilles’ Heel” for patients with long-term physical illness. These findings may have important clinical implications.Keywords: consultation-liaison psychiatry, psychosomatics, narcissism, physical illness, quality of life, psychological distress, personality
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".