Cognitive hypnotherapy for psychological management of depression in palliative care
Bibliographic record
Abstract
The prevalence of psychiatric disorders in palliative care is well documented, yet they often remain undetected and untreated, adding further to the burden of suffering on patients who are already facing severe physical and psychosocial problems. This article will focus on depression as it represents one of the most common psychiatric disorders treated by psychiatrists and psychotherapists in palliative care. Although depression in palliative care can be treated successfully with antidepressant medication and psychotherapy, a significant number of depressives do not respond to either medication or existing psychotherapies. This is not surprising considering depression is a complex disorder. Moreover, the presentation of depression in palliative care is compounded by the severity of the underlying medical conditions. It is thus important for clinicians to continue to develop more effective treatments for depression in palliative care. This article describes cognitive hypnotherapy (CH), an evidence-based multimodal treatment for depression which can be applied to a wide range of depressed patients in palliative care. CH, however, does not represent a finished product; it is a work in progress to be empirically validated and refined by advances in cancer and clinical depression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".