Psychocorrective care for palliative cancer patients in a hospital setting
Bibliographic record
Abstract
Currently, special attention is being paid to improving the efficiency and quality of medical care for palliative cancer patients. However, the problems faced by patients and their loved ones affect not only the physical health of these patients, but also their emotional sphere. In this regard, the aim of the study was to compare the meaningful and dynamic characteristics of the emotional state of palliative cancer patients receiving and not receiving psychocorrective care. The subject of the study is the possibility of correcting the emotional state in palliative cancer patients through the use of visualization, relaxation, and art therapy methods. Experimental sample of the study: 33 patients of oncological palliative profile aged 38 to 65 years. In the course of the study, the authors studied the psychological characteristics of these patients. Special attention is paid to the development and implementation of a program aimed at providing psychocorrective support for palliative patients diagnosed with oncology in a hospital setting, in particular, to reduce anxiety levels and harmonize emotional state. Empirical methods: (Testing methods, group clinical conversation with patients, conducting a group psychological program. Research methods: The test "Index of life satisfaction" and its adaptation by N.V. Panina. The test "Toronto scale of alexithymia" TAS adaptation V.M.Bekhterev Institute. The personal scale of anxiety manifestation by J. Taylor, adaptation by T. A. Nemchinov. The presented work examines the possibilities of providing psychocorrective support to palliative patients diagnosed with oncology. The study revealed the peculiarities of the psyche, developed mechanisms for providing appropriate psychocorrective care, psychological interaction with the above category of people. A psychocorrection program has been developed and implemented aimed at reducing the level of anxiety, harmonizing the emotional state, working on the phenomenon of death and acceptance of the phenomenon of dying, working on anxiety, working on the search and activation of resource states. Testing of the program on an experimental group of palliative patients showed positive results. It was possible to reduce the level of anxiety and alexithymia. To achieve positive dynamics in life satisfaction indicators. The obtained research results will contribute to the creation of an empirical and practical basis for psychocorrective support for palliative patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".