Group Psychological Therapy: An Integral Part of Care for Cancer Patients
Bibliographic record
Abstract
Adjuvant psychological therapy can help cancer patients in 2 main ways. It has, first, a well-documented capacity to alleviate distress and thus improve quality of life. However, if this kind of assistance is to be made available to the majority of cancer patients, a number of problems need to be solved: administrators need to become aware of the evidence for efficacy of psychosocial care for cancer patients; the treatment needs to be advocated in a manner that would benefit patients rather than being left to the patient to request it; and, for reasons of economy, large, classroom-style, psychoeducational classes may need to be offered in place of small support groups. Furthermore, to allow for individual differences in preferences and abilities, a variety of modes of help should ideally be made available. The author discusses how the provision of coping strategies can be organized in a progressive way to encourage development of greater coping skills. An example of such a stepwise program is given, all aspects of which have been researched and made available in manuals over some 20 years. The possibility of prolonging life with this kind of therapy is still controversial. While randomized controlled trials have become the method of choice to investigate this question, reasons are given for strongly preferring more exploratory modes of research at the present early stage of knowledge. The central task is seen as understanding the states of mind that promote healing or longer life, something that cross-sectional, psychometric research has not been able to accomplish. As an alternative, prospective, longitudinal designs are needed, with detailed interview-style analyses of patients' mental attributes. An example is given of one such study. Furthermore, it is suggested that we consider much more intensive therapies of this kind, since the impact of mind on body will logically be related to the extent of psychological change experienced.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".