PERSPECTIVAS E DESAFIOS DA PSICOLOGIA POSITIVA NOS CUIDADOS PALIATIVOS: Uma revisão sistemática
Bibliographic record
Abstract
This article presents a reflection on the main psychological interventions of Positive Psychology in palliative care, an approach that expands and innovates the need to nourish what is best in oneself, and thus improve the quality of life, valuing people's peculiar aspects, based on their own strengths and virtues, in the search prevention of pathologies. For the systematic review, the bibliographic databases PubMed, BVS, LILACS and SciELO were searched, limited to scientific production from the year 2014 to 2024, without language restrictions, from May 1st to May 5th, 2024. The descriptors used were [“positive psychology” AND “palliative care”], we chose not to include specific descriptors such as: intervention or techniques. The research presents a reduced volume of scientific studies, a sample of seven selected articles from six countries: Switzerland, the United States of America, Canada, Italy, Portugal and Spain. From the proposed reflection, it was possible to observe that the knowledge of palliative care therapy and positive psychology interventions are consistent with a sense of meaning and purpose, with emerging challenges, the lack of theorization and the absence of scientific debates on the topic.
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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 | 0.053 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".