Engaging in creativity so as to have a better quality of life during cancer: An experimental study
Bibliographic record
Abstract
The aim of this study is to identify the links between creativity, quality of life, and negative emotions in the context of cancer, and to identify the concept that has the greatest impact on quality of life. The study is based on a sample of thirty-five cancer patients (average age sixty-one + eleven). The assessment tools used were the Corsi block-tapping test, the Big Five Inventory, the Hospital Anxiety and Depression Scale, the Toronto Alexithymia Scale, and the World Health Organization Quality Of Life. Creativity was found to have significant links with depression, alexithymia, and quality of life (r = -.43; p < .05 and r = -.31; p < .10 and r = .54; p < .01, respectively). Moreover, creativity was the variable that had the greatest impact on quality of life (β = .32; p = .05). These results support the idea that creativity is an important factor to consider in maintaining cancer patients' quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 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".