Bibliographic record
Abstract
Introduction:The level of gratitude may explain the increase in psychological well-being.Some studies demonstrated also the mediating effect of social support for the relationship of gratitude to well-being.The aim of the research was to present the role of the sense of social support and gratitude for the quality of life of patients.It was hypothesized that social support mediates the relationship between gratitude and the quality of life in the group of oncological patients with a moderating effect of gender.Material and methods: The participants comprised 96 Polish cancer patients, with breast or prostate cancer, hospitalized during 5-7 weeks of radiotherapy, and aged 31-79 years.A gratitude questionnaire, the social support scale by Kmiecik-Baran, and the sense of quality of life questionnaire by Straś-Romanowska et al. were used [1].Results: Social support has not proven to be a mediator of the relationship of gratitude to any dimension of quality of life.However, gender turned out to be a moderator in terms of the relationship between gratitude and instrumental support for the global, psychosocial, and subjective quality of life, but only in women.Conclusions: Gender also turned out to be a moderator of the instrumental support relationship with the global, psychosocial, and subjective sphere of quality of life, and this relationship was found only in men.There was also moderation in the emotional support relationship with psychosocial quality of life in the group of men.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.007 |
| 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".