Well-being in patients with breast cancer and healthy women: The role of expected and actual support for personal projects
Bibliographic record
Abstract
Abstract Background For breast cancer patients, the partner’s support for personal projects can serve as a means of adaptation. We aimed to investigate the associations between the intimate partner’s personal project support and women’s well-being. Methods A sample of 274 Hungarian women (breast cancer patients n = 137, control = 137) took part in the study. Expected and actually received autonomy-, and directive- and emotional project support was assessed by the procedure of Personal Project Assessment. Well-being was measured by the Relationship Assessment Scale and the Rosenberg Self-Esteem Scale. For investigating the associations between project support and well-being in a multivariate way, structural equation modelling was used. Results Except for autonomy support, participants expected more support than they received. A path model indicated multiple associations between types of project support and relationship satisfaction and self-esteem. The partner’s emotional project support was predictive of women’s relationship satisfaction and self-esteem, while directive support was predictive of self-esteem. The associations showed similar patterns in the subgroups of patients with breast cancer and control. Conclusions Our results highlight the importance of involving women’s subjective perspectives regarding the partner’s project support and have important practical implications for rehabilitation interventions.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".