Enhancing health outcomes in cancer patients: exploring self-forgiveness and the mediating role of spiritual growth through the transcendental self-healing model – a longitudinal study
Bibliographic record
Abstract
This study explores the role of self-forgiveness and spiritual growth in enhancing health outcomes among cancer patients through a three-wave longitudinal mediation model. Conducted within a Christian demographic in Western Canada, the research involved 212 participants undergoing treatment at oncological rehabilitation centres. Utilising validated scales, the study measured self-forgiveness, spiritual growth, and health outcomes, with data collected at three-month intervals. The findings reveal that spiritual growth significantly mediates the relationship between self-forgiveness and improved mental and physical health. The study highlights the therapeutic potential of integrating spiritual and emotional dimensions into healthcare practices, suggesting that self-forgiveness and spiritual development can play critical roles in patient care and well-being. This research contributes to the literature on psycho-oncology and offers insights into the mechanisms through which spirituality and self-forgiveness impact health outcomes in chronic illness contexts.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".