A Model to Predict Psychological- and Health-Related Adjustment in Men with Prostate Cancer: The Role of Post Traumatic Growth, Physical Post Traumatic Growth, Resilience and Mindfulness
Bibliographic record
Abstract
Background: Post traumatic growth (PTG) can be defined as positive change following a traumatic event. The current conceptualisation of PTG encompasses five main dimensions, however, there is no dimension which accounts for the distinct effect of a physical trauma on PTG. The purpose of the present research was to test the role of post traumatic growth, physical post traumatic growth, resilience and mindfulness in predicting psychological and health related adjustment. Method: Ethical approval was obtained from relevant institutional ethics committees. Participants (n=241), who were at least one year post prostate cancer treatment, were invited to complete a battery of questionnaires either through an online survey or a paper and pencil package received in the post The sample ranged in age from 44 to 88 years (M = 64.02, SD = 7.76). Data was analysed using confirmatory factor analyses and structural equation modelling. Results: The P-PTGI was used to evaluate the role of physical post traumatic growth in predicting adjustment using structural equation modelling (SEM). Physical post traumatic growth predicted lower distress and improvement of quality of life, whereas conversely, the traditional post traumatic growth measure was linked with poor adjustment. The relationship between resilience and adjustment was found to be mediated by physical post traumatic growth. Conclusion: Findings suggest the central role of PTG in the prostate cancer survivorship experience is enhanced by the inclusion of physical PTG. Adjusting to a physical trauma such as illness (internal transgressor) is unlike a trauma with an external transgressor as the physical trauma creates an entirely different framework for adjustment. The current study demonstrates the impact of physical PTG on adjustment. This significantly adds to the theory of the development of PTG by highlighting the interplay of resilience with PTG, physical PTG and adjustment.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".