A scoping review of psychosocial oncology interventions promoting posttraumatic growth
Bibliographic record
Abstract
Abstract Problem Identification: Many cancer patients experience posttraumatic growth (PTG), and psycho-oncologists are exploring ways to facilitate PTG through psychosocial intervention. This study utilized a scoping review protocol to provide a comprehensive evaluation of psychosocial interventions aiming to promote PTG in oncology. Literature Search: Three databases were used to identify empirical studies implementing psychosocial interventions to promote PTG in cancer patients, according to Calhoun and Tedeschi's Posttraumatic Growth Inventory. Data Evaluation: Two independent reviewers screened articles for inclusion and extracted data for qualitative synthesis. 8275 abstracts and 116 full-text articles were assessed, with 33 studies included in this review. Conclusions: Common treatment components of psychoeducation, peer support, and mindfulness skills identified by this review may be considered for future interventions targeting post-traumatic growth. The results of this review also identified areas where PTG research may be strengthened, including standardized reporting of PTG outcomes and cancer-related variables.
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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 | 0.041 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".