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 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 | 0.013 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".