Correlated factors of posttraumatic growth in patients with colorectal cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
This systematic review and meta-analysis aimed to identify and synthesize the factors correlated with posttraumatic growth (PTG) in patients with colorectal cancer (CRC). PubMed, Web of Science, Embase, PsycINFO, CINAHL, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang database, China Science and Technology Journal Database (VIP) and SinoMed were searched for studies that reported data on the correlated factors associated with PTG in patients with CRC from inception to September 3, 2024. The methodological quality of the included studies was assessed via the Agency for Healthcare Research and Quality (AHRQ) methodology checklist and the Newcastle-Ottawa Scale (NOS). Pearson correlation coefficient ( r ) was utilized to indicate effect size. Meta-analysis was conducted in R Studio. Thirty-one eligible studies encompassing 6,400 participants were included in this review. Correlated factors were identified to be significantly associated with PTG in patients with CRC including demographic factors: residential area ( r = 0.13), marital status ( r = 0.10), employment status ( r = 0.18), education level ( r = 0.19), income level ( r = 0.16); disease-related factors: time since surgery ( r = 0.17), stoma-related complications ( r = 0.14), health-promoting behavior ( r = 0.46), and sexual function ( r = 0.17); psychosocial factors: confrontation coping ( r = 0.68), avoidance coping ( r = −0.65), deliberate rumination ( r = 0.56), social support ( r = 0.47), family function ( r = 0.50), resilience ( r = 0.53), self-efficacy ( r = 0.91), self-compassion ( r = −0.32), psychosocial adjustment ( r = 0.39), gratitude ( r = 0.45), stigma ( r = −0.65), self-perceived burden ( r = −0.31), fear of cancer recurrence ( r = −0.45); and quality of life ( r = 0.32). This meta-analysis identified 23 factors associated with PTG in CRC patients. Medical workers can combine those relevant factors from the perspective of positive psychology, further explore the occurrence and development mechanism of PTG, and establish targeted interventions to promote PTG.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".