Personality Traits and Coping Strategies Relevant to Posttraumatic Growth in Patients with Cancer and Survivors: A Systematic Literature Review
Bibliographic record
Abstract
The possibility of positive psychological changes after cancer, namely, posttraumatic growth, is a growing field of research. Identifying personality traits and coping strategies related to posttraumatic growth may help find vulnerable individuals as well as promote helpful coping strategies to help more patients make positive changes at an early stage. The aim of this systematic literature review is to provide an overview of the quantitative data on coping strategies and personality traits associated with posttraumatic growth in patients with cancer and cancer survivors as well as the methods used in included studies. A systematic literature search was conducted using five databases (PubMed, PubPsych, PsycInfo, Web of Science, and PSYNDEXplus). The 70 reports of included studies assessed posttraumatic growth using questionnaires in a sample of patients with cancer or survivors. In addition, associations with a personality trait or coping strategy had to be examined cross-sectionally or longitudinally. All 1698 articles were screened for titles and abstracts by two authors, after which disputed articles were reviewed by a third author. Afterwards, articles were screened for full texts. Most studies had a cross-sectional design and used a sample of patients with breast cancer. Coping strategies have been researched more than personality factors. The personality traits of resilience, hardiness, dispositional positive affectivity, and dispositional gratitude seem to be related to posttraumatic growth, while the Big Five personality traits (openness to experience, conscientiousness, extraversion, agreeableness, neuroticism) have been less researched and/or seem to be unrelated. The use of social support, religious coping, positive reframing, and reflection during illness as coping strategies seems to be related to posttraumatic growth. The findings can be used for the development of interventions. Future studies should investigate associations longitudinally.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".