Trauma-Informed Approaches in the Context of Cancer Care in Canada and the United States: A Scoping Review
Bibliographic record
Abstract
Cancer is predominantly understood as a physical condition, but the experience of cancer is often psychologically challenging and has potential to be traumatic. Some people also experience re-traumatization during cancer because of previous, non-cancer-related trauma, such as intimate partner violence or adverse childhood experiences. A trauma-informed approach to care (TIC) has potential to enhance care and outcomes; however, literature regarding cancer-related TIC is limited. Accordingly, the objective of this scoping review was to identify what is known from existing literature about trauma-informed approaches to cancer care in Canada and the United States. A scoping review (using Arksey and O'Malley's (2005) framework) was conducted. The PsycINFO, CINAHL, MEDLINE (Ovid), Embase (Ovid), and Scopus databases, key journals, organizations, and reference lists were searched in February 2022. In total, 124 sources met the review criteria and 13 were included in the final review. Analysis included a basic descriptive summary and deductive thematic analysis using conceptual categories. Theorizations, applications, effectiveness, and feasibility of TIC were compiled, and gaps in TIC and recommendations for TIC were identified. TIC appeared to be growing in popularity and promising for improving cancer outcomes; however, gaps in the theorization, effectiveness, and feasibility of TIC persisted. Many recommendations for the application of TIC were not issued based on a strong body of evidence due to a lack of available literature. Further research is required to develop evidence-based recommendations regarding TIC related to cancer. A systematic review and meta-analysis would be warranted upon literature proliferation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".