Coping during COVID-19: a mixed methods study of older cancer survivors
Bibliographic record
Abstract
PURPOSE: Older cancer survivors are among the most vulnerable to the negative effects of COVID-19 and may need specific survivorship supports that are unavailable/restricted during the pandemic. The objective of this study was to explore how older adults (≥ 60 years) who were recently (≤ 12 months) discharged from the care of their cancer team were coping during the pandemic. METHODS: We used a convergent mixed method design (QUAL+quan). Quantitative data were collected using the Brief-COPE questionnaire. Qualitative data were collected using telephone interviews to explore experiences and strategies for coping with cancer-related concerns. RESULTS: The mean sample age (n = 30) was 72.1 years (SD 5.8, range 63-83) of whom 57% identified as female. Participants' Brief-COPE responses indicated that they commonly used acceptance (n = 29, 96.7%), self-distraction (n = 28, 93.3%), and taking action (n = 28, 93.3%) coping strategies. Through our descriptive thematic analysis, we identified three themes: (1) drawing on lived experiences, (2) redeploying coping strategies, and (3) complications of cancer survivorship in a pandemic. Participants' coping strategies were rooted in experiences with cancer, other illnesses, life, and work. Using these strategies during the pandemic was not new-they were redeployed and repurposed-although using them during the pandemic was sometimes complicated. These data were converged to maximize interpretation of the findings. CONCLUSIONS: Study findings may inform the development or enhancement of cancer and non-cancer resources to support coping, particularly using remote delivery methods within and beyond the pandemic. Clinicians can engage a strengths-based approach to support older cancer survivors as they draw from their experiences, which contain a repository of potential coping skills.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".