Exploring grandparents' psychosocial responses to childhood cancer: A qualitative study
Bibliographic record
Abstract
OBJECTIVE: A childhood cancer diagnosis is a traumatic experience for patients and their families. However, little is known about the effect on grandparents. We aimed to investigate the negative psychosocial impact, coping strategies, and positive outcomes of grandparents of childhood cancer patients in Switzerland. METHODS: We collected data using a semi-structured interview guide and applied qualitative content analysis. RESULTS: We conducted 20 interviews with 23 grandparents (57% female; mean age = 66.9 years; SD = 6.4; range = 57.0-82.4) of 13 affected children (69% female; mean age = 7.5 years; SD = 6.1; range = 1.0-18.9) between January 2022 and April 2023. The mean time since diagnosis was 1.0 years (SD = 0.5; range = 0.4-1.9). Grandparents were in shock and experienced strong feelings of fear and helplessness. They were particularly afraid of a relapse or late effects. The worst part for most was seeing their grandchild suffer. Many stated that their fear was always present which could lead to tension and sleep problems. To cope with these negative experiences, the grandparents used internal and external strategies, such as accepting the illness or talking to their spouse and friends. Some grandparents also reported positive outcomes, such as getting emotionally closer to family members and appreciating things that had previously been taken for granted. CONCLUSIONS: Grandparents suffer greatly when their grandchild is diagnosed with cancer. Encouragingly, most grandparents also reported coping strategies and positive outcomes despite the challenges. Promoting coping strategies and providing appropriate resources could reduce the psychological burden of grandparents and strengthen the whole family system.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".