Trajectory of parental hope when a child has difficult‐to‐treat cancer: a prospective qualitative study
Bibliographic record
Abstract
OBJECTIVE: This prospective and longitudinal study was designed to further our understanding of parental hope when a child is being treated for a malignancy resistant to treatment over three time points during the first year after diagnosis using a qualitative approach to inquiry. METHODS: We prospectively recruited parents of pediatric cancer patients with a poor prognosis who were treated in the Hematology/Oncology Program at a large children's hospital for this longitudinal grounded theory study. Parents were interviewed at three time points: within 3 months of the initial diagnosis, at 6 months, and at 9 months. Data collection and analysis took place concurrently using line-by-line coding. Constant comparison was used to examine relationships within and across codes and categories. RESULTS: Two overarching categories defining hope as a positive inner source were found across time, but their frequency varied depending on how well the child was doing and disease progression: future-oriented hope and present-oriented hope. Under future-oriented hope, we identified the following: hope for a cure and treatment success, hope for the child's future, hope for a miracle, and hope for more quality time with child. Under present-oriented hope, we identified hope for day-to-day/moment-to-moment, hope for no pain and suffering, and hope for no complications. CONCLUSIONS: For parents of children with a diagnosis of cancer with a poor prognosis, hope is an internal resource that can be present and future focused. These views fluctuated over time in response to changes in the child's well-being and disease progression.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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 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".