How Do I Cope? Factors Affecting Mothers’ Abilities to Cope With Pediatric Cancer
Bibliographic record
Abstract
The overall objective of this exploratory research was to examine the lived experiences of female caregivers of children with cancer during diagnosis, treatment, and the period thereafter. Specifically, the authors examined factors that affected mothers' abilities to cope with a diagnosis of cancer. The interviews were completed with 9 mothers of children who had been treated for pediatric cancer, in addition to 3 health care workers who provided care for families with children with cancer. From this process, a number of salient issues were identified, one of which was factors that assisted or hindered mothers' abilities to cope. The subthemes of this theme consisted of: (1) support; (2) faith, positive thinking, and hope; (3) taking care of self; (4) being fearful and protective--keeping family close; and (5) living life--during and after the diagnosis. This research enabled caregivers of children with cancer to express their experiences about provision of care and factors that affected their ability to cope. Health care professionals, particularly pediatric oncology nurses and social workers, are perfectly aligned to help families reduce or manage the turmoil in families that must cope with a diagnosis of pediatric cancer.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".