The experiences of mothers who have a child diagnosed with cancer
Bibliographic record
Abstract
Objective: This qualitative study explored the experiences of mothers who had a child diagnosed with cancer.Design and Outcome Measure: Informed by Interpretative Phenomenological Analysis, semi-structured interviews were completed with 13 participants, transcribed verbatim with individual and cross-case analysis conducted.Results: One superordinate theme, Protecting My Child, Whatever the Cost, was identified with five related subordinate themes. Participants battled to protect the development of their ill child. They richly described the personal costs and losses experienced, including putting their life on hold, and lost time with their healthy children. Participants faced realities of cancer treatment that were incongruent with their goal of protecting their child. Self-care awareness was significant for well-being as they protected themselves from reminders of their child’s mortality. Despite living in a crisis, participants reported changes suggestive of posttraumatic growth.Conclusion: Childhood cancer brings profound psychosocial and biographical disruption to the lives of mothers as they lose socially valued roles and have their identity as competent mothers challenged. Mothers protect their child, often at a cost to their health and well-being but also bringing positive consequences. The findings offer insights for psychologists in supporting mothers to reclaim their identity as competent mothers and renegotiate their mothering expectations.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".