Cancer symptom transition periods of children and families
Bibliographic record
Abstract
BACKGROUND: Children with cancer are reported to experience many symptoms during the cancer trajectory. However, minimal qualitative research has been conducted that explores children's and families' experiences of symptoms. An understanding of the symptom trajectory, grounded in children's and families' experiences, is essential to providing comprehensive and sensitive care to children with cancer and their families. AIM: This paper reports a study designed to explore and describe the symptom course in childhood cancer as experienced by children and their families. DESIGN: Guided by the philosophy of interpretive interactionism, a longitudinal qualitative study was undertaken. A purposive sample of 39 families of children with cancer who resided in Western Canada participated. The children ranged in age from 4.5 to 18 years and varied in their cancer diagnoses. METHODS: Multiple data collection methods included formal and informal interviewing and participant observation. Data were analysed by the constant comparative method. Development of illness narratives added to an understanding of children's and families' experiences. FINDINGS: A substantive theory entitled 'Children's and Families' Lived Experience of Childhood Cancer Symptoms' emerged from the findings. This depicts the experience of cancer in relation to children's changing symptom trajectory. A core category of the theory, 'passage through the transition periods', shows how changing symptom experiences affected children's and families' ways of being in the world. These were reflected in six transition periods: (1) it is just the flu; (2) it is more than the flu; (3) it hits home; (4) it is nasty; (5) it is not so bad, it is pretty good; and (6) it is 'dragsville'. The changing roles and responsibilities of family members, and how the family existed in the cancer world, varied depending on the transition period through which they were passing. CONCLUSIONS: Transition periods not only reinforce the dynamic nature of the experience of childhood cancer but, more importantly, show how symptoms can greatly affect the quality of children's and families' day-to-day living. Interpreting cancer in the context of the symptom trajectory provides nurses with a new perspective for understanding childhood cancer, and will assist in the development of symptom relief strategies that will help to contain symptoms and improve overall quality of life for children and families.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".