Symptom experiences in the illness trajectory of children with cancer and their families
Bibliographic record
Abstract
Many childhood malignancies once regarded as fatal have become curable with the initiation of multimodal therapy. However, such therapy is not without its costs. Aggressive treatment is associated with many adverse consequences for both children with cancer and their families. Uncontrolled symptoms can have a negative impact on families, leading to increased suffering and impaired quality of life. Knowledge about how the childhood cancer-symptom course is experienced by childr n and their families is required to improve symptom management. Guided by the philosophy of interpretive interactionism, an interpretive research design framed within the qualitative paradigm as undertaken to explore and describe the childhood cancer-symptom course experienced by children and their families. Such an approach was required to interpret and understand the personal meanings and responses that the children and families constructed around living day-to-day with symptoms throughout the childhood cancer trajectory. Tenets from the following two philosophical approaches of interpretive work shaped the research process: the grounded theory research method and illness narratives. Data analysis led to the development of two substantive theories. The first theory, Keeping the Spirit Alive: The Spirit Within, describes a developing model that depicts the children's and families' overall experience with cancer. From the telling of their stories, the first model, Keeping the Spirit Alive, evolved. In this model, the core category of "getting through all the rough spots" was identified as the basic psychosocial phenomenon or problem experienced by children and their families. The second core category of the model, "keeping the spirit alive," emerged as the basic psychosocial process. The "keeping the spirit alive" process referred to the children's and families' ability to not let all the roughness of the cancer-symptom trajectory get the better of them. The second theory, Children's and Families' Lived Experience of Childhood Cancer-Symptoms, depicts the lived experience of cancer in relation to the changing personal meanings that children and families assigned to the cancer-symptom experiences. Two core categories form the foundation of the second substantive theory: (1) Personal meanings of the cancer-symptom experiences; and (2) Passage through the transition periods. (Abstract shortened by UMI.)
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".