The Impact of a Childhood Cancer Diagnosis on the Children and Siblings’ School Attendance, Performance, and Activities: A Qualitative Descriptive Study
Bibliographic record
Abstract
Families of children with cancer are confronted with unexpected out-of-pocket expenses and productivity costs associated with the diagnosis. One productivity cost that falls on children is the impact of cancer on children's school attendance, performance, and activities (eg, play, friendships, and socialization). Nested within the Childhood Cancer Cost Study, this qualitative descriptive study used convenience sampling to recruit and interview parents of children newly diagnosed with cancer. Content analysis techniques were used to inductively descriptive the semistructured interview data. Sixty-six parents of 65 children with cancer and of 73 siblings participated. The most commonly reported productivity loss in children with cancer was school absenteeism mainly due to cancer treatment. Children fell behind their classmates academically and lost important social time with peers. A few siblings also fell behind their peers primarily due to limited parental attention. Parents adopted various strategies to lessen the impact of the diagnosis on their children's school attendance, performance, and activities. Providing parents with additional resources and support may optimize their children's academic and social reintegration into school.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".