Financial hardship among siblings of long‐term survivors of childhood cancer: A Childhood Cancer Survivor Study report
Bibliographic record
Abstract
BACKGROUND: Siblings of children with cancer may experience adverse household economic consequences, but their financial outcomes in adulthood are unknown. METHODS: A total of 880 siblings (aged 18-64 years) of adult-aged childhood cancer survivors were surveyed to estimate the prevalence of financial hardship by three established domains (behavioral, material, and psychological). For individual financial hardship items matching the contemporaneous National Health Interview Survey or Behavioral Risk Factor Surveillance System, siblings were compared with the general population by calculating adjusted prevalence odds ratios (ORs) to sample-weighted responses. Multivariable logistic regression models examined associations between sibling characteristics and each hardship domain and between sibling hardship and survivors' cancer/treatment characteristics. RESULTS: Behavioral, material, and psychological hardship was reported by 24%, 35%, and 28%, respectively. Compared with national survey respondents, siblings were more likely to report worries about medical bills (OR, 1.14; 95% confidence interval [CI], 1.06-1.22), difficulty affording nutritious foods (OR, 1.79; 95% CI, 1.54-2.07), and forgoing needed medical care (OR, 1.38; 95% CI, 1.10-1.73), prescription medications (OR, 2.52; 95% CI, 1.99-3.20), and dental care (OR, 1.34; 95% CI, 1.15-1.57) because of cost. Sibling characteristics associated with reporting financial hardship in one or more domains included female sex, older age, chronic health conditions, lower income, not having health insurance, high out-of-pocket medical expenditures, and nonmedical/nonhome debt. No survivor cancer/treatment characteristics were associated with sibling financial hardship. CONCLUSIONS: Adult siblings of childhood cancer survivors were more likely to experience financial hardship compared with the general population. Childhood cancer may adversely affect entire households, with potentially lasting implications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".