Baseline characteristics of parents enrolled in ACCL20N1CD: Financial distress during treatment for pediatric acute lymphoblastic leukemia (ALL) in the US.
Bibliographic record
Abstract
220 Background: Personal costs of childhood cancer can contribute to disparities in health outcomes. The purpose of ACCL20N1CD is to examine trajectories of parental costs and the associated financial distress, cost coping behaviors, and household material hardships (HMH) during treatment for pediatric ALL. Objective is to report baseline characteristics of the parents and their households. Methods: The study used a prospective cohort design with repeated measures. Setting was Children’s Oncology Group (COG) practices at National Cancer Institute Community Oncology Research Program (NCORP) institutions. Parents who use English or Spanish, and have children newly diagnosed with ALL treated at COG NCORP practices were eligible. Parents were asked to complete surveys at 3 time points, including baseline (T1; during induction and <7 days after planned induction remission evaluation). Surveys included items about (a) parent socio‐economic status, financial distress measured by 8-item Personal Wellness Scale (PFWS), and cost coping behaviors, and (b) HMH. Factors related to high PFWS scores were evaluated by logistic regression. Results: Of 104 evaluable parents, most were female (83.7%), white (65.4%), non-Hispanic (48.1%), partnered (79.8%), > high school diploma (93.3%), used English (84.6%), worked full (48.1%) or part (5.8%) time, and paid for their child’s care with public insurance (57.7%). Median household income=$50,000 (Inter-Quartile Range/IQR 20,000-100,000) for 4 (IQR 4-5) people. Not including wages lost due to caregiving, out of pocket payments for medical care + other ALL-related costs in the prior month >15% of monthly income for 51.9% of households, which is considered financially catastrophic. 24.0% of households lacked food stability; 21% had housing insecurity. Conclusions: At baseline, sizeable proportions of parents exhibit high out of pocket costs, high financial distress level, and multiple cost coping behaviors with implications for future health and individual and household quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".