Determining the Costs of Families’ Support Networks Following a Child’s Cancer Diagnosis
Bibliographic record
Abstract
BACKGROUND: Cancer in children may place considerable economic burden on more than individual family members. The costs incurred to families' support networks (FSNs) have not been previously studied. OBJECTIVES: The study objectives were to (a) identify and determine independent predictors of the direct and time costs incurred by the FSN and (b) explore the impact of these cancer-related costs on the FSN. METHODS: A prospective mixed-methods study was conducted. Representing the FSN, parents recorded the resources consumed and costs incurred during 1 week per month for 3 consecutive months, beginning 1 month following their child's diagnosis. Descriptive statistics, multiple regression modeling, and descriptive qualitative analytical methods were used to analyze the data. RESULTS: In total, 28 fathers and 71 mothers participated. The median total direct and time costs for the 3 months were CAN$154 and $2776, respectively, per FSN. The largest component of direct and time costs was travel and foregone leisure. Direct and time costs were greatest among those parents who identified a support network at baseline. Parents relied on their FSN to "hold the fort," which entailed providing financial support, assuming household chores, maintaining the siblings' routines, and providing cancer-related care. CONCLUSIONS: Families' support networks are confronted with a wide range of direct and time costs, the largest being travel and foregone leisure. IMPLICATIONS FOR PRACTICE: Families' support networks play an important role in mitigating the effects of families' costs. Careful screening of families without an FSN is needed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".