The Impact of the Early COVID-19 Global Pandemic on Children Undergoing Active Cancer Treatment and Their Parents
Bibliographic record
Abstract
(1) Background: The COVID-19 global pandemic has impacted people worldwide with unique implications for vulnerable groups. In this cross-sectional study, we examined the impact of the early pandemic on children undergoing active cancer treatment and their parents. (2) Methods: In May 2020, 30 parents of children undergoing active cancer treatment completed an online survey regarding the impact of COVID-19 on their child's cancer care, perceived utility of telemedicine, and child and parent mental health status. (3) Results: Most participants (87%) reported that they did not experience any changes to major cancer treatments. Among those who reported using telemedicine, 78% reported this to be beneficial. Over half of the participants reported that their child's mental health status was worse now than prior to the COVID-19 global pandemic. Parent-reported child anxiety scores were significantly higher for those who reported changes to mental health care for their child compared to those who did not report the same, t(25.99) = −3.04, p = 0.005. (4) Conclusion: Child and parent mental health status were affected when compared to pre-pandemic. Telemedicine appears to be a promising complement to face-to-face meetings for some families and warrants further exploration.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".