Emotional Distress Among Pediatric Cancer Patients and their Siblings
Bibliographic record
Abstract
Objectives: Cancer being a serious chronic illness, causes profound effects on physical and mental health of the individual as well as affects their caregivers and family members' mental health. This study aims to find out the burden of emotional distress in patients of childhood cancer as well as their healthy siblings. Methods: It was a descriptive cross-sectional study. Parents of the children undergoing cancer treatment or having completed treatment within past one year were asked to complete an interview proforma (Pediatric Emotional Distress Scale) about their child’s behaviour over past one month, scoring each behaviour on a scale of 1 to 5 according to the frequency of symptoms. The data was then analysed using SPSS 20. The frequency distribution, central tendencies and standard deviations were calculated accordingly. Results: Almost eighty-five% of the patients showed scores above the clinical threshold for emotional distress. Eighteen% of the healthy siblings also had scores above the clinical threshold. Patients as well as their healthy siblings showed high levels of anxiousness in their behaviours. Conclusions Childhood cancer is a cause of major emotional trauma in patients. Age-matched siblings usually cope well with the illness.
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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 | 0.000 |
| 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) | 0.002 | 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".