The relationship of pain catastrophizing in principal caregivers of postoperative children with malignant bone tumors and children's kinesiophobia and pain perception: A cross-sectional survey
Bibliographic record
Abstract
OBJECTIVE: To examine the phenomenon of pain catastrophizing among the principal caregivers of postoperative children with malignant bone tumors and explore its impact on pain perception and kinesiophobia in children. DESIGN: A cross-sectional study design. METHODS: Using a cross-sectional study design, a questionnaire-based survey was conducted among 140 children with malignant bone tumors and their principal caregivers, who were admitted to a tertiary hospital in Shanghai from 2020 to 2023. Pearson's univariate and multiple regression analyses were conducted. The questionnaire included general data, the Parental Pain Catastrophizing Scale, the Short-Form McGill Pain Questionnaire, and the Tampa Scale of Kinesiophobia. RESULTS: = 0.249, F = 11.579, and p < 0.001. CONCLUSIONS: The level of pain catastrophizing in the principal caregivers was an important factor in postoperative kinesiophobia and pain perception in children with a malignant bone tumor. PRACTICE IMPLICATIONS: It is important to evaluate the patients' and their families' emotional changes and psychological needs during the perioperative period. Nurses play a crucial role in providing appropriate interventions for patients or families to reduce the negative pain experience and improve patients' prognosis.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".