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Record W4402546900 · doi:10.1016/j.ijotn.2024.101137

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

2024· article· en· W4402546900 on OpenAlexaboutno aff
Fang Fang, Lan Chen, Qiuli Wang, Dai Wei

Bibliographic record

VenueInternational Journal of Orthopaedic and Trauma Nursing · 2024
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
FundersSchool of Medicine, Shanghai Jiao Tong UniversityShanghai General Hospital
KeywordsMedicineCross-sectional studyPain catastrophizingPain perceptionPhysical therapyPerceptionChronic painPathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.295
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Orthopaedic and Trauma NursingSame topicPediatric Pain Management TechniquesFrench-language works237,207