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Posttraumatic growth in children aged 8–18 years with malignancies in China
OBJECTIVE: To establish a nomogram prediction model for posttraumatic growth (PTG) in children aged 8–18 years with malignancies in China and to convenient intuitively judge psychological tendencies. METHODS: We recruited 358 children aged 8–18 years with malignancies in China as the study participa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798681/ https://www.ncbi.nlm.nih.gov/pubmed/36581859 http://dx.doi.org/10.1186/s12887-022-03799-w |
Sumario: | OBJECTIVE: To establish a nomogram prediction model for posttraumatic growth (PTG) in children aged 8–18 years with malignancies in China and to convenient intuitively judge psychological tendencies. METHODS: We recruited 358 children aged 8–18 years with malignancies in China as the study participants. Data from 250 cases collected from June 2019 to November 2019 were used as the model group, data from 108 cases collected from December 2019 to January 2020 were used as the validation group. Logistic regression was used to analyze the influencing factors of PTG in the model group. A prediction model was then established using a nomogram. The centrality measurement index(C-index) and receiver operating characteristic curves (ROC) were used to verify the model. RESULTS: Among the 250 children in the model group, 65 children with malignancies had PTG, with an occurrence of 26%. The model showed that the child’s age, diagnosis, coping style and self-efficacy level and the educational level of the caregiver were core predictors of PTG (P < 0.05). The ROC of the model was 0.837, the best cutoff value was 0.566. The C-indexes of the internal and external validation were 0.837 (95% CI: 0786 ~ 0.886) and 0.813 (95% CI: 0732 ~ 0.894), respectively. CONCLUSIONS: The prediction model of PTG in children aged 8–18 years with malignancies in China has good discrimination and consistency and can accurately predict PTG. It can be used to clinically assess the psychological status of children in the future. |
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