Decision tree analysis of mental resilience trajectory and core influencing factors in patients with traumatic fracture

Objective To investigate the trajectory of mental resilience in patients with traumatic fracture and analyze the predictive factors of different trajectory subtypes, so as to provide a reference for intervention. Methods A total of 102 patients with traumatic fractures treated at the Qingdao Hospital of University of Health and Rehabilitation Sciences from August 2020 to August 2023 were selected as the study subjects. General data questionnaires were used to collect clinical data of patients. The Social Support Rating Scale, Hospital Anxiety and Depression Scale, and Herth Hope Index were used to evaluate the degree of social support, anxiety/depression levels, and hope level of patients. Follow. ups were conducted at 1, 3, and 6 months after the survey, and the Connor.Davidson Resilience Scale was used to assess patients’mental resilience. Differences in mental resilience levels at different time points were analyzed. Latenttrajectory subgroups of potential changes were identified using latent growth mixtured models, and trajectory subtypes of core influencing factors were analyzed. Results The mental resilience scores of patients with traumatic fracture at the time of admission and 1, 3, 6 months after discharge were (49.67±8.54) points, (56.32±9.45) points, (67.45±7.23) points, and (79.36±8.41) points, respectively, showing an overall upward trend with significant differences (F=242.979,P<0.01) . Three potential change tracks of mental resilience were identified: high mental resilience symptoms.rapid increase group (29.41%) , moderate mental resilience symptoms.sustained stability group (28.43%) , low mental resilience symptoms.slow increase group (42.16%) . The decision tree model showed that gender, age, degree of social support, hope score, depression score and anxiety score could all predict the subtype of mental resilience defense trajectory, and the importance of social support was 100%. Conclusion The mental resilience of patients with traumatic fracture has a population heterogeneity, and social support is the core predictive index. Intervention programs centered on social support can be developed to assist patients with this disease, which has significant benefits for improving the mental resilience of patients.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.13429/j.cnki.cjcr.2025.05.025
Primary Topic
Resilience and Mental Health
Type
article
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article

Decision tree analysis of mental resilience trajectory and core influencing factors in patients with traumatic fracture

SHILAP Revista de lepidopterología
Resilience and Mental Health
article

Decision tree analysis of mental resilience trajectory and core influencing factors in patients with traumatic fracture

article en

Abstract

Objective To investigate the trajectory of mental resilience in patients with traumatic fracture and analyze the predictive factors of different trajectory subtypes, so as to provide a reference for intervention. Methods A total of 102 patients with traumatic fractures treated at the Qingdao Hospital of University of Health and Rehabilitation Sciences from August 2020 to August 2023 were selected as the study subjects. General data questionnaires were used to collect clinical data of patients. The Social Support Rating Scale, Hospital Anxiety and Depression Scale, and Herth Hope Index were used to evaluate the degree of social support, anxiety/depression levels, and hope level of patients. Follow. ups were conducted at 1, 3, and 6 months after the survey, and the Connor.Davidson Resilience Scale was used to assess patients’mental resilience. Differences in mental resilience levels at different time points were analyzed. Latenttrajectory subgroups of potential changes were identified using latent growth mixtured models, and trajectory subtypes of core influencing factors were analyzed. Results The mental resilience scores of patients with traumatic fracture at the time of admission and 1, 3, 6 months after discharge were (49.67±8.54) points, (56.32±9.45) points, (67.45±7.23) points, and (79.36±8.41) points, respectively, showing an overall upward trend with significant differences (F=242.979,P<0.01) . Three potential change tracks of mental resilience were identified: high mental resilience symptoms.rapid increase group (29.41%) , moderate mental resilience symptoms.sustained stability group (28.43%) , low mental resilience symptoms.slow increase group (42.16%) . The decision tree model showed that gender, age, degree of social support, hope score, depression score and anxiety score could all predict the subtype of mental resilience defense trajectory, and the importance of social support was 100%. Conclusion The mental resilience of patients with traumatic fracture has a population heterogeneity, and social support is the core predictive index. Intervention programs centered on social support can be developed to assist patients with this disease, which has significant benefits for improving the mental resilience of patients.

SHILAP Revista de lepidopterología
Qingdao University (CN), Qingdao Municipal Hospital (CN)
Gender equality
Openalex Percentile: Top 45%
Resilience and Mental Health
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