Psychometric properties of the German version of the multidimensional perceived social support scale

Illness uncertainty, resilience, and perceived social support among patients with moyamoya disease: a cross-sectional study

Objective

The present study aims to investigate the levels of illness uncertainty in patients with moyamoya disease and to determine the association of socio-demographic characteristics, perceived social support and resilience with illness uncertainty in patients with moyamoya disease.

Method

A cross-sectional survey using convenience sampling was conducted in two hospitals in China from August to December 2023. A socio-demographic characteristics questionnaire, the Chinese versions of Mishel’s Unsurety in Disease Scale (MUIS), the Chinese version of Connor-Davidson Resilience Scale (CD-RISC), and the Chinese version of Multidimensional Scale of Perceived Social Support (MSPSS) were used to perform this research. The collected data were analyzed using SPSS 24.0 statistical software. The t-test, one-way analysis of variance (ANOVA), pearson correlation analysis and hierarchical regression analysis were used to identify associated factors.

Result

A total of 263 patients with moyamoya disease were recruited in this survey. The score of illness uncertainty was at a moderate level of (100.03 ± 18.59). The present study identified a negative correlation between illness uncertainty with resilience perceived social support. Hierarchical regression analysis showed that gender, occupation, education level, resilience and perceived social support were the related factors of illness uncertainty.

Conclusion

Patients with moyamoya disease experienced moderate disease uncertainty on average, which was related to gender, occupation, education level, resilience and perceived social support. Future research is needed to better explore the complex relationships between illness uncertainty, resilience, and perceived social support with different types of moyamoya disease using longitudinal research.

Relationships among perceived social support, mindful self-care, and resilience among a sample of nurses in three provinces in China: a cross-sectional study

Objective

In this study, we aimed to determine the relationships among perceived social support, mindful self-care, and resilience in a sample of nurses in three provinces of China.

Methods

A cross-sectional study was conducted in seven hospitals in Guangdong, Guizhou, and Henan provinces between August and October, 2023; the provinces are located in south, southwest, and central China. A total of 389 nurses were surveyed using a self-designed sociodemographic characteristics questionnaire and the Chinese versions of Multidimensional Scale of the Perceived Social Support, Brief-Mindful Self-Care Scale and the 10-item Connor-Davidson Resilience Scale (CD-RISC-10).

Results

Of the 389 nurses, the majority were women (n = 365; 93.8%), aged 26-35 years (n = 244; 62.7%) and had bachelor's degrees (n = 337; 86.6%), had worked for 10-20 years (n = 136; 35%), with junior professional titles (n = 331; 85.1%), and had a monthly income in the range 3,001-6,000 yuan in CNY (n = 239; 61.4%). Nurses' resilience was measured using the CD-RISC-10, which ranges from 10 to 40 points. And average score of nurses' resilience was (23.94 ± 6.95). Multiple linear regression showed that scores for resilience were higher among nurses who had higher educational attainment (95% confidence interval: 0.568-3.024, p < 0.01), professional titles (95% confidence interval: 0.009-1.693, p < 0.05), scores of mindful self-care (95% confidence interval: 0.086-0.155, p < 0.01), and scores of perceived social support (95% confidence interval: 0.242-0.328, p < 0.01).

Conclusion

Nurses with higher educational attainment and professional titles exhibited higher levels of resilience. Perceived social support and mindfulness self-care are significantly positively correlated with resilience of nurses. The findings of this study are beneficial to further our understanding of nurses' resilience. The identification of associated factors is conducive to providing more support for nurses who tend to have lower resilience earlier, and can provide useful information for research targeted intervention and support plans aimed at improving nurses' resilience in the future.