Farzaneh Fouladi, Masoumeh Fouladi,
Volume 20, Issue 4 (12-2021)
Abstract
Background: Covid-19 pandemic peak put additional strains on healthcare system. In this crisis, the resilience of nursing staff is critical. This study aimed to investigate the relationship between burnout and resilience in frontline nursing staff working in high-risk areas during the outbreak of Covid-19 pandemic.
Materials and Methods: The present study is a Descriptive-analytical survey, and the target group is Iranian nurses. According to the Ministry of Health statistics, 125369 people are participated in this study. information is collected from 384 people by cluster distribution using questionnaire. The statistical analysis in this study is performed by SPSS and SMART-PLS software
Results: According to the study, all the collected information is normal. Based on factor analysis, there is an inverse significant relationship between resilience and burnout, and also, the sense of success has a significant effect on resilience as part of burnout.
Conclusion: In order to increase the resilience of nursing staff in such conditions, it is necessary to pay more attention to the factors affecting their burnout and plan to minimize it. Developing educational programs and adding diversity in service delivery might be useful to enhance personal feelings and also reduce burnout.
Omid Mazlumi, Mehraban Parsamehr, Akbar Zare-Shahabadi,
Volume 22, Issue 1 (5-2023)
Abstract
Background: Cancer is often stigmatized in many societies and this has unfortunate consequences for sufferers. The aim of this research was to know the factors related to the social stigma of cancer.
Materials and Methods: The research method was correlation-analytical, and the sampling method was multi-stage cluster. Data were collected using CSI and CAM standard questionnaires.The statistical population included three categories of ordinary citizens, medical staff, and companions of patients in Tehran; Using Cochran's formula, the sample size was 384, 201, 384 people, respectively. In order to fit the model and measure the relationships between the variables, the method of structural equation modeling was used in the form of AMOS software.
Findings: Goodness of fit indices (chi-square/df=2.851, Rmsea=0.08, Cfi=0.945) all indicated the appropriate fit of the model. Except for the variable of inequality in treatment, other independent variables had a significant relationship with stigma. The r2 explanatory coefficient showed that the variables of habitus, optimism, cancer awareness, religiosity, social support, and social capital together predicted 48% of stigma changes. Habitus and social support with standard coefficients (beta) of 0.48 and -0.28 had the highest and lowest contribution in explaining stigma, respectively. Based on the mean difference test, the amount of stigma among ordinary people was more than the other two groups.
Conclusion: Awareness of different aspects of cancer disease (such as symptoms, causative factors), removing false stereotypes about cancer (such as cancer means death), constant communication with cancer patients, and receiving the necessary social support from various sources, were the most important tools necessary to reduce the stigma of cancer.
