4 resultados para SATISFACTION INDEX-A
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
This descriptive study addresses the job satisfaction of nurse managers and clinical nurses working at the Hematology and Hemotherapy Services of a public hospital in Sao Paulo. The study objectives were to identify the factors that caused job satisfaction among nurse managers and clinical nurses, and support the results in the development of indicators to evaluate the quality of nursing human resource management. The components of the study were: autonomy, interaction, professional status, job requirements, organizational norms and remuneration. Participants were 44 nurses. Data were collected using a Job Satisfaction Index (JSI) questionnaire. In conclusion, this study permitted the identification of the clinical nurse group, which was the most satisfied, with a JSI of 10.5; the managerial group scored 10.0. Regarding the satisfaction levels in regards to the current activity, 88.9% of the nurse managers reported feeling satisfied, as did 90.9% of clinical nurses. For both groups, autonomy was the component with the highest level of professional satisfaction.
Resumo:
Shift workers from control centers of electrical systems are a group that has received little attention in Brazil. This study aimed to compare workers' job satisfaction at five control centers of a Brazilian company electrical system, and according to their job titles. Method: The Organization Satisfaction Index (OSI) questionnaire to assess job satisfaction was used. ANOVA was used to compare OSI means, according to job title and control center. The results showed that there is no difference in job satisfaction among job titles, but a significant difference was found according to the control center. A single organizational culture cannot be applied to several branches. It is required to implement actions that would result in job satisfaction improvements among workers of all studied control rooms centers. The high level of education of operators working in all centers might have contributed to the similar values of perceived satisfaction among distinct job titles.
Resumo:
The study analyzed the correlations among the different factors of subjective well-being (SWB) using a sample of 106 married people with an average of 16.11 years of marriage. The following instruments were used: Sociodemographic Questionnaire, Socioeconomic Questionnaire, and Subjective Well-being Scale (SWBS). Data analyses were conducted using the Software R and a multivariate model to understand the correlations among the factors of the SWBS. All factors of the SWBS were significantly inter-correlated, which confirm the results of the scale validation study. Future studies are necessary to evaluate the SWB in couples (dyads), which can help to understand whether this concept is influenced by the spouse or only by the marital status.
Resumo:
Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.