Cross-Overs Assess Quality of GOCE Gradients

Author(s):  
Phillip Brieden ◽  
Jürgen Müller
Keyword(s):  
Author(s):  
José Andrade Louzado ◽  
Matheus Lopes Cortes ◽  
Márcio Galvão Oliveira ◽  
Vanessa Moraes Bezerra ◽  
Sóstenes Mistro ◽  
...  

Background: This study aimed to identify the factors associated with the quality of life of young workers of a Social Work of Industry Unit. Methods: This was a cross-sectional study conducted on 1270 workers. Data were collected using a digital questionnaire built on the KoBoToolbox platform that included the EUROHIS-QOL eight-item index to assess quality of life. Demographic, socioeconomic, behavioral, and clinical variables were considered explanatory. The associations were analyzed using the ordinal logistic regression model at a 5% significance level. Results: Men and women had a mean quality of life of 31.1 and 29.4, respectively. Workers that rated their health as “very good” had an odds ratio of 7.4 (95% confidence interval (CI) = 5.17–10.81), and those who rated it as “good” had an odds ratio of 2.9 (95% CI = 2.31–3.77). Both these groups of workers were more likely to have higher levels of quality of life as compared to workers with “regular”, “poor”, or “very poor” self-rated health. Physically active individuals were 30% more likely to have higher levels of quality of life (odds ratio = 1.3; 95% CI = 1.08–1.65). After adjusting the model by gender, age group, marital status, socioeconomic class, self-rated health, nutritional status, and risky alcohol consumption, the odds ratio of active individuals remained stable (odds ratio = 1.3; 95% CI = 1.05–1.66). Conclusions: In the present study, self-rated health, physical activity, and gender were associated with young workers’ quality of life.


2013 ◽  
Vol 16 (1) ◽  
pp. 117-126 ◽  
Author(s):  
Mariana Martinez Orlando ◽  
Maria Stella Peccin da Silva ◽  
Império Lombardi Junior

INTRODUCTION: Ageing has become a huge public health challenge due to the need to find solutions for improving quality of life. OBJECTIVE: This study aimed to assess quality of life, muscle strength, balance and physical capacity among elderly practitioners and non-practitioners of physical activity. MATERIALS AND METHODS: An observational, cross-sectional study was carried out involving 74 elderly individuals in the city of Santos (state of São Paulo, Brazil), divided into two groups: practitioners and non-practitioners of physical activity. The International Physical Activity Questionnaire was used for the classification of the participants. The generic SF-36 questionnaire was used to assess quality of life. The Berg scale was used for the analysis of balance. Dynamometry was used for the muscle strength test. The six-minute walk test was used for the assessment of physical capacity. RESULTS: Significant differences were found between elderly practitioners and non-practitioners of physical activity regarding quality of life (p = 0.001), muscle strength (p = 0.001), balance (p = 0.001) and physical capacity (p = 0.001). The data also showed that aspects of quality of life were strongly correlated with physical capacity among the non-practitioners of physical activity (r = 0.741). CONCLUSION: Elderly individuals in the city of Santos (Brazil) who practice physical activity have better quality of life, muscle strength, physical capacity and balance in comparison to those who do not practice physical activity.


Author(s):  
Jessica A. Tang ◽  
Taemin Oh ◽  
Justin K. Scheer ◽  
Andrew T. Parsa

The patient-generated index (PGI) is a more novel approach to evaluating health-related quality of life (HRQOL) that allows patients to formulate their own responses in an open-ended format in order to measure HRQOL based on each patient’s own stated goals and expectations. To date the use of PGI in the setting of patients diagnosed with cancer remains relatively less common compared to other health conditions. This systematic review primarily aims to identify current literature in which PGI has been used as a tool to assess quality of life in cancer patients. A systematic review using the MEDLINE database from January 1990 to July 2013 was performed with the following search terms to identify the implementation of PGI in oncology settings: (PGI OR patient generated index OR patient-generated OR patient-reported OR patient generated OR patient reported) AND (cancer OR oncology OR tumor OR neoplasm OR malignancy). Of the 2167 papers initially identified, 10 papers evaluated quality of life in oncology patients by collecting free-form responses from the patient, 4 of which actually used PGI. An overarching theme observed in these studies highlighted the concerns mentioned by patients that were not targeted or detected by standardized quality of life measures. While implementing the PGI may require slightly more investment of resources in the beginning, the potential implications of allowing patients to characterize their quality of life on their own terms are tremendous.


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