A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Quality of Life Predictors and Normative Data

This study identifies predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population. A cross-sectional correlational study was undertaken with two hundred and fifty-five (N = 255) individuals from Portuguese general population (mean age 43 years, range 25–84 years; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale. Demographic information was also collected. Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44 % of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25 % of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL and can be helpful for researchers and practitioners using this assessment tool to compare their results with normative data

An Exercise Program Improves Health-Related Quality of Life of Workers

Low back problems are associated with decreased quality of life. Specific exercises can improve quality of life, resulting in better professional performance and functionality. The purpose of this study was to evaluate the effect of following a 21-month exercise program on the quality of life of warehouse workers. The population included 557 male warehouse workers from a food distribution company in Oporto, Portugal. Upon application of the selection criteria, 249 workers were deemed eligible, which were randomized into two groups (125 in the intervention group and 124 in the control group). Then, subjects were asked to volunteer for the study, the sample being formed by 229 workers (112 in the intervention group and 117 in the control group). All subjects completed the SF-36 questionnaire prior to beginning the program and on the 11th and 21st months following it. The exercises were executed in the company facilities once a day for 8 min. Data were analyzed using SPSS® 17.0 for Windows®. After 11 months of following the exercise program, there was an increase in all scores for the experimental group, with statistically significant differences in the dimensions physical functioning (0.019), bodily pain (0.010), general health (0.004), and rolephysical (0.037). The results obtained at the end of the study (21 months) showed significant improvements in the dimensions physical functioning (p = 0.002), rolephysical (p = 0.007), bodily pain (p = 0.001), social functioning (p = 0.015), role-emotional (p = 0.011), and mental health (p = 0.001). In the control group all dimensions showed a decrease in mean scores. It can be concluded that the implementation of a low back specific exercise program has changed positively the quality of life of warehouse workers.