905 resultados para Health statistics


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Privacy has become one of the main impediments for e-health in its advancement to providing better services to its consumers. Even though many security protocols are being developed to protect information from being compromised, privacy is still a major issue in healthcare where privacy protection is very important. When consumers are confident that their sensitive information is safe from being compromised, their trust in these services will be higher and would lead to better adoption of these systems. In this paper we propose a solution to the problem of patient privacy in e-health through an information accountability framework could enhance consumer trust in e-health services and would lead to the success of e-health services.

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This article presents the results of a study on the association between measured air pollutants and the respiratory health of resident women and children in Lao PDR, one of the least developed countries in Southeast Asia. The study, commissioned by the World Health Organisation, included PM10, CO and NO2 measurements made inside 181 dwellings in nine districts within two provinces in Lao PDR over a 5- month period (12/05–04/06), and respiratory health information (via questionnaires and peak expiratory flow rate (PEFR) measurements) for all residents in the same dwellings. Adjusted odds ratios were calculated separately for each health outcome using binary logistic regression. There was a strong and consistent positive association between NO2 and CO for almost all questionnaire-based health outcomes for both women and children. Women in dwellings with higher measured NO2 had more than triple of the odds of almost all of the health outcomes, and higher concentrations of NO2 and CO were significantly associated with lower PEFR. This study supports a growing literature confirming the role of indoor air pollution in the burden of respiratory disease in developing countries. The results will directly support changes in health and housing policy in Lao PDR.

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We review the literature on the combined effect of asbestos exposure and smoking on lung cancer, and explore a Bayesian approach to assess evidence of interaction. Previous approaches have focussed on separate tests for an additive or multiplicative relation. We extend these approaches by exploring the strength of evidence for either relation using approaches which allow the data to choose between both models. We then compare the different approaches.

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There are increasing numbers of refugees worldwide, with approximately 16 million refugees in 2007 and over 2.5 million refugees resettled in the United States since the start of its humanitarian program. Psychologists and other health professionals who deliver mental health services for individuals from refugee backgrounds need to have confidence that the therapeutic interventions they employ are appropriate and effective for the clients with whom they work. The current review briefly surveys refugee research, examines empirical evaluations of therapeutic interventions in resettlement contexts, and provides recommendations for best practices and future directions in resettlement countries. The resettlement interventions found to be most effective typically target culturally homogeneous client samples and demonstrate moderate to large outcome effects on aspects of traumatic stress and anxiety reduction. Further evaluations of the array of psychotherapeutic, psychosocial, pharmacological, and other therapeutic approaches, including psychoeducational and community-based interventions that facilitate personal and community growth and change, are encouraged. There is a need for increased awareness, training and funding to implement longitudinal interventions that work collaboratively with clients from refugee backgrounds through the stages of resettlement.

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This article focuses on mental health assessment of refugees in clinical, educational and administrative-legal settings in order to synthesise research and practice designed to enhance and promote further development of culturally appropriate clinical assessment services during the refugee resettlement process. It specifically surveys research published over the last 25 years into the development, reliability measurement and validity testing of assessment instruments, which have been used with children, adolescents and adults from refugee backgrounds, prior to or following their arrival in a resettlement country, to determine whether the instruments meet established crosscultural standards of conceptual, functional, linguistic, technical and normative equivalence. The findings suggest that, although attempts have been made to develop internally reliable, appropriately normed tests for use with refugees from diverse cultural and linguistic backgrounds, matters of conceptual and linguistic equivalence and test–retest reliability are often overlooked. Implications of these oversights for underreporting refugees' mental health needs are considered. Efforts should also be directed towards development of culturally comparable, valid and reliable measures of refugee children's mental health and of refugee children's and adults' psychoeducational, neuropsychological and applied memory capabilities.

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The Electrocardiogram (ECG) is an important bio-signal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. The HRV signal can be used as a base signal to observe the heart's functioning. These signals are non-linear and non-stationary in nature. So, higher order spectral (HOS) analysis, which is more suitable for non-linear systems and is robust to noise, was used. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, we have extracted seven features from the heart rate signals using HOS and fed them to a support vector machine (SVM) for classification. Our performance evaluation protocol uses 330 subjects consisting of five different kinds of cardiac disease conditions. We demonstrate a sensitivity of 90% for the classifier with a specificity of 87.93%. Our system is ready to run on larger data sets.