A relaxation technique enhances psychological well-being and immune parameters in elderly people from a nursing home: A randomized controlled study

Background: The aging process involves a decline in immune functioning that renders elderly people more vulnerable to disease. In residential programs for the aged, it is vital to diminish their risk of disease, promote their independence, and augment their psychological well-being and quality of life. Methods: We performed a randomized controlled study, evaluating the ability of a relaxation technique based on Benson’s relaxation response to enhance psychological well-being and modulate the immune parameters of elderly people living in a geriatric residence when compared to a waitlist control group. The study included a 2-week intervention period and a 3-month follow-up period. The main outcome variables were psychological well-being and quality of life, biomedical variables, immune changes from the pre-treatment to post-treatment and follow-up periods. Results: Our findings reveal significant differences between the experimental and control groups in CD19, CD71, CD97, CD134, and CD137 lymphocyte subpopulations at the end of treatment. Furthermore, there was a decrease in negative affect, psychological discomfort, and symptom perception in the treatment group, which increased participants’ quality of life scores at the three-month follow-up. Conclusions: This study represents a first approach to the application of a passive relaxation technique in residential programs for the elderly. The method appears to be effective in enhancing psychological well-being and modulating immune activity in a group of elderly people. This relaxation technique could be considered an option for achieving health benefits with a low cost for residential programs, but further studies using this technique in larger samples of older people are needed to confirm the trends observed in the present study. Trial registration: International Standard Randomised Controlled Trial Number Register ISRCTN85410212.

A qualitative exploration of the impact of the economic recession in Spain on working, living and health conditions: reflections based on immigrant workers' experiences

Background: This study aimed to analyse how immigrant workers in Spain experienced changes in their working and employment conditions brought about Spain's economic recession and the impact of these changes on their living conditions and health status. Method: We conducted a grounded theory study. Data were obtained through six focus group discussions with immigrant workers (n = 44) from Colombia, Ecuador and Morocco, and two individual interviews with key informants from Romania living in Spain, selected by theoretical sample. Results: Three categories related to the crisis emerged – previous labour experiences, employment consequences and individual consequences – that show how immigrant workers in Spain (i) understand the change in employment and working conditions conditioned by their experiences in the period prior to the crisis, and (ii) experienced the deterioration in their quality of life and health as consequences of the worsening of employment and working conditions during times of economic recession. Conclusion: The negative impact of the financial crisis on immigrant workers may increase their social vulnerability, potentially leading to the failure of their migratory project and a return to their home countries. Policy makers should take measures to minimize the negative impact of economic crisis on the occupational health of migrant workers in order to strengthen social protection and promote health and well-being.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.