Novel ageing-biomarker discovery using data-intensive technologies

Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for biomarker discovery; (1) microarray analyses and/or proteomics in cell systems e.g. endothelial progenitor cells or T cell ageing including a stress model; and (2) investigation of cellular material and plasma directly from tightly-defined proband subsets of different ages using proteomic, transcriptomic and miR array. The first approach provided longitudinal insight into endothelial progenitor and T cell ageing.This review describes the strategy and use of hypothesis-free, data-intensive approaches to explore cellular proteins, miR, mRNA and plasma proteins as healthy ageing biomarkers, using ageing models and directly within samples from adults of different ages. It considers the challenges associated with integrating multiple models and pilot studies as rational biomarkers for a large cohort study. From this approach, a number of high-throughput methods were developed to evaluate novel, putative biomarkers of ageing in the MARK-AGE cohort.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

Stress, burnout and coping strategies in the emergency and intensive care hospital departments

Doctors and nurses working at the accident and emergency (A&E), and intensive care departments are at risk of burnout. They often spend substantial time in intense interactions with other people, centered on patients? health problems (physical, psychological and social) that may lead to feelings of anger, anxiety and frustration, and eventually to burnout. Burnout is a syndrome of emotional exhaustion, depersonalization and reduced personal accomplishment (Maslach & Jackson, 1981) The purpose of this chapter is to assess work stressors, burnout and stress-coping mechanisms among doctors and nurses at the A&E and intensive care departments. A quantitative design using the survey approach was used to collect data from a sample of 200 participants with a response rate of 71% (n=154) Work stressors were associated with burnout in both doctors and nurses. Workload was the most salient work stressor in the sample. Nurses experienced more stress (M=1.5, SD=0.4) than doctors (M=1.2, SD=0.4) in all the work stressor variables examined. The A&E department was reported as more stressful than the intensive care department. Avoidance-oriented and task-oriented coping were the most and the least frequently reported coping strategies respectively. Additionally, only emotion-oriented coping strategy was significantly different between doctors and nurses, and this strategy was also significantly positively correlated with all the variables in the adapted nursing stress scale, and the three burnout variables. Death and dying was most strongly correlated with emotion-oriented coping. This chapter provides an assessment of stress, burnout and coping experienced by both doctors and nurses within the A&E and intensive care departments. Methods that may mitigate stress in these environments may be adequate staffing, supportive management, stress management programs, as well as improvement in communication strategies between doctors and nurses.