Leveraging Mindfulness to Build Resilience and Professional Quality of Life in Human Service Professionals

Objective: Mindfulness-based interventions (MBIs) have shown promise in cultivating resilience and are widely accepted as efficacious in the treatment of a range of psychological disorders. This paper explores the feasibility of a Mindful-Awareness and Resilience Skills Training (MARST) program to enhance mindfulness and resilience, as a means of increasing psychological well-being and alleviating burnout and compassion fatigue in human service professionals. Method: In this randomised control trial, 46 human service professionals were randomly allocated to either a MARST group or to a no intervention, control group. Results: Multivariate analysis of covariance (MANCOVA), with pre-test scores as the covariates, revealed that the MARST intervention resulted in significant improvements in mindfulness, resilience, compassion satisfaction, and psychological well-being, and significant reductions in burnout and compassion fatigue; at post-intervention. These results were maintained at one month follow-up, with the exception of compassion satisfaction which was non-significant. Mediation analysis using a bootstrap resampling method indicated that mindfulness fully mediated changes in resilience and psychological well-being, as a result of the MARST intervention. Self-reported reductions in burnout following the intervention were mediated by mindfulness and resilience, and decreased compassion fatigue was mediated by resilience. Conclusions: The results of this study suggest that the MARST program may assist in developing resilience and ameliorating burnout and compassion fatigue in human service professionals. The study also provides evidence for the potential of mindfulness-based approaches to enhance resilience.</jats:p

Examining the differences between university students' levels of resilience on mindfulness, psychological distress and coping strategies

University students can face numerous stressors which can contribute to the development of psychological distress shown to be associated with decreasing completion and retention issues throughout Australian universities (Willcoxson, Cotter, &amp; Joy, 2011). A positive predictor and outcome of successful student coping and adjustment to university and retention outcomes is resilience, the ability to cope in difficult situations and bounce back from adversity. Mindfulness has also been shown to be promote resilience. The present study examined differences in psychological distress, mindfulness, and coping strategies (adaptive vs. maladaptive) in university students (N = 122) with high and low levels of resilience. The results of a one-way MANOVA were consistent with hypotheses, revealing higher resilience scores were associated with greater mindfulness, higher adaptive coping scores, lower maladaptive coping, and reduced psychological distress. Students in the low resilience group were also found to have significantly lower levels of mindfulness, higher levels of psychological distress, reduced use of adaptive coping, and greater use of maladaptive coping, when compared to students with high resilience levels. Overall, findings of the current study are consistent with previous research and highlight the potential benefit of mindfulness-based coping interventions to foster resilience in university students

Mass and power modeling of communication satellites

Analytic estimating relationships for the mass and power requirements for major satellite subsystems are described. The model for each subsystem is keyed to the performance drivers and system requirements that influence their selection and use. Guidelines are also given for choosing among alternative technologies which accounts for other significant variables such as cost, risk, schedule, operations, heritage, and life requirements. These models are intended for application to first order systems analyses, where resources do not warrant detailed development of a communications system scenario. Given this ground rule, the models are simplified to 'smoothed' representation of reality. Therefore, the user is cautioned that cost, schedule, and risk may be significantly impacted where interpolations are sufficiently different from existing hardware as to warrant development of new devices