Compassion fatigue (CF) is stress resulting from exposure to a traumatized individual. CF has been described as the convergence of secondary traumatic stress (STS) and cumulative burnout (BO), a state of physical and mental exhaustion caused by a depleted ability to cope with one’s everyday environment. Professionals regularly exposed to the traumatic experiences of the people they service, such as healthcare, emergency and community service workers, are particularly susceptible to developing CF. This can impact standards of patient care, relationships with colleagues, or lead to more serious mental health conditions such as posttraumatic stress disorder (PTSD), anxiety or depression. A systematic review of the effectiveness of interventions to reduce CF in healthcare, emergency and community service workers was conducted. Thirteen relevant studies were identified, the majority of which were conducted on nurses (n = 10). Three included studies focused on community service workers (social workers, disability sector workers), while no studies targeting emergency service workers were identified. Seven studies reported a significant difference post-intervention in BO (n = 4) or STS (n = 3). This review revealed that evidence of the effectiveness of CF interventions in at-risk health and social care professions is relatively recent. Therefore, we recommend more research to determine how best to protect vulnerable workers at work to prevent not only CF, but also the health and economic consequences related to the ensuing, and more disabling, physical and mental health outcomes.

Objectives The aim of the study was to investigate whether different types of health promotion intervention in the workplace reduce depression and anxiety symptoms. Methods A systematic review and meta-analysis of the literature was undertaken on workplace health promotion published during the period 1997–2007. Studies were considered eligible for inclusion if they evaluated the impact of an intervention using a valid indicator or specific measure of depression or anxiety symptoms. The standardized mean difference was calculated for each of the following three types of outcome measures: depression, anxiety, and composite mental health. Results Altogether 22 studies were found that met the inclusion criteria, with a total sample size of 3409 employees postintervention, and 17 of these studies were included in the meta-analysis, representing 20 intervention–control comparisons. The pooled results indicated small, but positive overall effects of the interventions with respect to symptoms of depression [SMD 0.28, 95% confidence interval (95% CI) 0.12–0.44] and anxiety (SMD 0.29, 95% CI 0.06–0.51), but no effect on composite mental health measures (SMD 0.05, 95% CI -0.03–0.13). The interventions that included a direct focus on mental health had a comparable effect on depression and anxiety symptoms, as did the interventions with an indirect focus on risk factors. Conclusions When the aim is to reduce symptoms of depression and anxiety in employee populations, a broad range of health promotion interventions appear to be effective, although the effect is small.

Owner/managers of small-to-medium enterprises (SMEs) are an under-researched population in terms of psychological distress and the associated health and economic consequences. Using baseline data from the evaluation of the Business in Mind program, a mental health promotion intervention amongst SME owner/managers, this study investigated: (i) prevalence of high/very high psychological distress, past-month sickness absenteeism and presenteeism days in SME owner/managers; (ii) associated, self-reported lost productivity; and (iii) associations between work, non-work and business-specific factors and work attendance behaviours. In our sample of 217 SME owner/managers 36.8% reported high/very high psychological distress. Of this group 38.7% reported past-month absenteeism, 82.5% reported past-month presenteeism, and those reporting presenteeism were 50% less productive as than usual. Negative binomial regression was used to demonstrate the independent effects of socio-demographic, work-related wellbeing and health-related factors, as well as various individual and business characteristics on continuous measures of absenteeism and presenteeism days. Health-related factors (self-rated health and treatment) were the strongest correlates of higher presenteeism days (p < 0.05). Work-related wellbeing factors (job tension and job satisfaction) were the strongest correlates of higher absenteeism days (p < 0.05). Higher educational attainment, treatment and neuroticism were also correlated with more absenteeism days. SME-specific information about the occurrence of psychological distress, work attendance behaviour, and the variables that influence these decisions, are needed for the development of guidelines for managing psychological distress within this sector.

Background: Historically, the focus of Non Communicable Disease (NCD) prevention and control has been cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), cancer and chronic respiratory diseases. Collectively, these account for more deaths than any other NCDs. Despite recent calls to include the common mental disorders (CMDs) of depression and anxiety under the NCD umbrella, prevention and control of these CMDs remain largely separate and independent. Discussion: In order to address this gap, we apply a framework recently proposed by the Centers for Disease Control with three overarching objectives: (1) to obtain better scientific information through surveillance, epidemiology, and prevention research; (2) to disseminate this information to appropriate audiences through communication and education; and (3) to translate this information into action through programs, policies, and systems. We conclude that a shared framework of this type is warranted, but also identify opportunities within each objective to advance this agenda and consider the potential benefits of this approach that may exist beyond the health care system.

Lifestyle factors are important in the development of chronic diseases, such as heart disease, respiratory disease, and diabetes, and chronic disease risk can be reduced by changes in lifestyle behaviors linked to these conditions. The use of mass media and community-wide strategies targeting these behaviors has been extensively evaluated since the 1970s. This review summarizes some examples of interventions and their use of media conducted within the old communications landscape of the 1970s and 1980s and the key lessons learned from their design, implementation, and evaluation. We then consider the potential and evidence base for using contemporary technology applications and platforms—within the new communications landscape—to improve the prevention and management of lifestyle-related chronic diseases in the future. We discuss the implications and adaptation of lessons derived from the ways in which new technologies are being used in commercial and political contexts and their relevance for public health. Finally, we consider some recent examples of applying new technologies to public health issues and consider some of the challenges in this rapidly developing field.

No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population. Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods. The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: −0.18, SE: −0.01, p < 0.001), MM3+ (β: −0.23, SE: −0.02, p < 0.001), cluster-1 (β: −0.10, SE: 0.01, p < 0.001) and cluster-2 (β: −0.36, SE: 0.01, p < 0.001). Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.