The impact of shift-work and organizational climate on health outcomes in nurses

Shift workers have a higher rate of negative health outcomes than day shift workers. Few studies however, have examined the role of difference in workplace environment between shifts itself on such health measures. This study investigated variation in organizational climate across different types of shift work and health outcomes in nurses. Participants (n = 142) were nursing staff from a metropolitan Melbourne hospital. Demographic items elicited the type of shift worked, while the Work Environment Scale and the General Health Questionnaire measured organizational climate and health respectively. Analysis supported the hypotheses that different organizational climates occurred across different shifts, and that different organizational climate factors predicted poor health outcomes. Shift work alone was not found to predict health outcomes. Specifically, permanent night shift workers had significantly lower coworker cohesion scores compared with rotating day and evening shift workers and significantly higher managerial control scores compared with day shift workers. Further, coworker cohesion and involvement were found to be significant predictors of somatic problems. These findings suggest that differences in organizational climate between shifts accounts for the variation in health outcomes associated with shift work. Therefore, increased workplace cohesion and involvement, and decreased work pressure, may mitigate the negative health outcomes of shift workers.

Understanding and influencing physical activity to improve health outcomes

Participation in physical activity is associated with significant benefits to health. We provide an overview of research relevant to understanding and influencing health-enhancing physical activity in adults. We describe a behavioural epidemiology framework that is designed to integrate the range of studies in the field; give brief examples of studies on the relationships between physical activity and health outcomes; and, we consider descriptive studies of adult populations on levels of participation. We describe research findings on the correlates of physical activity participation; describe ecological models of health behaviour that may be used in understanding and influencing physical activity; and, we review research findings on how environmental attributes can influence adults’ physical activity, particularly walking. There is considerable potential to use evidence-based approaches to increase the physical activity levels of whole populations, particularly through a focus on developing the attributes of community environments that can promote walking.

Predictors of the attitudinal and health outcomes of aged care nurses

This study examines the predictive capacity of the Demand-Control-Support (DCS) model in combination with organizational justice variables on attitudinal- and health-related outcomes for aged care nurses. Multiple regression analyses of aged care nurses (n=168) from a medium to large Australian healthcare organization. The DCS model explains the largest amount of variance across both the attitudinal and health outcomes with 27% of job satisfaction and 44% of organizational commitment, and 33% of psychological distress and 35% of wellbeing, respectively. Additional variance was explained by the justice variables for job satisfaction, organizational commitment and psychological distress. The addition of the organizational justice variables to the DCS model proved to be a valuable step in understanding the work conditions of aged care nurses. The inclusion of curvilinear effects clarified the potentially artefactual nature of certain interaction variables. The results provide practical implications for managers of aged care nurses in developing and maintaining levels of job control, support and fairness, as well as monitoring levels of job demands. The results particularly highlight the importance of the nurses’ supervisor.

Non-standard work schedules and health outcomes in Australia : some evidence from the HILDA Panel

What does the around-the-clock economic activity mean for workers' health? Despite the fact that non-standard work accounts for an increasing share of the job opportunities, relatively little is known about the potential consequences for health and the existing evidence is ambiguous. In this paper I examine the associations between non-standard job schedules and workers' physical and mental health outcomes using longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA). Specifically, the four health indicators considered are self-rated health and the SF-36 health indices for general health, mental health and physical functioning. Overall results generally suggest a negative relationship between non-standard work schedules and better health for both males and females. Regarding the statistical significance and magnitudes of the associations, however, we observe apparent differences between males and females. Among females, most of the coefficients in all models are statistically insignificant, which implies very small magnitudes in terms of the correlation between non-standard working hours and health. These results apply uniformly to all health measures investigated. Among males, on the other hand, the negative relationship is more noticeable for self-rated health, general health and physical functioning than for mental health. The pooled OLS and random effects coefficients are usually larger in magnitude and more significant than the fixed effects parameters. Nonetheless, even the more significant coefficients do not imply large effects in absolute terms.

The quality and outcomes framework reduces disparities in health outcomes for cardiovascular disease

Jamie Robinson, the Berkeley health economist, famously remarked in 2001 that ‘the three worst ways to pay doctors are salary, capitation and fee-for-service.’ Different financial incentives produce different clinical and service outcomes, sometimes perversely.1 In 2004, the UK government introduced pay for performance (P4P) for general practitioners, the Quality and Outcomes Framework (QOF). Its introduction was associated with the general trend in the National Health Service away from placing implicit trust in doctors and more active monitoring of their performance. One-quarter of GP pay can be earned from achieving scores on 147 indicators.2 These indicators were acceptable to doctors because the majority are evidence-based clinical outcome measures for 10 chronic diseases. Others relate to patient access and satisfaction, and practice organisation.

Obstacles in the optimization of bone health outcomes in the female athlete triad

Maintaining low body weight for the sake of performance and aesthetic purposes is a common feature among young girls and women who exercise on a regular basis, including elite, college and high-school athletes, members of fitness centres, and recreational exercisers. High energy expenditure without adequate compensation in energy intake leads to an energy deficiency, which may ultimately affect reproductive function and bone health. The combination of low energy availability, menstrual disturbances and low bone mineral density is referred to as the ‘female athlete triad’. Not all athletes seek medical assistance in response to the absence of menstruation for 3 or more months as some believe that long-term amenorrhoea is not harmful. Indeed, many women may not seek medical attention until they sustain a stress fracture.
This review investigates current issues, controversies and strategies in the clinical management of bone health concerns related to the female athlete triad. Current recommendations focus on either increasing energy intake or decreasing energy expenditure, as this approach remains the most efficient strategy to prevent further bone health complications. However, convincing the athlete to increase energy availability can be extremely challenging.
Oral contraceptive therapy seems to be a common strategy chosen by many physicians to address bone health issues in young women with amenorrhoea, although there is little evidence that this strategy improves bone mineral density in this population. Assessment of bone health itself is difficult due to the limitations of dual-energy X-ray absorptiometry (DXA) to estimate bone strength. Understanding how bone strength is affected by low energy availability, weight gain and resumption of menses requires further investigations using 3-dimensional bone imaging techniques in order to improve the clinical management of the female athlete triad.

Health outcomes associated with hormone therapy in Australian women

The risks and benefits of hormone therapy (HT) in the treatment of postmenopausal women remain controversial. In this population-based, observational study, we documented health outcomes among postmenopausal Australian women using HT. Women aged 60-80 years were recruited into the Geelong Osteoporosis Study 1994-7 and followed over a median period of 6.6 years. Mortality, and the development of vascular events, breast and colorectal cancers were documented for 67 HT-users and 521 non-users. Median duration of HT-use was 5.0 years (IQR 3.0-10.0). There was no excess in all-cause mortality associated with HT-use. Based on 92 deaths (six HT-users, 86 non-users), the adjusted odds ratio (OR) for all-cause mortality was 0.79 (95%CI 0.32-1.97). With 99 reports of vascular events (13 HTusers, 86 non-users), the adjusted OR for vascular events was 1.30 (95%CI 0.66-2.57). There were insufficient numbers of breast or colorectal cancer cases (21 breast cancer cases, all non-HT users; and 7 colorectal cancer cases, one HT-user and six non-users) to adequately calculate the risk associated with exposure to HT. Although the sample size was small, these results do not support an association between HT and mortality, despite a possible link between HT and increased risk of developing vascular disease.

Training patterns and negative health outcomes in triathlon : longitudinal observations across a full competitive season

AIM: Despite heavy training requirements, triathlon is a sport that is rapidly increasing in popularity. Yet, there is limited research detailing the relationship between training, the incidence of injuries and illness, psychological stress, overtraining and athlete burnout amongst triathletes. Six hypotheses relating inter-individual differences to training factors were generated to evaluate change in self-reported measures of these negative health outcomes over a training year.

METHODS: Thirty, well-trained, triathletes (males n=20: age=27.1±9.1 years and females n=10: age=27.4±6.6 years) from a local triathlon club participated in this study. The study commenced during pre-season training, and involved weekly monitoring of each athlete until the end of the competitive season 45 weeks later. Linear Mixed Modelling was used for the analysis.

RESULTS: Signs and symptoms of injury and illness (SAS) were significantly associated with increases in training factors (P≤0.05); however, greatest impact on SAS was produced by psychological stressors (P≤0.001). Common symptoms of overtraining were significantly affected by increases in exposure to both training and psychological stressors (P≤0.05). Mood disturbance was not significantly affected by training factors (P>0.05) but rather increases in psychological stressors (P≤0.001). Finally, each of the three athlete burnout subscales were significantly affected by both psychological (P≤0.001) stressors as well as varying combinations of training factors (P≤0.05).

CONCLUSIONS: Exposure to stressors (either training or psychological) had significant effects on all negative health outcomes assessed.

Complexity of management and health outcomes in a prospective cohort study of 573 heart failure patients in Australia : does more equal less?

Aims and objectives : To compare the efficacy of chronic heart failure management programmes (CHF-MPs) according to a scoring algorithm used to quantify the level of applied interventions–the Heart Failure Intervention Score (HF-IS).

Background : The overall efficacy of heart failure programmes has been proven in several meta-analyses. However, the debate continues as to which components are essential in a heart failure programme to improve patient outcomes.

Design : Prospective cohort study of patients participating in heart failure programmes.

Method : Forty-eight of 62 (77%) programmes in Australia participating in a national register of CHF-MPs were evaluated using the HF-IS: derived from a summed and weighted score of each intervention applied by the CHF-MP (27 interventions overall). The CHF-MPs were prospectively categorised as relatively low (HF-IS < 190 – n = 39 programmes & 407 patients) or high (HF-IS ≥ 190 – n = 9 programmes & 166 patients) in complexity. Six-month morbidity and mortality rates in 573 consecutively recruited patients with systolic dysfunction and in New York Heart Association Class II–IV were prospectively examined.

Results : Patients exposed to CHF-MPs with a high HF-IS had a lower rate of unplanned, all-cause hospitalisation (n = 24, 14% vs. n = 102, 25%) compared with CHF-MPs with a low HF-IS within six months. On an adjusted basis, CHF-MPs with a high HF-IS were associated with a reduced risk of unplanned hospitalisation and/or death within six months and remained event-free longer.

Conclusion : High complexity CHF-MPs applying more evidence-based interventions are associated with a higher event-free survival over six months.

Relevance to clinical practice : The HF-IS is an easy-to-use evidence-based tool to assist programme coordinators to improve the quality of their heart failure programme which may also improve patient outcomes.

Statistical approaches to testing the relationships of the built environment with resident-level physical activity behavior and health outcomes in cross-sectional studies with cluster sampling

To achieve valid conclusions, studies exploring associations of the built environment with residents' physical activity and health-related outcomes need to employ statistical approaches accounting for clustered data. This article discusses the following main statistical approaches: analysis of covariance, regression models with robust standard errors, generalized estimating equations, and multilevel generalized linear models. The choice of a statistical method depends on the characteristics of the study and research questions. While the first three approaches are employed to account for clustering in the data, multilevel models can also help unravel more substantive issues within a social ecological theoretical framework of health behavior.