Impact of Prison Status on HIV-Related Risk Behaviors

Baseline data were collected to evaluate the effectiveness of interventions on completion of the hepatitis A and B vaccine series among 664 sheltered and street-based homeless adults who were: (a) homeless; (b) recently (<1 year) discharged from prison; (c) discharged 1 year or more; and (d) never incarcerated. Group differences at baseline were assessed for socio–demographic characteristics, drug and alcohol use, sexual activity, mental health and public assistance. More than one-third of homeless persons (38%) reported prison time and 16% of the sample had been recently discharged from prison. Almost half of persons who were discharged from prison at least 1 year ago reported daily use of drugs and alcohol over the past 6 months compared to about 1 in 5 among those who were recently released from prison. As risk for HCV and HIV co-infection continues among homeless ex-offenders, HIV/HCV prevention efforts are needed for this population

Time orientation and health-related behaviour: measurement in general population samples

Research on health behaviour and time orientation has been hindered by a lack of consensus about appropriate measurement. Study 1 assessed the reliability of the Consideration of Future Consequences Scale (CFC) and the Zimbardo Time Perspective Inventory (ZTPI) in a general population sample (n = 300). Although more reliable, the CFC was less readable. Study 2 assessed the validity of a shortened ZTPI, measuring future and present orientation, and the full CFC. The measures had good discrimination to distinguish interpersonal differences. Construct validity of present, but not future, orientation as measured by the ZTPI, was evidenced by its mediation of the association between socioeconomic status and expectations of participating in diabetes screening. The CFC mediated this relationship more weakly. Further investigation of present orientation in understanding health-related behaviour is warrante

A modelling tool for policy analysis to support the design of efficient and effective policy responses for complex public health problems

BACKGROUND: In the design of public health policy, a broader understanding of risk factors for disease across the life course, and an increasing awareness of the social determinants of health, has led to the development of more comprehensive, cross-sectoral strategies to tackle complex problems. However, comprehensive strategies may not represent the most efficient or effective approach to reducing disease burden at the population level. Rather, they may act to spread finite resources less intensively over a greater number of programs and initiatives, diluting the potential impact of the investment. While analytic tools are available that use research evidence to help identify and prioritise disease risk factors for public health action, they are inadequate to support more targeted and effective policy responses for complex public health problems. DISCUSSION: This paper discusses the limitations of analytic tools that are commonly used to support evidence-informed policy decisions for complex problems. It proposes an alternative policy analysis tool which can integrate diverse evidence sources and provide a platform for virtual testing of policy alternatives in order to design solutions that are efficient, effective, and equitable. The case of suicide prevention in Australia is presented to demonstrate the limitations of current tools to adequately inform prevention policy and discusses the utility of the new policy analysis tool. SUMMARY: In contrast to popular belief, a systems approach takes a step beyond comprehensive thinking and seeks to identify where best to target public health action and resources for optimal impact. It is concerned primarily with what can be reasonably left out of strategies for prevention and can be used to explore where disinvestment may occur without adversely affecting population health (or equity). Simulation modelling used for policy analysis offers promise in being able to better operationalise research evidence to support decision making for complex problems, improve targeting of public health policy, and offers a foundation for strengthening relationships between policy makers, stakeholders, and researchers