Background Housing plays a crucial role in providing resources for and aiding an individual’s reentry into the community following incarceration and substance use treatment. As such, this study examined the influence of recovery homes on a sample of former female substance using women with criminal justice involvement. Methods Two hundred women who had been involved with the criminal justice system within the preceding two years were recruited from multiple sites in metropolitan Chicago. These women were assigned to either one of two conditions: Oxford House (OH) recovery homes or usual aftercare (UA). Results Those with longer stays in OH (6 months or more) had better outcomes in terms of alcohol and drug use, employment, and self-efficacy than those with shorter stays. Outcomes for those who stayed in OH were not appreciably different than the UA condition on substance use and employment, but fewer deaths occurred for those in the OH condition. Conclusions Findings suggest that length of stay of 6 or more months is critical for those in recovery homes, but it is important for us to better understand the processes through which longer stays influence better outcomes.

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Sixty-three companies in the Chicago area were recruited to participate in a worksite smoking cessation program. Participants in each worksite received a television program and newspaper supplement (part of a community-wide media campaign), and one of three conditions: (1) self-help manuals alone (M), (2) self-help manuals and incentives for 6 months (IM) or (3) maintenance manuals, incentives and cognitive-behavioral support groups for 6 months (GIM). Results at the 2 year assessment are examined using a random-effects regression model. In addition, various definitions of quit-rate commonly used in smoking cessation research are explored and the advantages of using a public health approach in the worksite are examined.

This article will present findings related to critical needs in a group of 281 incarcerated women with co-occurring disorders. The women completed interviews while incarcerated and again at various time points after community reentry. Findings revealed that the number of basic needs increased over time, and a low level of social support was related to negative outcomes. Recommendations for this population include holistic evaluation assessments and integrated treatment plans that encourage staff to comprehensively assess clients at intake and link them to support services during and after incarceration. Implications of this female empowerment model will be discussed.

Although it is common in community psychology research to have data at both the community, or cluster, and individual level, the analysis of such clustered data often presents difficulties for many researchers. Since the individuals within the cluster cannot be assumed to be independent, the use of many traditional statistical techniques that assumes independence of observations is problematic. Further, there is often interest in assessing the degree of dependence in the data resulting from the clustering of individuals within communities. In this paper, a random-effects regression model is described for analysis of clustered data. Unlike ordinary regression analysis of clustered data, random-effects regression models do not assume that each observation is independent, but do assume data within clusters are dependent to some degree. The degree of this dependency is estimated along with estimates of the usual model parameters, thus adjusting these effects for the dependency resulting from the clustering of the data. Models are described for both continuous and dichotomous outcome variables, and available statistical software for these models is discussed. An analysis of a data set where individuals are clustered within firms is used to illustrate features of random-effects regression analysis, relative to both individual-level analysis which ignores the clustering of the data, and cluster-level analysis which aggregates the individual data.