Preventing violence in disadvantaged communities: Strategies for building collective efficacy and improving community health

ABSTRACT

Violence is a critical health issue that compromises the strength of communities and permanently damages the lives of individuals and families. The impact of violence on health and well-being is particularly devastating in disadvantaged and minority communities, leading to negative health outcomes, including premature death. However, research suggests that communities can prevent violence and negative health outcomes by developing collective efficacy, which happens when neighbors share norms and values, trust one another, and are willing to intervene to address problems. Despite the importance of collective efficacy in preventing violence and improving health, almost no research has investigated actionable strategies to build collective efficacy in disadvantaged neighborhoods. This article describes a theoretical and conceptual model that illustrates how collective efficacy impacts community violence and related health outcomes. We begin by reviewing other approaches to community violence prevention, including criminal justice and developmental approaches. We then discuss how collective efficacy works and why it matters, including theoretical and empirical research explaining collective efficacy and its impact on community violence and health. We then discuss a research-based intervention that social workers can use to facilitate collective efficacy, including our conceptual model and the key components of the intervention. Finally, we discuss implications for social workers who are working with communities to address violence and related health issues.     

The attitudes toward lesbians and gay men scale (ATLG): adaptation and testing the reliability and validity in Chile

Previous researchers have used the attitudes toward lesbians and gay men (ATLG) scale (Herek, 1988) and reported their own reliability coefficients and validity measures, but research on this subject is scarce in Chile. In order to determine if ATLG scale was a reliable and valid instrument in our country, we adapted and examined the psychometrics properties using a sample composed of 142 psychology and economics undergraduate students. This study found the ATLG scale to be reliable (a = .90) and valid for the Chilean population and is a recommended instrument for measuring attitudes toward gay men and lesbians.     

The effect of mergers and acquisitions on productivity: An empirical application to Spanish banking

Mergers and acquisitions are frequently justified in terms of value creation or efficiency improvements. Nevertheless, the evidence is not consistent with the existence of benefits in terms of the costs, productivity, profitability or market value of the firms involved. A distinguishing feature of extant research is that it focuses on the assessment of the consequences of mergers around the time in which the operation takes place, limiting the possibility of observing a complete integration between the merged firms. In this context, the objective of this paper is to evaluate the effects of mergers and acquisitions on the long-run productivity of Spanish savings banks. Our results show that productivity improvements can be found in only half of the mergers that take place during the period analyzed.     

The sliced inverse regression algorithm as a maximum likelihood procedure

It is shown that the sliced inverse regression procedure proposed by Li corresponds to the maximum likelihood estimate where the observations in each slice are samples of multivariate normal distributions with means in an affine manifold.     

Analytical expressions for the average adjustment interval and mean squared deviation for bounded adjustment schemes

This paper presents analytical expressions for the average adjustment interval and the mean squared deviation from target of the “bounded adjustment” schemes of Box and Luceno (1997a) under the assumption that the disturbances are generated from a double-exponential distribution. The solutions obtained are very close to those computed numerically for normally distributed innovations. This not only demonstrates the robustness of the schemes to the distributional assumptions, but also provides new useful expressions for the average adjustment interval and mean squared deviation from target. Expressions for the characteristic and probability mass functions of the adjustment interval are also given.     

Analyzing Small Samples of Repeated Measures Data with the Mixed-Model Adjusted F Test

This research examines the Type I error rates obtained when using the mixed model with the Kenward-Roger correction and compares them with the Between–Within and Satterthwaite approaches in split-plot designs. A simulated study was conducted to generate repeated measures data with small samples under normal distribution conditions. The data were obtained via three covariance matrices (unstructured, heterogeneous first-order auto-regressive, and random coefficients), the one with the best fit being selected according to the Akaike criterion. The results of the simulation study showed the Kenward-Roger test to be more robust, particularly when the population covariance matrices were unstructured or heterogeneous first-order auto-regressive. The main contribution of this study lies in showing that the Kenward–Roger method corrects the liberal Type I error rates obtained with the Between–Within and Satterthwaite approaches, especially with positive pairings between group sizes and covariance matrices.     

Optimal Resource Allocation for Defense of Targets Based on Differing Measures of Attractiveness

This article describes the results of applying a rigorous computational model to the problem of the optimal defensive resource allocation among potential terrorist targets. In particular, our study explores how the optimal budget allocation depends on the cost effectiveness of security investments, the defender's valuations of the various targets, and the extent of the defender's uncertainty about the attacker's target valuations. We use expected property damage, expected fatalities, and two metrics of critical infrastructure (airports and bridges) as our measures of target attractiveness. Our results show that the cost effectiveness of security investment has a large impact on the optimal budget allocation. Also, different measures of target attractiveness yield different optimal budget allocations, emphasizing the importance of developing more realistic terrorist objective functions for use in budget allocation decisions for homeland security.     

Landslide Risk Models for Decision Making

This contribution presents a quantitative procedure for landslide risk analysis and zoning considering hazard, exposure (or value of elements at risk), and vulnerability. The method provides the means to obtain landslide risk models (expressing expected damage due to landslides on material elements and economic activities in monetary terms, according to different scenarios and periods) useful to identify areas where mitigation efforts will be most cost effective. It allows identifying priority areas for the implementation of actions to reduce vulnerability (elements) or hazard (processes). The procedure proposed can also be used as a preventive tool, through its application to strategic environmental impact analysis (SEIA) of land-use plans. The underlying hypothesis is that reliable predictions about hazard and risk can be made using models based on a detailed analysis of past landslide occurrences in connection with conditioning factors and data on past damage. The results show that the approach proposed and the hypothesis formulated are essentially correct, providing estimates of the order of magnitude of expected losses for a given time period. Uncertainties, strengths, and shortcomings of the procedure and results obtained are discussed and potential lines of research to improve the models are indicated. Finally, comments and suggestions are provided to generalize this type of analysis.     

Toward a grounded theory of lesbians' recovery from addiction

This article presents the results of a qualitative study on lesbians' recovery from addiction. The study involved semi-structured interviews with 20 lesbians in recovery from addiction and was analyzed using grounded theory method. The central theme that emerged was self-acceptance, both as a lesbian and as a recovering alcoholic/addict, with considerable interaction between the two. Categories that contributed to this theme were learning to recover, relationships with other people, and relationship with something bigger than self. The discussion addresses how this information can be used to assist lesbians trying to recover from addiction.