Economic, social and mental health impacts of an economic intervention for female sexual violence survivors in Eastern Democratic Republic of Congo.

BACKGROUND: Conflict-affected communities face poverty and mental health problems, with sexual violence survivors at high risk for both given their trauma history and potential for exclusion from economic opportunity. To address these problems, we conducted a randomized controlled trial of a group-based economic intervention, Village Savings and Loans Associations (VSLA), for female sexual violence survivors in the Democratic Republic of Congo. METHODS: In March 2011, 66 VSLA groups, with 301 study participants, were randomized to the VSLA program or a wait-control condition. Data were collected prior to randomization, at 2-months post-program in June 2012, and 8-months later for VSLA participants only. Outcome data included measures of economic and social functioning and mental health severity. VSLA program effect was derived by comparing intervention and control participants' mean changes from baseline to 2-month follow-up. RESULTS: At follow-up, VSLA study women reported significantly greater per capita food consumption and significantly greater reductions in stigma experiences compared with controls. No other study outcomes were statistically different. At 8-month follow-up, VSLA participants reported a continued increase in per capita food consumption, an increase in economic hours worked in the prior 7 days, and an increase in access to social resources. CONCLUSIONS: While female sexual violence survivors with elevated mental symptoms were successfully integrated into a community-based economic program, the immediate program impact was only seen for food consumption and experience of stigma. Impacts on mental health severity were not realized, suggesting that targeted mental health interventions may be needed to improve psychological well-being.

The need for improved anthropometric methods for the development of helmet systems.

Fit for the modern flight helmet is not just comfort, but includes proper placement of added components (e.g., earcups, helmet-mounted optics, etc.), stability, and even center of gravity location. Many fielded and prototype helmets have been criticized for poor fit, not providing adequate sizes, and compromising safety. In this paper, evidence from studies using new surface digitizing techniques is presented revealing that a large part of the problem is due to the fact that the development of these helmets was based on traditional anthropometry. These findings demonstrate the need for improved methods of specifying, designing, and evaluating helmets. Specifically, for development of equipment which must interface with the human body, there is a need for fit assessment in conjunction with surface scanning to define: 1) correct positioning of the human with respect to the equipment; 2) proper sizing, and 3) proper size issuing schemes.

Size and shape analysis techniques for design.

A major problem in designing highly specialized equipment such as oxygen masks, respirators, etc, is that the effectiveness of the equipment depends on its appropriateness for the size and shape of the body part for which it is designed. However, in general, among the individuals who are likely to be using this equipment, there is considerable heterogeneity in size and shape of the body parts. One solution is to use the available data to form homogeneous clusters of the population and then make separate designs for each cluster, commonly referred to as sizing. Current sizing practices are hindered by a problem termed 'observer-inherence'; in other words, the positioning and orientation of the reference axis system can affect the size and shape groupings more than size and shape themselves do. The impact of observer-inherence is felt most on systems that require the most stringent fit, such as helmets with optical systems. For such systems, traditional measures and analysis practices can be almost useless. In this paper, an analysis technique is introduced which should be observer-invariant in the three-dimensional case. The method is illustrated using points selected along a horizontal cross-section. The points are first transformed into values called curvatures which are subsequently transformed into a series of Fourier coefficients. These are then used for arriving at shape clusters or groupings. The shape differences (and similarities) within and between clusters are examined graphically and discussed. The technique developed here can be extended to form clusters using the curvatures of a surface instead of that of a cross-section (ie, can be extended to the three-dimensional case) and methods for doing so are discussed.