Measuring Collateral Consequences Among Individuals Registered for a Sexual Offense: Development of the Sexual Offender Collateral Consequences Measure.

Collateral consequences faced by individuals convicted of a sexual offense have been widely referenced in the literature. There is yet to be a systematic examination of collateral consequences affecting individuals, however, due to measurement inconsistencies and the absence of a psychometrically validated instrument. The current study developed and validated a measure of collateral consequences faced by individuals convicted of a sexual offense. Specifically, this study investigated (a) the underlying factor structure of collateral consequences commonly endorsed by individuals convicted of a sexual offense through Exploratory Factor Analysis (EFA) procedures and (b) reliability and validity indicators of the aforementioned scale. Participants were 218 individuals convicted of and registered for a sexual offense in the state of Texas. Study measures included a pool of 66 collateral consequences items in addition to psychological self-report instruments addressing hopelessness, shame, social well-being, and discrimination. EFA results revealed a two-dimensional construct representing collateral consequences affecting areas of social and psychological well-being. The current measure demonstrated adequate reliability and validity. Limitations and future directions of findings are addressed.

Mental Health Self-Directed Care Financing: Efficacy in Improving Outcomes and Controlling Costs for Adults With Serious Mental Illness.

OBJECTIVE: Self-directed care allows individuals with disabilities and elderly persons to control public funds to purchase goods and services that help them remain outside institutional settings. This study examined effects on outcomes, service costs, and user satisfaction among adults with serious mental illness. METHODS: Public mental health system clients were randomly assigned to self-directed care (N=114) versus services as usual (N=102) and assessed at baseline and 12 and 24 months. The primary outcome was self-perceived recovery. Secondary outcomes included psychosocial status, psychiatric symptom severity, and behavioral rehabilitation indicators. Mixed-effects random-regression analysis tested for longitudinal changes in outcomes between the two conditions. Differences in service costs were analyzed with negative binomial and zero-inflated negative binomial regression models. RESULTS: Compared with the control group, self-directed care participants had significantly greater improvement over time in recovery, self-esteem, coping mastery, autonomy support, somatic symptoms, employment, and education. No between-group differences were found in total per-person service costs in years 1 and 2 or both years combined. However, self-directed care participants were more likely than control group participants to have zero costs for six of 12 individual services and to have lower costs for four. The most frequent nontraditional purchases were for transportation (21%), communication (17%), medical care (15%), residential (14%), and health and wellness needs (11%). Client satisfaction with mental health services was significantly higher among intervention participants, compared with control participants, at both follow-ups. CONCLUSIONS: The budget-neutral self-directed care model achieved superior client outcomes and greater satisfaction with mental health care, compared with services as usual.

Single frequency inverse obstacle scattering: a sparsity constrained linear sampling method approach.

The linear sampling method (LSM) offers a qualitative image reconstruction approach, which is known as a viable alternative for obstacle support identification to the well-studied filtered backprojection (FBP), which depends on a linearized forward scattering model. Of practical interest is the imaging of obstacles from sparse aperture far-field data under a fixed single frequency mode of operation. Under this scenario, the Tikhonov regularization typically applied to LSM produces poor images that fail to capture the obstacle boundary. In this paper, we employ an alternative regularization strategy based on constraining the sparsity of the solution's spatial gradient. Two regularization approaches based on the spatial gradient are developed. A numerical comparison to the FBP demonstrates that the new method's ability to account for aspect-dependent scattering permits more accurate reconstruction of concave obstacles, whereas a comparison to Tikhonov-regularized LSM demonstrates that the proposed approach significantly improves obstacle recovery with sparse-aperture data.

Participatory action research to establish self-directed care for mental health recovery in Texas.

OBJECTIVE: This article describes a public-academic collaboration between a university research center and the Texas state mental health authority to design and evaluate a unique "money follows the person" model called self-directed care (SDC). SDC programs give participants control over public funds to purchase services and supports for their own recovery. METHODS: Through a participatory action research process, the project combined use of evidence-based practice and community consensus as a tool for system change. RESULTS: The story of this effort and the program that resulted are described, along with quantitative and qualitative data from the project's start-up phase. CONCLUSIONS: Lessons learned about the importance of community collaboration are discussed in light of the current emphasis on public mental health system transformation through alternative financing mechanisms.

Shape and motion reconstruction from 3D-to-1D orthographically projected data via object-image relations.

This paper describes an invariant-based shape- and motion reconstruction algorithm for 3D-to-1D orthographically projected range data taken from unknown viewpoints. The algorithm exploits the object-image relation that arises in echo-based range data and represents a simplification and unification of previous work in the literature. Unlike one proposed approach, this method does not require uniqueness constraints, which makes its algorithmic form independent of the translation removal process (centroid removal, range alignment, etc.). The new algorithm, which simultaneously incorporates every projection and does not use an initialization in the optimization process, requires fewer calculations and is more straightforward than the previous approach. Additionally, the new algorithm is shown to be the natural extension of the approach developed by Tomasi and Kanade for 3D-to-2D orthographically projected data and is applied to a realistic inverse synthetic aperture radar imaging scenario, as well as experiments with varying amounts of aperture diversity and noise.