Rapid Review of Men's Behavior Change Programs.

Family violence is recognized as the violence toward a family member that is threatening, coercive, controlling, dominating, and causes people to fear for their safety and well-being; this complex problem primarily affects women and children. In order to enhance women and children's safety, Men's Behavior Change Programs (MBCPs) aim to achieve change in perpetrators' violent behaviors, by making men accountable and responsible for their actions. The objective of this rapid review was to examine MBCP content, implementation, and the impact on participant and family outcomes. Thirteen articles and 10 MBCPs were identified, using PRISMA guidelines, electronic database searches, and an inclusion criteria of English peer-reviewed articles examining MBCPs or domestic violence perpetrator programs with male perpetrators of family/domestic/intimate partner violence as program participants. The findings of this review indicated a limited evidence base of detailed MBCP evaluations. Information relating to program content was included for nine MBCPs and covered a wide range of topics. None of the articles examined the links between men's accountability and responsibility to the safety and well-being of women and children. Also, none of the articles included assessments of integrity of program delivery, system processes, or evaluations based on program logics. Positive changes were reported for MBCP participants, including communication, parenting, interpersonal relationships, aggression, abuse, responsibility for behavior, self-awareness power and control tactics, empathy, skills development, cognitive beliefs, behavior control, and abusiveness patterns. A whole family approach was utilized by some of the programs and one article reported on family outcomes.

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials.

A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from DBT clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper's ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were 0.51 ± 0.06 and 0.54 ± 0.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72 ± 0.01, 2.75 ± 0.01) and (2.77 ± 0.03, 2.82 ± 0.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average ß values (2D, DBT) of (3.10 ± 0.17, 3.21 ± 0.11) and (3.01 ± 0.32, 3.19 ± 0.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30 mm × 30 mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers.