College Students’ Perceptions of Barriers to Bystander Intervention

Sexual violence is a major problem on college campuses and is associated with a range of negative health consequences for victims. Teaching students to intervene as prosocial bystanders has become a common element of sexual assault prevention efforts; although these programs have demonstrated positive effects on participants’ beliefs and knowledge, their impact on actual behavior is weaker. Understanding the factors that inhibit intervening in risky situations may enhance the effectiveness of bystander programs by identifying material that addresses these barriers. A sample of 281 first-year college students indicated whether they had encountered 10 situations that may present elevated risk of sexual or physical assault since arriving on campus, and if so, whether they had done something to intervene. If they had not intervened, they were asked to identify the barriers that had inhibited them. Participants also completed measures of two factors proposed to predict bystander behavior, self-efficacy and emotion regulation. A majority of participants intervened in most of the situations, but only 27% of participants intervened in every situation they encountered. Men and women differed in the barriers they identified most frequently across situations, with men endorsing Perceived Responsibility more often than women, and women reporting Skill Deficits more often than men. Neither men nor women perceived Audience Inhibition to be a significant barrier; it was salient in only one of the 10 situations. Students higher in global bystander self-efficacy were more likely to intervene and less likely to report barriers related to skill deficits and perceived responsibility. These results suggest that existing bystander intervention programs efforts can be improved by fostering a greater sense of collective responsibility in students and teaching specific intervention behaviors

Caregiver Behaviors Associated With Emotion Regulation in High-Risk Preschoolers

Children who witness violence are at risk for developing a range of developmental problems, including deficits in understanding and regulating. The ability to adaptively manage emotions is associated with children’s mental health and their social and academic competence; however, little is known about how parents of at-risk youth can foster the healthy development of emotion regulation. The current study aimed to identify specific parenting practices associated with adaptive emotion regulation in at-risk preschoolers. Multimethod, multi-informant data were collected from 124 caregiver-child dyads from Head Start programs. Results indicated that interparental aggression was negatively associated with caregivers’ and children’s emotion regulation, but there were specific caregiver behaviors that moderated the association between interparental aggression and children’s emotion regulation. Specifically, care- givers’ sensitivity to children’s emotions during play, listening effectively to children’s expression of sadness, and their own capacity for emotion regulation buffered the association between exposure to interparental aggression and children’s emotion regulation. These findings provide practical insight into how parents can promote resilience in children exposed to violence by fostering healthy emotional regulation

Statistics of Lead Changes in Popularity-Driven Systems

We study statistical properties of the highest degree, or most popular, nodes in growing networks. We show that the number of lead changes increases logarithmically with network size N, independent of the details of the growth mechanism. The probability that the first node retains the lead approaches a finite constant for popularity-driven growth, and decays as N^{-phi}(ln N)^{-1/2}, with phi=0.08607..., for growth with no popularity bias.Comment: 4 pages, 4 figures, 2 column revtex format. Minor changes in response to referee comments. For publication in PR

Adverse Consequences to Assisting Victims of Campus Violence: Initial Investigations Among College Students

Despite growing interest in the use of bystander education programs to address the problems of sexual and relationship violence on college campuses, little knowledge exists on adverse consequences experienced by students intervening as a bystander. The current study examined the prevalence and correlates of adverse consequences of bystander intervention in two samples of first-year college students. In Study 1, 281 students completed a measure of negative consequences experienced when acting as a bystander to help someone at risk of sexual assault, relationship abuse, or stalking. Efficacy for bystander behavior was also assessed. Approximately one third of the students (97/281) reported having tried to help someone who had been at risk of violence during the previous academic year. Of these, approximately 17% (16/97) reported experiencing a negative consequence from having tried to help. Experiencing negative consequences was associated with lower levels of bystander efficacy. In Study 2, conducted at a different university, 299 students completed measures of negative consequences resulting from intervening as a bystander and efficacy for bystander behavior. Students also participated in virtual-reality simulations that provided opportunities to intervene as a bystander. Again, approximately one third of the students (99/299) reported having tried to help someone at risk of violence. Of these, 20% (20/99) reported experiencing a negative consequence. Two of the adverse consequences (physically hurt, got into trouble) were negatively associated with bystander efficacy and observed effectiveness of bystander behavior in the virtual simulations. Results of exploratory analyses suggest that training in bystander intervention might reduce the likelihood of experiencing adverse consequences

Analyzing X-ray variability by State Space Models

In recent years, autoregressive models have had a profound impact on the description of astronomical time series as the observation of a stochastic process. These methods have advantages compared with common Fourier techniques concerning their inherent stationarity and physical background. If autoregressive models are used, however, it has to be taken into account that real data always contain observational noise often obscuring the intrinsic time series of the object. We apply the technique of a Linear State Space Model which explicitly models the noise of astronomical data and allows to estimate the hidden autoregressive process. As an example, we have analysed a sample of Active Galactic Nuclei (AGN) observed with EXOSAT and found evidence for a relationship between the relaxation timescale and the spectral hardness.Comment: 4 pages, Latex, uses Kluwer Style file crckapb.cls To appear in Proc. of Astronomical Time Series, Tel Aviv, 199

Power-law distributions from additive preferential redistributions

We introduce a non-growth model that generates the power-law distribution with the Zipf exponent. There are N elements, each of which is characterized by a quantity, and at each time step these quantities are redistributed through binary random interactions with a simple additive preferential rule, while the sum of quantities is conserved. The situation described by this model is similar to those of closed $N$-particle systems when conservative two-body collisions are only allowed. We obtain stationary distributions of these quantities both analytically and numerically while varying parameters of the model, and find that the model exhibits the scaling behavior for some parameter ranges. Unlike well-known growth models, this alternative mechanism generates the power-law distribution when the growth is not expected and the dynamics of the system is based on interactions between elements. This model can be applied to some examples such as personal wealths, city sizes, and the generation of scale-free networks when only rewiring is allowed.Comment: 12 pages, 4 figures; Changed some expressions and notations; Added more explanations and changed the order of presentation in Sec.III while results are the sam

A Group-Based Yule Model for Bipartite Author-Paper Networks

This paper presents a novel model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random invitations from a group to an outside member. To analyze the model, a number of different metrics that can be obtained in author-paper networks were extracted. A simulation example shows that this model can effectively mimic the behavior of a real-world author-paper network, extracted from a collection of 900 journal papers in the field of complex networks.Comment: 13 pages (preprint format), 7 figure