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Studies evaluating the external validity of theoretically informed (risk-need-responsivity [RNR]) cognitive behavioral therapy (CBT) programs have not systematically assessed antisocial personality traits as a source of variability in outcomes. The purpose of this brief report is to examine antisocial traits as a potential source of variability in outcomes.

Using longitudinal, program-evaluation data (a sample of incarcerated men who were exposed to RNR-informed CBT), the authors examined how antisocial personality traits, attitudes toward treatment and dosage impacted treatment outcomes. A linear regression assessed the relationship between antisocial personality traits and attitudes toward treatment. A latent profile analysis identified participants with elevated antisocial traits and negative attitudes toward treatment. Treatment dosage groups (0, 5, 10 and 15 weeks) were used to assess treatment response per pro-criminal attitudes, skills and rates of recidivism.

Antisocial traits predicted negative attitudes toward treatment. Elevated antisocial traits and negative treatment attitudes predicted less change in criminal attitudes among those who completed 15 weeks of treatment; higher dosage did not significantly improve rates of recidivism. Variable-centered post hoc analyses largely corroborated these findings. These results suggest RNR-informed CBT may need to be modified for justice-involved persons with elevated antisocial traits.

Few studies have empirically examined the sources of variability in treatment effects for justice-involved persons with antisocial personality traits. This brief report provides a structured examination of factors that may impact treatment outcomes in this population, and therefore aims to inform future research on the effectiveness of empirically supported interventions for people in the legal system.

In this study, we drew on the theories of social exchange and social learning and hypothesized that the online social capital (SC) and offline SC of social networking affect the online self-disclosure (OSD) of individuals through social self-efficacy (SSE).

After retrieving 514 valid questionnaires, we used structural equation modeling to analyze the data.

The results indicated that the users’ SSE affected their OSD, and that both online and offline bridging and bonding SC increased their SSE. However, online bonding SC directly affected their OSD, whereas online bridging SC did not considerably affect their OSD. Given these findings, we presented both theoretical and practical implications to elucidate SSE and OSD behavior from the perspective of online and offline bridging and bonding SC.

In this study, we drew on theories of social exchange and social learning to examine the effects of online and offline bridging and bonding SC on users’ SSE and OSD on SNSs. Given the importance of SC and SSE in social relationships and the effects of OSD on SNSs, our goal was to provide SNS marketers with a thorough understanding of how to facilitate SSE and OSD from the perspective of online and offline bridging and bonding SC.