Although considerable empirieal attention has recently focused on forgiveness, less work has been done on examining self-forgiveness, A major stumbling block for self-forgiveness research has been the lack of a measure to assess self-forgiveness for specific transgressions. This article reports the development of the State Self-Forgiveness Scales and the test of a model of self-forgiveness' relation to psychological well-being in the context of the unwanted end of a romantic relationship. In Study 1, factor analysis revealed a 2-factor structure to the self-forgiveness data. Study 2 found that self-blame predicted depressive affect to the extent that participants forgave the self. The implications of state self-forgiveness for both basic research and therapy are discussed.

No abstract

Functional behavior assessment (FBA) is a process of assessing the purpose or "function" of a student's behavior in relation to its context (i.e., surrounding environment), so that appropriate interventions can be designed to meet the unique needs of individual students (Iwata et al., 2000; Jolivette, Scott, & Nelson, 2000). This assessment process facilitates the development of individualized behavior support plans for students with challenging behaviors (O'Neill et al., 1997; Scott & Nelson, 1999b; Sugai, Lewis-Palmer, & Hagan, 1998). Traditionally, FBA has been presented and practiced as a prescribed formalized procedure involving multiple direct observations of student behavior, quantitative analysis of behavioral patterns, and valid hypothesis testing prior to intervention (e.g., Liaupsin, Scott, & Nelson, 2000; O'Neill et al., 1997). Critical reviews examining empirical support for the use of FBA with students with or at risk for emotional or behavioral disorders (E/BD) have been the subject of other welldocumented discussions appearing in this journal (e.g.

This article proposes 2 new approaches to test a nonzero population correlation (rho): the hypothesis-imposed univariate sampling bootstrap (HI) and the observed-imposed univariate sampling bootstrap (OI). The authors simulated correlated populations with various combinations of normal and skewed variates. With alpha set=.05, N> or =10, and rho< or =0.4, empirical Type I error rates of the parametric r and the conventional bivariate sampling bootstrap reached .168 and .081, respectively, whereas the largest error rates of the HI and the OI were .079 and .062. On the basis of these results, the authors suggest that the OI is preferable in alpha control to parametric approaches if the researcher believes the population is nonnormal and wishes to test for nonzero rhos of moderate size.

Patients reported a high degree of satisfaction with the relaxation and guided imagery interventions. Patients in the relaxation and guided imagery or combined groups showed a trend toward improvement in fatigue and sleep disturbance scores. Pain remained a problem for the majority of patients. Difficulties in recruiting participants resulted in an insufficient sample size for generalizable findings. With hospital environments tending to be noisy, relaxation and guided imagery may facilitate rest and sleep for hospitalized patients. An examination of individual scores showed a trend toward improvement in sleep quality.