The present study investigated the directional relationship between practicing school counselors’ level of altruism to their degree of burnout. Specifically, this investigation tested the hypothesized directional relationship that practicing school counselors scoring at higher levels of altruism would have lower levels of burnout (emotional exhaustion, depersonalization, personal accomplishment). In addition, the investigation examined the relationship between the practicing school counselors’ levels altruism and burnout and their reported demographic information (e.g., age, school counseling level, self-reported levels of wellness). A thorough review of the literature is presented with supporting empirical research for each construct (altruism and burnout). A descriptive, correlational research design (Frankel et al., 2012) was employed to investigate the research hypothesis and exploratory questions. The research hypothesis was analyzed using structural equation modeling (SEM). More specifically, multiple regression, path analysis, and confirmatory factor analysis (Ullman, 2007) were conducted. The exploratory research questions were examined using: descriptive statistics, Spearman’s rho correlations, multiple regressions, Kruskal-Wallis test and Mann Whitney U test (Pallant, 2010). The results are reviewed and compared to existing research in the field. Furthermore, limitations of the current study are explained, and recommendations for future research are provided. Finally, implications of the study regarding professional school counseling and counselor education are discussed. The overall sample for this study is 437 practicing school counselors (ASCA members, n = 344; non-ASCA members, n = 93). The results of the study support that school counselors with higher levels of altruism have lower levels of burnout. The findings of this study show two dimensions of altruistic motivation: (1) positive future expectations and (2) self-efficacy v contribute significantly to all dimensions of burnout (emotional exhaustion, depersonalization, and personal accomplishment). Additionally, a significant relationship was found between altruism and burnout and self-reported wellness.

The purpose of the study was twofold: to explore how school counselors and athletic educators experienced implementing the 2010 Massachusetts Anti-bullying law and to explore how participants experienced using the Sharevision structured group reflection process as the format for group discussions. The Sharevision structured group reflection process provided the safety and support school counselors and athletic educators said they needed. Participants eagerly shared their experiences with one another. They used the Sharevision process to discuss the list of participant generated questions they posed during the individual interviews. They exchanged ideas and were able to generate new ways to respond to anti-LGBTQ bullying and gender-based harassment as a result of their reflective group discussions. The participants said that the Sharevision meetings relieved stress, were productive and inspired them to continue working together to take action on their ideas. After the study was over, members of the group met over the summer with the GSA Advisor to continue to work together. They designed and then co-facilitated their fall orientations for incoming students, athletes and parents proactively promoting diversity, their GSA and a positive LGBTQ school climate.

Educational content session for Frontier Health case managers.

The purpose of the study is to investigate a variety of character traits, stressors or traumatic event variables in order to develop a possible predictor model for individuals that seek out to become a student in a counseling program and how those variables relate to their level of empathy. The purpose of using a multiple linear regression analysis is to help determine if a linear relationship exist between the dependent variable and a set of independent variables. The multiple linear regression analyzes the data to determine if the residuals are homoscedastic and approximately rectangular-shaped. A multiple linear regression allows the researcher to assess for the absence of multicollinearity in the model, meaning that the independent variables are not highly correlated. The multiple linear regression analysis determines the single fit for the variables through a scatter plot. More specifically the multiple linear regression fits a line through a multi-dimensional space of data points in order to determine their correlation to each other (O’Brien, 2018).

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