TPC Journal-Vol 9 Issue 3-FULL

The Professional Counselor | Volume 9, Issue 3 231 .71 for Client Focus, .73 for Rapport, and .77 for Identification. In the current study, we found alpha coefficients for SWAI-S subscales as .98 for Client Focus, .99 for Rapport, and .99 for Identification. Convergent and divergent validity of the scales were established through intercorrelations with the Supervisory Styles Inventory (Efstation et al., 1990). For the purposes of the current study, participants were asked to indicate the extent to which SWAI-S items were characteristic of their work with trainees during their supervision. Modified Index for Interdisciplinary Collaboration (MIIC). Participants’ perceptions of collaboration on interdisciplinary teams were measured with the Modified Index for Interdisciplinary Collaboration (MIIC; Oliver, Wittenberg-Lyles, & Day, 2007). The MIIC is a 42-item self-report questionnaire with a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Including four subscales of Interdependence and Flexibility, Newly Created Professional Activities, Collective Ownership of Goals, and Reflection on Process, the MIIC’s conceptual framework is based on the original instrument, the Index for Interdisciplinary Collaboration (IIC; Bronstein, 2002); therefore, it is expected to have the same face validity with the IIC (Oliver et al., 2007). The internal consistency estimate of the MIIC, calculated as Cronbach’s alpha, was found to be .94 for the present study. The subscale internal consistency estimates were found to be .87 for Interdependence and Flexibility, .77 for Newly Created Professional Activities, .80 for Collective Ownership of Goals, and .79 for Reflection on Process (Oliver et al., 2007). For the purposes of our current study, participants were asked to specify their agreement on the MIIC statements with regards to their current primary work setting and organization. Data Screening and Analyses Confirmatory Factor Analysis (CFA). To examine the fit for the single-factor solution of the CSS in our sample, we utilized Mplus 6 to run a CFA. Prior to conducting the analysis, we initially examined the necessary assumptions for the CFA (i.e., multivariate normality; Kline, 2011). We observed 26 cases as multivariate outliers in our sample. Upon the examination of these cases’ influence on our results with and without them, we decided to remove these outliers from the final analysis. To have a robust understanding of our CFA results, we observed multiple fit indices for the single-factor model from Moe et al.’s (2018) EFA (i.e., chi-square test, root mean square error of approximation [RMSEA], confirmatory fit index [CFI], and standardized root mean square residual [SRMSR]), as recommended by Lent, Lopez, Brown, and Gore (1996). Other validity analyses. We also examined convergent, divergent, concurrent, and incremental validity psychometrics of the CSS. We first explored the correlations between the CSS and the subscales of the SWAI, namely Client Focus (CF), Rapport (R), and Identification (I), for the convergent validity— as they measured similar, but not identical concepts. To explore divergent validity, we checked the correlations between the CSS, the MIIC, gender (identifying as male), and ethnicity (identifying as European American)—as all measured different concepts. Next, concurrent validity of the CSS was investigated through the examination of mean differences between participants without consultation training, those with one to two consultation training experiences, and those with three or more consultation training experiences. Finally, we tested incremental validity of the CSS via a hierarchical regression analysis in which predictive ability of the CSS was examined to predict participants’ MIIC scores beyond the variables of age, gender, and years of experience. Reliability analyses. Finally, we examined Cronbach’s alpha coefficient as well as split-half reliability properties of the CSS for internal reliability.