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Counseling Center Analysis

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The Center for Collegiate Mental Health (CCMH) oversees a comprehensive, practice-research network, designed to help directors of university and college counseling centers (UCC) monitor clinical trends, enhance treatment effectiveness, and advocate for additional resources (McAleavey, Castonguay, Hayes, & Locke, 2014). Through this initiative, standardized measures are used to collect data from UCCs across the United States. One of these, the Counseling Center Assessment for Psychological Symptoms - 34 (CCAPS-34; Locke et al, 2012), was constructed as a brief multidimensional outcome measure, assessing seven clinical subscales including depression, eating concerns, alcohol abuse, generalized anxiety, hostility, social anxiety, and academic …show more content…

More recently, ML methods have also been extended to research applications involving structural equation modeling (Little, 2013), single case research designs (Rindskopf & Ferron, 2014), and meta-analysis (Feingold, 2017). Also, within a measurement context, psychometric researchers have introduced several strategies for reformulating both Rasch and item response theory (IRT) models to account for clustered data (Rijmen, Tuerlinckx, de Boeck, & Kuppens, 2003; Gorter, Fox, Twisk, 2015; Barbieri, Peyhardi, Conroy, Gourgou, Lavergne, & Mollevi, 2016; Blanchin, Hardouin, Neel, Kubis, Blanchard, Mirallié, & Sébille, 2015). From these developments and expanded access to user-friendly software, ML techniques are becoming more common in UCC research to help investigators study complex questions such as college student suicide (Drum, Brownson, Denmark, & Smith, 2009), therapeutic outcomes between white counselors and racial/ethnic minority clients (Hayes, McAleavey, Castonguay, and Locke, 2016), therapist effects on premature termination (Xiao, Castonguay, Janis, Youn,, Hayes,, & Locke, 2017; Xiao, Hayes, Castonguay, McAleavey, & Locke, 2017), and the effects of prior counseling on future outcomes (Boswell, McAleavey, Castonguay, Hayes, & Locke, 2012). However, for researchers studying the mechanisms of change in psychotherapy, it is important to understand the advantages of ML models over conventional statistical tests such as ANOVA, t -

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