Analysis
BASE-6 Analysis
Jacobson-Truax Classifications. The first step in analysis was to classify each participant according to the Jacobson-Truax framework. Descriptive statistics resulting from this process can be seen in Table 5. According to this framework, the majority of clients either recovered or did not significantly change. Those in the improved class began on average with the highest score (representing most severe symptoms) but also improved the most on average, even slightly more than those in the recovered class. Those in the no change class started with the lowest score. The average score of 18 for the no change class is less than the clinical cutoff for the BASE-6 of 19. It is important to note that clients varied on when …show more content…
For instance, the trajectories for both the improved and no change classes predict that clients in these classes experience early postitive change but then demonstrate a resurgence in their symptoms. Early Detection of Treatment Outcome. After computing the complete trajectories across all of therapy, we computed trajectories for the first three sessions. In performing backward elimination of the model terms, the fixed effects retained in the model were the linear time variable and the Jacobson-Truax classification term along with the interaction between these two terms. The quadratic time variable was not significant. Additionally, a random intercept term for participant was included in the model, but not a term for the slope.
Table 7 summarizes the fixed effect terms in the model. As in the previous model, the classification terms were done with respect to the deteriorated class. We can see from the table that the p-value for each of terms in the model besides the no change term. This indicates that at the first timepoint, all of the classes except the no change have significantly different scores in comparison to the deteriorated and that the slope of the
BASE-6 Analysis
Jacobson-Truax Classifications. The first step in analysis was to classify each participant according to the Jacobson-Truax framework. Descriptive statistics resulting from this process can be seen in Table 5. According to this framework, the majority of clients either recovered or did not significantly change. Those in the improved class began on average with the highest score (representing most severe symptoms) but also improved the most on average, even slightly more than those in the recovered class. Those in the no change class started with the lowest score. The average score of 18 for the no change class is less than the clinical cutoff for the BASE-6 of 19. It is important to note that clients varied on when …show more content…
For instance, the trajectories for both the improved and no change classes predict that clients in these classes experience early postitive change but then demonstrate a resurgence in their symptoms. Early Detection of Treatment Outcome. After computing the complete trajectories across all of therapy, we computed trajectories for the first three sessions. In performing backward elimination of the model terms, the fixed effects retained in the model were the linear time variable and the Jacobson-Truax classification term along with the interaction between these two terms. The quadratic time variable was not significant. Additionally, a random intercept term for participant was included in the model, but not a term for the slope.
Table 7 summarizes the fixed effect terms in the model. As in the previous model, the classification terms were done with respect to the deteriorated class. We can see from the table that the p-value for each of terms in the model besides the no change term. This indicates that at the first timepoint, all of the classes except the no change have significantly different scores in comparison to the deteriorated and that the slope of the