204 The Professional Counselor | Volume 12, Issue 3 Procedures We used AB SCRD to determine the effectiveness of an SFBT treatment program (Lundervold & Belwood, 2000; Sharpley, 2007) using scores on the DHS and OQ-45.2 total scale as outcome measures (Lambert et al., 1996). The two participants who were assigned to Himmelberger did not begin counseling until they consented to treatment and the research study. In other words, they did not receive counseling services prior to participation in this study. After 4 weeks of data collection, the baseline phase of data collection was completed. Participants did not receive counseling services during the baseline period. The treatment phase began after the fourth baseline measure. At the conclusion of each individual session, participants completed the DHS and OQ-45.2. Himmelberger collected and stored the measures in each participant’s folder in a locked cabinet in the clinic. After the 12th week of data collection, the treatment phase of data collection was completed, at which point the SFBT intervention was withdrawn. A percentage of non-overlapping data (PND) procedure was used to analyze quantitative data (Scruggs et al., 1987). A visual representation of change over time is graphically represented with a splitmiddle line of progress visual trend analysis showing data points from each phase (Lenz, 2015). Statistical process control charting was used to determine whether the characteristics of treatment phase data were beyond the realm of random occurrence with 99% confidence (Lenz, 2015). An interpretation of effect size was estimated using Tau-U to complement PND analysis (Lenz, 2015; Sharpley, 2007). Data Collection and Analysis We implemented the PND (Scruggs et al., 1987) to analyze scores on the Hope and OQ-45.2 scales across phases of treatment. The PND procedure yields a proportion of data in the treatment phase that overlaps with the most conservative data point in the baseline phase. PND calculations are expressed in a decimal format that ranges between 0 and 1, with higher scores representing greater treatment effects (Lenz, 2013). Upon considering the percentage of data exceeding the median procedure (Ma, 2006), we selected the PND because it is considered a robust method of calculating treatment effectiveness (Lenz, 2013). This metric is conceptualized as the percentage of treatment phase data that exceeds a single noteworthy point within the baseline phase. Because we aimed for an increase in DHS scores, the highest data point in the baseline phase was used. Finally, given that we aimed for a decrease in OQ-45.2 total scale scores, the lowest data point in the baseline was used (Lenz, 2013). To calculate the PND statistic, data points in the treatment phase on the therapeutic side of the baseline are counted and then divided by the total number of points in the treatment phase (Ikonomopoulos et al., 2016). Estimates of Effect Size and Clinical Significance PND values are typically interpreted using the estimation of treatment effect provided by Scruggs and Mastropieri (1998) wherein values of .90 and greater are indicative of very effective treatments, those ranging from .70 to .89 represent moderate effectiveness, those between .50 to .69 are debatably effective, and scores less than .50 are regarded as not effective (Ikonomopoulos et al., 2015, 2016). Tau-U values are typically interpreted using the estimation of treatment effect provided by Vannest and Ninci (2015) wherein Tau-U magnitudes can be interpreted as small (≤ .20), moderate (.20–.60), large (.60–.80), and very large (≥ .80). These procedures were completed for each participant’s scores on the Hope and OQ-45.2 scales. Clinical significance was determined in accordance with Lenz’s (2020a, 2020b) calculations of percent improvement (PI) values. Percent improvement values greater than 50% were interpreted as
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