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Figure 1 displays the participant flow diagram during treatment. There were 202 participants assessed at pre-treatment. In the initial sessions, six participants who chose not to attend the therapy groups were excluded from further treatment. Finally, 196 participants received psychotherapy: n = 121 received DBT, n = 32 received STEPPS, and n = 47 received TAU-CBT. During the treatment, in the DBT group, % (n = 21) dropped out, in the STEPPS group, % (n = 12) dropped out, and in the TAU-CBT group, % (n = 12) dropped out. Thus, the percentage of overall treatment dropout was % (n = 46). The clinical sample was older than the non-clinical sample (t(391) = 8.26, p < .001) (Cohen's d = 0.9).
Shot development through the treatment. DBT = Dialectical Behavioural Medication; STEPPS = Systems Knowledge for Psychological Predictability and you will Problem solving; TAU = Therapy as ever
Before beginning treatment, participants diagnosed with BPD had a statistically significant lower QoL (QoL T1) (M = 4.31, SD = 1.74) than the non-clinical population (M = 7.86, SD = 1.24) (t() = , p < .001), with a large effect size (Cohen's d = 2.37) . In the same way, participants diagnosed with BPD had statistically significant lower resilience (RS T1) (M = , SD = ) than the non-clinical population (M = , SD = ) (t() = , p < .001), with a large effect size (Cohen's d = 2.24).
As Table 1 shows, after the treatment, all the participants significantly increased their QoL scores (F(1,144) = , p < .001). However, there were no statistically significant differences between DBT, STEPPS, and TAU in the improvement in QoL after treatment (F(step one,144) = 0.31, p = .73). Moreover, participants did not show clinically significant improvements in QoL at post-treatment because no reliable changes occurred (Reliable change index = 1.53, p > .05), and the scores were not similar to those of the non-clinical population (range 6.62 to 9.1), with a moderate effect size (Hedges’ g = 0.39). Thus, the participants diagnosed with BPD still had lower QoL than the non-clinical sample (t(239,06), p < .001) after the treatment.
After the treatment, the participants significantly increased their resilience (t(118) = ? 4.35; p < .001) and significantly decreased their depression (t(118) = 5.08; p < .001). As Table 1 reveals, all the effect sizes were moderate (range Cohen's d = 0.35–0.41).
Just like the Table 2 suggests, resilience from the pre-medication (RS T1) is very and you can definitely synchronised having QoL (QoL T1), and you can highly and you may adversely correlated which have anxiety (BDI-II T1) and resilience in the article-cures (RS T2). Moreover, resilience at the pre-medication (RS T1) are modestly and you will certainly synchronised that have QoL blog post-cures (QoL T2) and you can meagerly and you may negatively synchronised with despair post-treatment (BDI-II T2). Strength within post-procedures (RS T2) try very and you can positively synchronised which have QoL (QoL T2) and you can highly and you will negatively correlated with anxiety (BDI-II T2). Desk 2 gift suggestions the rest of the correlations.
As Table 3 shows, the model composed of resilience before the treatment (RS T1), Type of psychotherapy, Gender, Age, and depression (BDI-II T1) predicted QoL pre-treatment (T1) (R 2 adjusted = .64; christianmingle prijs F(5.153) = , p < .001). After entering Type of psychotherapy, Gender, Age, and depression (BDI-II T1), Resilience before the treatment (RS T1) predicted QoL pre-treatment (T1) (?R 2 = .16). As Table 3 shows, when analysing the individual contribution of each predictor variable, the variables that significantly predicted QoL (T1) were Resilience pre-treatment (RS T1) (t = 8.48; p = .01) and depression pre-treatment (BDI-II T1) (t = ? 5.26; p = .01).