Objective: Sudden gains during psychotherapy have been found to be predictive of positive treatment outcomes. Previous attempts at predicting occurrence of sudden gains have yielded equivocal findings. Recently, intraindividual variability in symptoms during treatment was suggested as a trans-therapeutic and trans-diagnostic predictor of sudden gains. The goal of the present study was to examine this predictor in Internet-delivered treatment for social anxiety disorder (SAD) and to examine whether this predictor predicts sudden gains when measured before treatment begins. Method: We examined data from a preregistered randomized controlled trial (RCT) of Internet-delivered cognitive-behavioral therapy (CBT) for SAD (n ϭ 101). We measured variability in symptoms both within-treatment and before treatment (i.e. during waitlist). Results: Intraindividual variability in symptoms significantly predicted sudden gains both when measured before treatment or within-treatment and correctly classified 84% and 83% of individuals to sudden gains versus non-sudden gains status, respectively. Conclusions: Intraindividual variability in symptoms can predict sudden gains in Internet-delivered treatment for SAD, thus supporting its trans-diagnostic and trans-therapeutic nature. Predicting sudden gains before treatment begins has implications for treatment planning and clinical decision making as well as for personalized tailoring of interventions. What is the public health significance of this article?This study demonstrates that sudden gains in psychotherapy can be predicted by symptom fluctuations measured before treatment. Such early prediction of sudden gains can facilitate personalizing and tailoring future interventions to individuals based on likelihood of sudden gains.
Working memory (WM) training has gained interest due to its potential to enhance cognitive functioning and reduce symptoms of mental disorders. Nevertheless, inconsistent results suggest that individual differences may have an impact on training efficacy. This study examined whether individual differences in training performance can predict therapeutic outcomes of WM training, measured as changes in anxiety and depression symptoms in sub-clinical and healthy populations. The study also investigated the association between cognitive abilities at baseline and different training improvement trajectories. Ninety-six participants (50 females, mean age = 27.67, SD = 8.84) were trained using the same WM training task (duration ranged between 7 to 15 sessions). An algorithm was then used to cluster them based on their learning trajectories. We found three main WM training trajectories, which in turn were related to changes in anxiety symptoms following the training. Additionally, executive function abilities at baseline predicted training trajectories. These findings highlight the potential for using clustering algorithms to reveal the benefits of cognitive training to alleviate maladaptive psychological symptoms.
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