Using clustering algorithms to examine the association between working memory training trajectories and therapeutic outcomes among psychiatric and healthy populations

Agassi, O. D. ORCID: https://orcid.org/0000-0003-2685-6870, Hertz, U., Shani, R., Derakshan, N., Wiener, A. and Okon-Singer, H. (2022) Using clustering algorithms to examine the association between working memory training trajectories and therapeutic outcomes among psychiatric and healthy populations. Psychological Research. ISSN 1430-2772 doi: 10.1007/s00426-022-01728-1

Abstract/Summary

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.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/108723
Identification Number/DOI	10.1007/s00426-022-01728-1
Refereed	Yes
Divisions	Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
Publisher	Springer
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