The Use of an Errorless Learning Application to Support Re-Learning of (Instrumental) Activities for People Living with Korsakoff Syndrome

Author:

Biemond Roeline,Oudman ErikORCID,Postma Albert

Abstract

Korsakoff syndrome (KS) is a severe neuropsychiatric syndrome derived from acute thiamine deficiency and concomitant alcohol use disorders. KS patients need lifelong assistance because of the severity of their cognitive problems. In clinical practice and research, errorless learning has proven to be an effective cognitive rehabilitation method for patients with KS. Our study focused on optimizing errorless learning by introducing new software technology to support the training process of errorless learning. Although the benefits of errorless learning for patients with Korsakoff’s syndrome have been thoroughly investigated, it is currently unclear whether new technology could contribute to better learning and maintenance of everyday tasks. Therefore, an errorless learning application was built. This device is a web application and can be used on a tablet, laptop, or smartphone. The application allows clinicians and researchers to insert pictures, videoclips, timers, and audio fragments in the different steps of an errorless learning training plan. This way, the different steps are visible and easy to follow for patients. Moreover, it ensures as a learning method that the training is executed exactly the same way for each and every training. The aim of this study was twofold: to examine whether the use of the errorless learning application is effective, and whether it leads to better results than a regular errorless learning of everyday activities. In total, 13 patients with KS were trained in instrumental activities of daily living by means of the application, and 10 patients were trained with traditional instructions. Results showed an equal improvement for both training methods. Importantly, the technology group could better remember the training when probed at a later moment than the traditional errorless learning group. These results are promising for further development of novel technology to support errorless learning applications in clinical practice.

Publisher

MDPI AG

Subject

General Medicine

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