COMPUTER-ASSISTED INTERVENTIONS TO IMPROVE SELF-REGULATION IN PATIENTS WITH SELF-REGULATORY DEFICITS

The aim of the present thesis was to examine the efficacy of computer-assisted interventions in increasing self-regulation. Recent studies indicate that self-regulation is associated with executive function, mood disorders and heart rate variability (HRV).
In Study 1, we investigated the efficacy of the use of the visual software Tic-Tac tool in reducing anxiety-related behaviours during transition periods in three adults with autism and learning difficulties. Recently it has been suggested that anxiety-related behaviours in autism are associated with emotion regulation deficits. The results of this study revealed that all three participants showed a reduction in anxiety-related behaviours such as stereotypies and nervous utterances from baseline to intervention phase.
In Study 2, we investigated the effects of heart rate variability biofeedback (HRV BF) on mood and executive function in healthy volunteers, while contrasting different formats of HRV BF presentation. One group of participants completed 7 sessions of a computer-based HRV biofeedback while another group attended 10 sessions. No significant differences were found between groups. However, only Group 2, which completed 10 training sessions, showed an improvement in depression symptoms after intervention. Significant improvements were also found in positive mood, emotion regulation and flexibility at post-intervention in Group 2. In addition, this group showed an increase in positive mood and HRV indices (SDNN, Total HRV) from pre- to post-session levels. Group 1 showed a significant decrease in negative affect and an increase in HRV parameters (SDNN, Total HRV, LF HRV) across sessions.
In Study 3, we examined the effects of 12 sessions of HRV BF in 21 stroke patients. Participants were assessed using cognitive tasks and self-report two times before (extended baseline) and two times after the intervention (follow-up). While this study was not able to demonstrate that HRV BF improved long-term cognitive performance or affective state in stroke patients, short-term increases of mood after training suggest that this intervention may be useful to increase emotional well-being in stroke patients. In addition, stroke patients showed increases in HRV indices (RMSSD, SDNN, LF HRV, LF/HF ratio, total HRV) from pre- to post-training session. These findings are in line with previous studies, in which no long-term effects could be observed. In addition, in study 3, emotion dysregulation was found to be associated with mood disorders. Strong correlations were also found between mood before training and changes in HRV indices from pre- to post-training. These findings advance our knowledge on the association between mood and self- regulation.
In summary, these studies suggest that healthy participants, and clinical populations (e.g. stroke patients and individuals with autism) can improve self-regulation through computer-based interventions. These methods may, therefore, be useful adjunct treatments for the improvement of self-regulation.