Computer-assisted evaluation and treatment of depression in cystic fibrosis patients

Cystic fibrosis (CF) is a widespread chronic multisystem disease that profoundly impairs physical and mental health, with anxiety and depression being on the forefront of CF-associated problems. This study intends to explore alpha EEG patterns as main indicators of relaxation/anxiety, and to investigate prospective of neurofeedback treatment for depression in CF patients. The EEG data were obtained from 13 CF and 10 healthy subjects, in two sessions using BOSLAB equipment and additionally analyzed with WINEEG software. Between measurements, an alpha increasing neurofeedback session was applied. Values of Alpha Peak Frequency (APF) were compared with the standard personality assessment. Final statistical evaluation was performed with Statistica 5. Significant difference (t = -3,154, p< 0.05) for APF between experimental (mean 9.07 Hz) and control group (mean 10.33 Hz) was found in the initial EEG assessment. In addition, APF increased after just one alpha neurofeedback session in both groups (in CF patients, t = -5,226, p< 0.05). The psychological assessment in patients with cystic fibrosis revealed neurotic profile, while the score for depression was below the cutoff for its manifestation. These findings indicate that computer-assisted evaluation can support the process of successful estimation and treatment of depression in CF patients. However, being a pioneering study in this field, further investigations are recommended.