Previous research has shown that phobic subjects with low heart rate variability (HRV) are less able to inhibit an inappropriate response when confronted with threatening words compared to phobic subjects with high HRV [Johnsen, B.H., Thayer, J.F., Laberg, J.C., Wormnes, B., Raadal, M., Skaret, E., et al., 2003. Attentional and physiological characteristics of patients with dental anxiety. Journal of Anxiety Disorders, 17, 75-87]. The aim of this study was to evaluate changes in self-reported anxiety when low HRV and high HRV fearful flyers (N = 15) and a matched control group (N = 15) were exposed to flight-related pictures, flight-related sounds or both pictures and sounds. We hypothesized that sounds would be crucial to evoke fear. Also, low HRV fearful flyers were expected to report higher anxiety than high HRV fearful flyers assuming anxiety as their inappropriate response. Decreases on HRV measures were also predicted for a subgroup of phobic participants (N = 10) when confronted with the feared stimuli. Our data supported the hypothesis that sounds are crucial in this kind of phobia. Low HRV fearful flyers reported higher anxiety than high HRV fearful flyers in two out of three aversive conditions. The predicted HRV decreases were not found in this study. Results are discussed in the context of avoidance of exposure-based treatments.
Categoria: 2005
¿Caos en el electrocardiograma de estudiantes con miedo a volar? Un análisis de no linealidad
Chaos theory provides a new way to analyze the psychophysiological functioning of anxiety disordered people. However, in order to apply any of the nonlinear analysis techniques, nonlinearity tests must be performed and nonlinearity must be found in the psychophysiological signal. In this experimental study we use the surrogate data method to analyze the nonlinearity of the ECG time series of students with and without fear of flying under several stressing conditions. The prediction errors of the surrogate data were found to be much higher than the prediction errors of the ECG signals (p < .05) in all the experimental conditions as well as during the baseline period. We conclude that nonlinear properties are in fact in the ECGs of the participants, and therefore it would be possible to analyze these signals with nonlinear techniques to get knowledge about their comnplexity, entropy, regularity, and so on.