Bornas, X., Gelabert, J. M., Llabres, J., Balle, M., & Tortella-Feliu, M. (2011). Slope of change throughout exposure treatment for flight phobia: the role of autonomic flexibility. Journal of Clinical Psychology, 67(6), 550-560. doi:10.1002/jclp.20780; 10.1002/jclp.20780
This study tested the hypothesis that flight-phobic patients experience change at different rates even when they are receiving identical treatment. Faster within-session rates of change (WSRC) were expected for patients who required fewer exposure sessions. The study also tested the theoretical role of autonomic flexibility on WSRC. High flexibility should be associated with faster rates of change. Thirty-seven flight-phobic patients were successfully treated with a computer-assisted fear of flying treatment. A significant negative correlation was found between total number of sessions and WSRC: The fewer sessions patients attended, the faster their rate of change was. The role of autonomic flexibility was partially supported: A significant correlation between heart rate variability and WSRC revealed that flexible patients improved faster than less-flexible patients. (c) 2011 Wiley Periodicals, Inc. J Clin Psychol 67:1-11, 2011.
Xavier Bornas, Jordi Llabres, Miquel Tortella-Feliu, Miquel A. Fullana, Pedro Montoya, Ana Lopez, Miquel Noguera, Joan M. Gelabert, Vagally mediated heart rate variability and heart rate entropy as predictors of treatment outcome in flight phobia, Biological Psychology, Volume 76, Issue 3, October 2007, Pages 188-195, ISSN 0301-0511, DOI: 10.1016/j.biopsycho.2007.07.007.
In the present study a computer-assisted exposure-based treatment was applied to 54 flight phobics and the predictive role of vagally mediated heart rate (HR) variability (high frequency, 0.15-0.4 Hz band power) and heart rate entropy (HR time series sample entropy) on treatment outcome was investigated. Both physiological measures were taken under controlled breathing at 0.2 Hz and during exposure to a fearful sequence of audiovisual stimuli. Hierarchical regression analyses were conducted to assess the predictive power of these variables in these conditions on treatment self-report measures at the end of treatment and at 6 months follow-up, as well as on the behavioral treatment outcome (i.e. flying at the end of treatment). Regression models predicting significant amounts of outcome variance could be built only when HR entropy was added to the HR variability measure in a second step of the regression analyses. HR variability alone was not found to be a good predictor of neither self-reported nor behavioral treatment outcomes.