Pre-training heart rate variability as a predictor of Air Force Academy completion - Yosef Kula; Roy Horosov; Yori Gidron; Aya Ekshtein; Barak Gordon; Zev Iversen; Omer Tehori; Oded Ben-Ari (PLoS ONE, 2025)
Introduction Operational pilots are required to perform complex tasks under high stress and uncertainty. One of the major challenges of aviation medicine is the selection of suitable candidates to serve as pilots. The vagal nerve is a crucial moderator of stress responses, and its activity (indexed by heart rate variability, HRV) reflects psycho-physiological resilience and has been shown to predict performance in various settings. However, its predictive value in pilot training has not been examined. This study examined the relationship between HRV and success in an intensive and long pilot course. Methods In a historical prospective study, we derived an HRV parameter (RMSSD) from a 10-second ECG of 169 male and 16 female candidates attending a 3-year pilots’ course. The ECGs were performed 2–3 months before the courses. The predictive validity of other routinely obtained measures was also considered. Data were analyzed in two ways. First, we analyzed the entire sample using t-tests. Then, significant predictors of success and HRV were entered in a multivariate logistic regression. Second, we focused on a smaller sample of paired candidates (passed vs. failed), matched on significant predictors, and then examined differences in HRV between these groups using a paired t-test. Results High RMSSD significantly predicted the completion of the pilot course in a multivariate logistic regression. RMSSD and the selection test formula score were the only significant predictors. In the paired matched sample, candidates who passed the course had significantly higher initial HRV (M = 121.30ms) compared to those who failed (M = 84.31ms; t(25)= 1.78, p < 0.05). Conclusion The current study supports the predictive value of HRV for aviation selection. Given the high cost of training operational pilots and the physical and mental burdens they undergo, improved accuracy of the selection processes may be crucial.