Department of Special Education and Counselling, The Education University of Hong Kong, Hong Kong, China; Integrated Centre for Wellbeing, The Education University of Hong Kong, Hong Kong, China; Bioanalytical Laboratory for Educational Sciences, The Education University of Hong Kong, Hong Kong, China.
Department of Special Education and Counselling, The Education University of Hong Kong, Hong Kong, China; Integrated Centre for Wellbeing, The Education University of Hong Kong, Hong Kong, China; Bioanalytical Laboratory for Educational Sciences, The Education University of Hong Kong, Hong Kong, China.
Psychoneuroendocrinology. 2021 Jul;129:105267. doi: 10.1016/j.psyneuen.2021.105267. Epub 2021 May 14.
The hypothalamic-pituitary-adrenal (HPA) and parasympathetic nervous systems have been reported to play important roles in emotion regulation and stress coping. Yet, their direct relationship with psychological resilience remains unclear. These biophysiological features should be considered together with the traditional psychometric properties in studying resilience more comprehensively. The current study aimed to examine the role of these systems during a laboratory stress task and to determine the prediction power of resilience by combining psychological and biophysiological features. One hundred and seven (52 females) university students without psychiatric disorders underwent the Trier Social Stress Task (TSST). Psychometric properties of resilience were measured at rest; vagal heart rate variability (HRV), salivary cortisol, and dehydroepiandrosterone (DHEA) levels were captured at baseline, during, and after TSST. Multivariate linear regression as well as support vector regression machine-learning analyses were performed to investigate significant predictors and the prediction power of resilience. Results showed that positive and negative affects, HRV during the anticipatory phase of stress, and the ratio of cortisol/DHEA at the first recovery time point were significant predictors of resilience. The addition of biophysiological features increased the prediction power of resilience by 1.2-fold compared to psychological features alone. Results from machine learning analyses further demonstrated that the increased prediction power of resilience by adding the ratio of cortisol/DHEA was significant in "cortisol responders"; whereas a trend level was observed in "cortisol non-responders". Our findings extend the knowledge from the literature that high vagal activity during the anticipating phase of stress and the ability to restore the balance between cortisol and DHEA after a stress event could be an important feature in predicting resilience. Our findings also further support the need of combining psychological and biophysiological features in studying/predicting resilience.
下丘脑-垂体-肾上腺（HPA）和副交感神经系统被报道在情绪调节和应激应对中发挥重要作用。然而，它们与心理弹性的直接关系仍不清楚。在研究弹性时，应该将这些生物物理特征与传统的心理计量学特征结合起来，进行更全面的考虑。本研究旨在考察这些系统在实验室应激任务中的作用，并通过结合心理和生物物理特征来确定弹性的预测能力。107 名（52 名女性）无精神障碍的大学生参加了特里尔社会应激测试（TSST）。在休息时测量了弹性的心理计量学特征；在基线、TSST 期间和之后采集了迷走神经心率变异性（HRV）、唾液皮质醇和脱氢表雄酮（DHEA）水平。进行了多元线性回归和支持向量回归机器学习分析，以调查弹性的显著预测因子和预测能力。结果表明，积极和消极的影响、应激前预期阶段的 HRV 以及第一次恢复时间点的皮质醇/DHEA 比值是弹性的显著预测因子。与仅使用心理特征相比，添加生物物理特征可使弹性的预测能力提高 1.2 倍。机器学习分析的结果进一步表明，在“皮质醇反应者”中，添加皮质醇/DHEA 比值可显著提高弹性的预测能力；而在“皮质醇非反应者”中则观察到趋势水平。我们的研究结果扩展了文献中的知识，即应激前预期阶段高迷走神经活动和应激后恢复皮质醇和 DHEA 之间平衡的能力可能是预测弹性的一个重要特征。我们的研究结果还进一步支持了在研究/预测弹性时需要结合心理和生物物理特征。
