Personal Risk and Resilience Factors in the Context of Daily Stress.

This chapter focuses on the role that personal risk and resilience factors play as adults of all ages cope with the stressors encountered in everyday life. Theorists have suggested that researchers should focus on the effects of daily stress and coping rather than focusing exclusively on major life events and chronic stress and have proposed that understanding how adults cope with daily stress is a key aspect of understanding long-term well-being and adaptation in adulthood. After presenting a conceptual model outlining the major components of the daily stress process, the chapter reviews the existing empirical literature on personal risk and resilience factors in the context of daily stress. This research clearly suggests that there is no universal generalization that can be made regarding whether chronological age, in and of itself, confers greater vulnerability or resilience onto adults. Instead, we argue that researchers should ask when and under what conditions is age associated with greater vulnerability to daily stress and when and under what conditions is age associated with greater resilience to daily stress. Age differences in reactivity to daily stress are clearly embedded within a complex system of factors-structural, individual, and situational-that influence stress reactivity and stress recovery in several ways. This complexity should not be taken to mean that stress reactivity and recovery cannot be charted or understood. Researchers, however, will need to approach this complexity with a great deal of theoretical, methodological, and statistical rigor to move our understanding of the importance of age in shaping risk and resilience to daily stress forward. The final section of the chapter outlines several directions for future research in the area of aging and resilience. In particular, we argue that a focus on personal risk and resilience factors in the context of daily stress, in combination with the application of sophisticated statistical methods (e.g., dynamic systems modeling), will contribute to a more dynamic and person-centered understanding of processes of resilience.