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Published on: October 19, 2011
Exploring the Utility of a Real-Time Approach to Characterising Within-Person Fluctuations in Everyday Stress
Meynard John L Toledo1, Matthew J Zawadzki2, Stacey B Scott3
1Center for Self-Report Science, University of Southern California, Los Angeles, California, USA.
None:
Few studies have measured components of stress responses in real time-an essential step in designing just-in-time interventions targeting moments of risk. Using ecological momentary assessment (EMA), we characterised stress response components to everyday stressors, including reactivity (the response following a stressor), recovery (the return towards baseline), and pile-up (the accumulation of stressors) (RRPs) by quantifying the dynamics of response indicators (i.e., subjective stress, negative affect, and perseverative cognition). To determine the utility of these novel measures in capturing and characterising acute moments of the stress response, this study evaluated the proportion of variance in RRPs attributed to (1) between-person, (2) between-days, and (3) within-day (momentary) levels. Healthy adults (n = 123; aged 35-65, 79% women, 91% non-Hispanic White) participated in a 14-day study assessing stress response via EMA 6 times a day. RRPs were constructed from 10,065 EMA reports. Multilevel models with moments nested within days nested within persons were used to partition variance in the RRPs. Reactivity and recovery indicators captured the most variation within-days (i.e., across moments; range 76%-80% and 87%-89%, respectively), with small amounts of variance between-person. For pile-up, variation was mostly observed between-days (range 60%-63%) and between-persons (range 27%-31%). In contrast, raw measures of stress response reflected substantial between-person (range 32%-54%) and within-day (range 34%-53%) variance. These results demonstrated that a person-specific approach to measuring stress response components (i.e., RRPs) can capture the dynamic within-person variation in stress response, as it occurs in real time, making it well-suited for use in novel just-in-time interventions targeting moments of risk.
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