Affect variability and predictability: Using recurrence quantification analysis to better understand how the dynamics of affect relate to health.

• DOI: 10.1037/emo0000556
• Publication Date: 2019-02-04T14:47:57Z
• Authors: Brooke N. Jenkins; John F. Hunter; Michael J. Richar...; Tamlin S. Conner; Sarah D. Pressman
• Keywords: Affect; Recurrence quantification analysis; Predictability; PsycINFO

Changes in affect over time have been associated with health outcomes. However, previously utilized measurement methods focus on variability of (e.g., standard deviation, root mean squared successive difference) and ignore the more complex temporal patterns time. These may be an important feature understanding how dynamics relate to health. Recurrence quantification analysis (RQA) help alleviate this problem by assessing characteristics unassessed past methods. RQA metrics, such as determinism recurrence, can provide a measure predictability time, indexing often within affective experiences repeat. In Study 1, we first contrasted metrics commonly used measures demonstrate that further differentiate among affect. 2, analyzed associations between these new health, namely, depressive somatic symptoms. We found predicted above beyond levels The most desirable outcomes were observed people who had high positive affect, low negative variability, predictability. studies are utility for determining (PsycInfo Database Record (c) 2020 APA, all rights reserved).