Bouncing back from emotional ups and downs: insights in emotional recovery using survival analyses of burst ESM data

Many experience sampling (ESM) studies suggested that high resilience is reflected by quickly recovering one's emotional baseline. However, former studies relied on coarse data and did not look into differential recovery from emotional ups and downs. This preregistered proof-of-concept study therefore used high-resolution data collected in 2022 to compute emotional recovery after high levels of positive versus negative emotions. Adults (<i>N</i> = 68) participated in a three-week ESM study with eight assessments per day, complemented by short-spaced burst assessments. Resilience was assessed at baseline (trait-level; TR) and daily (day-level; DR). Multilevel survival analyses showed that high DR predicted faster returns from negative emotions, but also delayed returns following positive emotions (exp(<i>β</i>) = 1.32, <i>p</i> = 0.006). Instead, TR did not relate to emotional recovery (exp(<i>β</i>) = 0.85, <i>p</i> = 0.067). These findings were generally robust across different sensitivity analyses. This illustrates how innovative ESM designs combined with time-to-event analyses may further our insight in emotional recovery and the timescale at which it unfolds.

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Publication Details

Journal
Cognition & Emotion
Published
2024-11-05
DOI
https://doi.org/10.1080/02699931.2024.2423706
Citations
2
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
1.02

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article

Bouncing back from emotional ups and downs: insights in emotional recovery using survival analyses of burst ESM data

Ginette Lafit, Marieke J. Schreuder, Sigert Ariens, Eva Ceulemans
2 citations
Cognition & Emotion
Mental Health Research Topics
1.02
article

Bouncing back from emotional ups and downs: insights in emotional recovery using survival analyses of burst ESM data

Ginette Lafit, Marieke J. Schreuder, Sigert Ariens, Eva Ceulemans
article en
2 citations

Abstract

Many experience sampling (ESM) studies suggested that high resilience is reflected by quickly recovering one's emotional baseline. However, former studies relied on coarse data and did not look into differential recovery from emotional ups and downs. This preregistered proof-of-concept study therefore used high-resolution data collected in 2022 to compute emotional recovery after high levels of positive versus negative emotions. Adults (<i>N</i> = 68) participated in a three-week ESM study with eight assessments per day, complemented by short-spaced burst assessments. Resilience was assessed at baseline (trait-level; TR) and daily (day-level; DR). Multilevel survival analyses showed that high DR predicted faster returns from negative emotions, but also delayed returns following positive emotions (exp(<i>β</i>) = 1.32, <i>p</i> = 0.006). Instead, TR did not relate to emotional recovery (exp(<i>β</i>) = 0.85, <i>p</i> = 0.067). These findings were generally robust across different sensitivity analyses. This illustrates how innovative ESM designs combined with time-to-event analyses may further our insight in emotional recovery and the timescale at which it unfolds.

Cognition & EmotionVol. 39(4)
KU Leuven (BE)
Fonds Wetenschappelijk Onderzoek
Openalex Percentile: Top 20%
Mental Health Research Topics
1.02
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