Understanding the Dynamics of Hedonic and Eudaimonic Motives on Daily Well-Being: Insights from Experience Sampling Data

Abstract Previous studies have consistently found that hedonic and eudaimonic motives positively predict subjective well-being. In this study, we emphasized the importance of considering curvilinear effects alongside main effects and interactions to fully understand these relationships. Using polynomial regression models, we examined the relationships between hedonic motives, eudaimonic motives, and subjective well-being. To examine both trait-level and momentary-level relations with well-being, we used experience sampling methodology to collect real-time data from 161 participants over a 7-day period. Our findings suggested that engaging in activities towards fulfilling both motives was associated with positive experiences, and individuals with high levels of hedonic and eudaimonic motives in their daily lives generally reported higher subjective well-being. Nevertheless, we also identified negative interaction effects between both motives on subjective well-being, which imply that there may be a limit to the positive contributions of combinations of both motives to subjective well-being. We discuss the implications of our findings for understanding the nuanced relationships between hedonic and eudaimonic motives and subjective well-being.

Authors

Institutions

Publication Details

Journal
Journal of Happiness Studies
Published
2024-10-01
DOI
https://doi.org/10.1007/s10902-024-00812-0
Citations
8
Primary Topic
Psychological Well-being and Life Satisfaction
Type
article
Field-Weighted Citation Impact
5.15
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Understanding the Dynamics of Hedonic and Eudaimonic Motives on Daily Well-Being: Insights from Experience Sampling Data

Eeske van Roekel, Sjoerd van Halem, Jaap J. A. Denissen
8 citations
Journal of Happiness Studies
Psychological Well-being and Life Satisfaction
5.15
article

Understanding the Dynamics of Hedonic and Eudaimonic Motives on Daily Well-Being: Insights from Experience Sampling Data

Eeske van Roekel, Sjoerd van Halem, Jaap J. A. Denissen
article en
8 citations

Abstract

Abstract Previous studies have consistently found that hedonic and eudaimonic motives positively predict subjective well-being. In this study, we emphasized the importance of considering curvilinear effects alongside main effects and interactions to fully understand these relationships. Using polynomial regression models, we examined the relationships between hedonic motives, eudaimonic motives, and subjective well-being. To examine both trait-level and momentary-level relations with well-being, we used experience sampling methodology to collect real-time data from 161 participants over a 7-day period. Our findings suggested that engaging in activities towards fulfilling both motives was associated with positive experiences, and individuals with high levels of hedonic and eudaimonic motives in their daily lives generally reported higher subjective well-being. Nevertheless, we also identified negative interaction effects between both motives on subjective well-being, which imply that there may be a limit to the positive contributions of combinations of both motives to subjective well-being. We discuss the implications of our findings for understanding the nuanced relationships between hedonic and eudaimonic motives and subjective well-being.

Journal of Happiness StudiesVol. 25(7)
Utrecht University (NL), Tilburg University (NL)
Openalex Percentile: Top 5%
Psychological Well-being and Life Satisfaction
5.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.