Examining within-person relationships between state assessments of affect and eudaimonic well-being using multi-level structural equation modeling

ABSTRACT

Prior research has highlighted the possibility that current affect may be interchangeable with state assessments of other dimensions of subjective well-being. In the present study, we conducted a systematic replication and extension by examining the relationship between state assessments of affect and eudaimonic well-being (meaning, core self-evaluation, authenticity, and gratitude) in a 14-day diary assessment (N = 207 with 2,147 assessments). We utilized multi-level structural equation modeling (ML-SEM) with affect as a time-varying covariate and found that the impact of affect for these outcomes was less consequential than for assessments of state satisfaction, and that the impact of positive affect on these dimensions was stronger than that of negative affect.

KEYWORDS:

• Meaning
• purpose
• affect
• authenticity
• core self-evaluations
• gratitude
• well-being
• within-person differences

Authors’ contributions

EJ, ET and LB conceived the study; EJ, LB and BW developed materials and collected data; ET ran the analyses; EJ and ET drafted the paper; all authors provided feedback and edits on the final document.

Availability of data and materials

All data and materials are available from the first author upon request.

Compliance with ethical standards

Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the American Psychological Association’s ethical standards. The study was reviewed and approved by the Wake Forest IRB prior to data collection (IRB # IRB00021398). No study involved research on animals.

Disclosure statement

The authors have no known conflicts of interest to disclose.

Code availability

All code utilized in the analyses are available from the first author upon request.

Notes

1. To estimate multilevel reliability (see Geldhof et al., 2014), we ran multilevel confirmatory factor models and computed omega using the following formula: ω = (∑λ)²/[(∑λ)² + ∑ψ²].

Additional information

Funding

This study was funded by a grant from the John Templeton Foundation (grant ID: 24322). Informed consent: Informed consent was obtained from all individual participants included in the study.