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Preceding research has demonstrated the positive relation between gratitude and well-being at the trait level, but less is known about the day-to-day association between them. This study investigated the within-person associations of gratitude with hedonic and eudaimonic well-being using a daily diary design. A sample of 363 young adults (M = 19.77, SD = 1.84) finished an online questionnaire once a day for 14 consecutive days. The results indicated that gratitude was positively related to hedonic and eudaimonic well-being on the same day, and gratitude positively predicted next-day hedonic and eudaimonic well-being, but not vice versa. We also found the reciprocal relation between the cognitive component of daily hedonic well-being (i.e., life satisfaction) and daily gratitude measured by the Gratitude Questionnaire. Moreover, these cross-lagged relations were not moderated by trait gratitude. These results provide supportive and convincing evidence for the positive effect of gratitude at the state level. [ABSTRACT FROM AUTHOR]

Hedonia and eudaimonia have been proposed as pathways to well-being. However, the direction of the causal relationship between them remains unclear. This study examined if happiness motivations may be resources leading to a happy life, or vice versa. Cross-lagged associations between happiness motivations (i.e. hedonic motivation and eudaimonic motivation) and subjective well-being (i.e. positive affect, negative affect, and life satisfaction) were tested. Four hundred and ninety-four Chinese adolescents (233 males; mean age 13.26 ± 0.70 years) participated in a two-wave paper and pencil study. The cross-lagged analysis showed that eudaimonic motivation was a significant predictor of positive affect and life satisfaction over time. No cross-lagged effects between eudaimonic motivation and negative affect, or between hedonic motivation and subjective well-being components were established. The results highlight the predictive power of eudaimonic motivation on adolescents' subjective well-being later on. [ABSTRACT FROM AUTHOR]

Previous studies have rarely explored the predictive causality relationship between trait gratitude and subjective well-being (SWB) that has been demonstrated to have a bi-factor structure (i.e., three specific factors and a general factor of SWB). A sample of 494 adolescents participated in a two-wave study including the measurements of trait gratitude and SWB. We employed structural equation modeling techniques to assess cross-lagged effects between trait gratitude and the bi-factor structure of SWB (i.e., life satisfaction, negative affect, positive affect and the general SWB factor) in four models. The results showed that trait gratitude could predict life satisfaction and positive affect, but could not predict negative affect and the general SWB factor over two months. Besides, there was no evidence for the reverse or reciprocal relationships between trait gratitude and the bi-factor structure of SWB. Implications and future directions of the findings were discussed. [ABSTRACT FROM AUTHOR]

Although the Wong and Law Emotional Intelligence Scale (WLEIS) has been validated in many studies, it has not been validated with bifactor model. Study 1 conducted a confirmatory factor analysis with a sample of 525 Chinese university students aged 18–30 years old, and found that the bifactor model with a general factor and four specific factors showed the best fit to the data. Study 2 cross-validated these findings in another 724 adult sample aged 17–56 years old, and the measurement invariance between students and employees was obtained. Besides, the results of Structural Equation Modeling demonstrated that the general factor could predict the three components of subjective well-being (i.e., life satisfaction, positive affect, and negative affect), but only the specific factor of Use of Emotion could predict positive affect. Moreover, there were no differences in these relations between students and employees. Implications and future directions of the findings were discussed. [ABSTRACT FROM AUTHOR]