7 - (IOP 19) Examining the Clustering of Lifestyle Factors and Emotions in Daily Life: An Ideographic Approach

In recent decades there has been an increase in interest in healthy lifestyle factors and a growing focus on health and wellness in daily life (Firth et al., 2020; Walsh, 2011). Adherence to healthy lifestyle factors including limiting alcohol use, sufficient engagement in physical activity, maintaining a healthy diet, avoiding tobacco use, and maintaining good sleep quality have been associated with lower mortality rates and increased life expectancy . However, little research has examined how the links between lifestyle engagement and mental health may be unique across individuals in daily life. As such, this project sought to examine whether ideographic associations among lifestyle behaviors and emotional experiences in daily life could be assessed with personalized network models. Ninety-eight adults (Mage = 42.79, SDage = 17.28) participated in a 70-day daily diary study, where they reported on daily lifestyle engagement, positive affect, and negative affect each evening. Network models were used to examine the associations among these variables at the between-person level and within-person level. Further, separate person-specific ideographic network models were analyzed, to explore potential unique patterns of clustering across individuals.

Results indicated that lifestyle factors and emotional experiences were associated at each level in the sample - between-person associations, within-person contemporaneous (same-day) associations, and within-person temporal (t1->t2) associations. In conjunction with various significant associations in the whole sample, the results indicate that connection among lifestyle factors and emotional health may be unique for each person. In other words, certain lifestyle behaviors cluster together in day-to-day life differently across people, which highlights the potential benefits of utilizing intensive data collection in clinical care to inform individualized interventions focused on lifestyle change. Future research should explore the feasibility of implementing intensive measurement and individualized interventions within clinical samples. In conclusion, lifestyle factors and emotional outcomes cluster together in daily life, and the clustering differs across people.