Introduction
Physical activity is associated with numerous and substantial health benefits (Warburton & Bredin,
2017; Warburton et al.,
2006), but while the prevalence of meeting high aerobic physical activity guidelines has increased over the past decade (Whitfield et al.,
2021), only 53.3% of U.S. adults meet aerobic physical activity guidelines (CDC/National Center for Health Statistics,
2021). Excessive sedentary behavior may influence the development of chronic conditions such as cardiovascular disease (Chomistek et al.,
2013; Patterson et al.,
2018), type 2 diabetes (Bowden Davies et al.,
2018; Paing et al.,
2018; Patterson et al.,
2018; Sardinha et al.,
2017), certain cancers (Cong et al.,
2014; Schmid & Leitzmann,
2014), and low back pain (Citko et al.,
2018; Subramanian & Arun,
2017). It is especially important for individuals with type 1 diabetes to engage in physical activity (Riddell et al.,
2017) as a means of reducing the risk of complications and comorbid conditions. Hence, there continues to be a need for the promotion of physical activity and an effort to reduce physical inactivity and sedentary activity.
Besides reducing the risk of chronic health conditions, there is substantial, evidence-based support that physical activity improves psychological well-being (Warburton & Bredin,
2017). While numerous behavior change theories (e.g. Michie et al.,
2014) help to explain why people
adopt physical activity behaviors, it is equally if not more important to consider what may help people
sustain behaviors over time. For example, people are more likely to maintain behavior change if they are satisfied with the new behavior after weighing the relative costs and benefits (Rothman et al.,
2011). Therefore, it is important to consider physical activity’s impact on mood and well-being, as the promotion of short-term positive mood states (Shiota et al.,
2021; Van Cappellen et al.,
2018) and well-being variables (Razazian et al.,
2020; Stults-Kolehmainen & Sinha,
2014) may be beneficial in promoting sustainable long-term behavior change. Similarly, considering activity type and its importance to the individual may be useful when aiming to get people to move more, since certain activities may hold more meaning and impact compared to others. For instance, men spend a greater amount of time engaged in physical activity than women (Hamrik et al.,
2014; Saffer et al.,
2013), particularly in group-based occupations (e.g., sports), while women are more likely to participate in individual-level occupations (e.g., walking or housework) (Azevedo et al.,
2007). Contextual factors may also play a role (Craft et al.,
2014). For example, women and older adults are more likely to exercise at home, men are more likely to exercise outdoors or at work, younger adults are more likely to exercise with friends, and individuals with lower income are more likely to exercise with family members (Dunton et al.,
2008; Welk & Kim,
2015). Gaining a better understanding of the impacts on mood may be beneficial in promoting participation in physical activity and improving health and well-being.
Though there exists an extensive body of research related to physical activity, there are a number of methodological limitations that need to be addressed (Kanning et al.,
2013). For example, a vast majority of physical activity studies rely on retrospective self-report, such as estimating the amount of physical activity engaged in over the past week or month, which may be subject to participant bias and overestimation and may not be reliable (Warburton & Bredin,
2017). Some of these limitations may be addressed through the use of electronic ecological momentary assessment (EMA). EMA allows participants’ behaviors and experiences to be recorded in real-time and in real-world contexts while minimizing retrospective recall and memory biases (Shiffman et al.,
2008). Using electronic EMA may be even more advantageous than the traditional paper-and-pencil EMA in terms of reliability and compliance (Berkman et al.,
2014; Stone et al.,
2002). An additional benefit of using electronic EMA is the ability to record the exact time of survey completion, which is beneficial when pairing the EMA data with other types of data, such as accelerometry data, that is collected in real time.
Overall, while there are numerous studies examining the relationship between physical activity and well-being (Marquez et al.,
2020), relatively few studies have investigated the short-term, momentary relationships between the two. Furthermore, to our knowledge, activity type and activity importance have not been thoroughly explored in physical activity research. Lastly, there is a need to incorporate underrepresented populations, such as diverse racial and ethnic groups, in order to have a greater public health impact (Marquez et al.,
2020). The study sample consists of individuals with type 1 diabetes, who face the same barriers for physical activity as the overall population but who also may face different challenges and levels of healthcare support (Pyatak et al.,
2014). To address the present research gaps, this study selected and recruited from clinical sites with a diverse patient population, and used real-time data collection via EMA and accelerometry to examine the relationships between physical activity and well-being. Combined, these momentary data collection methods may offer greater insight into the relationship between physical activity and well-being. The purpose of this study is to investigate the relationship between physical activity and subsequent mood, while controlling for the effect of activity type on mood.
Discussion
This study adds to our understanding of how physical activity is associated with subsequent mood. Importantly, while previous studies have investigated objectively measured physical activity impacts on mood, this study examines the effects of activity type and activity importance. Accelerometry measures do not provide contextual information about the type of activity, so previous studies have remarked on the difficulty of disentangling the importance of activity type (Poole et al.,
2011), which this study helps to address. Additionally, the study was conducted among an ethnically and socioeconomically diverse population, which strengthens its generalizability.
Within-person
Results from this study suggest that within-person, more sedentary time is associated with subsequent decreased positive affect, while greater physical activity is associated with subsequent increased positive affect. The negative relationship between sedentary activity and positive affect is consistent with previous EMA studies (Smith et al.,
2020; Wen et al.,
2018)
. The positive relationship between positive affect and physical activity was found for light, moderate, and vigorous levels of activity. This finding is consistent with previous EMA studies where higher levels of positive affect were found after engagement in moderate-vigorous physical activity (Dunton et al.,
2014; Liao et al.,
2015; Wen et al.,
2018). No significant associations were found between physical activity and negative affect. These null findings are consistent with a meta-analysis of 12 studies that also examined affective responses from physical activity and found no significant relationship between light physical activity and negative affect (Wiese et al.,
2018). Numerous meta-analyses across different patient populations demonstrate a relationship between physical activity and the reduction of fatigue (Juvet et al.,
2017; Oberoi et al.,
2018; Razazian et al.,
2020). Activity type and activity importance are shown to have an effect on both positive affect and fatigue, where the types of activities people engage in and the perceived importance of the activities influence the change in positive affect and fatigue that is caused by differing levels of physical activity. In other words, the associations between both physical activity and positive affect and physical activity and fatigue are greater when activity type and activity importance are considered.
The low correlations are consistent with other studies examining short-term, momentary relationships (Bennett et al.,
2020; Yang et al.,
2021). Additionally, while the effect sizes for these relationships are small, they should be considered in the context of a lifetime. Experiencing slight fluctuations in mood on any given day may not seem significant, but these experiences have the potential to be repeated countless times throughout the lifespan. Thus, though the momentary effects are marginal, the overall effect on mood and well-being may be substantial.
Between-person
Between-person, people that spent more time in light activity over the study period also typically had higher average stress over the study period. This may be because light activities may include running errands or other hassles and stressful events that occur in people’s everyday lives that may lead to increased stress states. Previous studies have had mixed results regarding light physical activity and stress. Similar to this study, Jones et al. (
2017) found that higher light activity was associated with higher stress in real-time. These findings are in contrast to an earlier study that did not find any associations between objectively measured physical activity and stress (Poole et al.,
2011). The participant sample from this study is closer in similarity to Jones et al. (
2017), which may explain the differing results.
Limitations
Despite the advantages of using accelerometry to objectively measure activity level and electronic EMA survey methods to assess well-being, this study had a few limitations. To start, the sample consisted of individuals who had type 1 diabetes and had the added experience of participating in the study amidst the COVID-19 pandemic and its related social distancing effects during data collection, hence their experiences may differ from the general population. Furthermore, since the participants were limited to particular geographic areas (Los Angeles and New York), the results may not be applicable to other populations in other areas of the United States or around the world. Replication of this protocol with larger, more diverse samples is needed to confirm the relationships suggested by this study. Additionally, the construct of well-being is a broad, multidimensional concept and all aspects of well-being were not covered in this study. Well-being measures were limited to those included in the overarching study.
Conclusions
This study provides evidence that positive affect is predicted by previous activity and this relationship is still pertinent even when adjusting for the different activities that people were engaged in. Ultimately, when people were more active, they were in a better mood. Additionally, when people were engaged in activities that they enjoy, this also led to a better mood. There still exists an independent effect that suggests a portion of the improved mood was derived from purely the physical activity component and some portion comes from the activities that are considered important and meaningful.
This study also suggests that while people may experience increased positive affect and reduced fatigue after engaging in physical activity, people who had increased light physical activity also reported higher stress states. Results from this study highlight the value of engaging in meaningful activities to improve mood and reduce fatigue. These findings have implications for the timing of short-term interventions, such as just-in-time adaptive intervention approaches. For example, one direction that the findings from this study may serve to contribute to future interventions is through personalized communication which informs individuals about the types of occupations that may have improved their emotional well-being in the past based on their data. For healthcare practitioners who work directly with patients, it is suggested that physical activity recommendations consider the unique needs and characteristics of the patient, including which activities are important and meaningful for them. The promotion of physical activity should be part of an integrated approach to enhance meaningful occupations and healthy lifestyle behaviors.
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