Being awake and moving around throughout the day consistently correlates with how energized and fulfilled people feel. People who tend to experience low mood show the strongest association between daily activities and well-being. These findings demonstrate that small amounts of daily activity are important components of public health and individual mental health. A large meta-analysis detailing these patterns was published in the journal nature human behavior.
Historically, research into the relationship between movement and mood has been conducted in artificial laboratory settings or relied on questionnaires asking people to recall their mood over the past few weeks. This approach carries a high risk of introducing memory bias. Memory bias occurs when a person cannot accurately recall past emotional states, often remembering things better or worse than they actually are. Even in a laboratory setting, we struggle to recreate the chaotic reality of everyday life.
Relying on large differences between separate people also fails to capture how one person’s mood relates to that person’s own daily activity level. Assuming that group averages apply to individuals is a common statistical trap known as the ecological fallacy. Health experts needed to understand these internal micro-level processes to better motivate people to adhere to daily physical activity recommendations.
In recent years, researchers have begun using wearable motion sensors and smartphone diaries to track people in their natural environments. This method, often referred to as ecological momentary assessment, circumvents memory problems by pinging participants throughout the day and asking them how they are feeling in the moment. Wearables simultaneously measure how much a person is actually moving, eliminating the need for people to guess their activity level.
Despite this technological leap forward, the accumulated evidence remained confusing and sometimes contradictory. Previous reviews of these studies simply counted the number of papers that showed positive or negative results. This simple counting method gives equal weight to large, robust studies and small, weak studies. Nor can it measure the actual strength of mood-related associations.
To resolve these ambiguities, the team of researchers conducted a meta-analysis of individual participant data. This means they did not simply read the conclusions published in previous studies. Instead, they collected raw, original data from dozens of research groups around the world and analyzed it all together using a single, standardized mathematical approach.
The project was coordinated by Markus Reichert, professor at Ruhr University Bochum in Germany. Johanna Roeder, PhD student at Ruhr University Bochum, served as lead author of this publication. Other key contributors include researchers Julian Packheiser, Marco Giurgiu, Irina Timm, Gesa Berretz, and Onur Güntürkün.
“It has long been known that physical activity has a positive impact on well-being, but previously this evidence was only available from laboratory and cross-sectional studies,” says Professor Markus Reichert (PLUS, Ruhr-University Bochum, ZI), who coordinated the project. He points out that new smartphone and sensor technology allows researchers to assess everyday activities such as walking, climbing stairs, and doing housework. This real-world tracking provides a clearer picture of human habits.
The research team compiled 67 datasets from 14 countries. This large collection included information from 8,223 participants. In total, these individuals provided more than 300,000 individual mood ratings on their smartphones. At the same time, the wearable device recorded nearly 1 million hours of behavioral data, making it the largest analysis of daily behavior and mood ever conducted.
“This synthesis of large amounts of research data from everyday life required innovative and complex meta-analysis techniques,” added Dr. Julian Packheiser (Ruhr-University Bochum). The team used these advanced techniques to uncover hidden patterns within large datasets. This mathematical approach ensured that the original statistical modeling from individual papers did not distort the new results.
The research team looked at how movement was related to five specific categories of mood. These categories include positive emotional states such as happiness, negative emotional states such as sadness and anxiety, and general emotional valence. Valence is a psychological term that refers to the basic spectrum of generally satisfying and unpleasant emotions. They also measured energetic arousal, meaning feeling awake and energized, and tranquility, meaning feeling relaxed and calm.
The researchers examined the data in two time directions. They investigated whether physical activity predicted a person’s subsequent mood. They also looked at whether a person’s mood predicted how much they would move in the immediate aftermath.
The results showed a clear and positive relationship between daily activities and several aspects of health. “It was important to summarize the findings and to be able to estimate the range of correlations between different aspects of emotional well-being, such as positive and negative emotions, energy, calmness, and potentially identify differences between individuals,” explains Johanna Roeder (Ruhr-Universität Bochum, Plas, ZI), PhD student and first author of this publication. Both directions of time were found to be important for understanding the bidirectional relationship between feeling good and staying active.
The most consistent and significant association was found in energetic arousal. When people engaged in more physical activity than average for themselves, they almost always reported feeling awake and energetic afterwards. In fact, over 95% of participants felt more energized before and after moving around.
Moving around also reliably corresponded to a positive emotional state and overall sense of satisfaction. The researchers translated these statistical relationships into real-world examples to demonstrate real-world implications. For example, the difference in mood a person exhibits when transitioning from sitting to walking is comparable to the pleasure a person reports while engaging in leisure activities such as reading, playing, or listening to music.
Conversely, physical activity was associated with decreased calmness. This makes biological sense, since moving the body requires physical exertion that corresponds to an active state, rather than pure relaxation. Individuals were consistently more restless before and after movement compared to when they remained stationary.
For negative emotions such as sadness and anxiety, the overall average effect across all participants was not statistically significant. However, a closer look at individual differences reveals something completely different. The relationship between activity and moodiness varies greatly from person to person.
People who generally had lower overall happiness and higher levels of negative emotions reported their highest levels of positive mood when they were awake and moving. “Our study also shows that people with low levels of well-being particularly benefit from physical activity,” says Onur Güntürkün, Ruhr-University Bochum. This highlights the therapeutic potential of everyday mobility for vulnerable people suffering from mental health conditions.
This analysis also revealed interesting differences based on individual characteristics. A much stronger relationship between movement and subsequent satisfaction was found in young people and adults who had lower weight relative to height. Older people and heavier people did not experience a significant correlation of positive mood with physical activity.
Researchers believe that in older people and heavier people, physical discomfort, heat, and tension may increase at the same time as movement. This temporary discomfort may correspond to a less positive direct psychological experience. Finding ways to reduce this physical strain can be an important step in helping these groups enjoy their activities more.
Gender also influenced these statistical patterns. Women reported feeling more energized after physical activity than men. Men, on the other hand, tend to move more when they feel restless or restless.
Emotional patterns were also moderated by day of the week. The two-way positive relationship between movement and feeling energetic was significantly stronger on weekends than on weekdays. This suggests that leisure-time physical activity may feel better and lead to more positive emotions than physical activity required for work.
Despite the vast amount of data, the research team acknowledges some limitations. The studies included in the analysis were observational, with researchers observing what happened naturally without interference. Because of this design, the results cannot conclusively prove that physical activity directly caused mood swings.
“Our task in the coming years will be to identify additional personal and situational factors that can explain the differences in correlations,” says Reichert. He points out that unmeasured environmental factors, such as the weather outside, may have influenced both a person’s desire to move and their mood. The presence of green spaces and the immediate social environment may also play a hidden role.
Different studies within the dataset also used slightly different questionnaires to measure emotional states. The researchers needed to group these different questions into broad categories to smooth out the subtle emotional nuances. The team had to rely on sophisticated statistical models to ensure that these survey differences did not skew the final results.
Future research will need to conduct actual experiments in everyday environments. One new idea is to use personalized micro-interventions sent directly to smart devices. In such a setting, a smartphone app might notice when a person has been sitting for too long and prompt them to take a little walk.
By tracking the precise emotional consequences of these stimulated activities, researchers can gather conclusive evidence of how movement relates to mood in real time. Only through these real-world experiments can medical professionals design precise, personalized treatments. These customized interventions help people build sustainable exercise habits, ultimately supporting the health of people around the world.
This research was supported by Johanna Rehder, Irina Timm, Gesa Berretz, Iris Reinhard, Andreas B. Neubauer, Onur Güntürkün, Keisuke Takano, Walter Bierbauer, Miriam Cabrita, Matthew Bourke, Joshua Smyth, Jinhyuk Kim, Johannes Michalak, Joshua Curtiss, Bjorn Pannicke, Jacob B. This is due to Gallagher, Ana M. Abrantes, Toru Nakamura, Yoshiharu Yamamoto, Paul Cook, Lena M. Wieland, Birte von Haren-Mack, Brian McCormick, Justin Hutchenberger, Thomas Vetlovsky, Benajmin Henwood, Louise Poppe, Gorden Sadek, Laura Hollands, Andrea B. Goldschmidt, Lynn Martia, Martina Canning, Jaclyn P. Maher, Yu-Mei Li, Ulrich Reininghaus, Corina Berli, Caroline Seiferth, Derek J. Hevel, Kate Leger, Amanda E. Staiano, Almut Zeeck, Stefano Calza, Yue Liao, Geralyn R. Ruissen, CoCA Consortium, Andreas R. Schwerdtfeger, Matthias Haucke, Loree T. Pham, Siwei Liu, Mark C. Thomas, Andreas Mayer Lindenberg, Genevieve F. Danton, Steriani Eravsky, Ulrich W. Ebner Plimmer, Marco Giorgiu, Julian Packheiser, and Markus Reichert.
