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Acute and Chronic Physical Activity Increases Creative Ideation Performance: A Systematic Review and Multilevel Meta-analysis

Sports Medicine - Open volume 8, Article number: 62 (2022) Cite this article

Abstract

Background

Physical activity is a health-relevant lifestyle factor associated with various benefits on physical and mental health. Several meta-analyses indicated effects of acute and chronic physical activities on elementary cognitive functions such as executive control processes, memory, and attention. Meta-analytic evidence on the effects of physical activity on creative idea generation, which involves a conglomerate of these elementary cognitive functions, is largely missing.

Objective

A twofold approach was used to evaluate (1) if there is an association between habitual physical activity and creative ideation and (2) if physical activity interventions (acute and chronic) enhance creative ideation performance.

Methods

Multilevel meta-analytic methods were applied to (1) evaluate the cross-sectional association between creative ideation performance and measures of habitual physical activity and (2) the effect of physical activity on creative ideation performance. Indicators of creative ideation (fluency, flexibility, originality, elaboration, or composite score), creativity domain (verbal, figural), population (adults, children), gender, study quality, and publication year served as moderator variables for both meta-analyses. Analyses of intervention studies additionally examined the moderator variables study design (between, within), time of measurement (during, after), and implementation of intervention (acute, chronic).

Results

The applied meta-analytic multilevel analysis indicated a medium effect for cross-sectional studies (r = 0.22, SE = 0.06, p = 0.002, 95% CI [0.10–0.34]) based on 17 effects sizes from seven studies. The pooled effects of 28 intervention studies, providing 115 effect sizes, indicated a medium effect size of Hedges’ g = 0.47 (SE = 0.09, p < 0.001, 95% CI [0.30–0.65]). Furthermore, a stronger effect was observed for chronic interventions of several days or weeks in comparison with acute interventions of one single bout.

Conclusion

This study adds important new meta-analytic evidence on the beneficial role of physical activity beyond mental and physical health outcomes: Physical activity has a positive impact on creative ideation, which expands the literature on the role of physical activity in more elementary cognitive functions such as executive control, memory, and attention. Moderator analyses suggested that chronic interventions showed stronger effects than single bouts of physical activity. Rigorously conducted randomized controlled intervention studies and more cross-sectional studies are needed to broaden the evidence in this nascent field of research.

Key Points

  • Cross-sectional studies and interventional studies show a medium-sized positive effect of physical activity on creative ideation performance.

  • The effects of chronical physical activity are stronger compared to the effects of acute physical activity.

  • Rigorously conducted randomized controlled intervention studies and more cross-sectional studies are needed to broaden the evidence.

Introduction

Physical activity facilitates (mental) health and increases cognitive functions such as executive control, attention, and memory processes [1,2,3,4,5,6,7]. The dynamic interplay of specific cognitive functions is essential to produce creative solutions that are surprising, original, and applicable [8]. While research on creativity has long been restricted to classic domains such as music, science, or the arts, recent studies have begun to discover the prominent role of creativity in the domain of sports. For instance, creative cognition and cognitive flexibility can facilitate game-related decision-making and prevent sport injuries [9]. Furthermore, creative cognition is an important factor in team sports with the potential to determine victory or defeat [10]. Although the impact of physical activity on cognitive functions is well known, reviews and meta-analyses have largely ignored its potentially enhancing effect on creative idea generation.

Can physical activity stop mental blocks and increase the uniqueness of ideas [8, 11,12,13]? And if so, can even a short run boost creative thoughts? Or is it necessary to train for weeks to finally achieve a higher creative output? Are different domains of creative ideation affected to the same extent? Is the effect of physical activity restricted to quantitative facets of creativity (e.g., number of generated ideas), or does it similarly apply to creative quality (e.g., originality)? Although an increasing number of empirical studies have targeted these exciting questions, not all of them have confirmed a positive link between physical activity and participants’ creative potential (i.e., performance in a divergent thinking task [14]; for a critical review see [15]). The increasing number of studies and inconsistent results call for a meta-analysis, which quantifies the overall effect of physical activity on creative ideation and examine relevant moderators. But first, why should a walk, a run, or a higher fitness level boost creativity at all?

Importantly, creative ideation can be considered the result of a complex interplay of cognitive functions, which is outlined in prominent dual-process models of creative thinking [16, 17]. Specifically, dual-process models suggest a dynamic interplay of associative (divergent) and executive (convergent) processes that establish generative and elaborative/evaluative modes of creative thinking. Furthermore, creative ideation performance is associated with higher executive control [18,19,20,21,22] and fluid as well as crystallized intelligence [23]. In line with these behavioral findings, neuroscientific creativity studies indicated higher involvement of brain areas associated with executive control [24,25,26] (but see [27]; for meta-analyses see [28,29,30]), memory processes [31, 32], and internal attention [33] during creative idea generation tasks. Taken together, physical activity may increase creative ideation performance via improving executive control, attention processes, and memory [34, 35].

The enhancement of cognitive functioning through physical activity is a field of increased interest [6]. Etnier and colleagues [2] conducted one of the first meta-analyses on cognitive functioning and physical activity, which showed a small positive overall effect (d = 0.25). Chang et al. [36] indicated a positive effect of acute (i.e., one single bout of) exercise on information processing, attention, crystallized intelligence, and executive functions [37,38,39]. Ludyga et al. [40] confirmed these findings and suggested that age is an important moderator, as the effects of physical activity were strongest among preadolescent children and older adults. Wilke et al. [9] extended this finding to acute effects of resistance training (i.e., strength training involving series of different exercises in the upper and lower limbs), which also enhances cognitive functioning in healthy adults. Furthermore, the meta-analysis of Etnier et al. [34] indicated that not only single bouts of exercises, but also chronic (i.e., longer lasting and repeated) physical activities have a positive pooled effect on cognitive performance [6, 7]. This indicates that a broad range of physical activities is associated with a variety of cognitive function increases. However, although the impact of acute and chronic physical activity on basic cognitive functions has been replicated in several meta-analyses [9, 34, 35, 41, 42], it is still unclear if physical activity enhances creative ideation performance.

While some empirical studies indicated an association between creative ideation performance and acute as well as chronic physical activity [43, 44], others did not [45]. To the best of our knowledge, meta-analytic approaches on this topic are very rare [15, 46]. Only Chang et al. [36] evaluated performance changes in divergent thinking tasks (i.e., alternate uses tasks) after acute physical activity. They found a weakly positive, but not significant pooled effect size of d = 0.11. Yet, this analysis included only 26 effects and was not specifically designed to investigate creative ideation performance. Hence, systematic quantitative aggregation of studies examining associations between physical activity and creative ideation is needed.

Of note, creativity research on the boosting effects of physical activity is rather diverse, and studies largely differ in design (e.g., interventional, cross-sectional), type of physical activity (e.g., aerobic exercise, running), implementation of intervention (e.g., acute, chronic), time of measurement (e.g., during, after an intervention), and the creativity domain of the task (e.g., verbal, figural). Furthermore, the extant literature differentiates between qualitative and quantitative indicators of creative ideation performance [23]. In particular, the number of different ideas (i.e., fluency) is the most frequently applied quantitative measure of creative thinking, besides flexibility (i.e., number of different categories used to produce ideas) and elaboration (i.e., number of details added to an idea). Qualitative indicators, on the other hand, are originality and other measures of creativity, which are traditionally assessed with frequency-based scores and external creativity ratings [47, 48]. Furthermore, some studies utilized composite scores of creativity (e.g., adding up the originality of all responses), thus aggregating qualitative and quantitative aspects [49].

Using multiple creativity indices from single studies violates the criterion of effect size independence in meta-analysis, which is why this study applied a multilevel meta-analytic approach with three levels [50,51,52]. We performed two separate analyses. First, we focused on cross-sectional data, which allowed analysis of the association between habitual physical activity (both self-reported and behavioral) and creative ideation performance. Second, we meta-analyzed intervention studies, which experimentally modified physical activity to increase creative ideation performance. This two-step approach allowed us to investigate, first, if an association between habitual physical activity and creative ideation performance exists [43] and, second, whether physical activity may have causal effects on creative ideation performance outcomes [6, 53].

Methods

Search Strategy

A systematic literature search for studies examining physical activity and creative ideation performance was carried out, based on the guidelines of the PRISMA statement [54]. Relevant articles were identified in the following online databases: Scopus, PsyArXiv, Google Scholar, Zenodo, PsycINFO, PubMed, Web of Science, CINAHL, and ProQuest. The search strings comprised terms describing physical activity (physical activity, bodily movement, aerobic exercise, exercise program, dancing, physical fitness, walking, and running) and terms describing creative ideation performance (creativity, creative thinking, divergent thinking, creative potential, open problem-solving, creative ideation, originality, and fluency; see Additional file 1 for the exact search strings for each database). The date of last search was January 2022. Review articles, qualitative research, case studies, and study protocols were excluded. Furthermore, the reference sections of relevant articles were screened for additional research [15, 36, 46]. There were no time or language restrictions. Both published and unpublished studies (e.g., dissertations), cross-sectional, and longitudinal/intervention studies were eligible for analysis.

Inclusion and Exclusion Criteria

Studies were required to report measures of creative ideation performance. For the purpose of this study, we focused on the (more common) divergent thinking tasks of creativity [55] and the relevant indicators of quantity and quality of ideas. Performance data on convergent creativity tasks, such as the remote association task [56], were not extracted (similar approach, see [23].) Physical activity was defined as any kind of (bodily) movement (produced by skeletal muscles) that results in a substantial increase over the resting energy expenditure [39, 57]. Studies investigating movements of lower energy expenditure, such as hand waving [58] and hand contractions [59, 60], were thus excluded from analysis. Eligible studies comprised different types of physical activity such as running and aerobic exercise. For the meta-analysis of cross-sectional data, studies with various measures of physical activity, such as self-report, fitness-test, and accelerometers, were eligible.

Data Extraction and Coding

Extracted data included (a) basic study information (authors, publication year, mean age), (b) indicators of creative ideation (fluency, flexibility, originality, elaboration, and composite score), (c) creativity domain (verbal, figural), (d) population (adults, children), (e) gender (percentage of female participants), (f) implementation of intervention (acute, chronic), (g) time of measurement (during, after), (h) study design (between, within), (i) effect size measures (effect size, standard error, standard deviation), and (j) study quality (study quality score, see Additional file 2). Study authors were contacted in cases of insufficient data for effect size calculation.

Study Quality and Risk of Bias

We applied two scales adapted from Frith et al. [15] to assess the study quality of cross-sectional and intervention studies. The protocols comprised six items (for cross-sectional studies) and eight items (for intervention studies), focusing on bias detection, control group/condition, randomization, and creative ideation task specifications (Additional file 2). Each item was scored 1 if the respective criterion was met and 0 if not. The resulting study quality score served as moderator in analysis. For intervention studies, the maximum of the quality score was 7 and the lowest score was 2, with higher scores indicating higher quality of the study (see Table 2; for cross-sectional studies: Max = 5, Min = 3; see Table 1). Studies were not excluded based on quality.

Statistical Analysis

Most studies reported effect sizes for more than one indicator of creative ideation performance (e.g., fluency, originality). The independence of effect sizes is crucial to avoid an overlap of information of the included effect sizes and to provide unbiased effect size estimations [50, 52]. The present multilevel meta-analysis structure integrated multiple effect sizes both within and between studies by distinguishing three levels of variance. The sampling variance of the extracted effect sizes (i.e., outcomes) was modeled at level 1, the variance of effect sizes within the same study at level 2, and the variance of effect sizes between different studies at level 3 [50, 52]. Heterogeneity was examined with moderator analysis if less than 75% of the total amount of variance could be attributed to the sampling variance at level 1 [61], which indicated that a meaningful amount of variance lay within and between the studies (i.e., at level 2 and level 3 [52]).

Two separate multilevel meta-analyses were conducted. The first meta-analysis focused on cross-sectional effects of physical activity on creative ideation performance and used the correlation coefficient r as the effect size measure. Quantification of the effect size magnitude was based on the thresholds devised by Cohen: small (0.1), medium (0.3), and large (0.5) [62]. A positive effect size indicated that higher levels of habitual physical activity were associated with a higher level of creative ideation performance. The second meta-analysis examined the effects of physical activity interventions on creative ideation. This analysis used Hedges’ g, which provides a better effect size estimation for small sample sizes as compared to Cohen's d [62]. Quantification of the effect size magnitude for Hedges’ g was performed using the thresholds defined for Cohen’s d (see above; [62]). A positive effect size indicated higher levels of creative ideation after the physical activity intervention than before. The meta-analysis of intervention data included studies with between- and within-subjects designs. The correlation between two time points of assessment was set to r = 0.50 to estimate the corresponding effect sizes for studies with a within-design not reporting this association. We further calculated sensitivity analyses by applying the correlation coefficients of r = 0.10 and r = 0.90.

Statistical analysis was performed with R [63], using the rma.mv function of the metafor package ([64]; for a detailed tutorial, see [52]). Restricted maximum likelihood (REML) estimation method was used for estimating parameters of the meta-analytic model [50, 52]. Moderator analyses for categorical and continuous moderator variables were conducted (e.g., study quality). Dummy-coded variables were created for the categorical moderators, comprising indicators of creative ideation performance (flexibility, originality, elaboration, or composite score vs. fluency [reference category]; for a similar approach, see [23, 65]), population (adults vs. children [reference category]), and creativity domain (verbal vs. figural [reference category]). For the meta-analysis of intervention studies, the implementation of intervention (chronic vs. acute [reference category]), time of measurement (during vs. after [reference category]), and the study design (between vs. within [reference category]) were added as further categorical moderators. For both meta-analyses, publication year, gender (percentage of female participants), and study quality were treated as continuous moderators.

We provide visualization of individual studies’ results using forest plots for meta-analyses with multiple outcomes [66]. Before drawing the forest plot, separate random-effects meta-analyses were conducted for each study. Publication bias was examined through funnel plots [66] and Egger’s regression test. Publication bias refers to the problem that studies with significant results, and large effect sizes are more likely to be published than studies without significance [62]. This can lead to a bias in effect size estimation.

Table 1 Study characteristics: cross-sectional studies
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Results

Study Selection and Study Characteristics

Database search identified a total of 29,184 articles. Four articles were identified through other resources. After removing duplicates and screening titles and abstracts, 83 articles remained eligible for further examination. In total, another 48 articles had to be excluded that presented either another topic (14), qualitative research (2), or planned research (1), were a review article (2), a case study (1), or a study protocol (1); 17 studies did not provide sufficient data to calculate effect sizes, 6 studies investigated movements with low energy expenditure, 1 study measured creativity using a self-description scale, and 3 studies provided no details on the type of examined creativity. A total of 35 studies were included in the analyses (i.e., 7 cross-sectional studies and 28 intervention studies; see Fig. 1). Studies were published between 1985 and 2022. For detailed study description, see Table 1 and Table 2.

Fig. 1
figure 1

PRISMA flow diagram

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Table 2 Study characteristics: Intervention studies
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Cross-Sectional Studies

Seven studies were included for analysis, with a total of 17 effect sizes based on the data of 2073 participants. The aggregated effect was medium-sized, r = 0.22 (SE = 0.06, p = 0.002, 95% CI [0.10–0.34]). The estimated variance between studies (level 3) was τ2 = 0.025 (81.52%) and within studies (level 2) was τ2 = 0.000 (< 0.01%). 18.48% of the total variance could be attributed to the variance at level 1. Figure 2 shows a forest plot for all included effect sizes.

Fig. 2
figure 2

Forest plot of cross-sectional studies. J represents the number of outcomes. Black squares in the forest plot represent the meta-analytical study mean and the corresponding 95% confidence interval. Grey confidence intervals represent the sampling variance of observed effect sizes within each study and indicate the influence of the study sample mean on study precision. The thickness of the grey confidence intervals is proportional to the number of effect sizes within a study [66]. The numbers in parentheses designate the independent subsamples within a study

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Moderator analyses for indicators of creative ideation performance (p = 0.658), creativity domain (p = 0.727), population (p = 0.215), study quality (p = 0.586), gender (p = 0.271), and publication year (p = 0.060) were not significant. For details on moderator analysis, see Additional file 3. In line with Egger’s regression test (p = 0.228), the funnel plot did not indicate publication bias (Fig. 3).

Fig. 3
figure 3

Funnel plot of cross-sectional studies. The size of the dots is proportional to the number of effect sizes included in the studies

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Intervention Studies

Twenty-eight studies were included for analysis, with a total of 115 effect sizes and a total of 1624 participants. The aggregated effect size was medium, with Hedges’ g = 0.47 (SE = 0.09, p < 0.001, 95% CI [0.30–0.65]). The estimated variance components were at level 3 τ2 = 0.216 (62.65%) and at level 2 τ2 = 0.075 (21.84%). 15.51% of the total amount of variance could be attributed to the sampling variance at level 1. Figure 4 shows the forest plot of all effects.

Fig. 4
figure 4

Forest plot of cross-sectional studies. J represents the number of outcomes. Black squares in the forest plot represent the meta-analytical study mean and the corresponding 95% confidence interval. Grey confidence intervals represent the sampling variance of observed effect sizes within each study and indicate the influence of the study sample mean on study precision. The thickness of the grey confidence intervals is proportional to the number of effect sizes within a study [66]. The numbers in parentheses designate the independent subsample within a study

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Moderator analyses for indicators of creative ideation performance (all p = 0.699), creativity domain (p = 0.549), population (p = 0.060), time of measurement (p = 0.198), and study design (p = 0.673) were not significant. Furthermore, the continuous moderator analysis for study quality (p = 0.720), gender (p = 0.083), and publication year (p = 0.840) were not significant. However, the significant moderator analysis for implementation of intervention (p = 0.020) showed that the mean effect of acute physical activity was lower (Hedges’ g = 0.37, p = 0.020) than the mean effect of chronic physical activity (Hedges’ g = 0.89, p < 0.001; details on moderator analysis see Additional file 3). In accordance with a significant Egger’s regression test (p = 0.009), the asymmetrical distribution of effects in the funnel plot was indicative of small-study effects, which could imply publication bias (see Fig. 5).

Fig. 5
figure 5

Funnel plot of intervention studies. The size of the dots is proportional to the number of effect sizes included in the studies

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Robustness of the estimated effect was examined through outlier detection. The effects of studies were judged as outliers if the aggregated effect size exceeded ± 2 standard deviations. Due to this, we trimmed the available data and excluded five effect sizes (three from one study) from analysis. The nonsignificant Egger’s regression test of the trimmed dataset (p = 0.911) did not argue for an asymmetrical distribution of effects. The pooled effect size of the reduced dataset still indicated a significant Hedges’ g = 0.39 (SE = 0.06, p < 0.001, 95% CI [0.27–0.51]).

Further sensitivity analyses for the overall-effect were calculated for within-design studies applying r = 0.10 and r = 0.90 for the correlation between two time points to estimate the corresponding effect sizes. These analyses showed similar results for both correlations (r = 0.10: Hedges’ g = 0.47, p < 0.001; r = 0.90: Hedges’ g = 0.46, p < 0.001).

Discussion

In this systematic quantitative review, which includes two meta-analyses, we analyzed the effect of physical activity on creative ideation performance. The cross-sectional meta-analysis indicated a positive association between habitual physical activity and creative ideation performance. The second meta-analysis showed that physical activity interventions enhance creative ideation performance. Moderator analysis indicated that even short periods of physical activity such as running or walking may boost creative potential. However, longer trainings showed stronger effects. Furthermore, physical activity did neither differentially affect verbal or figural creative ideation, nor the quantity (e.g., fluency) or quality (e.g., originality) of ideas. Neither population, gender, nor study quality moderated the observed effect sizes. The highest proportion of variance of effects was observed between studies at level 3, which could indicate high variability in methods for intervention as well as cross-sectional studies.

The included cross-sectional studies showed a medium effect of habitual physical activity on measures of creative ideation performance. This effect is in line with findings for cognitive functioning [39]. However, the pooled effect was based on seven methodologically heterogeneous studies. Five of these studies assessed habitual physical activity by self-report measures such as the Freiburger Questionnaire on Physical Activity (FQPA [79]; see Table 1) and only two studies applied behavioral measures of physical activity. Rominger et al. [43] used accelerometer sensors, which were worn for 5 days in everyday life, and Latorre Román and colleagues [74] applied a fitness test battery in a sample of 308 primary school students to measure physical activity. Although the meta-analysis on cross-sectional data indicated a medium-sized positive link between creative ideation performance and habitual physical activity, the causal direction of the effect in these studies remains unclear.

In order to investigate the causal effect of physical activity on creativity, the second part of this study examined intervention studies, which showed a medium-sized effect. In a recent narrative review, Frith et al. [15] concluded that the empirical rigor of available studies on the association between physical activity and creative ideation performance is quite diverse, which would consequently hamper the quality of meta-analyses. Basically, this criticism could also apply to the present meta-analysis. However, in this particular context it is important to consider that 16 further studies (46% of studies) have been published since Firth’s review. This indicates the increasing relevance of this research topic and the rapid accumulation of data. During the last decade, 86% of the seven cross-sectional studies and about 82% of the 28 included intervention studies have been published (see Tables 1 and 2). Furthermore, to address this critical issue statistically, we have added the continuous moderators of scientific quality to our multilevel analyses, which, however, did not show significant influences on the two pooled effect sizes.

While cross-sectional studies do not permit causal conclusions, their designs are much more robust [15]. This is particularly relevant because double-blinded intervention studies, which would control for potential placebo-effects, are not available in this field of research. This contrasts with studies investigating creativity-enhancing effects by means of substance intake, such as alcohol, cocaine, or caffeine [112,113,114,115], as well as brain stimulation studies [116,117,118]. In these experiments, the experimenter, the participants, and the originality raters can be blinded more easily. Furthermore, in these studies active control groups and control conditions only differ with respect to the dose of substance of interest.

All included studies in our meta-analyses used diverse methodological approaches, especially concerning the type of physical activity applied. Specifically, chronic physical activity intervention studies are less common, and most studies investigated the effects of single exercise sessions on creative ideation performance (75%; see Table 2). This might be one reason for the observed heterogeneity and high level of observed between-study variances of 63% for intervention studies. Nevertheless, most moderators of the present meta-analyses failed to show significance. This observation might have at least two potential explanations. First, these moderators have no effects. The null finding for indicator of creativity domain and indicators of creative ideation performance is in line with a meta-analysis reporting similar enhancing effects of chronic physical activity for memory, attention, and executive functions [119]. A second explanation might be a lack of statistical power to detect such moderators, specifically when looking at meta-analysis on more basic cognitive functions. A recent meta-analysis of Ludyga et al. [119] analyzed 80 studies, and the review of reviews of Biddle et al. [6] even reported the aggregated information of 392 studies. In this context, it should be noted that gender showed a trend for significance to moderate the pooled effect of the present meta-analysis. Physical activity interventions led to lower enhancement as the percentage of women increased. This finding is well in accordance with Ludyga et al. [119], who showed a generally small improvement in cognitive function after chronic interventions, which was less pronounced in women. In addition, due to the high heterogeneity of approaches to describe and report exercise interventions (e.g., intensity), the study details are not sufficient to investigate potentially relevant moderators, such as type of exercise and exercise intensity. This warrants further empirical studies with high methodological rigor [15]. Particularly, cross-sectional studies have the great potential to complement the findings of randomized and well-controlled intervention studies [39, 72]. This would be important to improve the quality and quantity of available data, which would in turn allow to investigate potential moderating variables in greater detail. The increase in available studies should also ameliorate the observed publication bias (for intervention studies), which did not strongly impact the reported study results. After adjustment for publication bias (via trimming of high effects), the effect size remained quite similar. Notwithstanding these restrictions, the present meta-analyses revealed a reliable and robust effect of acute, chronic, and habitual physical activity on creative ideation performance [2].

The meta-analysis of intervention studies indicated an effect of physical activity on creative ideation performance, which was more pronounced for chronic in contrast to acute (single bouts of) physical activity [36]. This finding is in line with Etnier et al. [2], who reported stronger effects for chronic interventions on cognition (but see [42] for children). Although differential effects on more basic cognition are well known, the relevant mechanisms for chronic and acute interventions are still poorly understood.

Presumed Psychological Mechanisms

The findings of the present meta-analyses are in line with the general assumption that physical activity offers a change, that is the transition from one state to the other, which could enhance the quality and the quantity of ideas by preparing people to deal with these changes [96, 98]. Main et al. [98] showed in three experiments that changes in physical activity enhanced creative thinking, while inactivity or repetitive physical activity lowered it. However, this line of argumentation is strongly restricted to acute effects of physical activity and does not provide explanations for the stronger chronic effects of physical activity on creative ideation performance. A second suggested mechanism why physical activity could boost creative ideation performance besides gearing for change is that acute as well as chronic physical activity is associated with higher positive affect and reduced negative affect and stress [120,121,122,123]. Based on the broaden and build theory, which assumes that positive affect coincides with more original ideas via cognitive flexibility [65, 124], the physical activity-associated affective shift was suggested to increase creative ideation performance [43, 87, 125]. Although this hypothesis has been investigated with cross-sectional and intervention studies, to the best of our knowledge, no study to date has confirmed the implied mediating role of positive affect on creative ideation outcome [43, 82, 98, 108]. However, as outlined by Biddle et al. [6], the effects of physical activity on stress (negative affect) and positive affect in ecologically valid settings could be a fruitful area for future research [43, 126]. The collection of extensive longitudinal data might provide a more detailed picture of the mechanisms of physical activity on affect and creative ideation performance [126]. Besides these psychological mechanisms, physiological mechanisms may also explain the enhancing effect of physical activity on creative cognition. If sports, exercise, and fitness training stimulate creative cognition via improvements in cognitive functioning, such as executive control, attention, and memory processes [7, 119], similar physiological mechanisms might be valid for both domains.

Presumed Physiological Mechanisms

Changes in the brain-derived neurotrophic factor (BDNF), structural changes in brain areas, functional connectivity changes, as well as changes in blood flow and neurotransmitters constitute powerful physiological mechanisms tightly linked to physical activity [2, 119, 127,128,129,130]. Although acute physical activity can induce changes in BDNF, (cerebral) blood flow, and the release of neurotransmitters dopamine and norepinephrine, structural and functional physiological changes are more strongly related to chronic interventions [5, 7, 38]. Accordingly, a two-week running intervention induced structural brain changes associated with improvements in participants’ affective functions. Fink et al. [131] further showed that (short) chronic physical activity interventions might have the potential to modulate psychological functions via changes in brain structure [39, 130]. Since positive affect is associated with creative ideation performance [43], this study might hence provide one potential line of reasoning of how creative ideation could be modulated by chronic physical activity-induced brain changes. A meta-analysis on fMRI activation data indicated that physical exercise leads to activation changes in the precuneus, frontoparietal networks, and default mode networks [132], which are associated with creative ideation performance [25, 26, 133,134,135,136]. This is in accordance with reviews concluding that physical activity has the potential to improve the structural plasticity and function of the brain throughout the life span, specifically in neurological and psychiatric patients [5, 7, 39, 137].

The neuro-protective role of physical activity was coined brain health and could constitute an important target of future creativity research [5, 7, 39, 41], where creative ideation performance may serve as a meaningful behavioral indicator of a flexible, original, innovative, and healthy brain in children as well as in adults. Importantly and critically, however, research on boosting creative performance by means of physical activity needs further rigorous and well-powered investigations in randomized controlled trials and with proper control groups involving neurophysiological methods (see [39], for cognitive functions). Specifically, the dose–response relationship (i.e., effect of duration, repetition, and intensity) between physical activity and creative ideation performance increases seems to be an important target for future research in order to further confirm causality [6, 9, 34, 53, 119].

Conclusion

Creative cognition is relevant for team sports [138], and physical activity and sports, in turn, can boost creative ideation performance. The present meta-analysis highlights this synergistic effect [39] by suggesting an impact of physical activity on creative idea generation. The observed enhancing medium-sized effect is in line with the current state of knowledge assuming a boost of basic cognitive functions, such as executive control, attention, and memory due to physical activity [2, 7, 119]. Furthermore, the present study expands this evidence to the field of creativity research and suggests that physical activity could increase the complex and dynamic interplay of cognitive functions, ultimately facilitating creative ideation. The present findings encourage further investigations in representative samples to learn more about the mechanisms of creativity enhancement via physical activity, which is a growing field of interest relevant for health, sport, and sports medicine [72, 82, 139]. In the future, rigorous cross-sectional and experimental intervention research could help to further develop public health recommendations for physical activity as an important lifestyle factor [39].

Availability of data and materials

All data are available on request.

Code availability

R script used in this study is available on request.

References

  1. Wewege MA, Desai I, Honey C, Coorie B, Jones MD, Clifford BK, et al. The effect of resistance training in healthy adults on body fat percentage, fat mass and visceral fat: a systematic review and meta-analysis. Sports Med. 2021. https://doi.org/10.1007/s40279-021-01562-2.

    Article  PubMed  Google Scholar 

  2. Etnier JL, Salazar W, Landers DM, Petruzzello SJ, Han M, Nowell P. The influence of physical fitness and exercise upon cognitive functioning: a meta-analysis. J Sport Exerc Psychol. 1997;19:249–77. https://doi.org/10.1123/jsep.19.3.249.

    Article  Google Scholar 

  3. Rodriguez-Ayllon M, Cadenas-Sánchez C, Estévez-López F, Muñoz NE, Mora-Gonzalez J, Migueles JH, et al. Role of physical activity and sedentary behavior in the mental health of preschoolers, children and adolescents: a systematic review and meta-analysis. Sports Med. 2019;49:1383–410. https://doi.org/10.1007/s40279-019-01099-5.

    Article  PubMed  Google Scholar 

  4. Hu MX, Turner D, Generaal E, Bos D, Ikram MK, Ikram MA, et al. Exercise interventions for the prevention of depression: a systematic review of meta-analyses. BMC Public Health. 2020;20:1255. https://doi.org/10.1186/s12889-020-09323-y.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Prakash RS, Voss MW, Erickson KI, Kramer AF. Physical activity and cognitive vitality. Annu Rev Psychol. 2015;66:769–97. https://doi.org/10.1146/annurev-psych-010814-015249.

    Article  PubMed  Google Scholar 

  6. Biddle SJ, Ciaccioni S, Thomas G, Vergeer I. Physical activity and mental health in children and adolescents: an updated review of reviews and an analysis of causality. Psychol Sport Exerc. 2019;42:146–55. https://doi.org/10.1016/j.psychsport.2018.08.011.

    Article  Google Scholar 

  7. Erickson KI, Hillman C, Stillman CM, Ballard RM, Bloodgood B, Conroy DE, et al. Physical activity, cognition, and brain outcomes: a review of the 2018 physical activity guidelines. Med Sci Sports Exerc. 2019;51:1242–51. https://doi.org/10.1249/MSS.0000000000001936.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Runco MA, Jaeger GJ. The standard definition of creativity. Creat Res J. 2012;24:92–6. https://doi.org/10.1080/10400419.2012.650092.

    Article  Google Scholar 

  9. Wilke J, Giesche F, Klier K, Vogt L, Herrmann E, Banzer W. Acute effects of resistance exercise on cognitive function in healthy adults: a systematic review with multilevel meta-analysis. Sports Med. 2019. https://doi.org/10.1007/s40279-019-01085-x.

    Article  PubMed  Google Scholar 

  10. Memmert D. Tactical creativity in sport. In: Kaufman JC, Glăveanu VP, Baer J, editors. Cambridge handbook of creativity across domains. Cambridge: Cambridge University Press; 2017. p. 479–91. https://doi.org/10.1017/9781316274385.026.

    Chapter  Google Scholar 

  11. Kaufman JC, Beghetto RA. In praise of Clark Kent: creative metacognition and the importance of teaching kids when (not) to be creative. Roeper Rev. 2013;35:155–65. https://doi.org/10.1080/02783193.2013.799413.

    Article  Google Scholar 

  12. Sternberg RJ, Lubart TI. The concept of creativity: prospects and paradigms. In: Sternberg RJ, editor. Handbook of creativity. Cambridge: Cambridge University Press; 1999. p. 3–15.

    Google Scholar 

  13. Beghetto RA, Karwowski M. Unfreezing creativity: a dynamic micro-longitudinal approach. In: Beghetto RA, Corazza GE, editors. Dynamic perspectives on creativity: new directions for theory, research, and practice in education. Cham: Springer; 2019. p. 7–25. https://doi.org/10.1007/978-3-319-99163-4_2.

    Chapter  Google Scholar 

  14. Runco MA, Acar S. Divergent thinking as an indicator of creative potential. Creat Res J. 2012;24:66–75. https://doi.org/10.1080/10400419.2012.652929.

    Article  Google Scholar 

  15. Frith E, Ryu S, Kang M, Loprinzi PD. Systematic review of the proposed associations between physical exercise and creative thinking. Eur J Psychol. 2019;15:858–77. https://doi.org/10.5964/ejop.v15i4.1773.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Sowden PT, Pringle A, Gabora L. The shifting sands of creative thinking: connections to dual-process theory. Think Reason. 2015;21:40–60. https://doi.org/10.1080/13546783.2014.885464.

    Article  Google Scholar 

  17. Benedek M, Jauk E. Spontaneous and controlled processes in creative cognition. In: Fox K, Christoff K, editors. The Oxford handbook of spontaneous thought: mind-wandering, creativity, and dreaming. New York: Oxford University Press; 2018. p. 285–98. https://doi.org/10.1093/oxfordhb/9780190464745.013.22.

    Chapter  Google Scholar 

  18. Rominger C, Fink A, Weiss EM, Bosch J, Papousek I. Allusive thinking (remote associations) and auditory top-down inhibition skills differentially predict creativity and positive schizotypy. Cogn Neuropsychiatry. 2017;22:108–21. https://doi.org/10.1080/13546805.2016.1278361.

    Article  PubMed  Google Scholar 

  19. Edl S, Benedek M, Papousek I, Weiss EM, Fink A. Creativity and the Stroop interference effect. PAID. 2014;69:38–42. https://doi.org/10.1016/j.paid.2014.05.009.

    Article  Google Scholar 

  20. Rominger C, Papousek I, Weiss EM, Schulter G, Perchtold CM, Lackner HK, Fink A. Creative thinking in an emotional context: specific relevance of executive control of emotion-laden representations in the inventiveness in generating alternative appraisals of negative events. Creat Res J. 2018;30:256–65. https://doi.org/10.1080/10400419.2018.1488196.

    Article  Google Scholar 

  21. Zabelina DL, Robinson MD, Council JR, Bresin K. Patterning and nonpatterning in creative cognition: insights from performance in a random number generation task. Psychol Aesthet Creat Arts. 2012;6:137–45. https://doi.org/10.1037/a0025452.

    Article  Google Scholar 

  22. Zabelina DL, Friedman NP, Andrews-Hanna J. Unity and diversity of executive functions in creativity. Conscious Cogn. 2019;68:47–56. https://doi.org/10.1016/j.concog.2018.12.005.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Gerwig A, Miroshnik K, Forthmann B, Benedek M, Karwowski M, Holling H. The relationship between intelligence and divergent thinking—a meta-analytic update. J Intell. 2021;9:23. https://doi.org/10.3390/jintelligence9020023.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Rominger C, Papousek I, Perchtold CM, Weber B, Weiss EM, Fink A. The creative brain in the figural domain: distinct patterns of EEG alpha power during idea generation and idea elaboration. Neuropsychologia. 2018;118:13–9. https://doi.org/10.1016/j.neuropsychologia.2018.02.013.

    Article  PubMed  Google Scholar 

  25. Rominger C, Papousek I, Perchtold CM, Benedek M, Weiss EM, Weber B, et al. Functional coupling of brain networks during creative idea generation and elaboration in the figural domain. Neuroimage. 2020;207: 116395. https://doi.org/10.1016/j.neuroimage.2019.116395.

    Article  PubMed  Google Scholar 

  26. Beaty RE, Benedek M, Kaufman SB, Silvia PJ. Default and executive network coupling supports creative idea production. Sci Rep. 2015;5:10964. https://doi.org/10.1038/srep10964.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Rominger C, Koschutnig K, Memmert D, Papousek I, Perchtold-Stefan CM, Benedek M, et al. Brain activation during the observation of real soccer game situations predicts creative goal scoring. Soc Cogn Affect Neurosci. 2021;16:707–15. https://doi.org/10.1093/scan/nsab035.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Gonen-Yaacovi G, de Souza LC, Levy R, Urbanski M, Josse G, Volle E. Rostral and caudal prefrontal contribution to creativity: a meta-analysis of functional imaging data. Front Hum Neurosci. 2013;7:465. https://doi.org/10.3389/fnhum.2013.00465.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Boccia M, Piccardi L, Palermo L, Nori R, Palmiero M. Where do bright ideas occur in our brain? Meta-analytic evidence from neuroimaging studies of domain-specific creativity. Front Psychol. 2015;6:1195. https://doi.org/10.3389/fpsyg.2015.01195.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Pidgeon LM, Grealy M, Duffy AHB, Hay L, McTeague C, Vuletic T, et al. Functional neuroimaging of visual creativity: a systematic review and meta-analysis. Brain Behav. 2016;6: e00540. https://doi.org/10.1002/brb3.540.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Benedek M, Jauk E, Fink A, Koschutnig K, Reishofer G, Ebner F, Neubauer AC. To create or to recall? Neural mechanisms underlying the generation of creative new ideas. Neuroimage. 2014;88:125–33. https://doi.org/10.1016/j.neuroimage.2013.11.021.

    Article  PubMed  Google Scholar 

  32. Benedek M, Schües T, Beaty RE, Jauk E, Koschutnig K, Fink A, Neubauer AC. To create or to recall original ideas: brain processes associated with the imagination of novel object uses. Cortex. 2018;99:93–102. https://doi.org/10.1016/j.cortex.2017.10.024.

    Article  PubMed  Google Scholar 

  33. Fink A, Benedek M. EEG alpha power and creative ideation. Neurosci Biobehav Rev. 2014;44:111–23. https://doi.org/10.1016/j.neubiorev.2012.12.002.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Etnier JL, Nowell PM, Landers DM, Sibley BA. A meta-regression to examine the relationship between aerobic fitness and cognitive performance. Brain Res Rev. 2006;52:119–30. https://doi.org/10.1016/j.brainresrev.2006.01.002.

    Article  PubMed  Google Scholar 

  35. Smith PJ, Blumenthal JA, Hoffman BM, Cooper H, Strauman TA, Welsh-Bohmer K, et al. Aerobic exercise and neurocognitive performance: a meta-analytic review of randomized controlled trials. Psychosom Med. 2010;72:239–52. https://doi.org/10.1097/PSY.0b013e3181d14633.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Chang YK, Labban JD, Gapin JI, Etnier JL. The effects of acute exercise on cognitive performance: a meta-analysis. Brain Res. 2012;1453:87–101. https://doi.org/10.1016/j.brainres.2012.02.068.

    Article  CAS  PubMed  Google Scholar 

  37. Lambourne K, Tomporowski P. The effect of exercise-induced arousal on cognitive task performance: a meta-regression analysis. Brain Res. 2010;1341:12–24. https://doi.org/10.1016/j.brainres.2010.03.091.

    Article  CAS  PubMed  Google Scholar 

  38. McMorris T, Hale BJ. Differential effects of differing intensities of acute exercise on speed and accuracy of cognition: a meta-analytical investigation. Brain Cogn. 2012;80:338–51. https://doi.org/10.1016/j.bandc.2012.09.001.

    Article  PubMed  Google Scholar 

  39. Donnelly JE, Hillman CH, Castelli D, Etnier JL, Lee S, Tomporowski P, et al. Physical activity, fitness, cognitive function, and academic achievement in children: a systematic review. Med Sci Sports Exerc. 2016;48:1197–222. https://doi.org/10.1249/MSS.0000000000000901.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ludyga S, Gerber M, Brand S, Holsboer-Trachsler E, Pühse U. Acute effects of moderate aerobic exercise on specific aspects of executive function in different age and fitness groups: a meta-analysis. Psychophysiol. 2016;53:1611–26. https://doi.org/10.1111/psyp.12736.

    Article  Google Scholar 

  41. Colcombe S, Kramer AF. Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychol Sci. 2003;14:125–30. https://doi.org/10.1111/1467-9280.t01-1-01430.

    Article  PubMed  Google Scholar 

  42. Sibley BA, Etnier JL. The relationship between physical activity and cognition in children: a meta-analysis. Pediatric Exerc Sci. 2003;15:243–56. https://doi.org/10.1123/pes.15.3.243.

    Article  Google Scholar 

  43. Rominger C, Fink A, Weber B, Papousek I, Schwerdtfeger AR. Everyday bodily movement is associated with creativity independently from active positive affect: a Bayesian mediation analysis approach. Sci Rep. 2020;10:11985. https://doi.org/10.1038/s41598-020-68632-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Oppezzo M, Schwartz DL. Give your ideas some legs: the positive effect of walking on creative thinking. J Exp Psychol Learn Mem Cognit. 2014;40:1142–52. https://doi.org/10.1037/a0036577.

    Article  Google Scholar 

  45. Frith E, Loprinzi PD. Experimental effects of acute exercise and music listening on cognitive creativity. Physiol Behav. 2018;191:21–8. https://doi.org/10.1016/j.physbeh.2018.03.034.

    Article  CAS  PubMed  Google Scholar 

  46. Frith E, Miller S, Loprinzi PD. A review of experimental research on embodied creativity: revisiting the mind-body connection. J Creat Behav. 2019;1:1. https://doi.org/10.1002/jocb.406.

    Article  Google Scholar 

  47. Ceh SM, Edelmann C, Hofer G, Benedek M. Assessing raters: what factors predict discernment in novice creativity raters? J Creat Behav. 2021. https://doi.org/10.1002/jocb.515.

    Article  Google Scholar 

  48. Forthmann B, Jankowska DM, Karwowski M. How reliable and valid are frequency-based originality scores? Evidence from a sample of children and adolescents. Think Skills Creat. 2021;41: 100851. https://doi.org/10.1016/j.tsc.2021.100851.

    Article  Google Scholar 

  49. Forthmann B, Szardenings C, Holling H. Understanding the confounding effect of fluency in divergent thinking scores: revisiting average scores to quantify artifactual correlation. Psychol Aesthet Creat Arts. 2020;14:94–112. https://doi.org/10.1037/aca0000196.

    Article  Google Scholar 

  50. van den Noortgate W, López-López JA, Marín-Martínez F, Sánchez-Meca J. Three-level meta-analysis of dependent effect sizes. Behav Res Methods. 2013;45:576–94. https://doi.org/10.3758/s13428-012-0261-6.

    Article  PubMed  Google Scholar 

  51. Acar S, Sen S. A multilevel meta-analysis of the relationship between creativity and schizotypy. Psychol Aesthet Creat Arts. 2013;7:214–28. https://doi.org/10.1037/a0031975.

    Article  Google Scholar 

  52. Assink M, Wibbelink CJM. Fitting three-level meta-analytic models in R: a step-by-step tutorial. TQMP. 2016;12:154–74. https://doi.org/10.20982/tqmp.12.3.p154.

    Article  Google Scholar 

  53. Hill AB. The environment and disease: association or causation? Proc R Soc Med. 1965;58:295–300. https://doi.org/10.1177/003591576505800503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg. 2010;8:336–41. https://doi.org/10.1016/j.ijsu.2010.02.007.

    Article  PubMed  Google Scholar 

  55. Lebuda I, Zabelina DL, Karwowski M. Mind full of ideas: a meta-analysis of the mindfulness-creativity link. PAID. 2016;93:22–6. https://doi.org/10.1016/j.paid.2015.09.040.

    Article  Google Scholar 

  56. Mednick SA. The remote associates test. J Creat Behav. 1968;2:213–4. https://doi.org/10.1002/j.2162-6057.1968.tb00104.x.

    Article  Google Scholar 

  57. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;100:126–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Hu Y, Du X, Bryan-Kinns N, Guo Y. Identifying divergent design thinking through the observable behavior of service design novices. Int J Technol Des Educ. 2019;29:1179–91. https://doi.org/10.1007/s10798-018-9479-7.

    Article  Google Scholar 

  59. Rominger C, Papousek I, Fink A, Weiss EM. Enhancement of figural creativity by motor activation: effects of unilateral hand contractions on creativity are moderated by positive schizotypy. Laterality. 2014;19:424–38. https://doi.org/10.1080/1357650X.2013.858725.

    Article  PubMed  Google Scholar 

  60. Kim J. Physical activity benefits creativity: squeezing a ball for enhancing creativity. Creat Res J. 2015;27:328–33. https://doi.org/10.1080/10400419.2015.1087258.

    Article  Google Scholar 

  61. Hunter JE, Schmidt FL. Methods of meta-analysis: correcting error and bias in research findings. 2nd ed. Thousand Oaks: Sage; 2004.

    Book  Google Scholar 

  62. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Introduction to meta-analysis. Chichester: Wiley; 2009.

    Book  Google Scholar 

  63. R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2021.

  64. Viechtbauer W. Meta-analysis package for R. 2021. https://cran.r-project.org/web/packages/.

  65. Baas M, De Dreu CK, Nijstad BA. A meta-analysis of 25 years of mood-creativity research: hedonic tone, activation, or regulatory focus? Psychol Bull. 2008;134:779–806. https://doi.org/10.1037/a0012815.

    Article  PubMed  Google Scholar 

  66. Fernández-Castilla B, Declercq L, Jamshidi L, Beretvas SN, Onghena P, van den Noortgate W. Visual representations of meta-analyses of multiple outcomes: extensions to forest plots, funnel plots, and caterpillar plots. Methodology. 2020;16:299–315. https://doi.org/10.5964/meth.4013.

    Article  Google Scholar 

  67. Cantarero JC, Carranque GA. Relationship between creative thinking and exercise in adults [Relación entre el pensamiento creativo y el ejercicio físico en personas adultas]. Revista Iberoamericana de Psicologia del Ejercicio y el Deporte. 2016;11:47–52.

    Google Scholar 

  68. Artola T, Barraca J, Mosteiro P, Ancillo I, Poveda B, Sánchez N. PIC-A: Prueba de Imaginación Creativa para Adultos. Madrid: TEA Ediciones; 2012.

    Google Scholar 

  69. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–95. https://doi.org/10.1249/01.MSS.0000078924.61453.FB.

    Article  PubMed  Google Scholar 

  70. Cavallera GM, Boari G, Labbrozzi D, Bello ED. Morningness-eveningness personality and creative thinking among young people who play recreational sport. Soc Behav Person. 2011;39:503–18. https://doi.org/10.2224/sbp.2011.39.4.503.

    Article  Google Scholar 

  71. Torrance PE. Torrance test of creative thinking: norms-technical manual research edition -verbal Tests, forms A and B -figural tests, forms A and B. Princeton: Personnel Press; 1966.

    Google Scholar 

  72. Chen C, Mochizuki Y, Hagiwara K, Hirotsu M, Nakagawa S. Regular vigorous-intensity physical activity and walking are associated with divergent but not convergent thinking in Japanese young adults. Brain Sci. 2021. https://doi.org/10.3390/brainsci11081046.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Guilford JP. The nature of human intelligence. New York: McGraw-Hill; 1967.

    Google Scholar 

  74. Latorre Román PÁ, Pinillos FG, Pantoja Vallejo A, Berrios AB. Creativity and physical fitness in primary school-aged children. Pediatr Int. 2017;59:1194–9. https://doi.org/10.1111/ped.13391.

    Article  PubMed  Google Scholar 

  75. Artola T, Ancillo I, Barraca J, Mosteiro P. PIC-N: Prueba de Imaginación Creativa-Ninos. Madrid: TEA Ediciones; 2010.

    Google Scholar 

  76. Perchtold-Stefan CM, Fink A, Rominger C, Weiss EM, Papousek I. More habitual physical activity is linked to the use of specific, more adaptive cognitive reappraisal strategies in dealing with stressful events. Stress Health. 2020. https://doi.org/10.1002/smi.2929.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Jäger AO, Süß H-M, Beauducel A. Berliner Intelligenzstruktur- Test. Göttingen: Hogrefe; 1997.

    Google Scholar 

  78. Urban KK, Jellen HG. Test zum schöpferischen Denken–zeichnerisch: (TSD-Z). Frankfurt am Main: Swets Test Services; 1995.

    Google Scholar 

  79. Frey I, Berg A, Grathwohl D, Keul J. Freiburger Fragebogen zur körperlichen Aktivität-Entwicklung. Prüfung und Anwendung Soz Präventivmed. 1999;44:55–64. https://doi.org/10.1007/BF01667127.

    Article  CAS  Google Scholar 

  80. Piya-Amornphan N, Santiworakul A, Cetthakrikul S, Srirug P. Physical activity and creativity of children and youths. BMC Pediatr. 2020;20:118. https://doi.org/10.1186/s12887-020-2017-2.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Amornsriwatanakul A, Nakornkhet K, Katewongsa P, Choosakul C, Kaewmanee T, Konharn K, et al. Results from Thailand’s 2016 report card on physical activity for children and youth. J Phys Act Health. 2016;13:S291–8. https://doi.org/10.1123/jpah.2016-0316.

    Article  PubMed  Google Scholar 

  82. Aga K, Inamura M, Chen C, Hagiwara K, Yamashita R, Hirotsu M, et al. The effect of acute aerobic exercise on divergent and convergent thinking and its influence by mood. Brain Sci. 2021. https://doi.org/10.3390/brainsci11050546.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Blanchette DM, Ramocki SP, O’del JN, Casey MS. Aerobic exercise and creative potential: immediate and residual effects. Creat Res J. 2005;17:257–64. https://doi.org/10.1080/10400419.2005.9651483.

    Article  Google Scholar 

  84. Bollimbala A, James PS, Ganguli S. Impact of acute physical activity on children’s divergent and convergent thinking: the mediating role of a low body mass index. Percept Mot Skills. 2019;126:603–22. https://doi.org/10.1177/0031512519846768.

    Article  PubMed  Google Scholar 

  85. Bollimbala A, James PS, Ganguli S. The effect of Hatha yoga intervention on students’ creative ability. Acta Psychol (Amst). 2020;209: 103121. https://doi.org/10.1016/j.actpsy.2020.103121.

    Article  Google Scholar 

  86. Bollimbala A, James PS, Ganguli S. Impact of physical activity on an individual’s creativity: a day-level analysis. Am J Psychol. 2021;134:93–105. https://doi.org/10.5406/amerjpsyc.134.1.0093.

    Article  Google Scholar 

  87. Campion M, Levita L. Enhancing positive affect and divergent thinking abilities: play some music and dance. J Posit Psychol. 2014;9:137–45. https://doi.org/10.1080/17439760.2013.848376.

    Article  Google Scholar 

  88. Donnegan KF, Setti A, Allen AP. Exercise and creativity: can one bout of yoga improve convergent and divergent thinking? J Cognit Enhance. 2018;2:193–9. https://doi.org/10.1007/s41465-018-0082-3.

    Article  Google Scholar 

  89. Goff K, Torrance PE. Abbreviated torrance test for adults manual. Bensenville: Scholastic Testing Service; 2002.

    Google Scholar 

  90. Frith E, Ponce P, Loprinzi PD. Active or inert? An experimental comparison of creative ideation across incubation periods. J Creat Behav. 2021;55:5–14. https://doi.org/10.1002/jocb.429.

    Article  Google Scholar 

  91. Wallach MA, Kogan N. Modes of thinking in young children: a study of the creativity-intelligence distinction. Oxford: Holt, Rinehart & Winston; 1965.

    Google Scholar 

  92. Gondola JC. The enhancement of creativity through long and short term exercise programs. J Soc Behav Person. 1986;1:77–82.

    Google Scholar 

  93. Herman-Tofler LR, Tuckman BW. The effects of aerobic training on children’s creativity, self-perception, and aerobic power. Child Adolesc Psychiatr Clin N Am. 1998;7:773–90. https://doi.org/10.1016/S1056-4993(18)30211-6.

    Article  CAS  PubMed  Google Scholar 

  94. Latorre Román PÁ, Vallejo AP, Aguayo BB. Acute aerobic exercise enhances students’ creativity. Creat Res J. 2018;30:310–5. https://doi.org/10.1080/10400419.2018.1488198.

    Article  Google Scholar 

  95. Latorre Román PÁ, Berrios-Aguayo B, Aragón-Vela J, Pantoja-Vallejo A. Effects of a 10-week active recess program in school setting on physical fitness, school aptitudes, creativity and cognitive flexibility in elementary school children. A randomised-controlled trial. J Sports Sci. 2021;39:1277–86. https://doi.org/10.1080/02640414.2020.1864985.

    Article  Google Scholar 

  96. Leung AKY, Kim S, Polman E, Ong LS, Qiu L, Goncalo JA, Sanchez-Burks J. Embodied metaphors and creative “acts.” Psychol Sci. 2012;23:502–9. https://doi.org/10.1177/0956797611429801.

    Article  PubMed  Google Scholar 

  97. Ludyga S, Gerber M, Mücke M, Brand S, Weber P, Brotzmann M, Pühse U. The acute effects of aerobic exercise on cognitive flexibility and task-related heart rate variability in children with ADHD and healthy controls. J Atten Disord. 2020;24:693–703. https://doi.org/10.1177/1087054718757647.

    Article  PubMed  Google Scholar 

  98. Main KJ, Aghakhani H, Labroo AA, Greidanus NS. Change it up: inactivity and repetitive activity reduce creative thinking. J Creat Behav. 2020;54:395–406. https://doi.org/10.1002/jocb.373.

    Article  Google Scholar 

  99. Matsumoto K, Chen C, Hagiwara K, Shimizu N, Hirotsu M, Oda Y, et al. The effect of brief stair-climbing on divergent and convergent thinking. Front Behav Neurosci. 2022. https://doi.org/10.3389/fnbeh.2021.834097.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Murali S, Händel B. Motor restrictions impair divergent thinking during walking and during sitting. Psychol Res. 2022. https://doi.org/10.1007/s00426-021-01636-w.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Netz Y, Tomer R, Axelrad S, Argov E, Inbar O. The effect of a single aerobic training session on cognitive flexibility in late middle-aged adults. Int J Sports Med. 2007;28:82–7. https://doi.org/10.1055/s-2006-924027.

    Article  CAS  PubMed  Google Scholar 

  102. Österberg P, Olsson BK. Dancing: a strategy to maintain schoolchildren’s openness for idea generation. J Phys Educ Recreat Dance. 2021;92:20–5. https://doi.org/10.1080/07303084.2020.1866719.

    Article  Google Scholar 

  103. Finke RA, Punker S, Farah MJ. Reinterpreting visual patterns in mental imagery. Cogn Sci. 1989;13:51–78. https://doi.org/10.1016/0364-0213(89)90011-6.

    Article  Google Scholar 

  104. Patterson R, Frith E, Loprinzi P. The experimental effects of acute walking on cognitive creativity performance. J Behav Health. 2018. https://doi.org/10.5455/jbh.20180415053930.

    Article  Google Scholar 

  105. Richard V, Ben-Zaken S, Siekańska M, Tenenbaum G. Effects of movement improvisation and aerobic dancing on motor creativity and divergent thinking. J Creat Behav. 2021;55:255–67. https://doi.org/10.1002/jocb.450.

    Article  Google Scholar 

  106. Ruiz-Ariza A, Suárez-Manzano S, López-Serrano S, Martínez-López EJ. The effect of cooperative high-intensity interval training on creativity and emotional intelligence in secondary school: a randomised controlled trial: a randomised controlled trial. Eur Phys Educ Rev. 2019;25:355–73. https://doi.org/10.1177/1356336X17739271.

    Article  Google Scholar 

  107. Corbalán J, Martínez F, Donolo D, Alonso C, Tejerina M, Limiñana M. CREA Inteligencia Creativa. Una medida cognitiva de la creatividad. Madrid: TEA Ediciones; 2003.

    Google Scholar 

  108. Steinberg H, Sykes EA, Moss T, Lowery S, LeBoutillier N, Dewey A. Exercise enhances creativity independently of mood. Br J Sports Med. 1997;31:240–5. https://doi.org/10.1136/bjsm.31.3.240.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Tilp M, Scharf C, Payer G, Presker M, Fink A. Physical exercise during the morning school-break improves basic cognitive functions. Mind Brain Educ. 2020;14:24–31. https://doi.org/10.1111/mbe.12228.

    Article  Google Scholar 

  110. Young-Mi K, Hye-Jeon H. The effects of ‘Physics, Let’s Dance’, as an integrated dance art education program related to science subject, on the personality and creative thinking ability of elementary school students. Indian J Sci Technol. 2016. https://doi.org/10.17485/ijst/2016/v9i29/94754.

    Article  Google Scholar 

  111. Zhou Y, Zhang Y, Hommel B, Zhang H. The impact of bodily states on divergent thinking: evidence for a control-depletion account. Front Psychol. 2017;8:1546. https://doi.org/10.3389/fpsyg.2017.01546.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Benedek M, Panzierer L, Jauk E, Neubauer AC. Creativity on tap? Effects of alcohol intoxication on creative cognition. Conscious Cogn. 2017;56:128–34. https://doi.org/10.1016/j.concog.2017.06.020.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Zabelina DL, Silvia PJ. Percolating ideas: the effects of caffeine on creative thinking and problem solving. Conscious Cogn. 2020;79: 102899. https://doi.org/10.1016/j.concog.2020.102899.

    Article  PubMed  Google Scholar 

  114. Hutten NRPW, Steenbergen L, Colzato LS, Hommel B, Theunissen EL, Ramaekers JG, Kuypers KPC. Cocaine enhances figural, but impairs verbal ‘flexible’ divergent thinking. Eur Neuropsychopharmacol. 2019;29:813–24. https://doi.org/10.1016/j.euroneuro.2019.06.003.

    Article  CAS  PubMed  Google Scholar 

  115. Benedek M, Zöhrer L. Creativity on tap 2: investigating dose effects of alcohol on cognitive control and creative cognition. Conscious Cogn. 2020;83: 102972. https://doi.org/10.1016/j.concog.2020.102972.

    Article  PubMed  Google Scholar 

  116. Colzato LS, Ritter SM, Steenbergen L. Transcutaneous vagus nerve stimulation (tVNS) enhances divergent thinking. Neuropsychologia. 2018;111:72–6. https://doi.org/10.1016/j.neuropsychologia.2018.01.003.

    Article  PubMed  Google Scholar 

  117. Grabner RH, Krenn J, Fink A, Arendasy M, Benedek M. Effects of alpha and gamma transcranial alternating current stimulation (tACS) on verbal creativity and intelligence test performance. Neuropsychologia. 2018;118:91–8. https://doi.org/10.1016/j.neuropsychologia.2017.10.035.

    Article  PubMed  Google Scholar 

  118. Luft CDB, Zioga I, Thompson NM, Banissy MJ, Bhattacharya J. Right temporal alpha oscillations as a neural mechanism for inhibiting obvious associations. Proc Natl Acad Sci USA. 2018;115:E12144–52. https://doi.org/10.1073/pnas.1811465115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Ludyga S, Gerber M, Pühse U, Looser VN, Kamijo K. Systematic review and meta-analysis investigating moderators of long-term effects of exercise on cognition in healthy individuals. Nat Hum Behav. 2020;4:603–12. https://doi.org/10.1038/s41562-020-0851-8.

    Article  PubMed  Google Scholar 

  120. Reed J, Buck S. The effect of regular aerobic exercise on positive-activated affect: a meta-analysis. Psychol Sport Exerc. 2009;10:581–94. https://doi.org/10.1016/j.psychsport.2009.05.009.

    Article  Google Scholar 

  121. Reed J, Ones DS. The effect of acute aerobic exercise on positive activated affect: a meta-analysis. Psychol Sport Exerc. 2006;7:477–514. https://doi.org/10.1016/j.psychsport.2005.11.003.

    Article  Google Scholar 

  122. Ekkekakis P, Hall EE, VanLanduyt LM, Petruzzello SJ. Walking in (affective) circles: can short walks enhance affect? J Behav Med. 2000;23:245–75. https://doi.org/10.1023/A:1005558025163.

    Article  CAS  PubMed  Google Scholar 

  123. Paluska SA, Schwenk TL. Physical activity and mental health: current concepts. Sports Med. 2000;29:167–80. https://doi.org/10.2165/00007256-200029030-00003.

    Article  CAS  PubMed  Google Scholar 

  124. Fredrickson BL. The broaden-and-build theory of positive emotions. Philos Trans R Soc Lond B Biol Sci. 2004;359:1367–78. https://doi.org/10.1098/rstb.2004.1512.

    Article  PubMed  PubMed Central  Google Scholar 

  125. Bledow R, Rosing K, Frese M. A dynamic perspective on affect and creativity. AMJ. 2013;56:432–50. https://doi.org/10.5465/amj.2010.0894.

    Article  Google Scholar 

  126. Rominger C, Schwerdtfeger AR, Benedek M, Perchtold-Stefan CM, Fink A. Ecological momentary assessment of creative ideation: measuring creative potential in an everyday life context. Eur Psychol. (in press).

  127. Voelcker-Rehage C, Niemann C. Structural and functional brain changes related to different types of physical activity across the life span. Neurosci Biobehav Rev. 2013;37:2268–95. https://doi.org/10.1016/j.neubiorev.2013.01.028.

    Article  PubMed  Google Scholar 

  128. Weber B, Koschutnig K, Schwerdtfeger AR, Rominger C, Papousek I, Weiss EM, et al. Learning unicycling evokes manifold changes in gray and white matter networks related to motor and cognitive functions. Sci Rep. 2019;9:4324. https://doi.org/10.1038/s41598-019-40533-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Colcombe SJ, Erickson KI, Scalf PE, Kim JS, Prakash R, McAuley E, et al. Aerobic exercise training increases brain volume in aging humans. J Gerontol A Biol Sci Med Sci. 2006;61:1166–70. https://doi.org/10.1093/gerona/61.11.1166.

    Article  PubMed  Google Scholar 

  130. Erickson KI, Voss MW, Prakash RS, Basak C, Szabo A, Chaddock L, et al. Exercise training increases size of hippocampus and improves memory. Proc Natl Acad Sci U S A. 2011;108:3017–22. https://doi.org/10.1073/pnas.1015950108.

    Article  PubMed  PubMed Central  Google Scholar 

  131. Fink A, Koschutnig K, Zussner T, Perchtold-Stefan CM, Rominger C, Benedek M, Papousek I. A two-week running intervention reduces symptoms related to depression and increases hippocampal volume in young adults. Cortex. 2021;144:70–81. https://doi.org/10.1016/j.cortex.2021.08.010.

    Article  PubMed  Google Scholar 

  132. Yu Q, Herold F, Becker B, Klugah-Brown B, Zhang Y, Perrey S, et al. Cognitive benefits of exercise interventions: an fMRI activation likelihood estimation meta-analysis. Brain Struct Funct. 2021;226:601–19. https://doi.org/10.1007/s00429-021-02247-2.

    Article  PubMed  Google Scholar 

  133. Rominger C, Papousek I, Perchtold CM, Benedek M, Weiss EM, Schwerdtfeger AR, Fink A. Creativity is associated with a characteristic U-shaped function of alpha power changes accompanied by an early increase in functional coupling. Cognit Affect Behav Neurosci. 2019;19:1012–21. https://doi.org/10.3758/s13415-019-00699-y.

    Article  Google Scholar 

  134. Perchtold CM, Papousek I, Koschutnig K, Rominger C, Weber H, Weiss EM, Fink A. Affective creativity meets classic creativity in the scanner. Hum Brain Mapp. 2018;39:393–406. https://doi.org/10.1002/hbm.23851.

    Article  PubMed  Google Scholar 

  135. Chen Q, Beaty RE, Qiu J. Mapping the artistic brain: common and distinct neural activations associated with musical, drawing, and literary creativity. Hum Brain Mapp. 2020;41:3403–19. https://doi.org/10.1002/hbm.25025.

    Article  PubMed  PubMed Central  Google Scholar 

  136. Jauk E, Neubauer AC, Dunst B, Fink A, Benedek M. Gray matter correlates of creative potential: a latent variable voxel-based morphometry study. Neuroimage. 2015;111:312–20. https://doi.org/10.1016/j.neuroimage.2015.02.002.

    Article  PubMed  Google Scholar 

  137. Firth J, Stubbs B, Vancampfort D, Schuch F, Lagopoulos J, Rosenbaum S, Ward PB. Effect of aerobic exercise on hippocampal volume in humans: a systematic review and meta-analysis. Neuroimage. 2018;166:230–8. https://doi.org/10.1016/j.neuroimage.2017.11.007.

    Article  PubMed  Google Scholar 

  138. Memmert D. Tactical creativity. In: McGarry T, O’Donoghue P, Sampaio J, editors. Routledge handbook of sports performance analysis. London: Routledge; 2013. p. 297–308.

    Google Scholar 

  139. Bernard P, Chevance G, Kingsbury C, Baillot A, Romain A-J, Molinier V, et al. Climate change, physical activity and sport: a systematic review. Sports Med. 2021;51:1041–59. https://doi.org/10.1007/s40279-021-01439-4.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors thank Daniel Schipfer, Luca Bartlmä, and Alex Finner for their valuable help in data collection and preparation. The authors acknowledge the financial support by the University of Graz.

Funding

The publication cost for this article was funded by the University of Graz. No additional external funding was received for this study.

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Authors and Affiliations

  1. Institute of Psychology, University of Graz, Graz, Austria

    Christian Rominger, Martha Schneider, Andreas Fink, Corinna M. Perchtold-Stefan & Andreas R. Schwerdtfeger

  2. Department of Cognition, Emotion, and Methods in Psychology, School of Psychology, University of Vienna, Vienna, Austria

    Ulrich S. Tran

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  1. Christian Rominger
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  3. Andreas Fink
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Contributions

CR and MS were responsible for the study design and the literature search. CR and MS participated in screening and data extraction. MS and UT conducted the statistical analysis and reported its results. AS was responsible for team management. All authors participated in drafting the manuscript. All authors read and approved the final manuscript.

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Correspondence to Christian Rominger.

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Christian Rominger, Martha Schneider, Andreas Fink, Ulrich Tran, Corinna Perchtold‑Stefan and Andreas Schwerdtfeger declare that they have no competing interests.

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Supplementary Information

Additional file 1

. Search string.

Additional file 2

. Study quality assessment protocol.

Additional file 3

. Results of moderator analyses.

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Rominger, C., Schneider, M., Fink, A. et al. Acute and Chronic Physical Activity Increases Creative Ideation Performance: A Systematic Review and Multilevel Meta-analysis. Sports Med - Open 8, 62 (2022). https://doi.org/10.1186/s40798-022-00444-9

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Keywords

  • Divergent thinking
  • Creative potential
  • Bodily movement
  • Open problem solving