individual sports research paper

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• Published: 31 August 2023

The impact of sports participation on individuals’ subjective well-being: the mediating role of class identity and health

• Ningning Liu   ORCID: orcid.org/0009-0008-2715-4110 1 &
• Qikang Zhong   ORCID: orcid.org/0000-0003-4911-2233 2  

Humanities and Social Sciences Communications volume  10 , Article number:  544 ( 2023 ) Cite this article

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Although studies have explored the relationship between physical activity and subjective well-being, exploration of the mechanisms underlying the effects of sports participation on subjective well-being remains limited. In the context of promoting the deep integration of national fitness and national health in China, we explore the patterns and differences in the effects of sports participation on the subjective well-being of different populations and explore the underlying mechanisms of the effects of sports participation on individual subjective well-being based on body and society theory. Using data from the China General Social Survey, this study used multiple linear regression models, propensity score matching methods, quantile regression and chain mediation models to explore the relationship between sport participation and subjective well-being, and further elaborated the mediating role of subjective class identity and health in it. The results of the study showed that sports participation significantly and positively affected individual subjective well-being. The results of quantile regression and heterogeneity tests showed that the effect of sports participation on individual subjective well-being showed a significant quantile effect and group heterogeneity. Sports participation had a more significant effect on the well-being of older adults. The results of the mediation effect test showed that sports participation increased subjective well-being by enhancing individuals’ subjective class identity and health, respectively, while subjective class identity and health had a significant chain mediation effect. Based on the findings of the study this paper provides some practical suggestions for improving the subjective well-being of residents, especially the elderly, which will provide some valuable references for the next studies on residents’ well-being and life satisfaction.

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Introduction.

Improving people’s well-being is an important development indicator recognized by the international community, and people’s pursuit and aspiration for a better life point to the concern for individual subjective well-being. Subjective well-being is an individual’s reflective cognition and emotional assessment of their life state (Diener, 2006 ). The multiple fields involved in subjective well-being have caused this topic to receive long-term attention from disciplines such as psychology, sociology and economics. Existing research has examined the effects of age (Becker & Trautmann, 2022 ), income (Toshkov, 2022 ), social networks (Huang et al., 2019 ), social capital (Xu et al., 2023 ), subjective health (Mohammadi et al., 2022 ), and depressive symptoms on subjective well-being (Soosova et al., 2021 ). It has also been suggested that economic factors and lifestyle changes have the greatest impact on individuals’ subjective well-being (Okulicz-Kozaryn & Mazelis, 2017 ). Based on these studies, what we would like to explore further is the effect of physical activity as a lifestyle or as a form of leisure on individuals’ subjective well-being. In China, the implementation of the Health China Strategy and the National Fitness Strategy has emphasized and highlighted the comprehensive value and multiple functions of sports participation in improving people’s health, promoting all-around human development, and promoting economic and social development. Although studies have verified the significant positive effects of physical exercise and physical activity on subjective well-being (Yuan & You, 2022 ), they have generally focused on the effects of physical activity on well-being, with limited analysis of the mechanisms underlying the effects of physical activity on subjective well-being. In addition, many studies have focused on the effects of physical activity on the well-being of specific age groups (Jiang et al., 2021 ; Panza et al., 2019 ), which does not clearly show the differences in the effects of physical activity participation on the subjective well-being of different age groups and the patterns and characteristics of the effects of physical activity participation on well-being . Therefore, our study expects to construct a theoretical framework for analyzing the effects of sports participation on subjective well-being based on body and society theory, and then explore the intrinsic pathways of the effects of physical activity participation on individuals’ subjective well-being.

Based on our research objectives, the rest of the paper is organized as follows: the second part is the literature review and research hypothesis. The third section discusses the required data, variable measurement, and estimation strategies. The fourth part provides an empirical analysis of the effect of sports participation on individuals’ subjective well-being. This section includes the use of propensity score matching to address sample selection bias, the use of quantile regression to explore patterns in the effect of sports participation on individual subjective well-being, a test of heterogeneity regarding age, and a test of chain mediating effects. The fifth section presents the conclusions of the paper and discusses them accordingly.

Literature review and research hypothesis

Physical activity, subjective class identity, and health.

From the perspective of the sociology of the body, the body becomes a kind of planning for modern people and a constituent part of the individual’s self-identity. The planning and devotion to the body give people a means of self-expression (Shilling, 2012 ). A typical example of using the body as a project is the individual’s quest for a healthy body. In this process, individuals expect to build a healthy body through daily behaviors such as fitness and diet to alleviate their concerns about body presentation. Physical activity plays an important role in shaping individuals into healthy bodies. Perceived health plays an important mediating role in physical activity participation and higher well-being or life satisfaction (Lera-Lopez et al., 2017 ). A growing body of research points to a positive correlation between physical activity and perceived health, physical health and mental health (Humphreys et al., 2014 ; Wang et al., 2022 ). In the process of long-term stable physical activity participation, participants can not only improve muscle strength (Shen et al., 2018 ), enhance cognitive ability and reduce the incidence of obesity directly through physical activity (Petridou et al., 2019 ; Sewell et al., 2021 ), but also gain a sense of pleasure and reduce anxiety and depression, thus enhancing the individual’s mental health (Buecker et al., 2021 ; Fortier & Morgan, 2022 ).

Physical fitness as a “soft technology” is not only a pathway to health but also an important means of communicating lifestyle and self-identity (Yongfeng & Ge, 2021 ). Featherstone ( 2007 ) points out that the body represents the self and that the relationship between the self and the body can be re-examined through physical fitness and other body technologies. In this study, we shifted the perspective of identity to subjective class identity. Class identity is an individual’s perception of his or her position in the class structure (Jackman & Jackman, 1973 ), and it is an individual’s identification of his or her social class based on certain criteria. The positive correlation between physical activity and subjective class identity has been verified in studies (Yang et al., 2022 ). This relationship between physical activity and subjective class identity can be further understood in terms of the effect of leisure style on subjective class identity. As lifestyle and consumption patterns have become mechanisms of social exclusion (Duncan & Duncan, 2001 ), tools of social competition and mean of identity construction (Cerneviciute, 2008 ). Physical activity is a form of leisure, so we cannot ignore its influence on an individual’s subjective class identity.

Subjective class identity is closely related to health. Unlike objective socioeconomic status, subjective class identity emphasizes one’s subjective consciousness, evaluation and feelings, and is a judgment of one’s social status and social identity (Peilin, 2005 ). In the subject’s perception of social status and identity, the individual will acquire a subjective status that is different from the objective one in accordance with life experiences and values (Adler et al., 2000 ). In the process of forming subjective class identity, individuals need to be compared with other groups, and in social comparison, those who subjectively feel inferior may develop a sense of relative deprivation (Xin, 2002 ), and the perception of relative deprivation will have a negative impact on individual health (Wang et al., 2023 ). This demonstrates the close association between individuals’ perceptions of their class and their physical and mental health (Adler et al., 2000 ; Garza et al., 2017 ). Related studies point out that the impact of subjective evaluation of social status on individual health has exceeded the impact of objective socioeconomic status on individual health (Hoebel & Lampert, 2020 ), Subjective status assessments provide key information for understanding health disparities (Cundiff & Matthews, 2017 ).

Subjective class identity and subjective well-being

Subjective class identity is closely related to subjective well-being (Sani et al., 2010 ; Tang & Tan, 2022 ). Studies on subjective class identity emphasize that stratification includes subjective awareness, evaluation and feelings, and that even objective social stratification cannot be separated from subjective identity (Peilin, 2005 ). Existing research points to differences in the effects of subjective social status and objective socioeconomic status on individual well-being. Sweeting and Hunt ( 2014 ) research on adults and adolescents points out that subjective socioeconomic status is associated with health and well-being, while objective socioeconomic status is less associated with health and well-being. Individuals’ self-rated social status has a higher impact on subjective well-being than objective socioeconomic status, which is driven by a sense of power and social acceptance (Anderson et al., 2012 ). Compared with other groups, residents with lower class status tend to have a sense of relative deprivation, which will affect personal happiness and psychological integration.

Health and subjective well-being

Perceptions of health lead to a positive relationship between physical activity and well-being (Lera-Lopez et al., 2017 ). The positive effect of physical health on subjective well-being has been widely recognized (Garrido et al., 2013 ), and the mediating role of physical and mental health issues such as pain, sleep problems, loneliness, anxiety and boredom in the relationship between lack of physical activity and subjective well-being has also been demonstrated (Gyasi et al., 2023 ). Even though there is a correlation between physical health and mental health, there is a need to be aware of the unique role of different dimensions of health in research (Wang et al., 2022 ) . What we need to be clear about is the relationship between mental health and well-being. This is because existing research often identifies mental health and happiness together as important variables in the analysis of human well-being (Mahmoodi et al., 2022 ; Perneger et al., 2004 ). However, the association and distinction between subjective well-being and mental health have been validated by studies (Chen et al., 2013 ). In our study, we emphasize the difference between mental health and well-being, that is, mental health and well-being are closely but not identically related (Keller, 2020 ), and it is important to note that mental health is a significant predictor of subjective well-being (Burns & Machin, 2010 ; Min, 2019 ).

Based on the above analysis, we constructed the research framework in Fig. 1 and proposed the following research hypotheses for this paper:

Note: A hypothetical model of the relationship between sports participation, subjective class identity, physical and mental health and subjective well-being.

H1: Sports participation has a positive effect on individual subjective well-being.

H2: Subjective class identity has a mediating role in the relationship between sports participation and individual subjective well-being.

H3: Physical and mental health has a mediating role in the relationship between sports participation and individual subjective well-being.

H4: There is a chain mediating role of subjective class identity and physical and mental health in the relationship between sports participation and individual subjective well-being.

Data and methods

Data source.

This article uses data from the Chinese General Social Survey (CGSS) 2017, a national, comprehensive and continuous academic survey launched in 2003. The survey provides data for the promotion of social science research and international comparative studies through the regular and systematic collection of data on various aspects of Chinese people and Chinese society. A total of 12,582 valid samples were completed for the CGSS 2017 data. Considering the research objectives of this paper, the study will exclude samples with missing key variables and those with outliers. The final sample we used contained 3501 observations.

Subjective well-being (SWB) was taken as the dependent variable. The 2017 China General Social Survey used the Subjective Well-being Scale to ask respondents how much they agreed with the 21 views on the scale. Respondents were asked to choose from the following levels of agreement: 1 = Strongly disagree; 2 = Disagree; 3 = Somewhat disagree; 4 = Somewhat agree; 5 = Agree; 6 = Strongly agree. The different levels of agreement were sequentially assigned a value from 1–6. After transforming the opposite statements in the scale, we analyzed the scale reliability. The analysis revealed a Cronbach’s α of 0.844, which indicates that the scale exhibits excellent internal consistency. The sum of the scores on these measures will be used as the value of the subjective well-being variable, with higher scores indicating higher subjective well-being.

Sports participation (SP) was used as the independent variable. The sports participation variable is measured by the question “In the past year, did you regularly engage in physical activity in your free time?” in the China General Social Survey. The survey classified the level of sports participation into five categories, which were “Daily”, “Several times a week”, “Several times a month”, “Several times a year or less” and “Never”. Since occasional participation in physical activity has been shown to be an episodic behavior and physical participation needs to be constant (Wei & Jianyong, 2020 ), we use this approach to treat physical participation as a dichotomous variable. In this study, “every day”, “several times a week” and “several times a month” were considered as regular physical activity participation and were combined and assigned a value of 1, while “several times a year and “never” are considered as not participating in physical activity and are assigned a value of 0.

Subjective class identity (SCI) and physical and mental health (PMH) were used as mediating variables. The CGSS questionnaire divides class identity into 10 levels, with a maximum score of 10 representing the top tier and a minimum score of 1 representing the bottom tier. We measured respondents’ subjective class identity by their responses to the question, “In general, where are you on the social scale?”. We evaluated the physical and mental health of the interviewees by their answers to the questions about self-rated health, physical health and mental health in the CGSS. The CGSS asked respondents “How healthy are you at the moment”, and measured their self-rated health on a scale of 1 to 5 (1 = very unhealthy; 5 = very healthy). About physical health and mental health, the CGSS questionnaire measures how often, over the past four weeks, health problems have affected your work or other daily activities, and how often, over the past 4 weeks, you have felt depressed. Studies have applied this scale to analyze the impact of physical and mental health on the subjective well-being of older people (Qiaolei & Zonghai, 2021 ). We used this as a reference and applied the total score to measure the physical and mental health of respondents. The Cronbach’s α coefficient for this scale in this study was 0.741 and the reliability of the scale was high.

Some variables that might be associated with subjective well-being were controlled. These variables included the respondent’s gender (1 = male, 0 = female), age, marital status (1 = married with the spouse, 0 = no spouse), years of education (never had any education = 0, private school = 2, primary school = 6, junior high school = 9, senior high school = 12, vocational high school, junior college, technical school = 13, university college (adult higher education) = 14, university college (formal higher education) = 15, undergraduate (adult higher education) = 15, undergraduate (formal higher education) = 16, postgraduate = 19), self-assessed personal socioeconomic status (PSES) (1 = lower class, 2 = lower middle class, 3 = middle class, 4 = upper middle class, 5 = upper class) and self-assessed household socioeconomic status (HSES) (1 = well below average, 2 = below average, 3 = average, 4 = above average, 5 = well above average).

Analytic strategies

Multiple linear regression was applied to examine the impact of sports participation on residents’ subjective well-being. In addition, when analyzing the effect of sport participation on individuals’ subjective well-being, it is necessary to take into account the problem of possible selective bias between individuals’ sport participation and their subjective well-being. Therefore, this paper uses the propensity score matching method proposed by Rosenbaum and Rubin ( 1983 ) to construct a counterfactual framework to correct for selection bias, so as to obtain the net effect of individuals’ sport participation on their subjective well-being and thus increase the robustness of the results. In a further analysis, we used quantile regression to explore the distribution of the effects of sport participation across different levels of subjective well-being. The use of quantile regression allows not only for robustness checks of the results of multiple linear regressions but also for analysis of the differentiation effects of sport participation between individuals with different levels of subjective well-being. Finally, we further explored the pathways inherent in the impact of sport participation on individual subjective well-being using Model 6 in the SPSS plugin PROCESS provided by Hayes ( 2017 ).

Descriptive statistics and correlation analysis

Table 1 presents the means, standard deviations and correlations for all variables. The Pearson correlation coefficient shows that the correlations between gender, marital status, and individual subjective well-being are not significant. Among the control variables, age, years of education, self-rated personal socioeconomic status, and self-rated family socioeconomic status have significant correlations with individual subjective well-being. There is a significant correlation between the key independent variable sport participation and individual subjective well-being; the mediating variables subjective class identity and physical and mental health are also significantly correlated with individual subjective well-being. Among them, all are positively correlated, except for age, which is negatively correlated with subjective well-being. In addition, there is a significant correlation between the mediating variable of subjective class identity and the mediating variable of physical and mental health. Based on the results of the correlation analysis, we will further verify the effect of physical activity participation on individuals’ subjective well-being.

Basic regression results

We further explored the effects of each predictor variable on individual subjective well-being through a hierarchical regression analysis, the results of which are displayed in Table 2 . Model 1 is the baseline model, to which control variables were added to analyze the effect of the main control variables on individuals’ subjective well-being. Age, years of education, self-rated personal socioeconomic status, and self-rated family socioeconomic status all have a significant effect on subjective well-being. In Model 2, we added the key independent variable of this study, sports participation, and the results showed that participation in physical activity significantly increased individuals’ subjective well-being. Model 3 adds mediating variables to Model 2. The results show that both subjective class identity and physical and mental health have a significant positive effect on subjective well-being, while the regression coefficients of the sports participation variable are reduced but still significant at the 1% level after the addition of the two mediating variables, which confirms hypothesis 1. At the same time, the decrease in the regression coefficient of the sport participation variable suggests that there may be a mediating effect of subjective class identity and physical and mental health in the way that sports participation affects individual well-being. The mediating effect will be tested further in a later section.

Propensity score matching

Data and variable limitations will make the basic analysis process highly susceptible to the problem of selective bias. To correct for selectivity bias, the propensity score matching method we used estimated the net effect of sport participation on individual subjective well-being. To ensure the robustness of the results, we used three methods: nearest-neighbor matching, radius matching, and kernel matching. Table 3 shows the results of the sample balance test. The data show a well-balanced sample after matching.

After matching, we measured the mean treatment effect of subjective well-being for individuals who participated in physical activity. The results are shown in Table 4 . The results of radius matching showed that the subjective well-being of the physical activity group was 1.033 higher than that of the non-physical activity group at a 5% confidence level. In addition, the ATT results for both Kernel density matching and nearest-neighbor matching showed that physical activity participation was significant on individual subjective well-being at the 5% confidence level after eliminating observable systematic differences between samples. This result ensures the robustness of the baseline regression results that participation in physical activity significantly increases an individual’s subjective well-being, which further validates Hypothesis 1.

Quantile regression

In this section, we have used quantile regression to further analyze the pattern of physical activity participation on individuals’ subjective well-being. Table 5 demonstrates the quantile effects of sport participation on individual subjective well-being. The estimates show that at the lower quartile (0.1), participation in sports does not have a significant effect on subjective well-being, but at the middle and low quartiles (0.25), sports participation has a positive effect on subjective well-being at a statistical level of 10%. And, as the quantile increases, the regression coefficient for sports participation shows an upward trend. This result suggests that sports participation has less of an impact on individuals with low and medium subjective well-being and more of an impact on individuals with high subjective well-being. In addition, physical and mental health passed the significance test at all quantile points, indicating that good physical and mental health can contribute to higher perceptions of well-being for individuals in different well-being states. In contrast to the trend in the regression coefficients for sports participation, the regression coefficients for the subjective class identity showed a decreasing trend as the quartile increased.

Heterogeneity analysis

We have analyzed the patterns of the effects of physical activity participation on individual subjective well-being above, and in this section, we will further explore group differences in the effects of physical activity participation on subjective well-being. Wang et al. ( 2022 ) point out that individuals under the age of 35 are more aware of their physical health, making exercise a greater impact on personal well-being. Individuals between the ages of 36 and 59 are more likely to recognize physical importance at work and to focus on physical activity. For those over-60s, physical health will directly affect their perception of subjective well-being. Therefore, we will further analyze the heterogeneity of the effect of sports participation on individuals’ subjective well-being by dividing the sample into groups under 35 years old, 36–59 years old, and over 60 years old according to their age. The results of the subgroup regressions are shown in Table 6 . The results show that there is no significant effect of sports participation on subjective well-being for the under 35 group. For the 36–59 year old group sports participation was only significant at the 10% level. However, the effect of sports participation on subjective well-being was significant at the 1% level for the older age group of 60 years and above, and the regression coefficient was significantly higher. The effect of subjective class identity on subjective well-being for different age groups is similar to the effect of sports participation on subjective well-being for different age groups. That is, there is no significant effect of subjective class identity on the subjective well-being of the group under 35 years old, but the effect of subjective class identity on the subjective well-being of the group between 36 and 59 years old is significant at the level of 10%, the effect on the subjective well-being of the group aged over 60 was significant at the level of 1%. The physical and mental health of different age groups has a significant impact.

Mediation effect analysis

In this section, we will further examine the mechanisms by which sport participation affects an individual’s subjective well-being. In the theoretical analysis section, we illustrate the internal logic of sport participation affecting well-being from two perspectives: subjective class identity and health. In the correlation analysis, we found that there was a significant correlation between sports participation, subjective well-being, subjective class identity and physical and mental health. In the stratified regression analysis, the coefficient of the effect of sports participation on subjective well-being was reduced after adding the variables of subjective class identity and physical and mental health. Based on this, this section will explore the mechanisms underlying the impact of sport participation on subjective well-being. We constructed a chain mediation test model with individual subjective well-being as the dependent variable, sports participation as the independent variable, and subjective class identity and physical and mental health as mediating variables. The results of the path coefficient estimation are shown in Fig. 2 , and the results of the chain-mediated effects analysis are shown in Table 7 . In order to clearly present the interrelationships between the variables, we report the standardized path coefficients in this section. We used the Bootstrap method to repeatedly sample 5000 times to analyze the main effect and chain-mediated effect. The results showed that the indirect effect of the pathway with subjective class identity as the mediating variable was 0.009 (95%CI = [0.003,0.016]), the indirect effect of the pathway with physical and mental health as the mediating variable was 0.065 (95%CI = [0.042,0.089]), the indirect effect of the pathway with subjective class identity and physical and mental health as the mediating variable was 0.004 (95% CI = [0.002,0.007]), with all indirect effects totaling 0.078 (95% CI = [0.054,0.103]). The chain mediating role of subjective class identity and physical and mental health in the positive effect of sport participation on individuals’ subjective well-being is established, which verifies hypothesis 2, hypothesis 3 and hypothesis 4.

Note: *** p  < 0.01. The numbers in the figure are the standardized regression coefficients for the path.

We examined the relationship between sports participation, subjective class identity, physical and mental health and subjective well-being using data from the 2017 China General Survey. Our study builds on previous research on physical activity and subjective well-being to further explore the mechanisms underlying the impact of sport participation on individual well-being. Our findings have several points that deserve further discussion, which will provide some valuable references for the next studies on residents’ well-being and life satisfaction.

Physical activity participation can significantly enhance individuals’ subjective well-being. This result remained significant after accounting for sample selection bias. This result further supports previous research findings on the significant positive effect of physical activity on individuals’ subjective well-being (Biddle & Asare, 2011 ; VanKim & Nelson, 2013 ). We further analyzed the patterns and group heterogeneity of the effects of sports participation on individual subjective well-being perceptions. The results showed that the effect of sports participation on individual subjective well-being was heterogeneous across populations. Specifically, the effect of sports participation on individual subjective well-being showed a significant quantile effect, and with increasing quantile values, this effect showed a significant linear upward trend. In addition, our results show that the effect of sports participation on individual subjective well-being differs significantly across age subgroups. Specifically, the effect of sports participation was not significant for the youth group aged 35 and younger, while the effect was more significant for the older age group aged 60 and older. This corresponds to the results of previous studies. Lera-Lopez et al. ( 2017 ) showed a significant relationship between physical activity during leisure time and personal well-being and life satisfaction among adults aged 50 to 70. Differences regarding the impact of sports participation on the well-being of individuals at different ages can be analyzed from the perspective of leisure time use. Different age groups face different life and work pressures, and in comparison, older people have more freedom to arrange their leisure time than young and middle-aged people. Cho and Kim ( 2020 ) point out that middle-aged groups are under pressure to balance family and work more than older groups and require more effort for acquiring personal free time, thus older people are more involved in regular physical activity than middle-aged people.

The analysis of the mechanism of the effect of sports participation on subjective well-being showed that sports participation enhances subjective well-being by improving individuals’ subjective class identity and physical and mental health, respectively, while subjective class identity and physical and mental health have a significant chain mediating effect. Our study confirms the significant positive effects of subjective class identity and physical and mental health on subjective well-being, and this finding can be supported by previous studies(Etxeberria et al., 2019 ; Tang & Tan, 2022 ). In addition, we focus on the relationship between physical activity, subjective class identity, physical and mental health and individual subjective well-being based on body and society theory, which has received less attention in existing studies. We will return to the theoretical framework of this paper to further explore the intrinsic causes. The sociological definition of exercise is not one-sidedly focused on physical exertion, but emphasizes the socially differentiated nature of the practice of exercise as a way of life(Lagaert & Roose, 2016 ). This points to the exploration and research about the social body. Individuals in the lifeworld maintain and express their class position and social identity through differentiated and compartmentalized social practices(Lawler, 2005 ; Mellor et al., 2010 ). Social networks play an important role in influencing individuals’ subjective assessment of their position in the social hierarchy and the construction of their social identity(Firat et al., 1994 ; Huang, 2023 ). Under this perspective, we argue that individuals’ physical activity behaviors and sports social networks during sports participation will influence the way individuals categorize themselves and form perceptions about their self-position. Social comparison in the process of acquiring a subjective class identity and the questions it raises about confidence and self-esteem will further point to concerns about individual mental health. Social comparison orientation has been shown to have a negative effect on mental health, and self-esteem has a significant negative mediating role in this (Lee, 2022 ). Thus, we connected the relationship between subjective class identity and physical and mental health, and further verified the positive effect of subjective class identity on physical and mental health. As a result, we conclude that sports participation affects individuals’ physical and mental health by influencing their subjective class identity. Combining the effects of subjective class identity and physical and mental health on subjective well-being, our study explored and validated the positive effects of sports participation on subjective well-being and the chain mediating effects of subjective class identity and physical and mental health.

Conclusions and limitations

Our findings confirm the positive effect of sports participation on subjective well-being and validate the mechanisms underlying the effect of sports participation on subjective well-being based on body and society theory. These findings can provide some practical suggestions for enhancing the subjective well-being of residents, especially the elderly. The impact of sports participation on subjective class identity, physical and mental health and subjective well-being requires the optimal allocation of sports resources between regions and urban and rural areas, especially to protect the needs of people at the bottom in their pursuit of a better life, thereby enhancing their opportunities for physical maintenance, and expression and reducing the relative deprivation they feel. The significant impact of sports participation on the subjective well-being of the elderly population calls for promoting age-friendly communities, improving the construction of sports facilities in the community, improving the sports environment for the elderly and enriching their leisure life.

There are still some research limitations present in our study. Due to the limitations of the study data, we used cross-sectional data, and the main content of the analysis was the effect of whether individuals participate in physical activity on residents’ subjective well-being and its underlying mechanisms. However, there are also differences in the duration and intensity of sports participation among individuals who participate in physical exercise, and further exploration is needed regarding the effect of the degree of participation of physical exercise participants on individual subjective well-being. In addition, we used cross-sectional data to verify the relationship between sports participation, subjective class identity, health, and subjective well-being in accordance with relevant theories, but future research would be more helpful to understand the relationship between sports participation and individual subjective well-being and to make logical causal judgments if we can break the data limitations and obtain tracking survey data for longitudinal studies.

Data availability

Raw data collected and analyzed in the current study are available in the Chinese General Social Survey: http://cgss.ruc.edu.cn/ . Data supporting the findings of this study are presented in the supplementary file.

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Liu, N., Zhong, Q. The impact of sports participation on individuals’ subjective well-being: the mediating role of class identity and health. Humanit Soc Sci Commun 10 , 544 (2023). https://doi.org/10.1057/s41599-023-02064-4

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Understanding a Player’s Decision-Making Process in Team Sports: A Systematic Review of Empirical Evidence

Michael ashford, andrew abraham, jamie poolton.

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Received 2021 Mar 30; Accepted 2021 May 14; Collection date 2021 May.

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Three perspectives were taken to explain decision-making within team sports (information processing, recognition primed decision-making, and ecological dynamics perspectives), resulting in conceptual tension and practical confusion. The aim of this paper was to interrogate empirical evidence to (1) understand the process of decision-making within team sports and (2) capture the characteristics of decision-making expertise in a team sport context. Nine electronic databases (SPORTDiscus, PsycINFO, PsycArticles, PsycTests, PubMed, SAGE journals online, Web of Knowledge, Academic Search Complete, and Web of Science) were searched until the final return in March 2021. Fifty-three articles satisfied the inclusion criteria, were analysed thematically, and synthesised using a narrative approach. Findings indicate that the relative absence or presence of mental representation within the decision-making process depends on factors, including complexity, typicality, time available, and contextual priors available in the game situation. We recommend that future research integrate concepts and methodologies prevalent within each perspective to better understand decision-making within team sports before providing implications for practitioners.

Keywords: decision-making, perception, cognition, action, information processing, recognition primed decision-making, ecological dynamics

1. Introduction

Post-match diagnosis of team performance will often find individual or collective decision-making to be the difference between a win, loss, or draw. The importance it holds leads practitioners to seek understanding of how best to develop expert decision makers. This is not easy as team sports are often seen as unpredictable [ 1 ] environments, which require players to respond effectively to uncertain situations that vary both in time and complexity [ 2 ]. The scrutiny on decision-making proficiency in applied practice has compelled research to better understand the decision-making process and the characteristics of expert performance [ 3 ]. As a result, three clear perspectives have emerged—information processing, ecological dynamics, and naturalistic decision-making—that are born from inherently different views of human behaviour. The crux of the debate typically revolves around a player’s access to memory representations in the decision-making process. From an information processing account, players are seen to make decisions through a process of selection from formalised responses that are stored in memory;

“ Perceptual-cognitive skill refers to the ability to identify and acquire environmental information for integration with existing knowledge such that appropriate responses can be selected and executed (Marteniuk, 1976) ”. [ 4 ] p. 457

In contrast, the ecological dynamics perspective proposes that decisions are made through online perceptual control where perception and action are coupled through the information available in the environment, absent of cognitive resources [ 5 ]. For example;

“ This theoretical rationale proposes that the most relevant informational constraints for decision-making and controlling action in dynamic environments such as a rugby match are those that emerge during on-going performer-environment interactions, not information from past experiences stored in the brain ”. [ 6 ] p. 131

Unfortunately, the differences between these perspectives present knowledge-hungry practitioners with a juxtaposition of theoretical concepts, terminology, and practical implications that they may conflate or misinterpret in their design of learning activities and adopted coach behaviours. Seeing as each perspective disputes the way decision-making is understood, it is useful to present each view clearly. Those schooled in information processing have tended to adopt an expert performance approach [ 7 ] to understand the mechanisms and processes that underpin elite performance and discriminate elite players from their less skilled counterparts [ 8 , 9 , 10 ]. The resulting evidence presents decision-making as a deliberate process of selection, in which expert players excel in their capability to; extract and process cues from the environment [ 11 , 12 ] recognise and interpret familiar patterns of play [ 12 , 13 , 14 ] form expectations by computing situational probability [ 15 , 16 , 17 ]. These processes of selection are viewed as an intermediate agent between what a player perceives (perception) and how a player responds to the play unfolding about them.

In contrast to the aforementioned process, the school of ecological dynamics describes how individual and team/shared behaviour emerges as a result of; an ongoing reciprocal relationship between perception of information, which constrains movement, and action, which creates information [ 9 , 18 , 19 , 20 ]. The coupling of perception and action can be captured as invitations for action (or options), known as affordances [ 21 ], which are defined relative to the task goal, structure of the environment and the action capabilities of the performer. Whilst shared affordances, capture a collective perception of what is possible within the constraints of a context. Decisions of one player interacting with another (to give or receive a pass for example) are made based on the affordances offered by the environment and the perception of the capability of teammates who they are in a position to interact with.

Finally, naturalistic decision-making was conceptualised by Klein, Calderwood, and Clinton-Cirrocco [ 22 , 23 ] to explain human performance in highly pressurised, time constrained situations. They argued that decisions are made through a recognition primed process that alters from situation to situation according to the decision maker’s familiarity with the perceptual information available (visual, auditory, olfactory, etc.) and their context relevant knowledge base [ 22 , 23 ]. In this theory the decision-making process happens through one of three levels [ 22 , 23 , 24 ]. Simple match—represents a case in which the decision maker recognises a situation as typical as the goals, cues, expectations, and action response present themselves in an obvious fashion. Diagnose the situation—where the information is not provided in a typical fashion. Using a process of rapid story telling through mental simulation, the decision maker has to clarify the goals, cues, and expectations through a process of diagnosis to restore typicality and come to a decision. Finally, evaluate a course of action—where the information available (goals, cues and expectations) is recognised but a course of action does not immediately present itself. As such a course of action is rapidly mentally simulated considering intended and unintended consequences to disregard or select an appropriate course of action. We recognise that both the information processing and naturalistic decision-making perspectives are both grounded in a cognitive view of the world. However, we propose they are sufficiently different that they are worthy of being considered as separate approaches to examining decision-making in teams sports. They will form two separate perspectives throughout this study.

The presence of the three theoretical perspectives and their associated narratives presents problems for coaches attempting to use theory to inform their practice. First, researchers are often guilty of taking a firm theoretical stance and presenting just one side of the argument when making sense of the coaching problem and when interpreting their findings. Second, differences in the lexicon of the different perspectives can hamper relational and abstract thinking by coaches. Third, sharing of the findings via social media can result in nuanced misinterpretations of empirical evidence [ 25 ]. Fourth, national governing bodies of team sports may prescribe to one point of view and nurture a bias towards one way of looking at a coaching problem. As a consequence, a practitioner’s engagement with research can result in bewilderment, conceptual blind spots and convoluted solutions to an intricate practical problem. In an attempt to provide clarity, a systematic review of empirical studies on decision-making in team sports was conducted to (i) fully understand the process of decision-making within team sports and (ii) comprehensively capture the characteristics of decision-making expertise within a team sport context.

2. Materials and Methods

2.1. development of a search strategy.

To start this review, a list of keywords was created by deconstructing the research aims [ 26 ]. These keywords were used to conduct a preliminary search on the SPORTDiscus database. The returns from the preliminary search were sampled to identify the relevance to the research aims (i.e., every 10th return) and mined to identify other possible keywords [ 27 ]. This process was repeated until the search typically returned highly relevant studies. The keywords originally entered also returned studies that were unrelated to the research aims, such as those associated with sport injury or decision-making in sports marketing. Subsequently, these terms were added to the search phrase using the NOT operator. The final search phrase emerging from this process was:

The following databases were accessed on the basis of relevance to the research question and accessibility to the lead researcher: SPORTDiscus, PsycINFO, PsycTests, PubMed, SAGE Journals Online, Web of Knowledge, Academic Search Complete, and Web of Science.

2.2. Inclusion/Exclusion Criteria

Inclusion/exclusion criteria were used to set clear boundaries to the review process and ensure returns would pinpoint all studies that met the research aims [ 28 , 29 ]. The studies included needed to: (i) be peer-reviewed research studies; (ii) be published in the English language; (iii) be published before March 2021 (when the final search criteria were established); (iv) have collected original empirical evidence; (v) have reference to decision-making in the title or abstract; (vi) only involve the investigation in the context of team sports [ 29 , 30 ]; and (vii) include data that related directly to the aims of the study; for example, studies reporting findings related to the development of player decision-making, but neither the decision-making process nor characteristics of decision-making expertise were omitted.

2.3. Search Returns

The initial search phrase was completed on the 10 May 2017, which returned 524 peer reviewed articles following the removal of duplicates. In applying the inclusion criteria, a further 359 articles were excluded for exploring the decision-making of athletes within individual sports, leaving a total of 165. The full text of each was then assessed against the inclusion criteria and research aims, which resulted in 123 articles being excluded. Of these 124, 36 were conceptual or review articles and 88 were articles that produced empirical data, the majority of which were excluded due to focusing on the development of player decision-making. Initially, a total of 41 papers met the inclusion criteria. Following feedback from an external panel of experts within the subject area in March 2021, a follow up search was conducted on 6 March 2021, for appropriate articles published after the initial search. 418 peer reviewed articles were returned and mined leaving 19 appropriate articles following the removal of duplicates. Of the 19 articles, 12 were excluded, 4 were conceptual, whilst 8 fell outside the scope of the inclusion criteria as they focused on external factors influencing the decision-making process (i.e., fatigue or emotional intelligence). A further 5 articles were signposted by the panel for inclusion having not arisen from either search. In total, 13 articles were added to the initial 41, leaving a total of 53 research articles meeting the inclusion criteria (See Figure 1 ).

PRISMA flow diagram demonstrating the process of identification, screening, eligibility, and inclusion of research articles returned from the search phrase.

2.4. Data Synthesis

The final 53 articles were read multiple times in full to capture the focus of investigation, method, findings, inferences and implications of each study [ 29 ]. Following this, a two-stage thematic analysis was completed to identify consistent themes within the data [ 29 , 31 ]. First, deductive analysis was used to identify data that informed the research aims [ 26 , 28 , 29 ]. Second, each study was rigorously explored and classified according to the perspectives that shaped the theoretical focus of investigation, the study design and/or the interpretation of the findings. This exploration enabled comparisons, similarities, and differences to be drawn between and within each perspective. There was a mix of quantitative and qualitative data sets across the 53 studies; therefore, to find a “middle ground” [ 29 ], p. 809 a narrative approach to synthesis was adopted to integrate, interpret, and communicate the relevant findings [ 32 , 33 ].

2.5. Establishing Trustworthiness and Audit Trail

Across the articles returned, an equal balance of quantitative and qualitative study designs were identified, which led us to take numerous precautions to ensure the trustworthiness of the review [ 29 ]. Trustworthiness is a term frequently used in qualitative research to describe the validity and reliability of a study’s method and findings [ 29 , 34 ]. In order to establish such trustworthiness, an audit trail was kept of the initial keywords, search terms, repeated search phrases and the search returns. Furthermore, the audit trail kept note of studies that were excluded following the application of the inclusion/exclusion criteria [ 26 ]. The audit trail was continuously reviewed and verified by a group of academics who have conducted research in this area or had a research interest in the area of decision-making in team sports [ 29 , 34 ]. This included providing support to the lead researcher, acknowledging and challenging personal bias when interpreting findings, shaping and guiding the methodology of the review, and the guidance of shaping the conclusive interpretations of the data. Additionally, in an attempt to abide by Tracy’s ‘Big Tent’ criteria of ensuring quality in our approach [ 35 , 36 ] a panel of expert researchers within the subject area ( n = 2) of decision-making in team sports, offered an external appraisal of the methods, approach, and returns taken following the initial search.

3.1. General Results

The 53 articles included in this systematic review comprised a total population size of 2078 participants, made up of 1552 males, 427 females, and 99 participants whose sex was not declared. Moreover, 2021 were team sport players and 57 were coaches. Table 1 is a summary of the research perspective, the level of the sample, the population size of the sample, the sport, the method, what was measured and an indication of whether the article assessed choice, perception or choice and perception.

Summary of decision-making perspectives, level of sample, population size, team sport, method, measures and assessments of perception, selection or a combination used in the included articles.

3.2. The Decision-Making Process

Forty-one articles explored the process of decision-making within team sports explicitly in their studies. Table 2 summarises these findings into the three broad perspectives. In seeking to extract a definitive decision-making process from the literature, clear descriptions (if available) have been directly quoted from relevant articles. The thematic analysis has shaped three broad processes that align with the three perspectives: perceptual–cognitive expertise, perception-action coupling, and recognition primed decision-making, respectively.

Summary of descriptions of the decision-making process used in the included articles.

3.2.1. Information Processing

Perceptual–cognitive expertise.

Sixteen studies presented the decision-making process as one encompassed by a player’s possession of specific key perceptual–cognitive skills [ 40 , 41 , 43 , 44 , 53 , 55 , 56 , 64 , 66 , 69 , 70 , 71 , 73 , 82 , 83 , 84 ] namely; the utilisation of domain knowledge in perceiving informational cues [ 44 , 55 , 66 ], the identification of global, salient and predictive cues [ 40 , 41 , 64 , 69 , 73 , 84 ], rapid retrieval of knowledge from memory representations [ 40 , 43 , 44 , 56 , 69 ], option generation [ 40 , 64 , 66 , 69 , 73 ], and the role of intuition in the form of the take the first heuristic [ 40 , 59 , 64 , 73 , 80 ]. A concurrent theme is the prevalence of representation as a connecting mechanism between what players see and how they act. McRobert et al. [ 71 ] found that skilled cricket batsmen fixated on predictive cues, which were processed through the retrieval of information and afforded anticipation of future outcomes. In two studies, Roca and colleagues [ 82 , 83 ] found that skilled players were better able to verbalise the retrieval process. They proposed that players use task specific memory representations that allow them to perceive the most relevant cues, retrieve the most suitable response and perform the most appropriate action. McPherson and Vickers [ 70 ] found that elite volleyball players update memory representations with knowledge of current event profiles (kinematic patterns, strengths, weaknesses, previous patterns of play) to inform future performance known as action-plan profiles. The sixteen studies on perceptual–cognitive expertise appear to agree that expert decision makers possess a larger ‘database’ of task specific information [ 40 , 43 , 44 , 56 , 69 ]. This ‘database’ of information is described as a catalyst for the retrieval of task specific mental representations that can be grown and refined to facilitate each stage of a perception-cognition-action process [ 40 , 71 ].

Four of these studies investigated expert team sport players decision-making, in the form of the intuitive take the first heuristic or option generation processes [ 40 , 64 , 73 , 80 ]. Klatt et al. [ 64 ] compared the decision-making accuracy of elite Brazilian and German senior academy football players through a video decision-making task. Intuition was measured by assessing the accuracy of participants’ first options, whilst creativity was measured in the number of appropriate options participants were able to generate. Basevitch et al. [ 40 ]; high skill vs. low skill and Musculus [ 73 ]; expert vs. near expert also employed video based decision-making tasks that assessed participants decision-making process in line with the “less is more” take-the first heuristic or “more-is-more” option generation processes whilst manipulating time available to make a decision. Participant responses in all three studies were valued against an expert coaching panel who indicated a rank of which options were best in each trial. Klatt et al. [ 64 ] found that Brazilian players were more accurate than German players in their decision-making as they generated a higher number of options, whilst also being more accurate in their first option. Basevitch et al. [ 40 ] reported that experts were more accurate than near experts in their decision response, their intuitive responses were more effective when less time was available, whilst generating more options was more effective when more time was available. Finally, Musculus et al. [ 73 ] only presenting findings supporting the less-is-more process, as participants who generated less options were more successful at indicating an accurate first response.

Dependence on Task Specific Declarative Knowledge

Six studies explored the role of consciousness within the cognitive control of the decision-making process [ 60 , 62 , 63 , 79 , 80 ]. Kinrade et al. [ 62 ] and Jackson et al. [ 60 ] both found that a player’s disposition to engage task specific declarative knowledge in decision-making (decision-reinvestment) or worry about the consequences of a decision (decision-rumination) predicted performance under pressure. Players with a raised tendency to ‘reinvest’ in task specific declarative knowledge or ruminate were more likely to suffer performance decrements when placed under pressure. Similarly, Raab and Laborde [ 80 ] found that players with a tendency to consciously process and deliberate over their decisions were less successful than those who acted through intuition.

Four studies considered the influence of the situation on the level of cognition employed by participants in the decision-making process. Four studies manipulated the complexity of information (number of attackers, defenders and options) and temporal constraints (time available) [ 40 , 63 , 73 , 79 ]. Kinrade et al. [ 63 ] found that tendencies for decision-reinvestment and decision-rumination were both negatively associated with performance on relatively complex tasks yet led to faster and more accurate decisions when the task was less complex. The amount of task specific declarative knowledge available to the players was not associated with the tendency to reinvest in this knowledge base under pressure, or to ruminate [ 63 ]. Raab [ 79 ] manipulated dependence on cognitive resources in learning either by providing a set of ‘if-then’ rules (i.e., task specific declarative knowledge) or by occupying cognitive resources with a subsidiary task (implicit learning condition). He found that task specific declarative knowledge facilitated transfer to relatively complex tasks, whereas, more implicit learning conditions led to superior performance when the task was less complex. Basevitch et al. [ 40 ] compared the anticipation, option generation and option prioritisation of high and low skill soccer players through a video-based decision-making task to explore automatic vs. analytical decision-making processes. Participants were required to watch video clips of footage from 11 vs. 11 game footage and once the screen occluded, anticipate what would happen, identify the possible options, and then prioritise those options by ranking them in their use. Additionally, the temporal constraints were time varied across three trials of 400 ms, 200 ms, and 0 ms and in cued (screen paused at point of occlusion) and non-cued (screen blacked out at point of occlusion) conditions. Skill based differences between groups indicated that high skilled participants automatic/intuitive and analytical decision-making complimented each other. More time gave higher skilled players an increased opportunity to explore and analyse all options successfully, whilst less time demanded a successful automatic/intuitive response. Musculus [ 73 ] employed a comparable video task with soccer players, with short-time (7.5 s) and long-time (30 s) of a paused frame at the point of occlusion. Their findings presented that intuitive decision-making was more effective for both near experts and experts across both conditions.

3.2.2. Ecological Dynamics

Perception-action coupling.

Eleven studies explored the decision-making process as a reciprocal relationship between the player’s perception of the environment and the actions of the player [ 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 74 , 75 , 76 ]. Eight of the eleven studies analysed patterns in players movements in the context of the task environment [ 45 , 46 , 48 , 49 , 50 , 51 , 52 , 74 ]. Passos et al. [ 74 ] found that the distance of the defender from the touchline within a 2 (attackers) vs. 1 (defender) situation in rugby union influenced the attackers decision to pass, which was taken as evidence for decision-making as an emergent process constrained by the player’s capability. Similar inferences emerged from an evaluation of movement responses in relation to variables, including distances between attackers and defenders and the time it took to close tau [ 46 ], the posture of the players [ 52 ], physical height [ 45 ], and the manipulation of instructional and task constraints [ 45 , 49 , 50 ]. Across these six studies, the authors encapsulate this relationship under the term ‘affordances’, which are defined as invitations for action. Similar findings were presented by Correia et al. [ 48 ] and Correia et al. [ 50 ]. Correia et al. [ 48 ] found that skilled rugby player’s decisions were dependent on the emergence of gaps between defenders. The skilled group were found to make a decision to run or pass depending on whether a clear gap emerged between the defenders, whereas the less skilled group were found to take the first gap frequently, regardless of a better option being available. Later, Correia et al. [ 50 ] indicated that decisions emerged depending on the interaction between attackers, defenders, and the touchline as findings demonstrated patterns in players decisions to use lateral movement towards or away from the side-line in 1 attacking vs. 1 defending rugby union player tasks. Esteves, di Oliveria, and Araujo [ 52 ] suggested that a superior capability to perceive affordances can be attributed to the attunement of the player to available perceptual information and better calibration between the information perceived and the capability of the player to meet their intended goal.

Paterson et al. [ 75 ] found that players were led by their intention within the task (to score) and their action capabilities (shooting ability, accuracy). Players tended to minimise the risk of shooting inaccurately by only selecting targets where their probability of scoring was high. Paterson et al. [ 75 ] suggested that a player’s skilled intention was directly guided by their capabilities to score, as a direct result of the decision-making process being ‘grounded in action’. Finally, Pepping, Heijmerikx, and De Poel [ 76 ] found that players decision-making behaviour adapted when shooting towards a target, passing to a teammate or passing over longer distances. They attributed these findings to a relationship between a player’s action capabilities, in this case mainly passing capability, and the opportunities for action that were presented to them. In summary, studies adopting an ecological dynamics perspective, report findings that were proposed to support the notion of decision-making as a coupled process of perception and action that cannot be separated.

Co-Adaption and Shared Affordances

Ten studies explored the process of synergies, co-adaption, and shared affordances within team decision-making behaviour. Silva et al. [ 85 ] found that national level rugby players covered a greater width of the pitch in attack and defence relative to their regional colleagues when the width of the pitch increased, suggesting a collective movement response to changes to task constraints. Collective movement was also identified when an attacking team had a numerical advantage [ 86 , 88 ] and when the number of football goals on the pitch increased [ 89 ]. This was attributed to the notion of co-adaption, where teams implicitly adapt their collective response to changes to the constraints within the performance environment [ 86 ]. Similarly, Correia et al. [ 47 ] explored territorial gain dynamics within sub-elite rugby union players. Their design analysed twenty-two attack vs. defence second phases of play within the opponents twenty-two metre line and measured distance gained by the attacking team. They found that functional groupings of attacking players termed synergies were a likely indicator of increase distance gained, findings also suggested that distance gained was a variable, which may have distinguished between successful and unsuccessful attacks. Ramos et al. [ 78 ] used an action research design to consider the development of team synchronisation, synergies and collective functionality in match play over the duration of a season. Their findings demonstrate that appropriate training environments that represent match demands and increase variability are likely to result in an increase in synchrony of counter attacking play.

Travassos et al. [ 87 ] found high variability in the interpersonal distances of attacking and defending players at the start of the passing task yet identified a convergence in movement at the point of pass initiation. They suggested that the convergence was driven by attacking players (both ball player and supporting teammates) perception of their opponent’s capability to intercept the pass. Correia et al. [ 50 ] also found that higher variability of displacement trajectories between attacking teammates and defensive opponents led attacking players to demonstrate positive decision-making behaviour rather than risk averse behaviour. Similarly, Passos et al. [ 74 ], found that the position of the supporting player and the distance of the defender from the touchline in a rugby 2 vs. 1 situation both influenced the timing of a pass, suggesting that a player making a decision takes into account the action capabilities of others. Four of these studies [ 47 , 78 , 85 , 86 ] explored the emergence of synergies in teams collective decision-making behaviour. Findings indicating co-adapted behaviour were also identified in a 1 attacker vs. 1 defender rugby union task [ 50 ].

3.2.3. Recognition Primed Decision-Making

Four studies [ 61 , 67 , 68 , 72 ] investigate the process of recognition primed decision-making in team sports. The findings of each study fit Zsambok and Klein’s [ 24 ] model of recognition primed decision-making, which proposes that the process a player follows to decide on the best course of action depends on the demands of the situation [ 24 , 61 , 67 , 68 ]. Mulligan et al. [ 72 ] reported that expert ice hockey players identify patterns of play that encapsulate salient information in an attempt to assess the typicality of the situation. Johnston and Morrison [ 61 ] found that expert rugby league players also possess higher levels of pattern recognition and tend to make decisions with little conscious thought when a situation is typical. Taken together the two studies are consistent with Zsambok and Klein’s [ 24 ] view that a situation that is rapidly perceived as typical may only demand a simple match between the situation and a decision as the goals, cues and expectancies present themselves in a rapid and simple fashion (Level I). A situation that is initially perceived as atypical requires diagnosis to decide on an appropriate course of action (Level II), [ 24 ]. Macquet and Kragba [ 68 ] found that as the typicality of the situation decreased, there was a greater requirement for players to deliberately make sense of the unfolding situation and assess the risk associated with, in this instance, running a pre-planned play; players were aware of the risk of a decision having a negative outcome (e.g., loss of the point being played; see also); [ 61 , 67 , 68 ]. The final level of decision processing proposed by Zsambok and Klein’s [ 24 ] describes, a situation that is perceived as typical yet leads to mental rehearsal of multiple courses of action in order to evaluate which course is likely to result in the best possible outcome (Level 3). Both Macquet [ 68 ] and Macquet and Krabga [ 67 ] found that in team sports players rarely verbalised decision-making processes that were consistent with this level of decision. Two studies explored the importance of pattern matching, although not explicitly aligned to the RPD process. Both Poplu et al. [ 77 ] and Gorman et al. [ 58 ] found recurrent relationships between a player’s capability to match patterns and the accuracy of their decision.

Two studies explored the influence of contextual priors on the naturalistic decision-making process of team sport players [ 57 , 65 ]. Levi and Jackson [ 65 ] interviewed professional football players for their perspectives on the impact of context on the decision-making process. Inductive thematic analysis of interview data indicated that dynamic themes, such as personal performance, score status, momentum and external/coach instruction, and static themes, such as match importance, personal pressures and preparation, shape and influence the nature of the decision-making process. Their findings suggest that positive momentum can lead to situational favourableness where players feel that the game is going their way. Winning can result in increased confidence and a higher tendency to take risks, whilst losing can increase risk averse behaviour. Gredin et al. [ 57 ] examined the impact of players’ judgments on available explicit contextual priors and anticipation in 2 vs. 2 video-based soccer decision-making tasks. Judgement and anticipation were measured through accuracy scores and verbal reports of their decision-making process. The findings indicated that expert players use knowledge to recognise explicit contextual priors to inform their judgment and anticipation.

3.3. Characteristics of Decision-Making Expertise

A total of thirty-six studies identified characteristics of decision-making expertise. The results of the thematic analysis have been summarised in Table 3 . Combined in the synthesis were a total of 21 key characteristics that fall under the three broader characteristics of perception, action capabilities and knowledge. We have deliberately chosen not to present these against an assumed theoretical perspective, as we are simply trying to capture the characteristics of decision-making expertise presented by empirical research.

Thematic analysis-characteristics of decision-making expertise extracted from the articles.

3.3.1. Perception

Cue identification.

Twelve studies explored the use of cues within player decision-making [ 40 , 54 , 57 , 59 , 61 , 64 , 65 , 69 , 70 , 71 , 73 , 84 ]. Johnston and Morrison [ 61 ] found that skilled players were able to cluster higher order cues together into one source of information (e.g., the width of a defensive line), whereas less skilled players more readily focus on discrete bits of information (e.g., gaps between individual defenders). ‘Cue clustering’ is presumed to allow numerous sources of information to be seen through one ‘global’ cue, thereby accelerating and optimising the decision-making process [ 61 ]. Similarly, McPherson and Vickers [ 70 ] concluded that expert volleyball players attended to rich chunks of information, as single visual search fixations were congruent with players’ verbalisations of cues and tactical information. These findings suggested that experts tend to perceive rich chunks of information that allow earlier opportunities to act.

Across the studies the findings were consistent in differentiating skill level based on perception of salient information to predict the outcome of an opponent’s action [ 54 , 59 , 61 , 71 , 84 ]. For instance, McRobert et al. [ 71 ] found that skilled cricket players focused on salient information that was proximal to the bowler, such as the bowler’s hand, to anticipate the conclusive location of the ball at the point it would reach the batsmen. Furthermore, within a simulated model of a basketball 1-on-1 situation, Fuji et al. [ 54 ] artificially changed the timing and location of a defenders front foot. The adjustment had a direct impact on the attackers drive direction and the performance outcome. Jackson et al. [ 59 ] found that high skilled rugby players were less susceptible to deceptive information than their less skilled counterparts; implying that skilled performers have learned to discriminate genuine visual information from deceptive information.

Studies included within this review that have explored experts decision-making processes through the take the first heuristic [ 40 , 64 , 73 ], option generation [ 40 , 44 , 64 , 73 ], and contextual priors [ 57 , 65 , 69 ] demonstrate clear findings that experts are able to perceive information of a global and salient nature earlier than less skilled players.

Visual Search

Nine papers used visual search tracking technology to attempt to gain insight into the mechanisms underpinning decision-making in team sport [ 37 , 38 , 41 , 43 , 66 , 70 , 71 , 82 , 83 ]. Four of these studies found that higher skilled players tended to make more visual fixations than lesser skilled players [ 38 , 43 , 71 , 82 ]. McRobert et al [ 71 ] attributed the higher number of fixations made by skilled cricket batsmen to their tendency to search for additional locations to identify the gaps between fielders. In direct contrast, Lex et al. [ 66 ] found that more experienced soccer players made less fixations than their less experienced counterparts when a 11 vs. 11 situation was presented. Roca et al. [ 83 ] reported a similar pattern of findings, when the situation contained only 1 or 2 opponents or teammates. However, unlike Lex et al. [ 66 ], when Roca et al. [ 83 ] presented a full 11 vs. 11 situation more experienced players made relatively more fixations [ 83 ]. The authors of these studies appear to agree that differences reflect the ability of skilled players to adapt their visual search behaviour to the changing demands of the task [ 66 , 71 , 83 ]. Two outstanding findings were presented by Afonso et al. [ 39 ], who found that players fixate for longer when they are in-situ compared to when they respond to screen based stimuli in the laboratory [ 39 ] and Bishop [ 41 ] found that players’ saccadic eye movements were faster left to right than right to left and provided habitual reading from left to right in western culture as the most likely explanation.

3.3.2. Action Capabilities

Six studies [ 43 , 45 , 50 , 52 , 74 , 75 ] explored players action capabilities as a characteristic of decision-making expertise. Bruce et al. [ 43 ] found that the lesser-skilled netball players made decisions independent of their capability to perform the requisite skill. Likewise, Esteves et al. [ 52 ] found that the decision on which side to attack a defender in a 1-on-1 situation was independent of expertise, but was significantly influenced by defender posture (i.e., foot placement). In this case, the action capability of the defender to regain a position to defend the basket influenced the attacker’s decision. The novice attacker’s posture gave away information regarding their upcoming drive direction, while intermediate attackers were better able to hide this information. In contrast, both Passos et al. [ 74 ] and Correia et al. [ 50 ] found significant relationships between rugby players tendency to run and the distance of the defender from the touchline. Passos et al. [ 74 ] suggested that the ball carrier’s capability (speed, skill) to run through the gap between the defender and touchline directly influenced the action performed. Similarly, Paterson et al. [ 75 ] found a significant relationship between a football player’s ability to shoot and the challenge point of the target (target size and distance) they chose to shoot at, as better players chose more challenging targets. The authors suggested that the players’ selections were partially based on perceptions of their capability to meet the task demands. Similarly, Cordovil et al. [ 45 ] found that the height of basketball players was associated with inefficient movement paths towards the basket, resulting in an updated decision response.

3.3.3. Knowledge

Task specific declarative knowledge.

Fourteen studies identified the role of task specific declarative knowledge in decision-making expertise [ 38 , 40 , 44 , 56 , 57 , 58 , 61 , 64 , 65 , 69 , 70 , 73 , 77 ]. Afonso et al. [ 38 ] found that highly skilled volleyball players tended to be able to verbalise a greater number of key pieces of game specific information than their lesser skilled colleagues. Afonso et al. [ 38 ] referred to this task specific knowledge as condition concepts, whereas studies reporting comparable findings refer to consciously accessible clusters of task and domain specific information mental representations, which are recalled from long term memory [ 58 , 61 , 71 , 77 ]. Studies exploring expertise differences present consistent findings where increased retrieval of memory representation is related to more accurate intuitive processes [ 64 , 73 ], option generative processes [ 40 ], and recognition of contextual priors [ 57 , 65 , 69 ]. McPherson and Vickers [ 70 ] found that elite participants are better able to verbalise game specific information following in-situ events. They suggested that the superior recall of game specific information is a result of stored responses in long term memory, which they referred to as mental representations. Additionally, Furley and Memmert [ 56 ] found that recreational basketball players with a low working memory capacity (i.e., more limited cognitive resources] were more susceptible to being distracted by secondary task-irrelevant information than players who have a high capacity, suggesting that the availability of cognitive resource influences a player’s capability to use task specific declarative knowledge. Finally, Klatt et al. [ 64 ] defined expert soccer players’ use of creativity as the ability to create novel and appropriate solutions to problems. In order to measure this they measured the quantity and effectiveness of option generation, which they linked to players knowledge of where to look and why.

Collective Knowledge

Seven studies [ 42 , 45 , 55 , 67 , 68 , 78 , 81 ] explored the concept of collective knowledge within teams. A consistent finding is that shared knowledge of tactical information across a team affords better decision-making. Richards et al. [ 81 ] reported that players adoption of a shared mental model of tactical understanding resulted in a game-to-game increase in effective decision-making and team performance. In a similar vein, findings were reported that signalled the importance to team performance of a ‘playbook’ or shared tactical understanding [ 67 , 68 ]. Similarly, Ramos et al. [ 78 ], albeit from an integrated ecological dynamics and constructivist approach, initiated an action research design to improve a volleyball teams collective synchronicity and decision-making behaviour over the duration of a season. Their findings demonstrated that explicit collective cue perception, shared tactical understanding, having shared strategic game plan, shared anticipation, and prioritisation of roles and responsibilities were at the heart of learning throughout the season. Macquet [ 68 ] refers to the use of teams having a shared understanding of pre-programmed tactics which support better execution of coordinated patterns of play in high-speed match specific situations. Bourbousson et al. [ 42 ] found a total of 47 knowledge elements were shared amongst a basketball team before the start of a competitive match. Following the game, player recollections showed that the collective knowledge pool of the team diminished throughout the duration of the match.

Cordovil et al. [ 45 ] found that tactical instruction had a significant influence on the actions and movements of players. The finding was interpreted as tactical instructions directly influencing the players’ goal directed intentions and the decision that emerges. Finally, Memmert and Furley [ 55 ] found evidence to suggest that specific tactical information provided by coaches can result in players missing important pieces of information.

4. Discussion

4.1. the decision-making process.

The first aim of this review was to use empirical research to better understand the process of decision-making in team sports. Table 2 classifies studies by perspective and presents the representative descriptions of information processing, ecological dynamics, and naturalistic decision-making processes that were extracted from the papers.

Interrogation of the data has unearthed views about the decision-making process that are shared by the different perspectives. Foremost, is the idea that perception of salient information actuates the decision-making process [ 40 , 44 , 48 , 61 , 64 , 68 , 71 , 73 , 77 ]. Taking an ecological standpoint, Esteves et al. [ 52 ] suggested that skilled players are better able to identify opportunities for action afforded by the task environment, which is consistent with the proposal by those taking an information processing view that skilled players are better able to identify salient [ 70 ], predictive [ 71 ], global cues [ 61 ] within the context of their intended goal. The ‘hunt’ for affordances/salient information appears adaptive and dependent on task demands [ 38 , 51 , 66 , 83 ]. It is noteworthy that all the studies reviewed conflate perception of the environment with visual perception, ignoring the prevalence of auditory cues in team sport, e.g., teammates talking to each other. This seems to be a particularly interesting route for investigation. It is important to know more about how perception of information of this kind is integrated into the decision-making process.

How team sport players use, interpret or act upon perceptual information reflects the differences of the three perspectives. Advocates of ecological dynamics suggest that players have an inherent perception of what is technically and physical possible (action capabilities) in the context of the intended goal [ 45 ]. In contrast, those taking an information processing or naturalistic view argue that players develop task specific representations of how (procedural) and why (declarative) to respond in a certain way, which are retrievable from long-term working memory [ 40 , 44 , 53 , 64 , 70 , 73 ]. The pool of task specific declarative knowledge is said to be continually updated with experience of competitive situations (i.e., current event profiles; [ 70 ]) or through an improved tactical understanding presented by the coach [ 68 ]. From an ecological perspective, competitive experience enables a refinement of what the performance environment affords via attuning the player to its salient properties and calibrating the players action capabilities to the perceptual information unfolding before them [ 52 ]. Refined perceptual attunement offers an ecological explanation for Jackson et al.’s [ 59 ] finding that experts are able to see through the deceptive acts of their opponents. Noteworthy, is the interpretation of data by Cordovil et al. [ 45 ] who concludes that expert actions are a result of an interaction between task constraints and coach-led instructional constraints (i.e., tactics). Cordovil and colleagues align themselves to an ecological view yet acknowledge a place for the cognitive processing of task specific declarative knowledge (tactical instruction). Interpretations such as this highlight a significant tension between the perspectives that centres on the presence (information processing and naturalistic decision-making) and absence (ecological dynamics) of mental representation. Taken at face value, the relative quantity of empirical studies aligned to information processing, adds weight to the argument for the presence of memory representations in the decision-making process. However, the reduced quantity of papers aligned to ecological dynamics may be a function of its recent arrival on the team decision-making landscape having been built on previous theoretical perspectives of dynamical systems theory [ 90 ] and ecological psychology [ 91 ]. Furthermore, the uneven representation of perspectives in the included papers may highlight the empirical challenges imposed on research taking a more holistic view of a problem; therefore, it is important not to dismiss this work purely on the quantity of evidence. Tensions can perhaps be calmed by the naturalistic perspective.

From the evidence associated with naturalistic decision-making, there is a suggestion that certain situations demand a cognitive assessment of perceptual information, whereas some situations require little to none. Experts appear to amend their visual search strategies dependent on the type of situation faced and these shifts in visual attention appear to correlate with players’ verbalisations of their cognitive processes [ 66 , 70 , 83 ]. This view is supported by Raab [ 79 ] who identified that the complexity of a task (e.g., number of teammates and/or opponents) dictates the process underpinning a player’s decision-making. Implicit processes lend themselves to low complex environments whereas more explicit processes are more likely to be used in high complex environments [ 79 ]. Situational complexity may be defined by player perception of the typicality of a performance environment [ 67 , 68 ]. Familiar environments afford a simple match of a response to the play unfolding (Level 1 of the RPD process) [ 67 , 68 ] underpinned by implicit processes [ 79 ], whereas atypical environments evoke explicit diagnosis of the decision-making problem (Level 2 of the RPD process). Parallels can be drawn here to Klatt et al.’s [ 64 ] findings regarding the complimentary use of intuition and option generation by elite Brazilian football players, which suggested that successful use of creative and intuitive decision-making processes may dependent on the situation presented in the game [ 64 , 92 , 93 ]. Furthermore, Basevitch et al. [ 40 ] found that the successful use of an intuitive process or option generation was dependent on the temporal constraints (400, 200, or 0 ms) presented in the task. When expert players had more time, they generated more appropriate options, whilst when they had less time, intuitive processes were identified as being more accurate. Based on the evidence, it is logical to subscribe to the view that “cognition is best understood by looking at its environment” [ 93 ], cited in [ 79 ] p. 428.

The data has also suggested that the tendency to engage cognitive resources in decision-making is dependent on the player. Certain individuals depend more on conscious processes to select a course of action [ 60 , 63 , 80 ] particularly under pressure and sometimes inappropriately (e.g., low complexity tasks) [ 63 ]. In sum, the findings imply that the role of cognition in the decision-making process in team sports is fluid and dependent on the complexity/typicality of information available [ 79 ], the time available [ 40 , 67 ] and player disposition [ 60 , 62 , 63 , 80 ]. Furthermore, findings presented from Levi and Jackson [ 65 ], Gredin et al. [ 57 ], and Magnaguagno and Hossner’s [ 69 ] indicated that it is not only the complexity and temporal constraints of a situation that drive a decision-making process, but the explicit contextual priors that are available to a player. Dynamic contextual priors include assessment of personal performance, the score status, feelings of momentum and external coach/player instruction [ 57 , 65 , 69 ]. Whilst static contextual priors include the match importance, personal pressures, and a player’s preparation for a game [ 65 ]. Contextual priors capture a significant amount of social and psychological factors that can cause players to: be more confident, make risk averse decisions or risky decisions, reinvest in task specific declarative knowledge, feel pressured, experience feelings of situational favourableness, and identify strengths and weaknesses of teammates and opposition [ 57 , 65 , 67 ]. Levi and Jackson [ 65 ] and Gredin et al. [ 57 ] findings suggest that both dynamic and static contextual priors significantly influence the perception of game information and the decision itself [ 57 , 65 , 69 ]. Subsequently, this evidence suggests that a more integrated view of the decision-making process may be the best way to progress our understanding of a player’s decision-making in team sports.

Consideration of Methods

From the findings three distinct methods were unearthed, which included real time in-situ experiments (on field and lab based), a posteriori assessments of the decision-making process and verbalisation methods. Additionally, ten articles combined a posteriori evaluation with verbalisation methods of assessment [ 40 , 61 , 64 , 66 , 67 , 68 , 71 , 72 , 82 , 83 ] whilst two articles combined real time assessments with verbalisations [ 53 , 70 ]. Given the consistency in methods used across and between the fifty three articles it is essential to discuss (i) the study design taken; (ii) the measure/assessment of the decision-making process; (iii) when/how the decision-making process was analysed; and (iv) the consistency and validity of the method adopted. From the thematic analysis it is clear that the research perspective adopted by authors has driven the method taken to assess the decision-making process. Put simply, in the assessment of decision-making in team sports, paradigm seems to drive method.

Logically, the findings from each of these methods or combination of methods have resulted in contrasting findings regarding the decision-making process. Real time experiments of basketball players [ 52 ] and rugby union players [ 74 ] taken from the ecological view suggest that players actions and therefore their decision-making is dependent on the constraints of the task and their attunement to it. Despite these conclusions, no examination of perceptual attunement takes place. Instead, real time experiments assessing netball [ 43 ] and rugby union [ 59 ] from the information processing perspective indicate that previous declarative knowledge, procedural knowledge, technical ability, and perception of options all influence the resulting course of action [ 43 , 59 ]. It would seem that research has been somewhat constrained by a mixture of perspective driven methodology and a need to make a complex problem simple enough to research (see Table 1 ). The use of real time experiments without eye tracking, verbalisations, or interviews therefore results in findings that often overlook key elements of the decision-making process. Similarly, articles that have used a posteriori or verbalisation methods alone have also disregarded central components of the decision-making process explored elsewhere. For instance, Correia et al.’s [ 46 , 47 , 51 ] use of performance analysis measures of match footage assessed team decision-making to find that synergies and coadaptation account for collective decision-making in team sports. This approach relies on the validity of each researcher’s assessment of the game situation and a reliance on subjective inclusion of which game variables should form post hoc analysis. Furthermore, this body of work overlooks the importance of tactics and strategy, which are frequently highlighted as a key variable in successful decision-making in numerous articles included in this review [ 61 , 67 , 68 , 81 , 82 , 83 ]. Unsurprisingly, the same questions present themselves for articles that employ verbalisation/interview methods alone to assess the decision-making process, as task and environmental contexts are often ignored or over-exaggerated [ 16 , 65 , 84 ].

In contrast, more balance is found in the findings from studies that have employed a combination of methods, such as self-confrontation interviews [ 67 , 68 , 72 ], combination of video decision-making tasks with eye tracking measures [ 53 , 66 , 70 , 82 , 83 ], or combining video tasks alongside verbalisations [ 61 , 64 , 72 ]. The methods used within these articles allow for players perception, selection and a combination of both in conjunction with one another to be considered. Subsequently, the findings from these studies offer inferences that draw connections between deep declarative knowledge of their sport [ 61 , 64 , 66 , 67 , 68 , 71 , 72 , 82 ], their use of knowledge in their sport [ 53 , 70 , 82 , 83 ], the capacity to recognize [ 61 , 64 , 67 , 68 ] and make sense [ 61 , 64 , 66 , 67 ] of perceptual information offered within competitive situations and how these variable impact on the first options taken [ 61 , 64 , 68 ], and possible options that are available [ 64 , 68 ].

As a result of these findings there are key limitations in the methods adopted in the articles reviewed in this paper. Researchers drawing on ecological dynamics have focused on small decontextualized sub-phases of team sports, such as 2 vs. 1 situations in rugby union [ 74 ] or 1 vs. 1 situations in basketball [ 52 ], which, somewhat ironically, can lack representativeness because they do not fully capture variants in the complexity (typicality) of the criterion environment. For instance, Correia and colleagues [ 46 , 47 , 48 , 49 , 50 ] study of decision-making in rugby union considered a player’s decision to pass or run with the ball, but the authors offered generalised practical implications to coach all decision-making instances within rugby union. Given the findings regarding the impact of the game situation on the decision-making process presented in this review, the generalizability of practical implications offered by these authors should be questioned. Second, all five of Correia and colleagues papers [ 46 , 47 , 48 , 49 , 50 ] make the assumption that mental representations do not exist in the decision-making process leading them to ignore the question regarding the presence/absence of cognitive mechanisms in their method. We would argue that this approach demonstrates high levels of confirmation bias in reference to the research questions they pose. Consequently, future research investigating player decision-making in rugby union from the ecological dynamics perspective should employ methods that will test their conception of the decision-making process, not simply confirm it. In a similar fashion, research adopting information processing or naturalistic perspectives reduce the ecological validity through decoupling perception and action when using verbal [ 70 ] or non-representative action responses to video stimuli [ 71 ].

In light of the findings and limitations from each of the articles adopting real time, a posteriori and verbalisation methodologies, it seems imperative that future research ensures a full assessment of the decision-making process. That is, what a player perceives, the choices they have and how and why they come to their final decision. The findings from this systematic literature review suggest that future research attempting to understand and assess the decision-making process should combine the use of real time, a posteriori and verbalisation methods. Furthermore, the findings lead us to suggest that future research should consider an approach to study design and measurement that is not informed by a single perspective, which is, paradigm should not drive method. Researchers should consider manipulating or measuring the complexity (or typicality) of information through task (space, time, number of players), contextual priors (dynamic and static), or environmental (pressure, fatigue) constraints in order to explore how player decision-making may change. The measurement of such tasks might aim to capture specifying variables (visual, auditory, and kinaesthetic cues) [ 61 , 82 , 83 ], the presence/absence of cognitive mechanisms [ 64 ], and the resultant actions through retrospective performance analysis task analysis [ 68 ] or self-confrontation interviews [ 67 ]. A broader view on how the process of decision-making in team sports can be investigated and how data may be explained, may advance both our understanding of how players make decisions in team sports and the communication of findings to applied practitioners [ 94 ].

4.2. Characteristics of Decision-Making Expertise

The second aim of this systematic review was to comprehensively capture the characteristics of decision-making expertise within team sports. Higher-order characteristics of perception, action capabilities, and knowledge emerged from the inductive analysis of the findings (see Table 3 ) that each comprised of more specific characteristics of decision-making expertise.

4.2.1. Perception

The identification of salient cues, predictive cues, and global cues within the performance environment have been presented as independent characteristics of perceptual expertise. Yet, closer inspection of the data suggest that, in a team sport context where temporal demands require players to anticipate the actions of opponents (and teammates), salient cues are most often predictive and are likely clustered into a global representation of the information [ 61 ]. Higher-order representations of salient information may underpin the concept of a simple match between perception and action [ 61 , 68 ] that allows experts to operate effectively under time pressure, as well as allowing experts to see through deceptive behaviour [ 59 ].

To provide insight into the information extracted by expert players, eye tracking technology has been employed. The research reviewed here identifies there is a level of ambiguity in the patterns of visual search data displayed by experts. Research suggests this ambiguity can be attributed to the specific demands of the task that attention is not necessarily aligned with gaze [ 66 ] or the decoupling of perception and action [ 95 ]. A cautious summary of the visual search data is that experts adapt their visual search behaviour according to the constraints of the task in order to extract salient information.

Despite no attempt to measure perceptual expertise (see Table 3 ), researchers adopting an ecological perspective in team sports have inferred that experts are better able to perceive opportunity for action (affordances) offered by the environment [ 48 , 74 ]. Support for such claims comes from research studying an individual sport. Berg and colleagues [ 96 , 97 ] compared experts and non-experts visual search during long jump performances. They presented evidence that the strategy of visual regulation of action in locomotion towards a target in space is not a function of extensive task-specific expertise, but instead the jumper can become better attuned to specifying information. Similarly, the superior decision-making behaviour of higher skilled players is assumed to be a consequence of the player being perceptually more attuned to the performance environment [ 52 ]. Further empirical work is needed to verify such claims in team sport environments.

4.2.2. Action Capabilities

The concept of action capabilities is at the heart of ecological psychology and much of the data supports the notion that a player’s physical (e.g., speed) [ 74 ] and technical [ 75 ] attributes influence the action taken. Two studies failed to differentiate the decision-making of higher-level players from their lower-level and, presumably, less physically and technically capable counterparts. Bruce et al. [ 43 ] found that lesser skilled players made decisions that they were unlikely able to execute. Similarly, Esteves et al. [ 52 ] could not differentiate novice and intermediate attackers by their decision to attack the defender’s most advanced foot. However, their findings did show that novice attackers gave away postural information about their upcoming action, while intermediate attackers were better able to conceal this information. Esteves et al. [ 52 ] interpreted these findings as the novice players being perceptually attuned to the posture of their opponent before their action capabilities were calibrated sufficiently to successfully beat the defender. In other words, novice players could see the opportunity for action (i.e., the affordance) but could not accept the invitation. Advocates of ecological psychology contend that player’s need time interacting with the performance environment in order to recalibrate (or scale) their action (motor) system should their action capabilities have changed [ 98 ]. How much time is needed to calibrate effectively and whether experience moderates the time needed for and the precision of the calibration are pertinent questions for future research. Presumably, expert players are better equipped to deal with fluctuations in physical conditions across a match.

In summary, the notion that responses to an opponent’s action are subject to a player’s action capabilities suggest that experts physical and technical prowess, if calibrated, offers a wider array, and presumably more effective, opportunities for action (or tactical options). This idea closely parallels Launder’s pithy phrase [ 99 ];

“ what is tactically desirable must be technically possible. ”. [ 99 ] p. 59

4.2.3. Declarative Knowledge

The use of task specific declarative knowledge and the use of collective knowledge both emerged as characteristics of expertise ( Table 3 ). There is a weight of evidence to suggest that experts possess a richer pool of task specific declarative knowledge [ 38 , 53 , 66 , 70 , 71 ]. Mental representations afford rapid selection of suitable action plans that allow experts to effectively operate in dynamic game environments [ 53 ]. Retrospective recall methods have been frequently used to gauge the quantity of task specific declarative knowledge accessible to players, but the methods are limited by assumptions that player’s accurately recall the knowledge used to formulate a response, e.g., [ 66 ]. Other ways of capturing knowledge have been employed and have tended to validate findings reported using recall methods, such as self-confrontation elicitation interviews [ 61 ] or the alignment of retrospective recall with visual search behaviour [ 70 ]. It is the job of research now to better understand how expert team players make best use of their more advanced declarative knowledge pool in competitive situations.

The data reviewed suggests that tactics are an extension of a player’s task specific declarative knowledge. Tactics, commonly imparted by a coach, guide players to key pieces of information [ 45 , 68 ], and allow them to respond to situations faster [ 66 ]. Decision-making expertise is not simply characterised by the knowledge of tactics, but how that tactical information can be operationalised in competitive game situations [ 66 , 81 ]. A caveat was put forward by Memmert and Furley [ 55 ] who argued that coach-led tactical instruction can blind a player’s perception of salient information. This assertion highlights the importance of coaches using tactics to scaffold the game for the players [ 2 ], while still allowing them to be attuned to salient information [ 55 ] and make use of individual players task-specific declarative knowledge [ 70 ] and experience [ 52 ] to identify opportunities for action. Indeed Pennington, Nicolich and Rahm [ 100 ] have long since suggested that allowing learners to elaborate procedural learning drawing on their own declarative knowledge, significantly supports transfer of that learning.

The use of tactical information has not only been explored at player level but also at team level. Shared mental models are presented as internalised tactical knowledge that extends to players having a shared view of salient information [ 81 ]. Teams who have a shared understanding of how they intend to play tend to be better able to coordinate more effectively and to make decisions in high pressure situations [ 67 , 68 , 84 ]. Shared mental models provide a framework for players to act within [ 2 ], but team adherence to the model can diminish across the course of a game [ 42 ]. This is may be a result of a team’s coordination through a shared mental model [ 81 ] being worked out by their opponent, which may demand a more emergent coordination of behaviour between teammates to achieve their intended goal [ 87 ]. Interestingly, Ramos et al.’s [ 78 ] study also employed an action research approach to improving team synchronisation in volleyball but from an ecological and constructivist perspective. Non-linear design principles are advocated as the central mechanism for the findings however the data clearly indicates that shared cue perception, shared tactical understanding, building a shared strategy and game plan, aiming for shared anticipation and shared priorities were all coach led practices used to improve the synchronicity of the teams counterattack behaviour. The similarities in method, approach, and strategies used throughout this action research seem to mirror that of Richards and colleagues [ 81 ] yet no reference is made to that work.

This explanation reflects conceptual research that has integrated the perspectives to explain team coordination [ 101 ]. Steiner et al. [ 101 ] consider shared mental models as a ‘top-down’ approach-in which internalised goal-directed tactics and behaviours drive coordinated group action-and the concept of shared affordances as a ‘bottom-up’ approach-in which group behaviour emerges from a shared inherent attunement to the opportunities for group action. Interestingly, these authors have stressed the importance of situational complexity on the nature of how decisions are executed, whether through shared mental models or shared affordances. In other words, team decision-making behaviour is dependent on the rules of the game and the demands of the situation, otherwise known as the internal logic of the sport. Steiner and colleagues [ 101 ] conception clearly implies that shared mental models [ 81 ] and shared affordances [ 74 ] sit at opposite ends of a team coordination continuum. Furthermore, co-adaption and synergies were highlighted a key discriminators of more successful decision-making teams, these papers have all identified collective patterns and functional movements of dyads (sub groups of players), but only through the assumption that this behaviour is emergent and self-organised [ 46 , 47 , 78 , 85 , 86 , 88 ]. It would be interesting to explore qualitative methods to explore the tactics and strategy that underpins team coordination, as it may unearth a more explicit motive behind the synchronicity and synergy demonstrated by players [ 101 , 102 ]. Thus, an appreciation of both ideas may help researchers and applied practitioners better understand how successful teams coordinate their actions and the key mechanisms behind it [ 94 ].

5. Conclusions

The interrogation of the empirical literature has identified a tension regarding the absence and presence of mental representations within the decision-making process that has been driven by differences in perspectives. However, an impartial appraisal of the data suggests that each perspective contributes to our collective understanding of decision-making in team sports. Decisions on how to act may be emergent [ 45 , 48 , 67 ], may be a product of a simple match [ 61 , 68 , 80 ] or require high-level diagnostic [ 68 , 82 , 83 ] or evaluative processing [ 4 , 67 , 68 , 81 ]. Therefore, the empirical evidence suggests that decisions can be placed on a continuum from bottom-up emergent behaviour to top-down evaluation according to the level of cognitive processing invested in the process. The early indication is that the complexity [ 79 ], typicality [ 68 ], time [ 40 ] and the contextual priors [ 57 , 65 ] within game information presented by dynamic team sport situations dictate the point a decision lies on the continuum.

The polarity of views is somewhat underscored by the lexicon adopted by different perspectives. Independent of perspective, perceptual expertise is defined by a player’s capability to identify the most salient information within the context of the intended goal [ 52 , 61 ] yet is described under three different terminologies, salient cues, perceptual attunement, and affordances. Long term working memory and perception of action capabilities describe factors that guide perception and are updated by current event profiles [ 70 ] and calibration [ 52 ], respectively. Decision-making processes are further influenced by tactics/coach-led instructional constraints [ 45 , 58 ] that reinforce goal-directed behaviour. At a team level, a group’s action is coordinated by reference to a shared mental model [ 80 ] and collective attunement to the shared affordances [ 6 , 87 ] offered by the game situation. Therefore, this systematic literature review formed the conceptual basis for Ashford, Abraham, and Poolton’s [ 94 ] communal language for decision-making in team sports.

It is our belief that the literature associated with understanding decision-making in team sports is selling itself short by failing to integrate ideas, accepting conceptual ideas over empirical evidence and accepting evidence and practical implications from unrelated sports and contexts that are fundamentally untested in the team sport domain. At present, research is this area is driven by specific perspectives that lead to interpretation of findings that fall victim to bias [ 103 ]. It may be better for empirical investigation of decision-making in team sports to be shaped by the rules of the sport [ 94 ] and the data examined through a variety of theoretical lenses to explore what happens, what works, and why.

Author Contributions

M.A., A.A. and J.P. contributed equally in the production of this review article. Additionally, All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement.

Data is contained within the article. The data presented in this study are available in the articles reviewed indluded in the reference list.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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A systematic review of the psychological and social benefits of participation in sport for children and adolescents: informing development of a conceptual model of health through sport

• Rochelle M Eime 1 , 2 ,
• Janet A Young 1 ,
• Jack T Harvey 2 ,
• Melanie J Charity 1 , 2 &
• Warren R Payne 1  

International Journal of Behavioral Nutrition and Physical Activity volume  10 , Article number:  98 ( 2013 ) Cite this article

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There are specific guidelines regarding the level of physical activity (PA) required to provide health benefits. However, the research underpinning these PA guidelines does not address the element of social health. Furthermore, there is insufficient evidence about the levels or types of PA associated specifically with psychological health. This paper first presents the results of a systematic review of the psychological and social health benefits of participation in sport by children and adolescents. Secondly, the information arising from the systematic review has been used to develop a conceptual model.

A systematic review of 14 electronic databases was conducted in June 2012, and studies published since 1990 were considered for inclusion. Studies that addressed mental and/or social health benefits from participation in sport were included.

A total of 3668 publications were initially identified, of which 30 met the selection criteria. There were many different psychological and social health benefits reported, with the most commonly being improved self-esteem, social interaction followed by fewer depressive symptoms. Sport may be associated with improved psychosocial health above and beyond improvements attributable to participation in PA. Specifically, team sport seems to be associated with improved health outcomes compared to individual activities, due to the social nature of the participation. A conceptual model, Health through Sport, is proposed. The model depicts the relationship between psychological, psychosocial and social health domains, and their positive associations with sport participation, as reported in the literature. However, it is acknowledged that the capacity to determine the existence and direction of causal links between participation and health is limited by the fact that the majority of studies identified (n=21) were cross-sectional.

It is recommended that community sport participation is advocated as a form of leisure time PA for children and adolescents, in an effort to not only improve physical health in relation to such matters as the obesity crisis, but also to enhance psychological and social health outcomes. It is also recommended that the causal link between participation in sport and psychosocial health be further investigated and the conceptual model of Health through Sport tested.

Regular participation in physical activity (PA) is imperative for good health. Active people benefit from higher levels of health-related fitness and are at lower risk of developing many different disabling medical conditions than inactive people [ 1 , 2 ]. It is widely acknowledged that the health benefits of participation in PA are not limited to physical health but also incorporate mental components [ 1 , 2 ].

Extensive research has resulted in clear recommendations of the level of PA required to produce health benefits [ 1 , 3 ]. There are specific health-related recommendations for children and adolescents distinct from those for adults. For people aged 5–17 years it is recommended that they undertake moderate or vigorous activities for at least 60 minutes per day [ 4 ]. Regular maintenance of this level of activity by children and adolescents can result in increased physical fitness, reduced body fat, favourable cardiovascular and metabolic disease risk profiles, enhanced bone health and reduced symptoms of depression and anxiety [ 1 ]. Whilst many different health benefits of participation in PA are acknowledged, the vast majority of research has focused on the physical health benefits of participation in PA, with less research focused on the mental and social health aspects. Although mental health benefits have been referenced in recent guidelines, to date ”insufficient evidence precludes conclusions about the minimal or optimal types or amounts of physical activity for mental health” [ 1 ] (Part G Section 8 p39).

Even though the World Health Organisation definition of health (2006) incorporates physical, mental and social health domains, the research providing evidence to the PA guidelines does not specifically address social health. However, the literature informing PA guidelines does suggest that aspects such as social support may contribute to some of the explanations of mental health outcomes [ 1 ].

Leisure-time PA is one domain of PA. Sport is one type of leisure-time PA which is organised and usually competitive and played in a team or as an individual [ 5 ]. Participation in sport is very popular among children. However there is evidence that participation in sport peaks at around 11–13 years before declining through adolescence [ 6 , 7 ]. Conversely, there is research indicating that children who are active through sport are more likely to be physically active in adulthood than those who do not participate in childhood sport [ 8 , 9 ]. Further, substantial public investment in sport development has been justified in terms of a range of health benefits [ 10 ], but without a clear understanding of the best way to achieve maximum health benefits - both mental and physical.

Extensive research has been conducted on the determinants of participation in PA [ 6 , 11 ] and on interventions that attempt to increase PA participation [ 12 ], with relatively little research focusing more specifically on sport [ 9 , 13 ]. Also, with regard to the health benefits of PA, the research has generally not extended to the mental and social health benefits of sport participation in particular.

A conceptual model in the public health area has been defined as “diagram of proposed causal linkages among a set of concepts believed to be related to a specific public health problem” [ 14 ] (p163). Determinants of PA are increasingly being understood using socio-ecological models, whereby intrapersonal, interpersonal, organisational, environmental and policy variables are identified as influences on participation [ 15 – 18 ]. As Earp and Ennett (1991) explain, conceptual models in health do take an ecological perspective, implying that behaviours or health outcomes result from the interaction of both individual and environmental determinants [ 14 , 19 ]. In terms of the sport and health nexus, we are not aware of a conceptual model that depicts the specific mental and social health outcomes of sport participation. Conceptual models have been developed which show the relationship between different types of PA, including sport, and the intensity and context of participation [ 20 ], however they do not extend to the health benefits of participation. In one systematic review of the effectiveness of interventions to increase physical activity, a conceptual model of the relationship between interventions, modifiable determinants, immediate outcomes and health outcomes was developed [ 21 ]. However, this study did not specifically identify sport. Furthermore, there are many clinical conceptual models depicting health outcomes of clinical conditions, however they do not focus on the general population or on preventive health or health promotion [ 22 ].

Firstly, this paper presents the results of a systematic review investigating the psychological and social benefits of participation in sport for children and adolescents. Secondly, the information obtained in the systematic review has been used to develop a conceptual model: the conceptual model of Health through Sport, for children and adolescents.

The criteria for considering studies for this review were as follows.

Inclusion criteria were:

Studies published in English between Jan 1990 and May 2012 inclusive.

Original research or reports published in peer review journals or government or other organisational publications which reported primary data.

Studies that presented data that addressed mental and/or social health benefits from participation in sport. In this context, the following definitions were adopted: ‘sport’ - “a human activity of achieving a result requiring physical exertion and/or physical skill which, by its nature and organisation, is competitive and is generally accepted as being a sport” [ 23 ]. ‘health’ – “a state of complete physical, mental and social well-being and not merely the absence of disease and infirmity” [ 24 ]; ‘mental’ - “of or referring to the mind or to the processes of the mind, such as thinking, feeling, sensing, and the like” [ 25 ] (p475) ‘mental health’ – "Mental Health refers to a broad array of activities directly or indirectly related to the mental well-being component included in the WHO's definition of health…It is related to the promotion of well-being, the prevention of mental disorders, and the treatment and rehabilitation of people affected by mental disorders” [ 26 , 27 ] ‘social’: “Relating to the interactions of individuals, particularly as members of a group or a community ” [ 25 ] (p475); ‘social health’: “That dimension of an individual’s well-being that concerns how he gets along with other people, how other people react to him, and how he interacts with social institutions and societal mores.” [ 28 ] (p 152). In this study, we also used the following terms: ‘psychological’ – as a synonym for ‘mental’; and ‘psychosocial’ - “…any situation in which both psychological and social factors are assumed to play a role” [ 29 ] (p638).

Studies where the data pertained to the individual level (i.e. for persons versus communal or national level).

Exclusion criteria were:

Studies or reports that addressed ‘exercise’ , ‘physical activity’ , ‘physical education’ , or ‘recreation’ , and not sport. Definitions of these terms are: ‘Exercise’ –“physical activity that is planned, structured, repetitive, and purposive in the sense that improvement or maintenance of one or more components of physical fitness is an objective” [ 27 ] (p128); ‘Physical activity’ - “bodily movement produced by skeletal muscles that results in energy expenditure” [ 27 ] (p126); ‘Physical education’ - “a sequential, developmentally appropriate educational experience that engages students in learning and understanding movement activities that are personally and socially meaningful, with the goal of promoting healthy living” [ 30 ] (p8); ‘Recreation’ – “pleasurable activity” [ 31 ] (p. 915).

Research/reports that addressed participation in ‘adapted’ sports (i.e. sport participation for persons with a physical and/or intellectual disability, such as wheelchair tennis).

Research/reports that addressed sub-populations subject to specific risks (i.e. studies with heroin users, ‘at risk’ individuals etc.).

Research/reports that addressed rehabilitation from, or management of, injury or illness.

Research/reports that addressed spectators, coaches or sports administrators.

Research/reports that addressed elite sports participants

Research/reports that addressed ‘sport development’ programs that have an educational objective.

Book chapters, abstracts, dissertations and conference proceedings.

Search methods for identification of studies, reports and publications

A systematic search of 14 electronic databases (AUSPORT, AusportMed, CINAHL, Cochrane Library, EBSCHOHost Research Databases, Health Collection, Informit, Medline Fulltext, PsycARTICLES, Psychology and Behavioral Sciences Collection, PsycINFO, PubMed, Scopus, SPORTDiscus Fulltext) was conducted in June 2012. We also consulted with the Australian Sports Commission to search the National Sports Information Centre records in order to identify relevant reports, publications and research not located through the search of the electronic databases cited above. Further, we conducted an internet search using the Google Scholar search engine ( http://www.googlescholar.com ) to locate studies in the Medicine, Social Sciences, Arts and Humanities subject areas. The Google Scholar search engine was also used to search for recognised International, National and State reports and publications that directly addressed the topic under consideration.

To search the electronic databases a combination of keywords and search terms was adopted. These key words and search terms were formulated by the authors of this systematic review as those they considered directly addressed the topic under consideration. These keywords and search terms constituted four groups, namely:

Group 1: sport

Group 2: health

Group 3: value, benefit, effect, outcome

Group 4: psychology, depression, stress, anxiety, happiness, mood, quality of life, social health, social relations, well, social connect, social functioning, life satisfaction, mental health, sociology, social.

Accordingly where possible, the database searches consisted of key words from Group 1 AND Group 2 AND Group 3 AND Group 4. The truncation symbol was added to the most basic word stem for each keyword to ensure all associated terms were included in the search.

Study selection

Figure  1 provides a summary of the stages of study selection. Titles and abstracts of potentially relevant articles were screened by JY. Authors, JY and RE examined all full-text articles, and assessed the studies to ensure that they met the inclusion criteria. Any discrepancies were resolved through discussion between the two reviewers. Consensus was obtained for all included articles. After reviewing the selected studies it was decided, given the breadth and complexity of the research domain, that studies focusing on children and adolescents should be reviewed separately from studies focusing on adults, This review focuses on children and adolescents only; studies that stated that they specifically investigated children and/or adolescents, but not adults (18 or above), were included.

Stages of study selection.

Data collection and analysis

Data extracted from each of the studies included: study design and methodology; sample size; country of origin; age of participants; cohort of participants; gender of participants; study aim; sport variable; other PA variables; theoretical construct; key findings in relation to psychological and social health outcomes.

Assessment of study quality

Study quality was objectively appraised using the Downs and Black checklist [ 32 ]. This checklist has been used in other systematic reviews within the physical activity and health field [ 33 , 34 ]. This checklist includes 27 items grouped into categories: reporting (10), external validity (3), internal validity - bias (7), internal validity – confounding (6), and power (1). Twenty five items are scored as 1 (compliance) or 0 (non-compliance or inability to determine compliance); one item about confounding is scored as 2 (full compliance), 1 (partial compliance) or 0 (non-compliance or inability to determine compliance); and the item concerning power is scored (via a more complex algorithm) on a scale of 0–5.

Because most of the studies we reviewed did not involve interventions, a number of the items on the Downs and Black checklist were not generally applicable. We substituted a simpler power item (presence or absence of reference to a power analysis), and scored all items as 0, 1 or NA (not applicable). We calculated a summary quality score for each paper (except the two qualitative papers for which only five items were applicable) by expressing the number of compliant items as a percentage of the number of applicable items. We included these scores (ranging from 33% to 88%) in Table  1 , and used the insights we gained through the scoring process in our discussion of study quality.

Conceptual model development

Based upon the literature presented in this review, a conceptual model of Health through Sport has been developed (Figure  2 ). The model depicts the relationship between determinants driving sport participation and the reported psychological and social health benefits of participation. The terminology used in this conceptual model is as defined in the inclusion criterion 3 above. The determinants are represented as per the Socio-Ecological Model [ 19 , 65 ]. Upon reviewing the studies, two dimensions of sport participation were identified, and it became evident that some reported health benefits were more likely to be associated with some contexts of sport participation than others. Therefore, a model was developed to represent the two contextual dimensions of sport participation and the different strengths of association between different contexts of sport participation and the three health aspects (physical, psychological and social).

Health through Sport conceptual model.

With regard to causality, we note that most studies have been cross-sectional and observational in nature, and hence do not provide strong evidence of causality. The literature suggests that sport can have positive health benefits; however it is also the case that better health may predispose people to initiate and maintain participation in sport. A few longitudinal studies provide stronger evidence of causality. However, in the absence of randomised and controlled experimental studies, which are challenging to implement in this domain, it will remain difficult to unequivocally determine the nature and direction of causality. Notwithstanding this, terms like ‘outcome’ and ‘benefit’ of sport participation have been used to describe the results of many of the studies reviewed, and we have used the same terminology in reviewing these studies.

Results and discussion

A total of 3668 publications were initially identified. Table  1 provides a summary of the 30 studies that met the inclusion criteria. Since the studies were generally conducted within schools, they included school age children and adolescents, generally 18 years or less. Most studies were quantitative (n=26) rather than qualitative (n=3), with one study incorporating both quantitative and qualitative methods. There were no randomised controlled trials, and the majority of studies were cross-sectional and observational (n=21). Of the longitudinal studies (n=9), the time between data collection was generally between 1 and 3 years (n=7), with one study reporting 12 years between data collection periods. The sample sizes ranged considerably, from 22 participants to large national surveys of over 50,000 participants. The United States of America was the country where most studies were conducted (n=21), followed by Canada (n=4), Switzerland (n=3), and Germany, United Kingdom and Puerto Rica (n=1). One study was conducted with participants across two countries, the USA and Puerto Rica. The age ranges of the children and adolescents differed considerably across studies. Six studies incorporated data from both the child or adolescent and their parent(s).

Most studies scored highly on the modified Downs and Black scale of study quality (median 75 percent; range 33–88 percent). Those studies within the highest tertile score range were all cross-sectional quantitative studies [ 39 , 41 – 43 , 46 , 49 , 51 – 53 , 62 ]. Only one of the 10 studies in the highest tertile score range incorporated a theoretical approach - the Theory of Youth Development [ 41 ]. Half of these 10 studies investigated differences in health measures between participants in sport/club sport and either other organised activities or no sport [ 41 , 43 , 49 , 53 , 62 ]; the other half more specifically investigated team sport participation in comparison to less or no team sport [ 39 , 42 , 46 , 51 , 52 ]. There was no clear distinction between the key findings of higher and lower ranked studies; both high and lower quality studies reported similar associations between sport participation and the psychological and social health domains.

Prima facie, longitudinal studies can provide greater strength of evidence regarding causality than can cross-sectional research. However, all of the longitudinal studies reviewed [ 35 , 40 , 44 , 50 , 58 ] had other methodological limitations, and as a consequence were not represented in the highest tertile of study quality scores. The results of these studies were consistent with those of the cross-sectional studies.

There were few (n=2) qualitative studies, and similar health benefits of participation in sport were also reported in the quantitative studies. The study by Holt et al., (2011) provided more depth than was captured in the other studies reviewed. Interviews with parents and children unearthed a wide range of developmental benefits, both personal and social benefits [ 36 ]. Psychological aspects of emotional control and exploration were reportedly related to sport participation. In addition, social benefits of relationships with coaches and friends were reported in this study [ 36 ].

The investigation of health benefits through participation in physical activity mainly involved cross-sectional surveys conducted through schools. In most cases the students were not allocated to a participation group prior to the study, and as such there were no control groups. This limits the capacity to attribute causality of participation on health outcomes.

The psychological and social health measures in each study were diverse (Tables  1 and 2 ). The most common variables related to psychosocial functioning and emotional wellbeing (n=6), followed by risk of depression and mental ill health (n=5), developmental aspects/behaviour (n=4), social anxiety and shyness (n=3), self-esteem (n=3) and suicidal behaviour (n=3). Some studies (n=15) investigated the differences between sports and non-sports participants, but many did not distinguish between sport and other categories of PA. In the studies involving adolescents, it was common to investigate differences in youth behaviour and development according to their participation (or not) in out-of-school extracurricular activities. Sport was sometimes defined as ‘school sport’ , ‘club sport’ or ‘team sport’; however no studies investigated associations between specific types of sport and psychological or social health domains.

Table  2 provides a broad overview of the health outcomes found to be significantly and positively associated with sports participation, and lists the studies that reported each health outcome. The most common positive outcomes were higher self-esteem (n=6 studies), better social skills (n=5 studies), fewer depressive symptoms (n=4 studies), higher confidence (n=3 studies) and higher competence (n=3 studies) amongst sport participants than non-sport participants. In total 40 different psychological and social health factors were reportedly associated with participation in sport.

In general, there were few theoretical constructs used to frame or explain the research findings. Only six studies (20%) incorporated theoretical or conceptual constructs. The most frequently adopted construct (n=3) was the theory of Positive Youth Development [ 36 , 40 , 41 ], which propounds the notion that children are ‘resources to be developed’ rather than ‘problems to be solved’, and that all youth have the potential for positive development [ 66 ].

One study that incorporated the theory of Positive Youth Development [ 36 ] also utilised an ecological approach, whereby the study was exploratory and not guided by one specific theory. In this case these researchers investigated the intrapersonal and interpersonal benefits of participation in sport. Similarly, an ecological approach has been combined with other theories such as the Socialisation Theory [ 57 ]. Brettschneider (2001) proposed that there are many contributing factors to the relationship between sports club participation and adolescent development [ 57 ]. As such, a multivariate structure, as well as cumulative and interactive effects, needs to be taken into account. Secondly, within his theoretical framework Brettschneider proposes that each individual is assumed to be the creator of his/her development. Whilst studies often discussed theories underpinning the research, it was not always clear how particular theories were incorporated into the methodology. For example Holt et al., introduced the Positive Youth Development theory in their introduction, but there was no mention of how this was applied in the methodology of data collection or in the analysis and interpretation [ 36 ]. On the other hand, Zarrett et al. clearly defined how they measured and indexed Positive Youth Development [ 40 ].

A recent study [ 37 ] incorporated Antonovsky’s Salutogenesis model [ 67 ] and Bandura’s theory of Social Learning [ 68 ]. The foundation of Antonovsky’s model is that heterostasis, ageing and progressive entropy are core characteristics of all living organisms. The model focuses on what makes a person maintain good health rather than focusing on the aetiology of sickness. In terms of the Social Learning theory, it is suggested that organised sport, particularly in teams, could be an important factor in a child’s social development [ 37 ]. However, this was a general discussion comment, and it is not clear how the Social Learning Theory was applied in the methodology of this study [ 43 ].

The theoretical perspective of Marsh [ 64 ] was adopted from Coleman’s [ 69 ] seminal work which “implies a zero-sum model in which greater involvement in extracurricular activities necessitates a decreased involvement in more narrowly defined academic pursuits” (p.19) in a way that is complementary rather than multiple roles being in conflict [ 64 ]. Stemming from Coleman’s earlier work, Marsh discussed Snyder et al. (1995) Multiple Role theory [ 70 ] which proposes that adolescents take on multiple roles as both a student and an athlete. Marsh suggests that “multiple roles may create psychological stress based in part on time and energy limitations, multiple roles may be complementary and may lead to energy expansion” (p19). In essence Marsh attempts to capsulate the perspective that sport participation as an additional extracurricular activity can have positive outcomes, rather than sport being seen, as depicted in earlier theoretical perspectives, as a burden, taking time away from academic pursuits. However, as with a number of other studies reviewed, it was not clear how the particular behavioural theory was applied in the study [ 64 ].

Few differences were evident between the conclusions of studies of higher and lower quality or of different study design. There were however, clear differences in the reported health outcomes associated with different contexts of participation. Therefore the following presents and discusses the reported psychological and social health benefits of participation in sport in the different contexts of: extracurricular activities; team sport; school or club sport; and sport in general. These categories, which are not mutually exclusive, were based upon the definitions or categorisation made within each individual study. Furthermore, the health benefits according to different types of participation are discussed. Lastly, given the greater strength of evidence regarding causality in longitudinal versus cross-sectional research, the key findings from the longitudinal studies are summarised.

Extracurricular activities

Several studies have investigated the influence of sport, as one type of extracurricular activity, on positive youth development [ 36 , 40 , 41 ] general behaviours [ 39 ] and personal development [ 53 ]. Other extracurricular activity categories considered were school-based activities, religious activities, youth groups, performing arts, volunteering, paid work, band and music lessons [ 40 , 41 , 52 ]. The definition of ‘sport’ as an extracurricular activity varied considerably. Sport was sometimes defined as including both team and individual sports [ 40 , 53 ] or encompassing different categorical groups for both team and individual sports participants [ 37 ], whilst others categorised groups as structured versus unstructured activities [ 55 ]. Howie et al. (2010) investigated extracurricular (outside school) activities - sports teams/lessons, sports clubs/organisations, or both - in the previous year [ 39 ].

While the qualitative study of Holt et al. (2011) did not compare sports participation with other activities, parents reported benefits for their children in personal and social development from sport participation. Social benefits included positive relationships with coaches, making new friends, and developing teamwork and social skills. Personal benefits included children being emotionally controlled, enjoying exploration, having confidence and discipline, performing well academically, managing their weight and being ‘kept busy’ [ 36 ].

Similarly, Bartko and Eccles (2003) reported that structured activities (sport being one of them) led to higher positive functioning for participants [ 55 ]. Howie et al. (2010) reported that children participating in both sports and clubs had higher social skill scores compared with children who did not participate in any outside-school activity [ 39 ]. Concurring with these findings, Linver et al. (2009) found that participation in sport and other organised activities had the greatest youth development outcomes, and low involvement in organised activities outside school was associated with less positive development across the board [ 41 ]. Sports participation alone had more developmental benefits than non-participation or other types of extracurricular activities, however the greatest benefits were seen for those involved with both sport and other activities [ 39 , 41 ].

Whilst positive social aspects of participation in sport have been consistently reported, it has also been found that young people involved with sport had higher rates of negative peer interaction [ 53 ]. These researchers concluded that this may be due to the competitive nature of sports activities compared to other activities. Even so, they found that, in addition to physical benefits, those involved with sport had higher rates of self-knowledge and emotional regulation than those involved with other activities [ 53 ]. While Harrison et al. (2003) defined team sport separately from other activities, their results were collated as sports only, activities only and sports and activities [ 52 ]. Contrary to some other findings, they found that sports alone (and also in combination with other activities) were associated with significantly better health outcomes, including higher healthy self-image and lower risk of emotional distress, suicidal behaviour and substance abuse.

Two longitudinal studies, one with a year between measurements and another three years, investigated the effects of participation in extracurricular activity on youth development [ 40 ] and social anxiety [ 37 ]. Dimech and Seiler (2011) investigated sport only, categorised as non-participation, individual or team involvement [ 37 ], whereas Zarrett et al. (2009) investigated team or individual sport participation in comparison to participation in development programs, performing arts, arts and crafts, school clubs, volunteering, religious groups, and paid work [ 40 ]. Consistent with the cross-sectional results of Linver et al. (2009) and Howie et al. (2010), Zarrett et al. (2009) concluded that a combination of sport plus other youth development programs was related to positive youth development, even after controlling for total time spent in the activities and the duration of sport participation.

Dimech and Seiler (2011) measured the effects of extracurricular participation in sport on social anxiety [ 37 ]. Comparing team sport, individual sport and no sport, they reported an interaction between sport mode and time, with team sport participants having reductions in social anxiety scores over time, whilst anxiety scores in the no-sport and individual-sport groups actually increased. Dimech and Seiler concluded that sport practice had a positive effect as a buffer against anxiety, but only team sport and not individual sport.

Whilst some studies highlighted the benefits of extracurricular sport, the focus was more commonly on ‘team sport’ in general, without distinguishing between in-school and out-of-school settings [ 42 , 43 , 46 , 50 , 51 , 58 , 59 , 61 ].

The psychological and social health aspects measured included mental health benefits [ 61 ], social isolation [ 59 ], depressed mood and symptoms of depression [ 46 , 58 ], self-esteem [ 50 ], life satisfaction [ 51 ], hopelessness and suicidality [ 42 ] and emotional self-efficacy [ 43 ].

Cross-sectional studies included a survey of US high school students, in which participation in team sport was associated with lower general risk-taking and fewer mental health and general health problems compared with non-participation [ 61 ]. In another cross-sectional survey, team sport involvement was positively associated with social acceptance and negatively associated with depressive symptoms [ 46 ]. Boone and Leadbeater concluded that benefits from team sport may be related to the effect of positive experiences (in coaching, skill development, peer support) in enhancing perceived social acceptance and reducing body dissatisfaction [ 46 ]. Team sport participation has also been reported to protect against feelings of hopelessness and suicidality, even after controlling for levels of physical activity [ 42 ]. Another reported health benefit of participation in team sport (both school and extracurricular participation) is life satisfaction [ 51 ]. A study investigated the relationship between different physical activity behaviours, distinguishing between vigorous and moderate levels as well as strength/toning and team participation contexts, and found that meeting recommended levels of PA and participation in sports teams was significantly associated with better emotional self-efficacy [ 43 ].

In a longitudinal study of adolescents with measurements one year apart, team sport participation was found to be protective against depressed mood associated with school performance levels [ 58 ]. In a longitudinal study of females, team sport achievement experiences in early adolescence were positively associated with self-esteem three years later in middle adolescence [ 50 ]. Another longitudinal study spanning 12 years found that participation in team sport (specifically school teams) was associated with lower social isolation later in life, compared with other activities categorised as pro-social, arts, and school-based [ 59 ].

School and/or club sport

Some studies distinguished between participation in ‘school sport’ and ‘club sport’ [ 38 , 54 , 56 , 57 , 62 ]. Snyder et al. (2010) while reporting school and club participation, then combined them into a single ‘athletes’ category and compared them to non-athletes on health-related quality of life measures. The athletes reported higher scores on physical functioning, general health, social functioning and mental health scales and a mental composite score, and lower on a bodily pain scale, than non-athletes [ 38 ]. Similarly, in a Swiss study, Ferron and colleagues classified adolescents as ‘athletes’ or ‘non-athletic’ on the basis of sports club participation. The athletes had superior well-being, including being better adjusted, feeling less nervous or anxious, being more often full or energy and happy about their life, feeling sad or depressed less often and having higher body image and fewer suicide attempts [ 62 ].

One longitudinal study of club sport participation over a three year period during adolescence in Germany, as well as identifying physical benefits, showed that sport club activities had a positive influence on the development of self-esteem, with girls discovering sports as a source of self-esteem earlier than boys [ 57 ]. In terms of relationships with peers and parents, club sport members did not differ significantly from non-members. Brettschneider and colleagues concluded that although sports club participants had better health outcomes, these benefits were due to self-selection bias rather than a sport club effect [ 57 ]. These researchers also acknowledged that research into the impact of sports by discipline, and studies of longer duration, are required.

In relation to school sport specifically, participation was found to be significantly associated with self-esteem in Latino subgroups of students living in the United States of America [ 56 ]. This was true for Mexican girls and boys, Puerto Rican girls and Cuban boys but not Puerto Rican boys and Cuban girls. Pyle and colleagues investigated participation in school sports defined as being high or low intensity. Participation in competitive sports was found to be associated with lower frequency of mental health problems [ 54 ].

Level of sport involvement

Most studies defined sport participation as a binary categorical variable without further information regarding level of involvement. However, a few studies have investigated psychological and social health outcomes in relation to different levels of intensity of sport activities (low, moderate, vigorous, or high) [ 60 , 63 ] or frequency of participation and number of sport activities [ 48 ].

Steptoe and Butler (1996) assessed the association between extent of participation in sport or vigorous recreational PA and emotional wellbeing in adolescents [ 63 ]. Without distinguishing between sport and other vigorous PA, Steptoe and Butler reported that greater participation in vigorous activities was associated with lower risk of emotional distress [ 63 ]. Sanders and colleagues found that for high school senior students moderate sport participation (3–6 hours per week) was associated with lower depression scores than low sport involvement (0–2 hours) [ 60 ]. Donaldson and Ronan (2006) investigated participation in both “formal” and “informal” sports and reported that greater participation was related to enhanced emotional and behavioural well-being. Those participating in more formal sports reported significantly lower levels of emotional and social problems compared to those participating in fewer formal sports [ 47 ]. Another study investigated frequency of extracurricular sport and perceived health, health attitudes and behaviour [ 49 ]. Those with greater frequency of participation (at least twice per week) had better feelings of well-being compared to those who participated less than once per week [ 49 ]. One study looked at number of sports, type of sport, and years participating in sport, and found that sport participation was positively related to self-assessments of physical appearance and physical competence, physical self-esteem and general self-esteem [ 48 ]. Furthermore, these researchers found that differences between competitive and non-competitive sports was minimal, and suggested that for young adolescents, it is more important to consider the total number of sports and total number of years in sports-related activities [ 48 ].

Sport in general

A few studies used a broad definition of sport without providing further context of participation [ 35 , 44 , 64 ]. Sport participation versus no sport participation was found to be significantly associated with enhanced self-concept [ 64 ]. A longitudinal study also reported benefits of participation in sport compared to no participation, in relation to lower rates of suicidal ideation including both thoughts and intentions [ 35 ]. In terms of the effect of sport participation on shyness, a longitudinal study with measurement at baseline and one year later found that sport was positively associated with positive adjustment (e.g. social skills and self-esteem) and that sport played a uniquely protective role for shy children, with shy children who participated in sport over time reporting significant decreases in anxiety [ 44 ]. Similarly, in a qualitative study of focus groups of parents of young people participating in sport, social factors as well as life skills and self-concept were stated as benefits of participation [ 45 ].

Longitudinal studies

Longitudinal studies can provide stronger evidence of causality than cross-sectional studies. However, the longitudinal studies reviewed were generally short in duration, usually with only two measurement points, one or two years apart [ 35 , 40 , 44 , 50 , 58 ]. They were all observational in nature, with no control groups, and with limited measurement of the level of participation and frequency or duration of sport activities. All studies were based on surveys conducted through schools, with participation in sport and other extracurricular activities reported mainly in binary categories.

The main findings were that, after controlling for factors such as income, parents’ education, age and ethnicity, compared to no participation or participation in individual sports, participation in team sport had resulted in benefits such as lower social anxiety [ 37 ], lower social isolation [ 59 ], better social self-concept [ 64 ], and improved self-esteem [ 50 ]. Sport in general has also been associated with positive youth development [ 40 ]; the young people who were highly engaged in general, and those who participated primarily in sports and youth development programs, had the highest positive youth development scores.

In a recent study undertaken longitudinally over a one-year period, where sport participation was generally reported to be of 1–2 hour duration per week, there was no effect of weekly hours of sport on social anxiety [ 37 ]. Similarly, Findlay and Coplan (2008) in a longitudinal analysis over a one-year period, did not find significant effects of sport participation over the year (neither main effects of time or participation-time interactions) on social skills, self-esteem, positive adjustment or externalising problem behaviours [ 44 ]. However, shy children who participated in sport over a one-year period demonstrated a decrease in anxiety over time. Sport was associated with positive psychological and social outcomes, including higher positive affect and well-being and greater social skills. Shy and aggressive children who participated in sport reported higher self-esteem [ 44 ]. A study of club sport members compared to non-club members also did not show a systematic effect of club membership on most measures of psychological and social health in adolescents over three years [ 57 ]. Notwithstanding, clubs had a positive effect on adolescent self-esteem and were reported, on the basis of high membership rates, to be a highly integrative social force [ 57 ].

A US study in which high school students were interviewed at two time points one year apart, showed that for females, but not for males, team sport involvement was protective against depressed mood state associated with poor school performance [ 58 ]. Another US study of female adolescents over three years found that sports achievement experiences in early adolescence were positively associated with self-esteem in middle adolescence [ 50 ]. Team sports achievements, team sports self-evaluations and individual sports self-evaluations tended to be significantly and positively associated both cross-sectionally and longitudinally. Team sport achievement in early adolescence was related to girls’ global self-esteem in middle adolescence, and team sport self-evaluations mediated the relation between achievement and self-esteem. In addition, the relationship between achievement and self-esteem was partially mediated by girls’ perceptions of competence and interest in team sport, and mastery in team sport contributed to global self-esteem development [ 50 ].

Another longitudinal study showed that adolescents involved with team sport had lower suicide ideation with regard to both contemplation and intention [ 35 ]. These researchers suggested that when young people discontinue playing sport they lose the protective social networks, as well as connections to caring adults and pro-social peers, that help to promote healthy youth development and reduce the risk of suicide.

Conceptual model

A conceptual model of Health through Sport is proposed that is based on three primary categories of outcome: physical, psychological and social, and two secondary categories: physical/psychological – aspects involving both the physical and psychological elements, and psychosocial – aspects involving both psychological and social elements.

While our model incorporates all five categories and thus depicts the full range of health aspects, the ‘physical’ aspects have been well reviewed elsewhere [ 1 ], and so this paper in focused on the psychological and social aspects, as defined above. Furthermore, while the present review was limited to research into children and adolescents, the general form of the Health through Sport model is believed to also apply to adults, although it is likely there would be some change in the specific elements of each component.

The model includes three major elements: determinants of sports participation, sport itself, and health outcomes of sport participation. The ‘determinants’ element is based on the well-established social ecological model [ 19 , 65 ] and is represented as concentric rings spreading out from the individual’s intrapersonal characteristics to widening spheres of influence. The sport element incorporates two dimensions of context: individual – team, and informal – organised, each of which is almost dichotomous, but also has some intermediate variants (e.g. running alone, running in an informal group, running for a club team, running in a club relay team). The three types of health outcomes - physical, psychological and social, are shown as overlapping, representing the fact that there may be interactions and interrelationships between physical and psychological aspects and between psychological and social health aspects. For example, there are relationships between physical fitness and mental state; and interpersonal relationships may satisfy needs for belongingness and, as such, influence psychological health. Another example is resilience, whereby psychological health may influence an individual’s capacity to engage in interpersonal relationships.

The different strengths of the various linkages between the sport element and the health outcomes represent the notion that all forms of sport contribute strongly to physical health, but that while organised and/or team forms also contribute strongly to psychological and social outcomes, informal and/or individual forms contribute somewhat less to psychological outcomes and relatively little to social outcomes. Finally, we have noted the limited evidence of causality in the literature reviewed. This ambiguity or reciprocity could perhaps be represented by double-headed arrows linking the physical, psychological and social elements to the sport element, but we have represented it by ‘feedback loops’ from the three outputs to the intrapersonal and interpersonal determinants.

Limitations

This systematic review has some limitations. Whilst the search strategy, based on a-priori inclusion and exclusion criteria, was comprehensive and encompassed grey literature which reported primary data, conference proceedings were not included. Nor were non-English language articles included. The studies reviewed included a wide range of aims, focuses, measurement tools and indicators of both sport participation and health outcomes. This diversity of focus and methodology limited the extent of synthesis and precluded meta-analysis. Most studies were cross-sectional and used self-report measures. Therefore results should be interpreted with caution, and any conclusions regarding causation are conjectural.

There is substantive evidence of many different psychological and social health benefits of participation in sport by children and adolescents. Furthermore, there is a general consensus that participation in sport for children and adolescence is associated with improved psychological and social health, above and beyond other forms of leisure-time PA. More specifically, there are reports that participation in team sports rather than individual activities is associated with better health. It is conjectured that this is due to the social nature of team sport, and that the health benefits are enhanced through positive involvement of peers and adults. However, the research is predominantly based on cross-sectional studies.

In light of the research evidence, acknowledging that research to date is predominantly based on cross-sectional studies, it is recommended that community sport participation is advocated as a form of leisure time PA for children and adolescents; in an effort to not only improve the obesity crisis associated with low PA levels, but to enhance other psychological and social health outcomes. It is also recommended that the causal link between participation in sport and health be further investigated and the conceptual model of health through sport tested. Furthermore, in light of the fact that our assessment of the quality of the studies to date has revealed considerable variation in study quality, it is recommended that researchers should give more attention to protocols such as CONSORT [ 71 ] and STROBE [ 72 ] in order to ensure high levels of methodological rigor in future studies.

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RME is supported by a VicHealth Research Practice Fellowship.

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RME contributed to the study design, the review of literature, analysis of literature, model conceptualisation, manuscript conceptualisation and preparation. JAY contributed to the study design, the review of literature, analysis of literature, model conceptualisation, manuscript conceptualisation and preparation. JTH contributed to analysis of literature, model conceptualisation and representation, and manuscript preparation. MJC contributed to analysis of study quality and critical review of the manuscript. WRP contributed to the study design and critical review of the manuscript. All authors read and approved the final manuscript.

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Eime, R.M., Young, J.A., Harvey, J.T. et al. A systematic review of the psychological and social benefits of participation in sport for children and adolescents: informing development of a conceptual model of health through sport. Int J Behav Nutr Phys Act 10 , 98 (2013). https://doi.org/10.1186/1479-5868-10-98

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Received : 10 December 2012

Accepted : 12 August 2013

Published : 15 August 2013

DOI : https://doi.org/10.1186/1479-5868-10-98

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