This study explains leisure satisfaction as determined by the perceived discrepancy between the actual and the desired situation, and by perceptions of internal and external barriers that block the attainment of the desired situation. Special attention is given to socioeconomic determinants. It is concluded that leisure satisfaction is higher for people who are older and have an optimistic outlook.
They do not perceive a discrepancy between their actual and desired number of hours spent on leisure activities. Persons with a low leisure satisfaction are younger and have a pessimistic outlook. They perceive internal barriers personal interest, capacity that block them from spending more time on some leisure activities.
Persons with medium leisure satisfaction perceive external barriers time, money, circumstances that block them from spending more time on some leisure activities. A tentative conclusion is that people from lower social classes more often belong to this latter group medium leisure satisfaction , while people from middle social classes more often are characterized by a low leisure satisfaction.
People from high social classes report most leisure satisfaction. Skip to Main Content. Search in: This Journal Anywhere. Advanced search. Submit an article Journal homepage.
Original Articles. Dick A. Fred van Raaij. Pages Published online: 13 Feb Satisfaction with Leisure Time Activities. Moreover, very few studies have paid attention to the role of leisure-time physical activity, most have concentrated on physical activity organized in school, although leisure-time physical activity may better reflect voluntary behaviour than compulsory, school-based physical activity. Accordingly, our main aim was to investigate the direction and magnitude of the associations between leisure-time physical activity and academic performance at four time points across adolescence and young adulthood.
Based on extensive previous evidence, we hypothesized that there would be a positive association between leisure-time physical activity and academic performance, i. We also aimed to examine whether environmental e. Furthermore, we aimed to investigate to what extent cognitive ability explains the association between leisure-time physical activity and educational attainment in young adulthood.
Descriptive statistics for leisure-time physical activity and academic performance are presented in Table 1. The most common grade point average for 12 and 14 year old participants was 8—9 The majority of the participants The most often reported frequency of leisure-time physical activity was 2—3 times a week in each study wave among participants percentages ranged from Academic performance variables were highly statistically significantly and positively correlated with each other across survey waves Table 2 ; polychoric correlations ranged from 0.
Similarly, leisure-time physical activity variables were statistically significantly positively correlated from one survey wave to the next, but the correlations were not as high as for academic performance variables from 0. We observed that academic performance at each survey wave statistically significantly predicted subsequent academic achievements standardized path coefficients from 0.
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The same was seen between the repeated measurements of leisure-time physical activity over time. The coefficients were somewhat lower than those for academic performance, but remained statistically significant standardized path coefficients from 0. This auto-regressive part of the model indicates that the temporal stability of academic performance from the age of 12 years to the age of 24 years is higher than the temporal stability of leisure-time physical activity over the same time period.
The cross-lagged effects, which were crucial to our hypothesis indicated that higher academic performance at ages of 12 and 14 years predicted a statistically significantly higher frequency of leisure-time physical activity in the follow-up time-points, even if the previous level of leisure-time physical activity was taken into account in the model; standardized path coefficients were 0.
This pattern was not found in young adulthood, and leisure-time physical activity did not predict subsequent academic performance at any time point. Residual correlations between leisure-time physical activity and academic performance at ages of 12 and 17 years were statistically significant standardized path coefficients of 0. Previous academic performance again positively predicted the subsequent frequency of physical activity in leisure-time at age 14 standardized path coefficient 0. One major change was that higher academic performance at age of 17 years predicted a statistically significantly higher frequency of leisure-time physical activity also at age of 24 years standardized path coefficient was 0.
Again, leisure-time physical activity was not a predictor of academic performance at any single time point. Minor effects on the auto-regressive coefficients were observed. Residual correlations between leisure-time physical activity and academic performance at age of 12 and 17 years were statistically significant standardized path coefficients of 0.
The covariates of sex, parental education and parental leisure-time physical activity were included in the model. Only statistically significant associations are presented in the figure. Results of the bivariate cross-lagged path model for the within-pair differences in leisure-time physical activity and academic performance suggested that environmental and genetic factors shared by co-twins did not explain the association between leisure-time physical activity and academic performance: within-pair differences in academic performance positively predicted subsequent within-pair differences in leisure-time physical activity at age 14 standardized path coefficients 0.
Linear regression results for cross-sectional data on leisure-time physical activity, educational attainment and cognitive ability showed that a statistically significant and independent association between leisure-time physical activity and academic performance remained even after cognitive ability was included in the model Supplementary material III.
We investigated the direction and magnitude of the associations between leisure-time physical activity and academic performance from adolescence to young adulthood in a cross-lagged path model. The results revealed a consistent pattern in which better academic performance in adolescence was modestly associated with an increased frequency of leisure-time physical activity in late adolescence and young adulthood, and that patterns was independent of the prior level of leisure-time physical activity as well as parental factors.
The examination of the association from the reverse direction, i. However, it should be noted that there was relatively less variance in academic performance to be explained by leisure-time physical activity than the other way around, which may have affected the result. Our results are consistent with recent studies and reviews confirming the positive association between physical activity and academic performance 4 , 5 , 9 , However, we were unable to demonstrate, and thus failed to confirm our working hypothesis, that physical activity would predict academic performance, as claimed in the review of Lees et al.
Although that previous review of randomized controlled trials found a positive association, it was only a weak relationship. Our study design cannot prove causal relationships 18 , but because of its longitudinal design with several follow-up waves, our results are nevertheless informative about potential causal effects i. Further, we demonstrated similar association within pairs of co-twins who share many childhood environmental factors and in the case of MZ twins, they are also genetically identical. This result suggests that the association between academic performance and physical activity is not explained by genetic and non-genetic factors shared by co-twins.
We also found that cognitive ability explained part of the association between educational attainment and leisure-time physical activity in young adulthood, but an independent association between academic performance and physical activity still remained although it was somewhat weaker.
The reduced association was expected as cognitive ability is a major predictor of educational achievement and has been linked with physical activity levels 5. The process of neuroselection 19 , 20 may be one of the mechanisms that could explain why cognitive ability is associated with physical activity. The neuroselection hypothesis states that healthier behaviour choices are selected by the individuals with better cognitive ability.
In other words, those who are cognitively more capable may have better learning and reasoning skills, and thus, they may be able to do better choices related to physical activity behaviour than those with lower cognitive ability Very few previous studies have concentrated on leisure-time physical activity when studying associations between physical activity and academic performance.
Our results with leisure-time physical activity, however, further support the positive association found between physical activity and academic performance in the reviews, which have concentrated on school-based physical activity 5 , 9 , Moreover, our study had one of the longest follow-ups in this field encompassing the transition from school to young adulthood and initiation of the working life.
The results we found over the age range of secondary school students were consistent with the results found in recent studies 5 , 9 , 10 as well as with confirming our own survey for follow-up time points from ages 12 to When comparing the results of different studies it is important to bear in mind that both physical activity and academic performance are complex to define and can be measured in many ways. For example, many of the recent studies revealing no association or negative results originate from studies, which measured physical activity behaviour objectively 12 , 13 , Methodological differences along with small sample sizes and the poor quality of many existing studies may also have resulted in the discrepant findings.
Long-term physical activity in leisure time and mortality from coronary heart disease, stroke, respiratory diseases, and cancer. One major change was that higher academic performance at age of 17 years predicted a statistically significantly higher frequency of leisure-time physical activity also at age of 24 years standardized path coefficient was 0. Table 3 Association between leisure-time activity and psychological distress. PLoS Med. Our findings suggest that better academic performance in adolescence modestly predicts more frequent leisure-time physical activity in late adolescence and young adulthood. In the present study, we examined the association between psychological health and volunteer, physical, outdoor, and art leisure-time activities in a community in Japan.
It can be speculated that the duration of interventions may be another factor explaining the diverging results. Therefore, the results from different studies need to be compared with caution. Varying results between studies could be due to national differences in the schooling systems. Finland offers an education that is publicly funded, and free to all children, which means that differences between schools are only marginal.
PISA studies during the last decades have revealed that Finnish students have been very successful in their assessments Most Finnish young people have similar opportunities to exercise in their leisure-time. More than eight out of 10 Finns aged 15 and older engage in some kind of sporting activity Thus, the Finnish results are not explained by the heterogeneity of the educational system or exercise opportunities.
Therefore, the conflicting results between previous publications and our current study may be explained by different educational and sport systems in different countries. One of the main potential limitations of the present study is the use of self-reported questionnaire data to estimate: 1 leisure-time physical activity, 2 student status at age of 17 years and 3 educational attainment in young adulthood.
It is well-known that self-reports may have shortcomings with respect to validity and the reliability of the measure Although the validity of the physical activity questionnaires used in Finnish twins has been demonstrated 25 , 26 , 27 , 28 , the possibility of errors cannot be avoided when using a non-objective instrument. In contrast to these subjective measurements, grade point averages in adolescence were reported by teachers when the twins were aged 12 and 14 years. This study was limited by the absence of an objective measure of leisure-time physical activity, and furthermore, criticism can be raised at the subjective assessment of physical activity.
Limiting the subjective assessment of physical activity to only its frequency measure was not the most optimal way to measure physical activity behaviour. However, the frequency of physical activity was the only variable for which longitudinal data were available in the present study. It is possible that a lack of comprehensiveness in the assessment of leisure-time physical activity dimensions does somewhat restrict the picture of the total leisure-time physical activity behaviour. It is, however, unlikely that issues related to the measurement of physical activity would explain the association between physical activity and academic performance, instead, they would tend to make the association weaker.
Moreover, our findings are limited to people over 12 years of age. Thus, the direction of the association between leisure-time physical activity and academic performance among individuals under the age of 12 years remains still poorly known. It may be that the pattern of associations in early childhood is not consistent with the pattern we found among twins over 12 years of age. For example, the process of neuroselection has been suggested to occur more likely from adolescence onwards than in childhood A key strength of the present study is the longitudinal study design with four waves, providing an opportunity to assess the mutual relationships between leisure-time physical activity and educational achievement.
Longitudinal studies are ideal for studying factors over time, but most importantly, they enable testing the temporal directions of the association which is a prerequisite for the investigation of potential causal associations. A further strength of this study is its large sample size, which ensures sufficient statistical power to detect statistically significant associations. Moreover, various selection biases are unlikely in our study due to the rather high participation rate in the survey and the inclusion of multiple domains in the questionnaire.
We were able to take several covariates into account and therefore to control for potential familial confounding. In addition, we could adjust the results for unmeasured environmental and genetic factors by using the twin design, and also adjust the results for cognitive ability. Finally, our results are based on a population-based sample with relatively equal sex representation and high response rates, which contributes to the good generalizability of the study findings.
This study demonstrated that a better academic performance in adolescence modestly predicts an increased level of leisure-time physical activity in late adolescence and young adulthood. However, we found that leisure-time physical activity did not predict later academic performance at any time point in our survey. Thus, our findings do not clearly support the belief that physically active adolescents would perform better academically in the future, but rather children and adolescents who perform well in school tend to be more physically active later on.
For future studies, more information on the role of leisure-time physical activity instead of school based physical activity in the field is needed. Intervention studies, especially large randomized controlled trials, would also help to develop a full picture of the association between physical activity and academic performance. In public health perspective, the main implication of the present study is the need for better-targeted physical activity promotion actions for children and adolescents with lower levels of academic performance.
Early detection and support may minimize the risk of lower levels of physical activity in later life. Such early-targeted interventions are also expected to be cost-effective, which is in the interest of policy makers. The participants were drawn from the FinnTwin12 FT12 study, which is a longitudinal study of health and behaviour in Finnish twins birth cohorts — and their families The twins were identified from the Central Population Registry of Finland, and the relevant data for the study were collected through mailed questionnaires.
To date, four waves of the FT12 study have been completed. In the first phase, the twins and their parents completed questionnaires when the twins were 11—12 years old.