| Literature DB >> 34941811 |
Alfredo Silva1, Pedro Sobreiro1, Diogo Monteiro2.
Abstract
This work contributes to an emerging literature focused on the role of physical activity on the subjective well-being of populations. Unlike the existing literature, it proposes an approach that uses algorithms to predict subjective well-being. The aims of this study were to determine the relative importance of sports participation and perceived value of elite sports on the subjective well-being of individuals. A total of 511 participants completed an online questionnaire. The statistical analysis used several machine learning techniques, including three algorithms, Decision Tree Classifier (DTC), Random Forest Classifier (RFC), and Gradient Boosting Classifier (GBC). In the three algorithms tested, sports participation, expressed as the weekly frequency and the time spent engaging in vigorous physical activity, showed a greater importance (between 47% and 53%) in determining subjective well-being. It also highlights the effect of perceived value of elite sport on the prediction of subjective well-being. This study provides evidence for public sport policy makers/authorities and for managers of physical activity and sport development programs. The surprising effect of the perceived value of elite sport on the prediction of subjective well-being.Entities:
Keywords: elite sport; physical activity; sports participation; sports policy; subjective well-being
Year: 2021 PMID: 34941811 PMCID: PMC8707714 DOI: 10.3390/sports9120173
Source DB: PubMed Journal: Sports (Basel) ISSN: 2075-4663
Figure 1The “virtuous cycle” of sports. Adapted from [27].
Variable definition, descriptive statistics, and measurement.
| Variable | Description | Scale | Mean (SD *) | Source |
|---|---|---|---|---|
| Physical activity (SportPart_1; SportPart_2) | (1) How often do you exercise or play sport? (in last month) (1 = Never; 2 = 1 to 3 times a month; 3 = 1 to 2 times a week; 4 = 3 to 4 times a week; 5 = 5 times a week or more). | Metric | (1) 2.83 (1.27) | Adapted from [ |
| Perceived value of elite sport (SportValue_1; SportValue_2) | (1) Currently, in the international context, the position of Portuguese high-competition sport is: (1 = Extremely bad, 2 = Very poor, 3 = Bad, 4 = Fair, 5 = Good, 6 = Very good, 7 = Extremely good); | Ordinal | (1) 5.4 (1.11) | Adapted from [ |
| Subjective well-being (SWB) | Satisfaction with Life Scale: Overall, I am satisfied with my life. (0 = Not at all satisfied to 10 = Extremely satisfied) Negative = 0; Positive =1 | Ordinal | 8.16 (1.91) | Adapted from [ |
| Gender (Gender) | (1 = Female; 2 = Male) | Dummy | 1.32 (0.46) | |
| Age (Age) | Age in years | Metric | 25.1 (9.74) | |
| Maritage status | (1 = Single, not married; 2 = Couple; 3 = Divorced; 4 = In union of fact; 5 = Widow) | Reference category | 1.29 (0.79) |
* SD—standard deviation.
Accuracy train/test and k-fold for each algorithm.
| Algorithm | DTC | RFC | GBC |
|---|---|---|---|
| Holdout | 0.84 | 0.88 | 0.90 |
| K-fold | 0.86 | 0.88 | 0.90 |
DTC—Decision Tree Classifier; RFC—Random Forest Classifier; GBC—Gradient Boosting Classifier.
Importance of the variables for each algorithm predicting the well-being using train test.
| DTC | RFC | GBC | |||
|---|---|---|---|---|---|
| Variable | Importance (%) | Variable | Importance (%) | Variable | Importance (%) |
| SportPart_2 | 30 | SportValue_2 | 28 | SportPart_1 | 31 |
| SportValue_2 | 26 | SportPart_2 | 27 | SportValue_1 | 29 |
| SportPart_1 | 24 | SportPart_1 | 26 | SportPart_2 | 22 |
| SportValue_1 | 20 | SportValue_1 | 19 | SportValue_2 | 18 |
Note: Sport Participation = SportPart_1 and SportPart_2; Perceived Value of Elite Sport = SportValue_1 and SportValue_2. DTC—Decision Tree Classifier; RFC—Random Forest Classifier; GBC—Gradient Boosting Classifier.
Importance of the variables for each algorithm predicting the well-being using k-fold.
| DTC | RFC | GBC | |||
|---|---|---|---|---|---|
| Variable | Importance (%) | Variable | Importance (%) | Variable | Importance (%) |
| SportValue_2 | 36 | SportValue_2 | 29 | SportPart_2 | 26 |
| SportPart_2 | 26 | SportPart_2 | 28 | SportPart_1 | 25 |
| SportPart_1 | 21 | SportPart_1 | 23 | SportValue_2 | 24 |
| SportValue_1 | 17 | SportValue_1 | 20 | SportValue_1 | 24 |
Note: Sport Participation = SportPart_1 and SportPart_2; Perceived Value of Elite Sport = SportValue_1 and SportValue_2. DTC—Decision Tree Classifier; RFC—Random Forest Classifier; GBC—Gradient Boosting Classifier.