Examining Sport and Physical Activity Participation, Motivations and Barriers among Young Malaysians
Bibliographic record
Abstract
<p>Although a considerable amount of research has contributed to our understanding of the underlying causes of sporting behaviour, there is a paucity of research examining the motivations and barriers in sport and physical activity participation among young Malaysians. In order to address the gap in the literature, thus, this study was designed to ascertain the motivations and barriers in sport or physical activity participation among young Malaysians across the country. The study included 2894 young Malaysians ranged in age from 15 to 30 years old. A cross-sectional survey questionnaires comprised of open and close-ended items pertaining to sport participation level, participation motivations and barriers, and socio-demographic characteristics were conducted. The results show that 1465 were active, 710 were less active and 719 were inactive in sport and physical activity participation. In terms of their motives and barriers to sport and physical activity participation, the results indicate that the common motives for participation included ‘physical fitness’, ‘improve health’, ‘reduce stress’, ‘leisure time’ and ‘active lifestyle’. On the other hand, common barriers for those who do not participate in sport and physical activity included ‘no time’, ‘no interest’, ‘weather’, ‘health reasons’, and ‘lack of facilities’. Thus, the sport organization management needs to understand the motives and barriers to sport and physical activity of young Malaysians participation in order to optimize throughout their sporting endeavor and exercise adherence.</p>
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".