Examining sport commitment and intentions to participate in intramural sports : application of the Sport Commitment Model and the Theory of Planned Behaviour in a campus recreational sport setting
Bibliographic record
Abstract
Fifty-six percent of Canadians, 20 years of age and older, are inactive (Canadian Community Health Survey, 200012001). Research has indicated that one of the most dramatic declines in population physical activity occurs between adolescence and young adulthood (Melina, 2001; Stephens, Jacobs, & White, 1985), a time when individuals this age are entering or attending college or university. Colleges and universities have generally been seen as environments where physical activity and sport can be promoted and accommodated as a result of the available resources and facilities (Archer, Probert, & Gagne, 1987; Suminski, Petosa, Utter, & Zhang, 2002). Intramural sports, one of the most common campus recreational sports options available for post-secondary students, enable students to participate in activities that are suited for different levels of ability and interest (Lewis, Jones, Lamke, & Dunn, 1998). While intramural sports can positively affect the physical activity levels and sport participation rates of post-secondary students, their true value lies in their ability to encourage sport participation after school ends and during the post-school lives of graduates (Forrester, Ross, Geary, & Hall, 2007). This study used the Sport Commitment Model (Scanlan et aI., 1993a) and the Theory of Planned Behaviour (Ajzen, 1991) with post secondary intramural volleyball participants in an effort to examine students' commitment to intramural sport and 1 intentions to participate in intramural sports. More specifically, the research objectives of this study were to: (1.) test the Sport Commitment Model with a sample of postsecondary intramural sport participants(2.) determine the utility of the sixth construct, social support, in explaining the sport commitment of post-secondary intramural sport participants; (3.) determine if there are any significant differences in the six constructs of IV the SCM and sport commitment between: gender, level of competition (competitive A vs. B), and number of different intramural sports played; (4.) determine if there are any significant differences between sport commitment levels and constructs from the Theory of Planned Behaviour (attitudes, subjective norms, perceived behavioural control, and intentions); (5.) determine the relationship between sport commitment and intention to continue participation in intramural volleyball, continue participating in intramurals and continuing participating in sport and physical activity after graduation; and (6.) determine if the level of sport commitment changes the relationship between the constructs from the Theory of Planned Behaviour. Of the 318 surveys distributed, there were 302 partiCipants who completed a usable survey from the sample of post-secondary intramural sport participants. There was a fairly even split of males and females; the average age of the students was twenty-one; 90% were undergraduate students; for approximately 25% of the students, volleyball was the only intramural sport they participated in at Brock and most were part of the volleyball competitive B division. Based on the post-secondary students responses, there are indications of intent to continue participation in sport and physical activity. The participation of the students is predominantly influenced by subjective norms, high sport commitment, and high sport enjoyment. This implies students expect, intend and want to 1 participate in intramurals in the future, they are very dedicated to playing on an intramural team and would be willing to do a lot to keep playing and students want to participate when they perceive their pursuits as enjoyable and fun, and it makes them happy. These are key areas that should be targeted and pursued by sport practitioners.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".