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A comparative study of swimmers, runners, cyclists and triathletes on sports motivation scale

Author: 
Dr. Kshetrimayum Rojeet Singh
Subject Area: 
Social Sciences and Humanities
Abstract: 

The objective of the present study is to compare the junior swimmers, runners, cyclists and traithletes on sports motivation scale and to assess which sports is more motivated among the selected sports. Method: 80 National junior boys’ swimmers (20), runners (cross country runners - 20), cyclists (20) and triathletes (20) were selected for the purpose of the study from Manipur, Pune, Madhya Pradesh, Delhi and Assam. The age of the athletes were ranged from 15 to 19 years. And to assess the level of motivation in the participation of sports by the athletes the sports motivation scale (28 SMS) questionnaire by Pelletier et al. (1995) was used. The descriptive statistics such as mean, standard deviation, std. error mean etc. was used and for the comparison between the sports on the factor of SMS the one way analysis of variance (ANOVA) was used. Results: The mean and standard deviation of the factors of sport motivation for triathletes, runners, cyclists and swimmers are Intrinsic motivation to know (IMTK) (24.45 ± 2.46), (23.55 ± 3.40), (20.3 ± 5.06) and (18.45 ± 2.77), Intrinsic motivation to accomplish (IMTA) (23 ± 2.78),(20.75 ± 5.15), (20.85 ± 3.89) and (18.7 ± 3.80), Intrinsic motivation to experience stimulation (IMTES) (22.8 ± 4.05), (23.85 ± 4.23), (20.45 ± 4.10) and (17.9 ± 3.81), Extrinsic motivation identification (EMI) (22.2 ± 4.47), (21.15 ± 4.38), (20.55 ± 4.57) and (17.7 ± 4.75), Extrinsic motivation Introjection (EMIJ) (22.3 ± 4.12), (21.6 ± 5.83), (20.3 ± 4.53) and (18.45 ± 4.21), Extrinsic motivation external regulation (EMER) (22.45 ± 3.63), (20.1 ± 5.08), (19.75 ± 5.08) and (18.15 ± 4.27) and Amotivation (AM) (21.05 ± 4.08), (22.4 ± 4.16), (20.05 ± 4.32) and (17.3 ± 3.45) respectively. The ANOVA result shows that the p-value of the factors of the sports motivation of the selected athletes was less than 0.05 and hence the F- value is significant at 5 % level. Since the ANOVA results was significant so the Post hoc Comparison of Means was applying by using LSD Test and the results shows that there exists a significant difference in the different factors in between triathletes and cyclists ( p = .000), triathletes and swimmers (p = .000), runners and cyclists (p = .005) and runners and swimmers (p = .000) in IMTK, triathletes and swimmers (p = .001) in IMTA, triathletes and swimmers (p = .000) runners and cyclists (p = .010) runners and swimmers (p = .000) and cyclists and swimmers (p = .050) in IMTES, triathletes and swimmers (p = .002) and runners and swimmers (p = .019) in EMI, triathletes and swimmers (p = .012) and runners and swimmers (p = .038) in EMIJ, triathletes and swimmers (p = .004) in EMER and triathletes and swimmers (p = .004), runners and cyclists (p = .000) and cyclists and swimmers (p = .034) in AM as their obtained p–values were less than 0.05 (p ˂ .05). This implies that in spite of similarities in nature of events there exist differences, or there are special requirements for participation in these sports. The existence of similarities in between these four sports is prevalent in triathletes and runners (p = .427) in IMTK, triathletes and runners (p = .079), triathletes and cyclists (p = .093), runners and cyclists (p = .937), runners and swimmers (p = .108) and cyclists and swimmers (p = .093) in IMTA, triathletes and runners (p = .414) and triathletes and cyclists (p = .070) in IMTES, triathletes and runners (p = .467), traithletes and cyclists (p = .254), runners and cyclists (p = .677) and cyclists and swimmers (p = .051) in EMI, traithletes and runners (p = .641), triathletes and cyclists (p = .185), runners and cyclists (p = .387) and cyclists and swimmers (p = .219) in EMIJ, triathletes and runners (p = .107) traithletes and cyclists (p = .065) runners and cyclists (p = .809), runners and swimmers (p = .180) and cyclists and swimmers (p = .270) in EMER and triathletes and runners (p = .291), traithletes and cyclists (p = .434) and runners and cyclists (p = .068) in AM as their obtained p-values were greater than .05 (p ˃ .05). Conclusion: It must be noted that the present research was solely comparison in nature and that future studies would be needed to assess how athletes actually interpret behavior in competitive sports situations. Elaboration of this information could be potentially useful to coaches and athletes in order to optimize the experience of participants in sport and exercise activities.

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