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Abdul Rahman A R, Hashim H A, Kuan G, Abdul Malik A. Factorial Validity and Internal Consistency of The Sports Imagery Ability Questionnaire (SIAQ) Malaysian Version. Ann Appl Sport Sci 2022; 10 (S1)
URL: http://aassjournal.com/article-1-1108-en.html
URL: http://aassjournal.com/article-1-1108-en.html
1- Exercise and Sports Science Unit, School of Health Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan, Malaysia , amir.rifaat@gmail.com
2- Exercise and Sports Science Unit, School of Health Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan, Malaysia
2- Exercise and Sports Science Unit, School of Health Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan, Malaysia
Abstract: (1596 Views)
Background. Imagery ability is one of the most potent factors influencing imagery effectiveness. Therefore, prior to imagery training, it is important to assess the participant’s imagery ability, typically using a self-report questionnaire.
Objectives. This study examined the factorial validity and internal consistency of the Malaysian adapted SIAQ using confirmatory factor analysis and Cronbach’s alpha.
Methods. The questionnaire was administered online to 193 participants (101 men and 92 women) with a mean age of 22.06 ± 3.72. The data were normalized, and four models were tested (model 1: data with square root transformation for values above the threshold; model 2: data with logarithm transformation for values above the threshold; model 3: data with values above threshold were logarithm transformed and values that were almost reaching the threshold (Item_4 and Item_12) were transformed by square root; and model 4: data with values above and reaching the threshold were logarithm transformed).
Results. The result of factorial analysis for model 2 revealed a good model fit (X^2=184.76, df=80, p<0.00, X^2/df=2.31, CFI=0.94, TLI=0.92, SRMR=0.05, and RMSEA=0.08) for the five-factor model structure implicating a good factorial validity. Furthermore, all path loadings exceeding 0.50 indicated good convergent validity of the subscales. Moreover, alpha coefficients range from 0.77 to 0.85 (0.85 for skill, 0.77 for strategy, 0.84 for goal, 0.77 for affect, and 0.78 for mastery).
Conclusion. It is concluded that SIAQ-M possesses acceptable factorial validity and internal consistency and can measure imagery ability among Malaysian athletes.
Objectives. This study examined the factorial validity and internal consistency of the Malaysian adapted SIAQ using confirmatory factor analysis and Cronbach’s alpha.
Methods. The questionnaire was administered online to 193 participants (101 men and 92 women) with a mean age of 22.06 ± 3.72. The data were normalized, and four models were tested (model 1: data with square root transformation for values above the threshold; model 2: data with logarithm transformation for values above the threshold; model 3: data with values above threshold were logarithm transformed and values that were almost reaching the threshold (Item_4 and Item_12) were transformed by square root; and model 4: data with values above and reaching the threshold were logarithm transformed).
Results. The result of factorial analysis for model 2 revealed a good model fit (X^2=184.76, df=80, p<0.00, X^2/df=2.31, CFI=0.94, TLI=0.92, SRMR=0.05, and RMSEA=0.08) for the five-factor model structure implicating a good factorial validity. Furthermore, all path loadings exceeding 0.50 indicated good convergent validity of the subscales. Moreover, alpha coefficients range from 0.77 to 0.85 (0.85 for skill, 0.77 for strategy, 0.84 for goal, 0.77 for affect, and 0.78 for mastery).
Conclusion. It is concluded that SIAQ-M possesses acceptable factorial validity and internal consistency and can measure imagery ability among Malaysian athletes.
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APPLICABLE REMARKS
APPLICABLE REMARKS
- This finding could provide knowledge to the coaches and athletes on the various imagery functions and employ this validated psychological tool to assess athletes’ imagery ability which is essential for imagery training, especially among Malaysian athletes.
- This tool could provide the coaches with their athletes’ imagery ability. The higher the ability, the more beneficial the imagery training would be. Therefore, realizing the current imagery ability could drive the coaches to tailor specific training accordingly.
Type of Study: Original Article |
Subject:
Sport Psychology and its Related Branches
Received: 2022/01/16 | Accepted: 2022/03/6
Received: 2022/01/16 | Accepted: 2022/03/6
References
1. Toth AJ, McNeill E, Hayes K, Moran AP, Campbell M. Does mental practice still enhance performance? A 24 Year follow-up and meta-analytic replication and extension. Psychology of Sport and Exercise. 2020;48:101672. [DOI:10.1016/j.psychsport.2020.101672]
2. Vealey RS, Forlenza ST. Understanding and Using Imagery in Sport. In: Williams JM, Krane V, editors. Applied Sport Psychology: Personal Growth to Peak Performance2. 7th ed. New York: McGraw-Hill; 2015. p. 240-73.
3. Weinberg R, Daniel G. Foundations of Sport and Exercise Psychology 7th Ed. 2019.
4. Hall CR, Mack DE, Paivio A, Hausenblas HA. Imagery use by athletes: Development of the sport imagery questionnaire. Int J Sport Psychol. 1998;29(1):73-89. [DOI:10.1037/t52953-000]
5. Cumming J, Williams SE. The role of imagery in performance. The Oxford handbook of sport and performance psychology. Oxford library of psychology. New York, NY, US: Oxford University Press; 2012. p. 213-32. [DOI:10.1093/oxfordhb/9780199731763.013.0011]
6. Filgueiras A, Hora G, Lacerda A, Baltar YC, Barreto BP, Melo R, et al. Difference in Imagery use between Full-contact and Limited contact sports. Cuad Psicol del Deport Murcia. 2018;18(2):57-65.
7. Kuan G, Morris T, Terry P. Effects of music on arousal during imagery in elite shooters: A pilot study. PLoS One. 2017;12(4):e0175022. [DOI:10.1371/journal.pone.0175022] [PMID] [PMCID]
8. Fortes LS, Freitas-Júnior CG, Paes PP, Vieira LF, Nascimento-Júnior JRA, Lima-Júnior DRAA, et al. Effect of an eight-week imagery training programme on passing decision-making of young volleyball players. Int J Sport Exerc Psychol. 2020;18(1):120-8. [DOI:10.1080/1612197X.2018.1462229]
9. Simonsmeier BA, Androniea M, Buecker S, Frank C. The effects of imagery interventions in sports: a meta-analysis. Int Rev Sport Exerc Psychol. 2020;0(0):1-22. [DOI:10.31234/osf.io/g5tp2]
10. Simonsmeier BA, Buecker S. Interrelations of Imagery Use , Imagery Ability , and Performance in Young Athletes. J Appl Sport Psychol. 2017;29(1):32-43. [DOI:10.1080/10413200.2016.1187686]
11. Martin KA, Moritz SE, Hall CR. Imagery use in sport: A literature review and applied model. Sport Psychol. 1999;13(3):245-68. [DOI:10.1123/tsp.13.3.245]
12. Morris T, Spittle M, Watt AP. Imagery in Sport. Leeds, England: Human Kinetics; 2005.
13. Robin N, Dominique L, Toussaint L, Blandin Y, Guillot A, Her M Le. Effects of motor imagery training on service return accuracy in tennis: The role of imagery ability. Int J Sport Exerc Psychol. 2007;5(2):175-86. [DOI:10.1080/1612197X.2007.9671818]
14. Bedir D, Erhan SE. The Effect of Virtual Reality Technology on the Imagery Skills and Performance of Target-Based Sports Athletes. Front Psychol. 2021;11(January):1-16. [DOI:10.3389/fpsyg.2020.02073] [PMID] [PMCID]
15. Dana A, Gozalzadeh E. Internal and External Imagery Effects on Tennis Skills Among Novices. Percept Mot Skills. 2017;124(5):1022-43. [DOI:10.1177/0031512517719611] [PMID]
16. Budnik-Przybylska D, Karasiewicz K, Morris T, Watt A. Original article Reliability, factor structure, and construct validity of the Polish version of the sport imagery ability measure. Curr Issues Personal Psychol. 2014;4(December):196-207. [DOI:10.5114/cipp.2014.47444]
17. Hall C, Pongrac J, Buckholz E. The measurement of imagery ability. Hum Mov Sci. 1985;4(2):107-18. [DOI:10.1016/0167-9457(85)90006-5]
18. Hall C, Martin K. Measuring movement imagery abilities: A revision of the Movement Imagery Questionnaire. J Ment Imag. 1997;21:143-54. Available [DOI:10.1037/t07979-000]
19. Williams SE, Cumming J, Ntoumanis N, Nordin-Bates SM, Ramsey R, Hall C. Further validation and development of the movement imagery questionnaire. J Sport Exerc Psychol. 2012;34(5):621-46. [DOI:10.1123/jsep.34.5.621] [PMID]
20. Isaac A, Marks DF, Russell DG. An instrument for assessing imagery of movement: The Vividness of Movement Imagery Questionnaire (VMIQ). J Ment Imag. 1986;10(4):23-30. [DOI:10.1037/t07980-000]
21. Roberts R, Callow N, Hardy L, Markland D, Bringer J. Movement imagery ability: development and assessment of a revised version of the vividness of movement imagery questionnaire. Journal of sport & exercise psychology. 2008;30(2):200-21. [DOI:10.1123/jsep.30.2.200] [PMID]
22. Martens R. Imagery in sport, unpublished paper presented at the Medical and Scientific Aspects of Elitism in Sport Conference. Brisbane (Australia); 1982.
23. Vealey R, Greenleaf C. Seeing believes: Understanding and using imagery in sport. Appl Sport Psychol Pers growth to Phys Perform. 1998;200-24.
24. Vealey RS. Conceptualization of Sport-Confidence and Competitive Orientation: Preliminary Investigation and Instrument Development. J Sport Exerc Psychol. 1986;8(3):221-46. [DOI:10.1123/jsp.8.3.221]
25. Vealey RS, Walter SM. Imagery training for performance enhancement and personal development. Appl Sport Psychol Pers growth to peak Perform. 1993;2:200-21.
26. Gregg M, Hall C. Measurement of motivational imagery abilities in sport. J Sports Sci. 2006;24(9):961-71. [DOI:10.1080/02640410500386167] [PMID]
27. Watt AP, Morris T, Andersen MB. Issues in the development of a measure of imagery ability in sport. J Ment Imag. 2004;28(3&4):149-80.
28. Williams SE, Cumming J. Measuring Athlete Imagery Ability: The Sport Imagery Ability Questionnaire. J Sport Exerc Psychol. 2011;33:416-40. [DOI:10.1123/jsep.33.3.416] [PMID]
29. Short SE, Monsma E V, Short MW. Is what you see really what you get? Athletes' perceptions of imagery's functions. Sport Psychol. 2004;18(3):341-9. [DOI:10.1123/tsp.18.3.341]
30. Spindler DJ, Allen MS, Vella SA, Swann C. Motivational-general arousal imagery does not improve decision-making performance in elite endurance cyclists. Cogn Emot. 2019;33(5):1084-93. [DOI:10.1080/02699931.2018.1529656] [PMID]
31. Quinton ML, van Zanten JV, Trotman GP, Cumming J, Williams SE. Investigating the protective role of mastery imagery ability in buffering debilitative stress responses. Front Psychol. 2019;10(JULY):1657. [DOI:10.3389/fpsyg.2019.01657] [PMID] [PMCID]
32. Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25(24):3186-91. [DOI:10.1097/00007632-200012150-00014] [PMID]
33. Alcaraz-Ibanez M, Manuel Aguilar-Parra J, Alias Garcia A, Rodriguez Martinez A. Spanish adaptation and validation of the sport imagery ability questionnaire. Rev Mex Psicol. 2017;34(1):65-76.
34. Arruza-Gabilondo JA, Gonzalez Rodríguez O, Cecchini Estrada JA, Fink-Smith C. Factorial validity and reliability of the Spanish version of Sport Imagery Ability Questionnaire (SIAQ). Cuad Psicol del Deport. 2018;18(1):229-36. [DOI:10.1037/t69097-000]
35. Ashrafi SVS, Talab RH, Shojaei M. Validity and reliability of Persian version of the Sport Imagery Ability Questionnaire. Int J Sport Stud. 2015;5(4):482-7.
36. Tahmasbi F, Hatami F, Hatami Shahmir E. The study of psychometric Properties of Persian Version of Sport Imagery Ability Questionnaire. Sport Psychol Stud. 2020;
37. Budnik-Przybylska D, Karasiewicz K. Reliability and Validity of the Polish Version of the Sport Imagery Ability Questionnaire. Polskie Forum Psychologiczne. 2020;25(2): 221-37.
38. Simonsmeier BA, Hannemann A. Die deutsche übersetzung des SIQ und SIAQ zur erfassung von vorstellungsgebrauch und vorstellungskompetenz im sport. Zeitschrift fur Sport. 2017;24(3):100-10. [DOI:10.1026/1612-5010/a000204]
39. Singnoy C, Vongjaturapat N, Fonseca AM. Development and Psychometric Evaluation of the Sport Imagery Ability Questionnaire Thai Version (SIAQt). Int J Sport Sci. 2015;5(1):33-8.
40. Tabachnick BG, Fidell LS. Using Multivariate Statistics. 7th ed. New York: Pearson; 2018.
41. Tabachnick BG, Fidell LS. Using Multivariate Statistic. 4th ed. New York: Harper and Row; 2001.
42. Stoet G. PsyToolkit: A Novel Web-Based Method for Running Online Questionnaires and Reaction-Time Experiments. Teach Psychol. 2017;44(1):24-31. [DOI:10.1177/0098628316677643]
43. Stoet G. PsyToolkit: A software package for programming psychological experiments using Linux. Behav Res Methods. 2010;42(4):1096-104. [DOI:10.3758/BRM.42.4.1096] [PMID]
44. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 8th ed. United Kingdom: Cengage Learning; 2019.
45. Kline RB. Principles and Practice of Structural Equation Modeling. 4th ed. New York: The Guilford Press; 2016.
46. Kim H-Y. Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restor Dent Endod. 2013;38(1):52. [DOI:10.5395/rde.2013.38.1.52] [PMID] [PMCID]
47. Bentler PM. Comparative fit indexes in structural models. Vol. 107, Psychological Bulletin. US: American Psychological Association; 1990. p. 238-46. [DOI:10.1037/0033-2909.107.2.238] [PMID]
48. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1-55. [DOI:10.1080/10705519909540118]
49. Byrne BM. Structural equation modeling with AMOS: Basic concepts, applications, and programming, 2nd ed. Structural equation modeling with AMOS: Basic concepts, applications, and programming, 2nd ed. New York, NY, US: Routledge/Taylor & Francis Group; 2010. xix, 396-xix, 396. (Multivariate applications series.).
50. Roemer E, Schuberth F, Henseler J. HTMT2-an improved criterion for assessing discriminant validity in structural equation modeling. Ind Manag Data Syst. 2021;121(12):2637-50. [DOI:10.1108/IMDS-02-2021-0082]
51. Fornell, C., & Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39-50.
https://doi.org/10.2307/3151312 [DOI:10.1177/002224378101800104]
52. Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci. 2015;43(1):115-35. [DOI:10.1007/s11747-014-0403-8]
53. Gold AH, Malhotra A, Segars AH. Knowledge management: An organizational capabilities perspective. J Manag Inf Syst. 2001;18(1):185-214. [DOI:10.1080/07421222.2001.11045669]
54. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 7th ed. Prentice Hall; 2010. (Always learning).
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