Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/157235
|
| Title: | 運動焦慮量表(SAS-2)的心理計量特質驗證
Validation of Psychometric Properties of Sport Anxiety Scale-2 for Athletes in Taiwan |
| Authors: | 黃裕成
Huang, Yu-Cheng |
| Contributors: | 余民寧
Yu, Min-Ning
黃裕成
Huang, Yu-Cheng |
| Keywords: | 運動焦慮量表
驗證性因素分析
Rasch測量模型
單向度多元計分的部份計分模型
多向度隨機係數多項式洛基模型
臺灣運動員
Sport Anxiety Scale-2
Confirmatory factor analysis
Rasch measurement model
Partial credit model
Multidimensional random coefficients multinomial logit model
Taiwanese athletes |
| Date: | 2025 |
| Issue Date: | 2025-06-02 14:49:25 (UTC+8) |
| Abstract: | 運動焦慮量表(SAS-2)的驗證性因素分析(CFA)模型由擔憂、身體焦慮和注意力分散分量表組成。然而，目前尚未明瞭受試者的作答反應組型，因此，本研究旨在評估臺灣運動焦慮量表的可靠性和有效性，並透過CFA模型與Rasch測量模型完善運動焦慮量表分析。547名受試者(年齡:18.21 ± 2.94 yr）的運動員完成了SAS-2，其中包括161名女性和386名男性。菁英運動員345人（佔總數的63.1%），一般運動員202人（佔總數36.9%）。單向度多元計分的部份計分模型（PCM）及多向度隨機係數多項式洛基模型 (MRCMLM) 用以評估運動焦慮量表的心理測量特性。在擔憂分量表中，受試者的能力表現範圍比題目難度更廣泛，顯示需要更具挑戰性和更簡單的受試題目來評估受試者的能力。在身體焦慮分量表中，則需加入較簡單的題目來評估受試者的能力。在注意力分散分量表中，因大部分的受試者能力分布範圍低於題目的難度範圍，也需加入較簡單的題目來評估受試者的能力。驗證性因素分析模型與臺灣運動員運動焦慮的資料良好適配（CFI = 0.96，NNFI = 0.95，RMSEA = 0.087），並透過PCM、MRCMLM進一步證實模型與資料同樣適配。本研究證明了不同性別和競爭水準的運動員在形貌、矩陣、數值和殘差測量的恆等性。運動焦慮量表中的第12題和第14題顯示出輕微的差異試題功能(DIF)現象的存在，第12題有利於女性，則第14題有利於男性。然而，標準化分數差異的結果顯示整體性別不存在顯著的DIF現象。運動焦慮量表中的第5題表現出輕微的DIF，有利於菁英運動員。然而，標準化分數差異的結果顯示不同競爭水準的運動員缺乏顯著的DIF差異。臺灣運動員在運動焦慮量表中具有良好的心理測量信度和效度，可做為初步評估臺灣運動員的運動焦慮。為了精確估算出具有較高擔憂傾向的受試者，SAS-2有必要增加擔憂分量表中的高難度題目，來測量涵蓋具有高擔憂運動焦慮情形的運動員。Rasch模型分析確定了SAS-2中最具挑戰性的試題，位於身體焦慮分量表，後續可探究高運動焦慮所帶來的影響。SAS-2常模參照表，可幫助體育界的教練、家長及運動員快速評估運動焦慮狀況，並作為學術界進一步研究運動員心理資源介入的參考，幫助運動員學習應對運動焦慮的方法，從而提升運動表現。
Current hierarchical confirmatory factor analysis (CFA) model of the Sport Anxiety Scale-2 (SAS-2) consists of worry, somatic anxiety, and concentration disruption subscales. However, it remains unclear how individual participants response to each item. Therefore, this study aims to assess the reliability and validity of the Taiwanese version of the SAS-2 and refine it by using CFA analysis and Rasch measurement models among athletes. 547 athletes aged M = 18.21 (SD = 2.94) completed SAS-2 questionnaire, including 161 females and 386 males. There were 345 elite athletes (63.1% of the total) and 202 general athletes (36.9% of the total). To evaluate sport anxiety, the SAS-2 was employed. The partial credit model (PCM）and the multidimensional random coefficients multinomial logit model (MRCMLM) were utilized to assess the psychometric properties of the SAS-2. In the worry subscale, the participants’ abilities exhibited a broader range than the item difficulty, indicating a requirement for both more challenging and simpler items. Similarly, in the somatic anxiety subscale, it was worth considering the addition of easier items. This consideration might also apply to the concentration disruption subscale, as a significant portion of participants’ abilities fell below the items’ difficulty levels. Confirmatory factor analysis showed a good fit of the model to the data for the Taiwanese version of the SAS-2 (CFI = 0.96, NNFI = 0.95, RMSEA = 0.087), which was further confirmed by using PCM and MRCMLM. The study demonstrated configural, metric, scalar and strict measurement invariances for genders and levels of competition. The items 12 and 14 show slight differential item functioning (DIF), favoring females for item 12 and males for item 14. However, the findings from the standardized score difference revealed the absence of significant DIF, suggesting that individuals of both genders with equivalent levels of sports anxiety would respond similarly to overall scale. The item 5 exhibited slight DIF, favoring elite athletes. Nevertheless, the findings of the standardized score difference revealed a lack of significant DIF in the overall comparison of levels of competition. When applied to Taiwanese samples, the SAS-2 has been demonstrated to possess good psychometric properties, including reliability and validity. Therefore, it can serve as a preliminary tool for assessing sports anxiety among Taiwanese athletes. To accommodate to participants with higher levels of worry tendencies, it is necessary for the SAS-2 to include additional high-difficulty items within the worry subscale. Rasch model analysis identified the most challenging item in SAS-2, which is associated with somatic anxiety, shedding light on the potential impact of high sports anxiety. The SAS-2 norm-referenced table can help coaches, parents, and athletes in the sports community quickly assess sports anxiety levels. It also serves as a reference for academic research on psychological resource interventions for athletes, helping them learn strategies to cope with sports anxiety and ultimately enhance their athletic performance. |
| Reference: | 中文
114學年度中等以上學校運動成績優良學生升學輔導委員會 (2025，1月12日)。114學年度高級中等以上學校運動成績優良學生升學輔導甄審甄試章。https://lulu.ntus.edu.tw/new/68/show
余民寧 (2020)。量表編製與發展：Rasch測量模型的應用。心理。
余民寧 (2021)。心理與教育統計學。三民。
吳穌、林紀玲（2009）。運動員焦慮量表編製。運動知識學報，(6)，45-57。https://doi.org/10.29596/BGYY.200910.0005
林明宏、黃美華、熊婉君、康琳翔（2012）。運動選手決策風格與運動焦慮的關係。彰化師大體育學報，(11)，69-82。https://doi.org/10.29964/NCUEPE.201209.0006
紀世清（2013）。多向度多層面羅西模式編製運動訓練反應量表。大專體育學刊，15(4)，421-428。https://doi.org/10.5297/ser.1504.004
張偉豪 (2011)。SEM論文寫作不求人。鼎茂。
趙珮均、陳美華（2017）。兒童運動狀態焦慮量表之信效度分析。彰化師大體育學報，(16)，1-13。https://www.airitilibrary.com/Article/Detail?DocID 18145167-201712-201803160016-201803160016-1-13
盧俊宏（1990）。大專運動員運動競賽特質性焦慮之研究。體育學報，(12)，45-69。https://doi.org/10.6222/pej.0012.199012.1404
賴素玲、吳治翰、賴素英（2016）。不同目標取向及條件對運動競賽焦慮的影響。運動教練科學，(42)，81-90。https://doi.org/10.6194/SCS.2016.42.09
謝和均、張若寧（2024）。射箭選手運動焦慮與專注力之研究。運動健康休閒學報，(15)，85-111。https://www.airitilibrary.com/Article/Detail?DocID=22180710-N202409110017-00008
外文
Adams, R. J., Wilson, M., & Wang, W.-C. (1997). The multidimensional random coefficients multinomial logit model. Applied Psychological Measurement, 21(1), 1-23. https://doi.org/10.1177/0146621697211001
Adams, R. J., Wu, M. L., & Wilson, M. R. (2012). ACER ConQuest: Generalised item response modelling software (version 3.0) [Computer software]. Australian Council for Educational Research. https://www.acer.org/au/conquest
Bianchin, M., & Angrilli, A. (2012). Gender differences in emotional responses: A psychophysiological study. Physiology & Behavior, 105(4), 925-932. https://doi.org/10.1016/j.physbeh.2011.10.031
Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Psychology Press. https://doi.org/10.4324/9781410614575
Boone, W. J. (2020). Rasch basics for the novice. In M. S. Khine (Eds.), Rasch measurement: Applications in quantitative educational research (pp. 9-30). Springer.
Briggs, D. C., & Wilson, M. (2003). An introduction to multidimensional measurement using Rasch models. Journal of Applied Measurement, 4(1), 87–100.
Brown, G. T. (Ed). (2014). Mind, body and sport understanding: Understanding and supporting student-athlete mental wellness. National Collegiate Athletic Association. https://www.ncaapublications.com/p-4375-mind-body-and-sport-understanding-and-supporting-student-athlete-mental-wellness.aspx
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834
Cheng, W. N. K., Hardy, L., & Markland, D. (2009). Toward a three-dimensional conceptualization of performance anxiety: Rationale and initial measurement development. Psychology of sport and exercise, 10(2), 271-278.
Cheng, W. K., Hardy, L. E. W., & Markland, D. (2011). Cross-cultural validation of a three-dimensional measurement model of performance anxiety in the context of Chinese sports. International Journal of Sport Psychology, 42(5), 417-435.
Cho, S., Choi, H., Eklund, R. C., & Paek, I. (2018). Validation and reliability of the Korean version of the Sport Anxiety Scale-2. Journal of Human Kinetics, 61, 217-225. https://doi.org/10.1515/hukin-2017-0138
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587
Correia, M., & Rosado, A. (2019). Anxiety in athletes: Gender and type of sport differences. International Journal of Psychological Research, 12(1), 9-17. https://doi.org/10.21500/20112084.3552
Cox, R. H., Martens, M. P., & Russell, W. D. (2003). Measuring anxiety in athletics: The revised Competitive State Anxiety Inventory-2. Journal of Sport & Exercise Psychology, 25(4), 519–533.
Duda, J. L. (1989). Relationship between task and ego orientation and the perceived purpose of sport among high school athletes. Journal of Sport & Exercise Psychology, 11(3), 318–335.
Duda, J. L., & Nicholls, J. G. (1992). Dimensions of achievement motivation in schoolwork and sport. Journal of Educational Psychology, 84(3), 290–299. https://doi.org/10.1037/0022-0663.84.3.290
Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286–299. https://doi.org/10.1037/1040-3590.7.3.286
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
Grossbard, J. R., Smith, R. E., Smoll, F. L., & Cumming, S. P. (2009). Competitive anxiety in young athletes: Differentiating somatic anxiety, worry, and concentration disruption. Anxiety, Stress, and Coping, 22(2), 153-166. https://doi.org/10.1080/10615800802020643
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8nd ed.). CENGAGE. https://www.cengageasia.com/title/default/detail?isbn=9781473756540
Hashim, H. A., Shaharuddin, S. S., Hamidan, S., & Grove, J. R. (2017). A multisample analysis of psychometric properties for the Malaysian adapted Sport Anxiety Scale-2 among youth athletes. Psychological Reports, 120(1), 141-157. https://doi.org/10.1177/0033294116685868
Hu, L.-T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453. https://doi.org/10.1037/1082-989X.3.4.424
IBM Corp. (2015). IBM SPSS Statistics for Windows (version 23.0) [Computer software]. IBM Corp. https://www.ibm.com/support/pages/downloading-ibm-spss-statistics-23
Jöreskog, K. G., & Sörbom, D. (2007). LISREL (version 8.8) [Computer software]. Scientific Software International. https://ssicentral.com/index.php/products/lisrel/
Leal, P. C., Goes, T. C., da Silva, L. C. F., & Teixeira-Silva, F. (2017). Trait vs. state anxiety in different threatening situations. Trends in Psychiatry and Psychotherapy, 39(3), 147–157. https://doi.org/10.1590/2237-6089-2016-0044
Linacre, J. M. (1994). Many-facet Rasch measurement. MESA Press.
Linacre, J. M. (2023). Winsteps® Rasch measurement computer program user’s guide (version 5.5.1.). https://www.winsteps.com/
Madrigal, L. A., Roma, V., Caze, T., Maerlender, A., & Hope, D. (2018). Factor structure and gender invariance testing for the Sport Anxiety Scale-2 (SAS-2). Journal of Clinical Sport Psychology, 12(2), 201-217. https://doi.org/10.1123/jcsp.2016-0036
Martens, R. (1977). Sport competition anxiety test. Human Kinetics.
Martens, R., Burton, D., Vealey, R. S., Bump, L., & Smith, D. E. (1990). Development and validation of the competitive state anxiety inventory-2 (CSAI-2). In R. Martens, R. S. Vealey, & D. Burton (Eds.), Competitive anxiety in sport (pp. 117-213). Human Kinetics.
Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149-174. https://doi.org/10.1007/BF02296272
Masters, G. N., & Wright, B. D. (1984). The essential process in a family of measurement models. Psychometrika, 49(4), 529–544. https://doi.org/10.1007/BF02302590
Matsunaga, M. (2010). How to factor-analyze your data right: Do’s, don’ts, and how-to’s. International Journal of Psychological Research, 3(1), 97-110. https://doi.org/10.21500/20112084.854
Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91(3), 328–346. https://doi.org/10.1037/0033-295X.91.3.328
Osterlind, S. J., & Everson, H. T. (2009). Differential item functioning (2nd ed.). SAGE. https://doi.org/10.4135/9781412993913
Putra, M. F. P., Guntoro, T. S., Wandik, Y., Ita, S., Sinaga, E., Hidayat, R. R., Sinaga, E., Muhammad, J., Sinaga, F. S. G., Kmurawak, R. M. B., & Rahayu, A. S. (2021). Psychometric properties at Indonesian version of the Sport Anxiety Scale-2: Testing on elite athletes of Papua, Indonesian. International Journal of Human Movement and Sports Sciences, 9(6), 1477-1485. https://doi.org/ 10.13189/saj.2021.090645
Ramis, Y., Viladrich, C., Sousa, C., & Jannes, C. (2015). Exploring the factorial structure of the Sport Anxiety Scale-2: Invariance across language, gender, age and type of sport. Psicothema, 27(2), 174-181. https://doi.org/10.7334/psicothema2014.263
Rasch, G. (1980). Probability models for some intelligence and attainment tests (Expanded ed.). The University of Chicago Press. (Original work published 1960)
Rönkkö, M., & Cho, E. (2022). An updated guideline for assessing discriminant validity. Organizational Research Methods, 25(1), 6-14. https://doi.org/10.1177/1094428120968614
Shealy, R. & Stout, W. (1993). A Model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF. Psychometrika, 58, 159-194. https://doi.org/10.1007/BF02294572
Silva-Rocha, V. V., de Sousa, D. A., & Osório, F. L. (2019). Psychometric properties of the Brazilian version of the Sport Anxiety Scale-2. Frontiers in Psychology, 10, 806. https://doi.org/10.3389/fpsyg.2019.00806
Smith, R. E., Smoll, F. L., & Barnett, N. P. (1995). Reduction of children's sport performance anxiety through social support and stress-reduction training for coaches. Journal of applied developmental psychology, 16(1), 125-142.
Smith, R. E., Smoll, F. L., Cumming, S. P., & Grossbard, J. R. (2006). Measurement of multidimensional sport performance anxiety in children and adults: The Sport Anxiety Scale-2. Journal of Sport & Exercise Psychology, 28(4), 479-501. https://doi.org/10.1123/jsep.28.4.479
Smith, R. E., Smoll, F. L., & Schutz, R. W. (1990). Measurement and correlates of sport-specific cognitive and somatic trait anxiety: The Sport Anxiety Scale. Anxiety Research, 2(4), 263-280. https://doi.org/10.1080/08917779008248733
Tomczak, M., Kleka, P., Walczak, A., Bojkowski, Ł., Gracz, J., & Walczak, M. (2022). Validation of Sport Anxiety Scale-2 (SAS-2) among Polish athletes and the relationship between anxiety and goal orientation in sport. Scientific Reports, 12(1), 1-11. https://doi.org/10.1038/s41598-022-16418-6
Walker, C. M., & Beretvas, S. N. (2001). An empirical investigation demonstrating the multidimensional DIF paradigm: A cognitive explanation for DIF. Journal of Educational Measurement, 38(2), 147-163.
Wang, W. C., Wilson, M., & Adams, R. J. (1997). Rasch models for multidimensionality between items and within items. In M. Wilson, G. Engelhard, & K. Draney (Eds.), Objective measurement: Theory into practice (Vol. 4, pp. 139-155). Ablex. http://works.bepress.com/ray_adams/33/
Wang, W. C., Wilson, M., & Adams, R. J. (2000). Interpreting the parameters of a multidimensional Rasch model. In M. Wilson & G. Engelhard (Eds.), Objective measurement: Theory into practice (Vol. 5, pp. 219-242). Ablex. http://works.bepress.com/ray_adams/22/
Weinberg, R. S., & Gould, D. (2019). Foundations of sport and exercise psychology (2nd ed.). Human Kinetics.
Wilson, M. (2023). Constructing measures: An item response modeling approach (2nd ed.). Routledge. https://doi.org/10.4324/9781003286929
Wright, B. D., & Linacre, J. M. (1989). Observations are always ordinal; measurements, however, must be interval. Archives of Physical Medicine and Rehabilitation, 70(12), 857-860. |
| Description: | 碩士
國立政治大學
教育學系
111152012 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111152012 |
| Data Type: | thesis |
| Appears in Collections: | [教育學系] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 201201.pdf | | 2257Kb | Adobe PDF | 0 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
