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Journal ArticleDOI

Validation of the revised sport motivation scale (SMS-II)

TL;DR: The validity and reliability of the sport motivation scale (SMS-II) has been examined in two studies as discussed by the authors, and the structure of the SMS-II and its relation with outcomes was further examined.
About: This article is published in Psychology of Sport and Exercise.The article was published on 2013-05-01. It has received 339 citations till now. The article focuses on the topics: Construct validity & Validity.
Citations
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Journal ArticleDOI
TL;DR: Results largely supported a continuum-like structure of motivation and indicate that self-determination is central in explaining human motivation, but did not support the inclusion of integrated regulation or the 3 subscales of intrinsic motivation.
Abstract: Self-determination theory proposes a multidimensional representation of motivation comprised of several factors said to fall along a continuum of relative autonomy. The current meta-analysis examined the relationships between these motivation factors in order to demonstrate how reliably they conformed to a predictable continuum-like pattern. Based on data from 486 samples representing over 205,000 participants who completed 1 of 13 validated motivation scales, the results largely supported a continuum-like structure of motivation and indicate that self-determination is central in explaining human motivation. Further examination of heterogeneity indicated that while regulations were predictably ordered across domains and scales, the exact distance between subscales varied across samples in a way that was not explainable by a set of moderators. Results did not support the inclusion of integrated regulation or the 3 subscales of intrinsic motivation (i.e., intrinsic motivation to know, to experience stimulation, and to achieve) due to excessively high interfactor correlations and overlapping confidence intervals. Recommendations for scale refinements and the scoring of motivation are provided. (PsycINFO Database Record

245 citations

Journal ArticleDOI
TL;DR: In this article, the authors explore the nature of workplace motivation by testing the continuum structure of motivation proposed by self-determination theory through the application of relatively new and advanced methodological techniques and demonstrate the usefulness of the overarching bifactor exploratory structural equation modeling framework in organizational psychology and discuss implications of such models over more traditional confirmatory factor analyses.

172 citations

Journal ArticleDOI
TL;DR: In this article, the influence of pressure from above (sport administrations) and pressure from below (athlete motivation) on coach motivation and autonomy-supportive coaching behaviours was tested using structural equation modeling.

74 citations


Cites background or methods or result from "Validation of the revised sport mot..."

  • ...In this study, it was anticipated that the final model developed by Pelletier et al. (2002) would provide the best explanation of the interaction of the factors in a coaching context....

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  • ...Since the objective of this study was to replicate the results of the Pelletier et al. (2002) study, a full mediation model was tested....

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  • ...These objectives were met by replicating Pelletier et al.’s (2002) model for an academic setting in a sport setting. Specifically, this study used structural equation modelling to demonstrate that perceived pressure from above (administrative pressure) and perceived pressure from below (perceptions of athlete motivations), were related to coach motivation, and subsequently related to coaches’ reported autonomy-supportive coaching styles. This model was selected as it emphasized the importance of motivation and its relationship with environmental factors and autonomy-supportive behaviours. This model also differentiated between two types of environmental factors that may be influencing the coaches’ motivation: pressure from above and pressure from below. Pressure from above speaks to administrative or peer pressure that may be exerted on the coach. This type of pressure is very relevant in sport, as the coaching context can be competitive and coaches may feel additional pressure from their club administration and coaching peers to perform and be successful (e.g. Allen & Shaw, 2009). Pressure from below concerns the coaches’ perceptions of their athletes’ motivations for participating in sport. Research has shown that when someone in a position of authority believes that the subordinate is intrinsically motivated, or highly self-determined, they are more likely to engage in autonomy supportive behaviour (Pelletier & Vallerand, 1996). Additional research has identified other environmental factors like time constraints (Taylor et al., 2009) or job security (Stebbings et al., 2012), and psychological factors like emotional exhaustion (Soenens et al., 2012) as predictors of autonomy-supportive behaviours. However, for the purposes of shortening the length of the present study, only the factors identified in the Pelletier et al.’s model (2002) were selected for the analyses. Finally, in order to begin systematically examining coaches within specific coaching environments, the present study targeted coaches at the developmental level, as described by Trudel and Gilbert (2006). Specifically, coaches at this level began coaching because they used to actively compete in their sport and they are often coaching their own children....

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  • ...These objectives were met by replicating Pelletier et al.’s (2002) model for an academic setting in a sport setting. Specifically, this study used structural equation modelling to demonstrate that perceived pressure from above (administrative pressure) and perceived pressure from below (perceptions of athlete motivations), were related to coach motivation, and subsequently related to coaches’ reported autonomy-supportive coaching styles. This model was selected as it emphasized the importance of motivation and its relationship with environmental factors and autonomy-supportive behaviours. This model also differentiated between two types of environmental factors that may be influencing the coaches’ motivation: pressure from above and pressure from below. Pressure from above speaks to administrative or peer pressure that may be exerted on the coach. This type of pressure is very relevant in sport, as the coaching context can be competitive and coaches may feel additional pressure from their club administration and coaching peers to perform and be successful (e.g. Allen & Shaw, 2009). Pressure from below concerns the coaches’ perceptions of their athletes’ motivations for participating in sport. Research has shown that when someone in a position of authority believes that the subordinate is intrinsically motivated, or highly self-determined, they are more likely to engage in autonomy supportive behaviour (Pelletier & Vallerand, 1996). Additional research has identified other environmental factors like time constraints (Taylor et al., 2009) or job security (Stebbings et al., 2012), and psychological factors like emotional exhaustion (Soenens et al., 2012) as predictors of autonomy-supportive behaviours. However, for the purposes of shortening the length of the present study, only the factors identified in the Pelletier et al.’s model (2002) were selected for the analyses....

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  • ...In one of the first studies to examine these constructs, Pelletier et al. (2002) examined the impact of perceived administrative pressure, perceived student motivation, and teachers’ self-reported motivation and their relationship with autonomy-supportive behaviours. These environmental factors were selected as they had previously been tested in laboratory settings and were related to self-determined motivation (Deci, Spiegal, Ryan, Koestner, & Kauffman, 1982; Pelletier & Vallerand, 1996). They tested a number of models using these factors and their final model suggested that teachers’ self-determined motivation positively predicted autonomy-supportive teaching behaviours. Furthermore, they found teachers’ self-determined motivation was negatively impacted by their impressions of administrative burdens (Pressure from Above) and positively impacted by their perceptions of their students’ motivation for learning (Pressure from Below). Taylor and colleagues (Taylor, Ntoumanis, & Smith, 2009) built upon these findings and identified additional environmental factors such as teachers’ own performance evaluation, cultural norms, and time constraints that were related to autonomy-supportive teaching behaviour. In additional studies examining the psychological factors, Taylor and colleagues (Taylor, Ntoumanis, & Standage, 2008) found that teachers’ perceptions of the satisfaction of their psychological needs predicted autonomy-supportive teaching styles, and Soenens and colleagues (Soenens, Sierens, Vansteenkiste, Dochy, & Goossens, 2012) identified perceived emotional exhaustion and depersonalization as predictors of controlling teaching styles. While researchers have examined the predictors of autonomysupportive behaviours in school physical education settings (e.g. Hagger, Chatzisarantis, Culverhouse, & Biddle, 2003; Pihu, Hein, Koka, & Haggar, 2008), to date, only a couple of studies have examined such predictors in sport contexts. Stebbings, Taylor, and Spray (2011) focused on psychological factors and autonomysupportive coaching behaviours....

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Journal ArticleDOI
TL;DR: In this article, the authors used a confirmatory factor analysis (CFA) to investigate if the original 4-factor structure of the TEIQue could be replicated in a sample of athletes.

74 citations

Journal ArticleDOI
TL;DR: Evaluated motivation questionnaires are psychometrically strong instruments for quantifying motivation that are widely supported in the literature and suggested that the IMI ranks first and the SMS ranks sixth according to the average weighted impact factors of their original publications.
Abstract: Motivation is widely-researched, in both sport psychology and other fields. As rigorous measurement is essential to understanding this latent construct, a critical appraisal of measurement instruments is needed. Thus, the purpose of this review was to evaluate the six most highly cited motivation measures in sport. Peer-reviewed articles published prior to August 2016 were searched to identify the six most highly cited motivation questionnaires in sport: Sport Motivation Scale (SMS), Intrinsic Motivation Inventory (IMI), Situational Motivational Scale (SIMS), Perceptions of Success Questionnaire (POSQ), Behavioural Regulation in Sport Questionnaire (BRSQ), and Task and Ego Orientation in Sport Questionnaire (TEOSQ). The questionnaires were then evaluated and discussed in four sections: Development, Reliability, Correlates, and Summary. Bibliometric data were also calculated (average weighted impact factor) and assessed (e.g., citations per year) to evaluate the impact of the use of each questionnaire. Despite some variance in their psychometric properties, conceptualisation, structure, and utility, the six questionnaires are psychometrically strong instruments for quantifying motivation that are widely supported in the literature. Bibliometric analyses suggested that the IMI ranks first and the SMS ranks sixth according to the average weighted impact factors of their original publications. Consideration of each questionnaire’s psychometric strengths/limitations, and conceptualisation of motivation in the context of specific research questions should guide researchers in selecting the most appropriate instrument to measure motivation in sport. The average weighted impact factor of each questionnaire is a useful value to consider as well. With these points in mind, recommendations are provided.

74 citations


Cites background from "Validation of the revised sport mot..."

  • ...Although the SMS has had a “significant impact on the measurement, prediction, and understanding of sport motivation” (Pelletier et al., 2013, p. 331), a revised version was later developed, namely the SMS-II, to address some of the limitations of the SMS....

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  • ...Pelletier et al. (2013) reported Cronbach’s alpha values of 0.70–0.88 for the SMS-II....

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References
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Book
01 Jan 1983
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs

53,113 citations

Journal ArticleDOI
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

37,124 citations

Journal ArticleDOI
TL;DR: Research guided by self-determination theory has focused on the social-contextual conditions that facilitate versus forestall the natural processes of self-motivation and healthy psychological development, leading to the postulate of three innate psychological needs--competence, autonomy, and relatedness.
Abstract: Human beings can be proactive and engaged or, alternatively, passive and alienated, largely as a function of the social conditions in which they develop and function. Accordingly, research guided by self-determination theo~ has focused on the social-contextual conditions that facilitate versus forestall the natural processes of self-motivation and healthy psychological development. Specifically, factors have been examined that enhance versus undermine intrinsic motivation, self-regulation, and well-being. The findings have led to the postulate of three innate psychological needs--competence, autonomy, and relatednesswhich when satisfied yield enhanced self-motivation and mental health and when thwarted lead to diminished motivation and well-being. Also considered is the significance of these psychological needs and processes within domains such as health care, education, work, sport, religion, and psychotherapy. T he fullest representations of humanity show people to be curious, vital, and self-motivated. At their best, they are agentic and inspired, striving to learn; extend themselves; master new skills; and apply their talents responsibly. That most people show considerable effort, agency, and commitment in their lives appears, in fact, to be more normative than exceptional, suggesting some very positive and persistent features of human nature. Yet, it is also clear that the human spirit can be diminished or crushed and that individuals sometimes reject growth and responsibility. Regardless of social strata or cultural origin, examples of both children and adults who are apathetic, alienated, and irresponsible are abundant. Such non-optimal human functioning can be observed not only in our psychological clinics but also among the millions who, for hours a day, sit passively before their televisions, stare blankly from the back of their classrooms, or wait listlessly for the weekend as they go about their jobs. The persistent, proactive, and positive tendencies of human nature are clearly not invariantly apparent. The fact that human nature, phenotypically expressed, can be either active or passive, constructive or indolent, suggests more than mere dispositional differences and is a function of more than just biological endowments. It also bespeaks a wide range of reactions to social environments that is worthy of our most intense scientific investigation. Specifically, social contexts catalyze both within- and between-person differences in motivation and personal growth, resulting in people being more self-motivated, energized, and integrated in some situations, domains, and cultures than in others. Research on the conditions that foster versus undermine positive human potentials has both theoretical import and practical significance because it can contribute not only to formal knowledge of the causes of human behavior but also to the design of social environments that optimize people's development, performance, and well-being. Research guided by self-determination theory (SDT) has had an ongoing concern with precisely these

29,115 citations


"Validation of the revised sport mot..." refers background in this paper

  • ...Individuals who are autonomously regulating their behaviour are more likely to experience task involvement over ego involvement (Ryan & Deci, 2000), intrinsic goals and objectives (Sheldon, Ryan, Deci, & Kasser, 2004), approach instead of avoidance orientations (Nien & Duda, 2009), and more…...

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Journal ArticleDOI
TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 10 Structural Equation Modeling: Overview 10a Appendix -- SEM 11 CFA: Confirmatory Factor Analysis 11a Appendix -- CFA 12 SEM: Testing A Structural Model 12a Appendix -- SEM APPENDIX A Basic Stats

23,353 citations

Posted Content
TL;DR: The Satisfaction With Life Scale is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness, but is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability.
Abstract: This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is suited for use with different age groups, and other potential uses of the scale are discussed.

21,449 citations