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Alex C. Garn

Multidimensional measurement is a common theme in motivation research because many constructs are conceptualized as having an overarching general factor (e.g., situational interest) and specific dimensions (e.g., attention demand, challenge, exploration intention, instant enjoyment, novelty). This review addresses current issues associated with the multidimensional measurement of situational interest in elementary physical education (PE) and illustrates the application and benefits of bifactor exploratory structural equation modeling (ESEM). I perform secondary analysis on a large, previously published data set used to provide validation support for the Situational Interest Scale for Elementary PE. Findings clearly demonstrate the advantages of capturing the multidimensional nature of situational interest using bifactor ESEM. Specifically, a more accurate measurement model of situational interest is reproduced using bifactor ESEM compared with other techniques such as first-order and second-order confirmatory factor analysis. There is empirical support for an overall general factor of situational interest when using the Situational Interest Scale for Elementary PE, however, examining the five dimensions of situational interest as unique factors after accounting for the general factor does not appear warranted.

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Nicholas D. Myers, Melissa A. Chase, Scott W. Pierce and Eric Martin

The purpose of this article was to provide a substantive-methodological synergy of potential importance to future research in sport and exercise psychology. The substantive focus was to improve the measurement of coaching efficacy by developing a revised version of the coaching efficacy scale (CES) for head coaches (N = 557) of youth sport teams (CES II-YST). The methodological focus was exploratory structural equation modeling (ESEM), a methodology that integrates the advantages of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) within the general structural equation model (SEM). The synergy was a demonstration of how ESEM (as compared with CFA) may be used, guided by content knowledge, to develop (or confirm) a measurement model for the CES II-YST. A single-group ESEM provided evidence for close model-data fit, while a single-group CFA fit significantly worse than the single-group ESEM and provided evidence for only approximate model-data fit. A multiple-group ESEM provided evidence for partial factorial invariance by coach’s gender.

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Inés Tomás, Herbert W. Marsh, Vicente González-Romá, Víctor Valls and Benjamin Nagengast

Test of measurement invariance across translated versions of questionnaires is a critical prerequisite to comparing scores on the different versions. In this study, we used exploratory structural equation modeling (ESEM) as an alternative approach to evaluate the measurement invariance of the Spanish version of the Physical Self-Description Questionnaire (PSDQ). The two versions were administered to large samples of Australian and Spanish adolescents. First, we compared the CFA and ESEM approaches and showed that ESEM fitted the data much better and resulted in substantially more differentiated factors. We then tested measurement invariance with a 13-model ESEM taxonomy. Results justified using the Spanish version of the PSDQ to carry out cross-cultural comparisons in sport and exercise psychology research. Overall, the study can stimulate research on physical self-concept across countries and foster better cross-cultural comparisons.

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Nicholas D. Myers, Deborah L. Feltz, Félix Guillén and Lori Dithurbide

The purpose of this multistudy report was to develop, and then to provide initial validity evidence for measures derived from, the Referee Self-Efficacy Scale. Data were collected from referees (N = 1609) in the United States (n = 978) and Spain (n = 631). In Study 1 (n = 512), a single-group exploratory structural equation model provided evidence for four factors: game knowledge, decision making, pressure, and communication. In Study 2 (n = 1153), multiple-group confirmatory factor analytic models provided evidence for partial factorial invariance by country, level of competition, team gender, and sport refereed. In Study 3 (n = 456), potential sources of referee self-efficacy information combined to account for a moderate or large amount of variance in each dimension of referee self-efficacy with years of referee experience, highest level refereed, physical/mental preparation, and environmental comfort, each exerting at least two statistically significant direct effects.

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Simon Mark Payne, Joanne Hudson, Sally Akehurst and Nikos Ntoumanis

Impression motivation is an important individual difference variable that has been under-researched in sport psychology, partly due to having no appropriate measure. This study was conducted to design a measure of impression motivation in team-sport athletes. Construct validity checks decreased the initial pool of items, factor analysis (n = 310) revealed the structure of the newly developed scale, and exploratory structural equation modeling procedures (n = 406) resulted in a modified scale that retained theoretical integrity and psychometric parsimony. This process produced a 15-item, 4-factor model; the Impression Motivation in Sport Questionnaire–Team (IMSQ-T) is forwarded as a valid measure of the respondent’s dispositional strength of motivation to use self-presentation in striving for four distinct interpersonal objectives: self-development, social identity development, avoidance of negative outcomes, and avoidance of damaging impressions. The availability of this measure has contributed to theoretical development, will facilitate research, and offers a tool for use in applied settings.

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Collin A. Webster, Diana Mîndrilă, Chanta Moore, Gregory Stewart, Karie Orendorff and Sally Taunton

variable by computing the item response means and SD s. Exploratory Structural Equation Modeling Although DOIT is an established theory, it has not been applied to the investigation of physical education teachers’ adoption of CSPAPs. Therefore, exploration of the factor structure constituted an important

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Daniel Milton, Paul R. Appleton, Anna Bryant and Joan L. Duda

draws from AGT and SDT to capture empowering and disempowering motivational climates. An initial study by Appleton et al. ( 2016 ) suggested that Exploratory Structural Equation Model (ESEM; compared with confirmatory factor analysis [CFA]) solutions of the EDMCQ multidimensional, higher-order structure

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Valérian Cece, Noémie Lienhart, Virginie Nicaise, Emma Guillet-Descas and Guillaume Martinent

, and other models have been proposed to overcome these limitations (bifactor, exploratory structural equation modeling [ESEM], and bifactor-ESEM [Bi-ESEM]). Bifactor models, ESEM, and Bi-ESEM are well-suited to address self-determination theory (SDT; Deci & Ryan, 2000 )-based research questions

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Mark Eys, Mark R. Beauchamp, Michael Godfrey, Kim Dawson, Todd M. Loughead and Robert J. Schinke

items and engage in several content validity exercises to yield a manageable first version of the survey. Second, we test the factor structure of the survey using exploratory structural equation modeling (ESEM) with responses from a sample of athletes from a wide variety of sports and levels. Finally

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Collin A. Webster, Diana Mindrila, Chanta Moore, Gregory Stewart, Karie Orendorff and Sally Taunton

. Exploratory factor analysis Exploratory factor analysis within the exploratory structural equation modeling framework ( Marsh, Morin, Parker, & Kaur, 2014 ) with mean and variance adjusted weighted least squares estimation was used to examine the DSI and “School Support” latent variables. The exploratory