The Adult-Oriented Sport Coaching Survey: An Instrument Designed to Assess Coaching Behaviors Tailored to Adult Athletes

2020 ◽  
Vol 42 (5) ◽  
pp. 368-385
Author(s):  
Scott Rathwell ◽  
Bradley W. Young ◽  
Bettina Callary ◽  
Derrik Motz ◽  
Matt D. Hoffmann ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Root Mean Square ◽  
Structural Equation ◽  
Equation Modeling ◽  
Mean Square ◽  
Root Mean Square Residual ◽  
Confirmatory Factor ◽  
Masters Athletes ◽  
Fit Index

Adult sportspersons (Masters athletes, aged 35 years and older) have unique coaching preferences. No existing resources provide coaches with feedback on their craft with Masters athletes. Three studies evaluated an Adult-Oriented Coaching Survey. Study 1 vetted the face validity of 50 survey items with 12 Masters coaches. Results supported the validity of 48 items. In Study 2, 383 Masters coaches completed the survey of 50 items. Confirmatory factor analysis and exploratory structural equation modeling indicated issues with model fit. Post hoc modifications improved fit, resulting in a 22-item, five-factor model. In Study 3, 467 Masters athletes responded to these 22 items reflecting perceptions of their coaches. Confirmatory factor analysis (comparative fit index = .951, standardized root mean square residual = .036, and root mean square error of approximation = .049) and exploratory structural equation modeling (comparative fit index = .977, standardized root mean square residual = .019, and root mean square error of approximation = .041) confirmed the model. The resultant Adult-Oriented Sport Coaching Survey provides a reliable and factorially valid instrument for measuring adult-oriented coaching practices.

scholarly journals Erfassung der Emotionsregulation bei Jugendlichen anhand des „Affective Style Questionnaire – Youth (ASQ-Y)“

Diagnostica ◽  
2019 ◽  
Vol 65 (1) ◽  
pp. 49-59
Author(s):  
Johannes Graser ◽  
Christiane Heimlich ◽  
Augustin Kelava ◽  
Stefan G. Hofmann ◽  
Ulrich Stangier ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Root Mean Square Error ◽  
Root Mean Square ◽  
Structural Equation ◽  
Equation Modeling ◽  
Mean Square ◽  
Affective Style ◽  
Root Mean Square Residual ◽  
Fit Index ◽  
Tucker Lewis Index

Zusammenfassung. Zur Erfassung der 3 Emotionsregulationsstrategien Unterdrücken, Anpassen / Neubewerten und Akzeptieren wurde der Affective Style Questionnaire für Jugendliche (ASQ-Y) adaptiert und an einer entsprechenden Stichprobe (N = 1 092) validiert. Die Dimensionalität des englischen Originalfragebogens und der deutschen Version für Erwachsene konnte auch für Jugendliche bestätigt werden. Während der Analyse kam das ESEM-Verfahren (Exploratory Structural Equation Modeling) zum Einsatz, die Kennwerte bewegten sich im akzeptablen bis sehr guten Bereich. Der Comparative Fit Index (CFI) erreichte einen akzeptablen Wert von .938, ebenso der Tucker–Lewis Index (TLI) mit einem Wert von .911. Der Root Mean Square Error of Approximation (RMSEA) lag bei einem sehr guten Wert von .050, das Standardized Root Mean Square Residual (SRMR) erreichte einen guten Wert von .030. Die internen Konsistenzen der 3 Skalen (Unterdrücken: α = .77; Anpassen / Neubewerten: α = .76; Akzeptieren: α = .76) erreichten (vergleichbar mit dem englischen Original und der deutschen Erwachsenenstichprobe) zufriedenstellende Werte. Die Subskalen zeigten hypothesenkonforme diskriminante und konvergente Zusammenhänge mit etablierten Verfahren des Forschungsbereichs Emotionsregulation, was für die Konstruktvalidität spricht. Insgesamt ist der ASQ-Y als Messinstrument zur Erfassung von verschiedenen Emotionsregulationsstrategien bei Jugendlichen geeignet und ökonomisch in seiner Anwendung. Der ASQ-Y kann in der Allgemeinbevölkerung und in der Prävention eingesetzt werden. Nach entsprechender Validierung ist der Einsatz auch im klinischen Setting möglich.

scholarly journals The eating motivations scale (EATMOT): Development and validation by means of confirmatory factor analysis (CFA) and structural equation modelling (SEM)

2020 ◽  
Vol 60 (1) ◽  
pp. 4-9
Author(s):  
P. F. Guiné Raquel ◽  
João Duarte ◽  
Ana Cristina Ferrão ◽  
Manuela Ferreira ◽  
Paula Correia ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Root Mean Square ◽  
Structural Equation Modelling ◽  
Food Choice ◽  
Structural Equation ◽  
Mean Square ◽  
Root Mean Square Residual ◽  
Equation Modelling ◽  
Confirmatory Factor

AbstractIntroductionThe objective was to develop and validate an instrument that measures different determinants of people’s food choices and simultaneously accounts for a variety of factors: health, emotions, price and availability, society and culture, environment and politics, and marketing and advertising.MethodsThis is a cross-sectional study focusing on food choice determinants. It was carried out in 16 countries in 2017 and 2018. This study included 11,960 volunteer adult participants from different countries. The data was validated using Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM).ResultsValidation using CFA with SEM revealed that multi-factor modelling produced first- and second-order models that could be used to define the EATMOT scale, the first presenting better fitting indices, with the goodness-of-fit and comparative-fit indices very close to 1, as well as root-mean-square-error-of-approximation, root-mean-square-residual and standardised-root-mean-square-residual at practically zero.ConclusionThe validated EATMOT scale guarantees confidence in the information obtained through this instrument, and can be used in future studies to better understand food choice determinants in different geographical areas and help plan strategies to improve healthy eating patterns and diminish the burden of non-communicable diseases.

scholarly journals Modeling and Analysis of the Motivations of Fast Fashion Consumers in Relation to Innovativeness

2016 ◽  
Vol 16 (4) ◽  
pp. 205-213
Author(s):  
Canan Saricam ◽  
Nazan Erdumlu
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Motivational Factors ◽  
Equation Modeling ◽  
Fast Fashion ◽  
Modeling And Analysis ◽  
Confirmatory Factor ◽  
The Relationship

Abstract In this study, fast fashion concept is investigated in order to understand the motivations of the consumers that make them adopt these products because of their willingness for the innovativeness. The relationship between the motivational factors which were named as “Social or status image” and “Uniqueness” as expressions of individuality, “Conformity” and the willingness for “Innovativeness” is analyzed using a conceptual model. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling were used to analyze and validate the model. The data used for the study was obtained from 244 people living in Turkey. The findings showed that the motivational factors “Social or status image” and “Uniqueness” as expressions of individuality are influential on the consumers’ willingness for “Innovativeness”.

Correlation of Reverse Logistics Performance to Solutions Using Structural Equation Modeling

2019 ◽  
Vol 18 (04) ◽  
pp. 511-525
Author(s):  
Pornwasin Sirisawat ◽  
Tossapol Kiatcharoenpol
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Reverse Logistics ◽  
Empirical Data ◽  
Sustainable Management ◽  
Structural Equation ◽  
Electronics Industry ◽  
Equation Modeling ◽  
Proposed Model ◽  
Confirmatory Factor

Nowadays, reverse logistics (RL) is one of the key strategies in many industries, especially in the electronics industry due to increasing environmental awareness and sustainable management. The main aim of this research is to investigate the correlation of RL performance to solutions for RL practice of the electronics industry in Thailand. In this research, questionnaires were distributed to 417 companies in the electronics industry of Thailand. A conceptual model was developed and the model examined by using structural equation modeling (SEM). Both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used in this study. The hypotheses were tested in which RL performance was directly positively associated with the overall solutions for RL practices. RL performance was also indirectly positively associated with management & organization solutions, legal & technology solutions and collaboration and support solutions of the various solutions for RL practices. Empirical data was tested by using SEM and it was found that the proposed model could fit with the empirical data. The proposed results of this study will help to understand more about RL practices and could provide further direction for researchers and practitioners in the electronics industry and other related industries.

Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review

2006 ◽  
Vol 99 (6) ◽  
pp. 323-338 ◽  
Author(s):  
James B. Schreiber ◽  
Amaury Nora ◽  
Frances K. Stage ◽  
Elizabeth A. Barlow ◽  
Jamie King
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Equation Modeling ◽  
Confirmatory Factor

Investigating the Structure of the Pediatric Symptoms Checklist in the Preschool Setting

2016 ◽  
Vol 35 (5) ◽  
pp. 494-505 ◽  
Author(s):  
Christine DiStefano ◽  
Jin Liu ◽  
Yin Burgess
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Short Form ◽  
School Setting ◽  
Equation Modeling ◽  
Confirmatory Factor ◽  
Psychological Instruments ◽  
Preschool Setting

When using educational/psychological instruments, psychometric investigations should be conducted before adopting to new environments to ensure that an instrument measures the same constructs. Exploratory structural equation modeling and confirmatory factor analysis methods were used to examine the utility of the short form of the Pediatric Symptoms Checklist (PSC-17) in the school setting. Using a sample of 836 preschool children rated by teachers, three factors were identified across both techniques, with factors matching the hypothesized structure of the instrument. The PSC-17 may be an option for use in preschool settings when conducting behavioral and emotional screening.

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