Testing the Psychometric Properties and Measurement Invariance of the Perceived Motivational Climate in Sport Questionnaire (PMCSQ-2): Online Assessment
Pérez-Romero, Nuria; Reigal, Rafael E.; Franquelo, María Auxiliadora; Balaguer, Isabel; Falco, Coral; Hernández-Mendo, Antonio; Morales-Sánchez, Verónica
Peer reviewed, Journal article
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Date
2022Metadata
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Abstract
Athletes’ perception of competence and success can be influenced by the motivational climate created by the coach. The Perceived Motivational Climate in Sport Questionnaire (PMCSQ-2) assesses this. Although its reliability and validity have been analyzed in previous studies, this has never been done for the online version. This type of evaluation can be beneficial for data collection, sustainability, speed, and generating larger samples. Therefore, the aim of this study is to analyze the psychometric properties of the PMCSQ-2 in its online version. The sample consisted of 1637 participants (37.8% men and 62.2% women) from 18 to 68 years of age (M = 24.39, SD = 6.51) who practiced physical-sport activities regularly. A second-order confirmatory factor analysis (CFA) model and its invariance for gender were studied from a 24-item version obtained from the MenPas 1.0 platform. The analyses provided an adequate fit for the CFA (CFI = 0.91, TLI = 0.90, RMSEA = 0.07, SRMR = 0.07, df = 224, B-S p = 0.02–0.07) when an alternative model was realized (χ2 = 1858.89, χ2/df = 8.30), as they also did for the women (χ2 = 1356.90, χ2/df = 6.06), men (χ2 = 883.58, χ2/df = 3.95) individual sports (χ2 = 1153.55, χ2/df = 5.15), and team sports (χ2 = 1008.92, χ2/df = 4.05) items. The data were also suitable for invariance analysis. Similarly, appropriate values were obtained for convergent and discriminant validity and for composite reliability. Therefore, the results obtained show appropriate psychometric properties for the online version of the PMCSQ-2 using an alternative model, suggesting that its use is suitable for research and showing the importance of the subscales.
Keywords: motivation; data collection; digital questionnaire; subscales; sustainable assessment