Psychometric Properties of Online Versions of Mental Toughness Questionnaires in Basketball Players


DOI: https://doi.org/10.15308/Sinteza-2023-251-258
Authors:
Petar Šešlija
Nenad Trunić
Srđan Marković
Jovana Popović
Miloš Milošević

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Keywords:
Online platforms, Online questionnaires, SMTQ, PPI-A, MTI


Abstract:
The aim of this study was to examine the psychometric properties of using the online version of the questionnaires for assessing mental toughness to gather and analyse the data in scientific research. It was assumed that, with the right introduction, written explanation, and usage of available IT solutions the results will have good psychometric properties. The sample of 79 male athletes that played basketball in a 2022/2023 season, filed online version of the Sports Mental Toughness Questionnaire (SMTQ), the Psychological Performance Inventory - A (PPI–A), and Mental Toughness Inventory (MTI). Results of descriptive analyses showed that good metric characteristics and discriminativeness of all three instruments. Reliability was also confirmed with obtained Cronbach's alpha coefficient scores. Obtained low to high significant positive correlations among all scales and subscales confirmed construct validity of online versions of all three questionnaires for assessing MT. It was concluded that further research of this way of using of measuring instruments is needed but also justify.

CITATION:

IEEE format

P. Šešlija, N. Trunić, S. Marković, J. Popović, M. Milošević, “Psychometric Properties of Online Versions of Mental Toughness Questionnaires in Basketball Players,” in Sinteza 2023 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2023, pp. 251-258. doi:10.15308/Sinteza-2023-251-258

APA format

Šešlija, P., Trunić, N., Marković, S., Popović, J., Milošević, M. (2023). Psychometric Properties of Online Versions of Mental Toughness Questionnaires in Basketball Players. Paper presented at Sinteza 2023 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2023-251-258

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