Psychometric Properties of the RESTQ-Sport-36 in a Collegiate Student-Athlete Population.

Stacy L Gnacinski,Barbara B Meyer,Carly A Wahl

doi:10.3389/fpsyg.2021.671919

Abstract

The purpose of the current study was to examine the reliability and validity of the RESTQ-Sport-36 for use in the collegiate student-athlete population. A total of 494 collegiate student-athletes competing in National Collegiate Athletic Association Division I, II, or III sanctioned sport completed the RESTQ-Sport-36 and Brief Profile of Mood States (POMS). Structural equation modeling (SEM) procedures were used to compare first order to hierarchical model structures. Results of a confirmatory factor analysis (χ2[528] = 1129.941, p < 0.001; SRMR = 0.050; CFI = 0.929) and exploratory structural equation modeling analysis (χ2[264] = 575.424, p < 0.001; SRMR = 0.013; CFI = 0.963) indicated that the first order 12-factor structure demonstrated the best fit of all models tested. Support was not observed for the fit of any hierarchical model. Moderate to strong correlations were observed between stress and recovery subscales and mood states, thus supporting the construct validity of the abbreviated RESTQ measurement model. The current findings provide support for the measure’s use in this population and give pause as it relates to the scoring and interpretation of hierarchical factors such as Total Stress and Total Recovery. Overall, the current results indicate that the RESTQ-Sport-36 may be a useful tool for collegiate student-athlete training load and competition monitoring.

Highlights

The contemporary sport performance literature highlights the benefit of incorporating psychological surveys within elite athlete training load monitoring and management protocols (Saw et al, 2016; Schwellnus et al, 2016; Soligard et al, 2016; Bourdon et al, 2017)
Measurement model parsimony was observed in Model 1 (χ2[528] = 1129.941, p < 0.001; SRMR = 0.050; CFI = 0.929), indicating that the first order 12-factor structure is the best fitting model of the three models tested
This finding was further reinforced by the exploratory structural equation modeling (ESEM) model test (χ2[264] = 575.424, p < 0.001; SRMR = 0.013; CFI = 0.963), which demonstrated improvements in the SRMR and CFI parameters beyond those which were observed in the confirmatory factor analysis (CFA) procedure for Model 1

Summary

Introduction

The contemporary sport performance literature highlights the benefit of incorporating psychological surveys within elite athlete training load monitoring and management protocols (Saw et al, 2016; Schwellnus et al, 2016; Soligard et al, 2016; Bourdon et al, 2017). Among other measures like the Profile of Mood States (POMS), the Recovery Stress Questionnaire for Athletes (RESTQ-Sport, Kallus and Kellmann, 2016) is one of the most frequently used measures for monitoring elite athlete responses to training load (Saw et al, 2016; Kellmann et al, 2018). Concurrent with the widespread popularity of the original 76-item RESTQ-Sport measure among researchers, the authors developed a shortened 52-item version. Due to the growing practical concerns regarding the psychometric properties, measure length, scoring procedures, and translational utility of 76-item RESTQ-Sport data to inform interventions aimed at overtraining prevention (Taylor et al, 2012; Saw et al, 2015), the authors recently developed a further abbreviated 36item version called the RESTQ-Sport-36 (Kallus and Kellmann, 2016). To the extent of the authors’ knowledge, no examinations of hierarchical models were conducted in this initial validation

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