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Article

Preliminary Latvian RESTQ-76 for Athletes: A Tool for Recovery–Stress Monitoring and Health Promotion

by
Behnam Boobani
1,*,
Juris Grants
1,
Žermēna Vazne
2,
Katrina Volgemute
2,
Aleksandrs Astafičevs
1,
Rihards Leja
1,
Daido Dagne Brūvere
1,
Renars Licis
1,
Sergejs Saulite
1 and
Artur Litwiniuk
3
1
RSU Latvian Academy of Sport Education, Riga Stradins University, LV-1006 Riga, Latvia
2
Department of Health Psychology and Pedagogy, Riga Stradins University, LV-1007 Riga, Latvia
3
Faculty of Physical Education and Health, Jozef Pilsudski University of Physical Education in Warsaw, 21-500 Biala Podlaska, Poland
*
Author to whom correspondence should be addressed.
Sci 2026, 8(1), 6; https://doi.org/10.3390/sci8010006 (registering DOI)
Submission received: 20 October 2025 / Revised: 23 December 2025 / Accepted: 30 December 2025 / Published: 4 January 2026
(This article belongs to the Special Issue Enhancing Health Through Physical Activity and Sports Science: Advances in Applied Research)
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Abstract

This study aims to report the first Latvian version of the RESTQ-76, focusing on its internal validity, reliability, structural validity, and the relationships between the factors of the questionnaire. A total of 394 athletes (225 men and 169 women), aged 18–30 years (average age = 21, SD = 1.65), participated in the study. They were recruited from various sports clubs and universities. The RESTQ-76 was translated into Latvian through a forward-backward translation process to ensure accuracy of cultural relevance. To examine the questionnaire’s structure, principal component analysis (PCA) was performed. This analysis revealed a stable four-factor model comprising 18 scales, with acceptable fit indices (RMSEA = 0.089, CFI = 0.914, TLI = 0.896, NFI = 0.889), indicating good model fit. The psychometric validity of the Latvian version is supported by the original, indicating it is appropriate for use in sports settings throughout Latvia. As research on training load and recovery continues to expand, tools like the RESTQ-76 are becoming increasingly important. They help athletes and coaches monitor recovery and stress levels, which is essential for optimizing performance and preventing overtraining in competitive sports.

1. Introduction

Recovery is a core element of athletic training and plays a vital function in sports to adapt and return to balance after exertion [1]. It is a process that unfolds both within individuals and between them and can span short or extended timeframes depending on various factors [1]. In high-level sports, where physical and mental demands are intense, it is essential to plan training loads and recovery phases wisely [2]. When training intensity increases, athletes often experience heightened physical strain and psychological stress [3]. Combined with competitive pressure, self-evaluation, inadequate recovery, and environmental influences, these stressors can lead to fatigue, reduced performance, and even overtraining [4].
To prevent these outcomes, it is crucial to emphasize recovery and promote strategies that help athletes manage stress and monitor their recovery status effectively [5,6]. This monitoring can involve tracking physiological signals, psychological states, biochemical markers, and immune responses [7]. However, collecting such data daily is often impractical, as many of these methods are invasive, expensive, and time-consuming [8].
Recent developments in sport performance research, along with updated consensus statements from the International Olympic Committee (IOC), emphasize the value of integrating psychological assessments into athlete-monitoring and training-management systems [9,10,11]. In alignment with these IOC guidelines, a growing number of studies have outlined best practices for self-report tools in athletic contexts [12]. One such tool is the Recovery Stress Questionnaire (RESTQ-Sport) [13,14,15], which assesses athletes’ perceived stress and recovery. Researchers widely endorse this instrument for its usefulness in tracking training-related changes both in research and practical settings [1,4,12,16,17,18,19]. Additionally, the RESTQ-Sport has shown promise in identifying risks of illness or injury [20] and in assessing performance outcomes [21].
The RESTQ is available in three formats—76, 52, and 36 items—each designed to assess how frequently athletes experience stress symptoms and engage in recovery-related behaviors over the past three days and nights [14]. In this study, all references to the RESTQ refer to the 76-item version, which has been translated into numerous languages [13,14,15,19,22,23,24,25,26,27,28,29] and applied across a wide range of sports disciplines and environments [3,6,7,17,21,27,28,29,30,31,32,33,34,35,36,37]. Effective recovery helps offset stress, promotes physiological adaptation, and enables athletes to maintain consistent training. In contrast, insufficient recovery can lead to accumulated stress, increasing the risk of adverse health and performance outcomes [38]. Research indicates that individuals and athletes in Latvia report elevated levels of psychophysiological and cognitive stress [39,40,41,42]. These stress levels tend to rise during competitive events and preparation phases, driven by the pressure to succeed. This heightened stress response can contribute to overtraining if not properly monitored. Without appropriate recovery strategies, athletes may experience a decline in performance and overall well-being [41]. Poor athletic performance can result not only from insufficient training but also from overtraining, which increases stress when recovery is inadequate. In Latvian sports psychology, there is a clear lack of culturally adapted tools to assess psychological aspects accurately [39,41]. Since Latvian is the national language, a localized version of the RESTQ is needed to support athletes and professionals. This highlights the importance of translating and adapting the RESTQ-76 for use within the Latvian sports community.
Many coaches lack a clear understanding of what the recovery phase entails and how it connects to the overall recovery process. This knowledge gap can lead to disrupted or insufficient recovery, often reflected in irregular patterns or overly brief rest periods. In some cases, recovery may be compromised even when optimal conditions are provided, especially if external factors, such as emotionally charged interactions between coach and athlete, interfere with the capability to recover. As such, the trainer’s behavior is essential to shape and help the athlete during and after stressful situations [43].
Research suggests that self-report tools are more responsive to training-related changes than physiological, biochemical, or immunological indicators [44]. As a result, they are widely favored in practical athlete monitoring [45]. Developing a valid and reliable Latvian-language instrument to assess stress and recovery is a key step toward enabling consistent monitoring throughout training and competition. Such a questionnaire would offer a practical means of identifying early signs of overtraining and burnout in athletes [43]. To ensure accurate assessment, it is important to have instruments that are psychometrically sound, valid, and reliable. In light of this, this study aims to report the first Latvian version of the RESTQ-76, focusing on its internal validity, reliability, structural validity, and the relationships between the factors of the questionnaire.

2. Materials and Methods

2.1. Participants

Participants were recruited by email, word of mouth, and direct invitations. Eligibility criteria included being an active athlete and being at least 18 years old. No additional restrictions were applied, as the study aimed to validate a cross-cultural instrument. Large sample sizes are essential for psychological validation studies to ensure population representativeness [46]. Therefore, recruitment targeted diversity in gender, age, and sport disciplines. Broad usage across various sports was also considered important for validating the RESTQ-Sport [13]. The final sample consisted of 394 athletes aged 18–30 years (M = 21, SD = 1.65), including 225 males (57.1%) and 169 females (42.9%). All participants were regularly engaged in sports, training at least three times per week for a minimum of 1.5 h per session. Athletes came from 34 different disciplines, including football (n = 70), basketball (n = 61), martial arts (n = 50), handball (n = 48), athletics (n = 41), volleyball (n = 30), fitness (n = 16), sport dance (n = 9), cycling (n = 8), floorball (n = 8), swimming (n = 7), skiing (n = 6), hockey (n = 6), kayaking (n = 5), and others (n = 29).

2.2. The Instrument

The RESTQ by Kellmann and Kallus [13] is grounded in a biopsychological framework. It consists of 76 items, including one introductory item (item 1), based on a 7-point Likert scale from 0 (never) to 6 (always). It assesses the frequency of stress-related and recovery-related experiences over the past three days and nights. Items are phrased as statements such as: “In the past three days/nights, I laughed.” The RESTQ-76 is structured into 19 subscales grouped under four main factors. These include General Stress (GS): general Stress (GS), emotional Stress (ES), social stress (SS), conflicts/pressure (C/P), fatigue (F), lack of energy (LE), and physical complaints (PC); General Recovery (GR): success (S), social recovery (SR), physical recovery (PR), general well-being (GWB), and sleep quality (SQ); Sport-Specific Stress (SS): disturbed breaks (DB), emotional exhaustion (EE), and injury (I); Sport-Specific Recovery (SSR): being in shape (BS), personal accomplishment (PA), self-efficacy (SE), and self-regulation (Self-R). Twelve subscales (GS and GR) are general, while seven (SS and SSR) are sport-specific. Each subscale includes four items.

2.3. Translation and Cross-Cultural Adaptation Process of REST Q-76

The RESTQ-S-76 was translated into Latvian according to the manual guidelines [15] and adhered to the translation process outlined by [47,48] for both forward and back translation. After obtaining the author’s permission to adapt the RESTQ, there were several steps (Figure 1). Three native Latvian speakers were selected for translation and adaptation. The Latvian translations underwent a thorough review by experts (n = 5) to evaluate their linguistic clarity, conceptual correspondence, and alignment with the source questionnaire. The primary version of the Latvian RESTQ was pre-tested with eleven athletes. Participants were instructed to complete the questionnaire and provide feedback on the clarity of individual items as well as the overall structure of the instrument. No changes were considered necessary. Following the initial revisions, the Latvian version was independently back-translated into English by three translators. These back-translated versions were subsequently compared with the original English items to verify that the content and intent of each item were preserved. A panel of experts reviewed the forward and back translations for linguistic accuracy and cultural relevance. The Latvian RESTQ-S-76 was then pilot-tested with 100 athletes, showing acceptable internal consistency (Cronbach’s α = 0.70–0.81). No items need to be modified. The research team considered the questionnaire translation complete at this stage.

2.4. Data Collection Procedures and Ethical Considerations

Data were collected using online (Microsoft Forms) and paper questionnaires. Researchers briefed participants via coaches and lecturers, and implied consent was given upon completion. The survey (10–15 min) included the RESTQ-S-76 and demographic questions. Of the 400 distributed, 394 were fully completed. Data collection occurred from November 2024 to May 2025. Participation was voluntary, anonymous, and approved by the Latvian Academy of Sport Education Ethics Committee (Protocol No. 9/3, 31 May 2024), following the Declaration of Helsinki. All participants were adults, provided informed consent, and could withdraw at any time. Data were anonymized, securely stored, and analyzed using statistical procedures consistent with the original version [13,14,15]. The adequacy of the sample size was evaluated using G*Power 3.1.9.6, with a significance level of 5% (α = 0.05) and a statistical power of 80% (β = 0.20).

2.5. Statistical Procedures

Statistical analyses followed established guidelines and the original RESTQ protocol to ensure valid adaptation for Latvian athletes. Descriptive statistics (M, SD, skewness, kurtosis) were computed, with values within ±2 considered acceptable for parametric analyses [49]. Principal component analysis (PCA) with varimax rotation was conducted on all 76 items, retaining factors with eigenvalues ≥1.0 [15]. Model fit was assessed using RMSEA (≤0.08), CFI, GFI, TLI, NFI (≥0.90), and AGFI (≥0.85) [50,51]. Factor structure was further validated via SEM; bootstrapping addressed non-normality, providing robust estimates and confidence intervals. Reliability was evaluated using Cronbach’s α (>0.70), composite reliability (CR > 0.70), and average variance extracted (AVE ≥ 0.50, acceptable if CR > 0.70) [15,52]. Temporal stability was assessed with ICC (≥0.70) [53]. Analyses were performed using SPSS v.26, JASP v.0.18.3, and AMOS v.29.

3. Results

3.1. Distribution of the RESTQ Scales

Descriptive statistics for the 19 RESTQ scales showed mean scores ranging from 6.15 (Emotional Exhaustion, EE) to 12.82 (Being in Shape, BS), with standard deviations ranging from 3.90 to 4.96. Skewness values ranged from 0.03 (Social Recovery, SR) to 0.67 (Physical Complaints, PC), while kurtosis values varied from −0.51 (SR) to 0.31 (Lack of Energy, LE). All subscales exhibited skewness and kurtosis within ±2, supporting normality assumptions (Table 1). Cronbach’s alpha indicated satisfactory to strong internal consistency across the scales (α = 0.70).

3.2. Factor Analysis and Structural Model

Two separate factor analyses were conducted for the general and sport-specific components, following the original development procedures [13,14,15] (Table S1). Although exploratory factor analysis (EFA) is more appropriate for a validation study, the principal component analysis reported in the original RESTQ-76 versions, with varimax rotation, was used. PCA confirmed the two-factor structure—general recovery (GR) and general Stress (GS)—as reported in the original versions [13,14,15]. In the general module, sampling adequacy was supported by a KMO = 0.91 and Bartlett’s test of Sphericity (χ2(1128) = 9935.56, p < 0.001), indicating suitability for factor analysis. Two factors were extracted, with eigenvalues of 13.64 and 4.87, accounting for 38.58% of the total variance. GS items showed loadings ranging from 0.51 to 0.73. GR loading between 0.46 and 0.71. Item 9 (physical recovery) had loadings of 0.33; items 9, 27, 36, and 46 from SQ had lower loadings (0.33, 0.36, 0.20, and 0.22). For sport-specific items, the KMO was 0.89, and Bartlett’s test yielded χ2(378) = 4508.17, p < 0.001. Two factors—sport stress (SS) and sport recovery (SSR)—had eigenvalues of 7.31 and 4.27, accounting for 41.39% of the variance. SS items loadings 0.44–0.68). SR items with loadings ranging from 0.49 to 0.80, except item 53 (0.25).
Scale scores were recalculated after removing items that did not meet the factor loading threshold. The sleep scale was excluded due to low loadings for items 27, 36, and 46, with the latter two falling below 0.25 (Table 2). Items 9 (physical recovery) and 53 (being in shape) had loadings of 0.33 and 0.25, respectively, but were retained. While a loading of 0.40 is commonly used as a cutoff [54], studies with similar designs have accepted thresholds of 0.30 [25] or even 0.25 [13,22]. A second-level factor analysis was conducted using the revised structure, recalculating scales accordingly. This adjustment reduced Cronbach’s alpha for the General Stress factor (excluding sleep) from 0.94 to 0.82—still within acceptable reliability. Following this, Structural Equation Modeling (SEM) was employed to validate the Latvian RESTQ’s factor structure, investigate interrelations among latent constructs, and assess the adequacy of the overall model.
Based on the acceptance thresholds (Table 3), the initial model (M1) did not achieve an adequate fit, as several indices were below the recommended cutoff values (RMSEA = 0.099 > 0.08; GFI = 0.850 < 0.90; CFI = 0.891 < 0.90). To improve model fit, the recommendations of [50,55] were followed by consulting modification indices (MI > 10) and introducing theoretically justified error covariances.
First, we allowed the residuals of ES and SS to covary, as these items reflect closely related interpersonal emotional experiences. This modification (M2) improved the model fit substantially (RMSEA decreased from 0.099 to 0.090; CFI increased from 0.891 to 0.910; χ2/df enhanced from 4.85 to 4.20). Second, the residuals of Fatigue and Physical Complaints are expected to covary, as both items represent somatic manifestations of strain. This adjustment (M3) further improved the fit, with the RMSEA decreasing slightly to 0.089, and incremental fit indices continuing to increase (CFI = 0.914; TLI = 0.896; NFI = 0.889).
Although not all indices reached the “good fit” thresholds, the final model (M3) met most acceptable fit criteria and showed clear improvement over the initial model. M3 was retained as the best-fitting and theoretically justified measurement model for conducting SEM (Figure 2). The Latvian RESTQ identified four latent factors (GS, 7 scales; GR, 4 scales; SS, 3 scales; and SSR, 4 scales) across 18 subscales. Correlation analysis revealed a negative relationship between GS and SSR (r = −0.36), a strong positive link between GS and SS (r = 0.62), and a moderate negative correlation between GS and GR (r = −0.51). GR also showed a weak negative association with SS (r = −0.20), while GR and SSR were highly positively correlated (r = 0.82). Loadings (λ) spanned 0.44–0.93, with most items showing strong associations above 0.70, indicating solid construct validity. For instance, the GS subscale showed a strong loading on the General Stress factor (λ = 0.89), whereas the Injury subscale had a lower loading on Sport Stress (λ = 0.44).

3.3. Reliability Analysis

Cronbach’s alpha indicated strong internal consistency for the Latvian RESTQ factors, ranging from 0.78 (Sport Stress, SS) to 0.94 (General Stress, GS) (Table S1). Composite reliability (CR) exceeded 0.70 for all factors—GS (0.92), Sport-Specific Recovery (SSR, 0.88), General Recovery (GR, 0.83), and SS (0.71)—while AVE values were adequate for GS (0.62), GR (0.55), and SSR (0.66); SS (0.47) was acceptable due to high CR [52]. Test-retest reliability over 10 days (n = 63) showed ICCs ranging from 0.66 to 0.78, with slightly lower values for Conflicts/Pressure (C/P, 0.69), Fatigue (F, 0.66), Lack of Energy (LE, 0.66), Physical Recovery (PR, 0.68), and Disturbed Breaks (DB, 0.69). Overall, these results indicate satisfactory to strong reliability and temporal stability across all constructs.

4. Discussion

This study aims to report the first Latvian version of the RESTQ-76, focusing on its internal validity, reliability, structural validity, and the relationships between the factors of the questionnaire. The cross-cultural translation followed established guidelines [15,47,48], requiring only minor adjustments to the original format. To ensure semantic, conceptual, idiomatic, and psychometric equivalence, the Latvian version underwent thorough validation. The final instrument included 72 items across 18 factors—four items fewer than the original—and was excluded due to factor loadings below <0.40.
Following the fairness principles outlined in [47,48], a rigorous methodology was applied to ensure the questionnaire’s cultural, linguistic, and content accuracy across languages. Despite these efforts, some translation challenges may have gone unnoticed, potentially affecting the adaptation of certain items. The findings confirm the multidimensional structure of the RESTQ-76, capturing both stress and recovery aspects. This two-factor model has been consistently supported in prior research, reinforcing the robustness of the original theoretical framework [13,14,15,26,56]. It also aligns with the holistic approach of the scissors model and previous studies on the interplay between stress and recovery [57]. Including both dimensions offers a well-rounded evaluation of an athlete’s recovery-stress profile.
Following the original RESTQ-76 framework [13,14,15], the study tested a four-factor structural model based on prior empirical evidence and researcher judgment. The factors were grouped into two stress-related sets (GS and SS) and two recovery-related sets (GR and SR). Correlations between GS and SS, and between GR and SR, were strong and positive, consistent with previous findings [25,26,28]. While most relationships in the factor analysis showed strong dependencies, some inconsistencies emerged. Notably, the Injury subscale had a relatively low loading on Sport Stress (λ = 0.44), suggesting it contributes less to that construct. This result aligns with earlier research by [58], which reported a lower loading of 0.23 for the same variables.
The measurement model for the Latvian RESTQ showed acceptable fit across most scales, except for Sleep Quality. Three items (27, 36, and 46) had factor loadings below 0.40, likely due to polarity differences: items 36 and 46 are negatively worded, while the others reflect positive sleep experiences. This inconsistency suggests the need for careful handling in structural modeling. Following common RESTQ validation practices [28], the sleep scale was removed based on high modification indices to improve model fit. Although sleep is vital for recovery and is sensitive to stress and rumination, its measurement remains challenging, as sleep loss can heighten stress reactivity [15]. Despite recurring issues in the General Scales, the overall construct validity of the RESTQ-76 has been supported by Kellmann and Kallus [13], who acknowledge the limitations of the sleep quality subscale. The robust two-factor structure (stress and recovery) and solid sport-specific factor loadings provide a strong foundation for validity. Previous studies have noted similar weaknesses in both the original English and French versions [28,59], often recommending restructuring the subscales. While alternative models have been proposed, few have undergone further empirical testing [59]. The RESTQ-76, comprising 48 general and 28 sport-specific items, reflects over a decade of iterative development and refinement [13].
Adding residual covariances between Emotional Stress and Social Stress, and between Fatigue and Physical Complaints, was theoretically supported and improved model fit [50,55]. These adjustments reflect conceptual overlap—Emotional and Social stress share interpersonal emotional content, while Fatigue and Physical Complaints relate to somatic strain. Similar correlations have been reported in previous RESTQ validations [60]. These modifications did not change the core factor structure but helped account for shared variance, enhancing model accuracy. Fatigue, in particular, remains a complex construct that warrants further research on recovery-stress dynamics [61]. According to [62], sample size affects model estimation, especially when there are many variables or indicators per factor. A recommended sample range of 200–500 was met in this study [63]. As noted by [50], correlated residuals often indicate item redundancy or content overlap. While alternative models may exist, additional studies with larger samples are required to evaluate whether removing certain items is warranted.
Cronbach’s alpha showed acceptable internal consistency across all factors (≥0.70), consistent with the original RESTQ validation [13,22] and other studies [24,27,64]. In fact, reliability scores in this study matched or exceeded those of similar tools [19,23,25,28], reflecting the strong link between stress and recovery factors and the general RESTQ framework. Test-retest reliability over 10 days was adequate for 13 of the 18 scales. Five—Conflicts/Pressure (C/P), Fatigue (F), Lack of Energy (LE), Physical Recovery (PR), and Disturbed Breaks (DB)—fell below the 0.70 threshold, a pattern also noted in prior research [19]. Recent literature highlights limitations of Cronbach’s alpha, especially when its assumptions are violated, leading to biased estimates [65]. McDonald’s omega (ω) is suggested as a more robust alternative. While RESTQ generally shows acceptable reliability, further evaluation is needed. Declines in test-retest scores are expected, given the tool’s focus on short-term stress and recovery (typically over the past 3 days).
Cultural and linguistic factors appear to have minimal impact on the validity of the RESTQ, as studies consistently support its applicability across diverse contexts. While the four-factor model—general stress, general recovery, sport-specific stress, and sport-specific recovery—is not universally confirmed, it remains broadly accepted and aligns with our findings [13,14,15].

Limitations and Practical Applications

Although the study yielded promising results, some limitations should be noted. The use of self-administered questionnaires may have introduced response bias, as participants completed them in groups. To reduce this risk, confidentiality was emphasized, and participants were encouraged to respond honestly and independently. Additionally, future research should include a more diverse sample that encompasses various competitive levels (such as regional, national, and elite) and educational backgrounds. This research marks an initial step in validating the Latvian RESTQ. Although the 72-item version fits the sample well, further studies are needed to confirm external and concurrent validity, especially regarding behavioral outcomes. Future research should consider employing more appropriate methods, such as exploratory factor analysis (EFA), to confirm the component structure. The sleep scale remains problematic and warrants closer examination. Future research could tailor the RESTQ to specific sports and exercise types in Latvia and examine criterion validity (associations with measures of stress, recovery, or performance) and predictive validity (prediction of overtraining outcomes). Longitudinal studies incorporating training load metrics (e.g., volume, sRPE) and performance or health outcomes (e.g., injury incidence) could help explore how athletes manage recovery and stress over time.

5. Conclusions

Based on this study, it can be concluded that the initial Latvian version of the RESTQ for Athletes shows good factorial validity and internal consistency. The Latvian RESTQ could be useful for exercise educators and sports psychologists to assess current recovery and stress levels among the athletes involved in sports, monitor stress–recovery patterns in athletes, and identify whether variations in different subscales or dimensions suggest that the athlete is at risk of overtraining or if their athletic progress is on track. Many theories behind periodization and training load management suggest that positive training adaptations and performance improvements rely on effective recovery periods [66]. As research on training load measurement and prescription continues to grow rapidly, it is clear that recovery strategies and tools like RESTQ are a top priority in sports science. Further adaptation in other languages is needed. Our results endorse the use of the Latvian RESTQ in practical settings.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/sci8010006/s1, Table S1: RESTQ factors (general and specific).

Author Contributions

Conceptualization, B.B., J.G., Ž.V., K.V., A.A., R.L. (Rihards Leja), D.D.B., R.L. (Renars Licis), S.S., and A.L.; methodology, B.B., J.G., Ž.V., K.V., and A.L.; formal analysis and data curation, B.B., J.G., Ž.V., K.V., A.A., R.L. (Rihards Leja), D.D.B., R.L. (Renars Licis), S.S., and A.L.; investigation, B.B.; writing—review and editing, B.B., J.G., Ž.V., K.V., and A.L.; visualization, B.B., J.G., Ž.V., K.V., and A.L.; supervision, B.B., J.G., Ž.V., K.V., and A.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by a Postdoctoral Grant No. RSU/LSPA-PG-2024/1-0002 ‘Recovery strategies to improve the performance of martial arts athletes’, of project No. 5.2.1.1.i.0/2/24/I/CFLA/005 RSU Internal and RSU with LSPA External Consolidation (financed by the European Union’s Recovery and Resilience Mechanism and the budget of the Republic of Latvia).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethical Committee of Riga Stradins University, Latvian Academy of Sport Education (protocol code no. 9/3, approval date: 31 May 2024).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available upon request to the corresponding author.

Acknowledgments

We are thankful to all participants for participating in this study.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
RESTQRecovery stress questionnaire
GSGeneral stress
ESEmotional stress
SSSocial stress
C/PConflicts/pressure
FFatigue
LELack of energy
PCPhysical complaints
GRGeneral recovery
SSuccess
SRSocial recovery
PRPhysical recovery
GWBGeneral well-being
SQSleep quality
SSSport stress
DBDisturbed breaks
EEEmotional exhaustion
IInjury
SSRSport-specific recovery
BSBeing in shape
PAPersonal accomplishment
SESelf-efficacy
Self-RSelf-regulation

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Figure 1. RESTQ-76 translation and validation process.
Figure 1. RESTQ-76 translation and validation process.
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Figure 2. Standardized Parameter Estimates of the RESTQ-Sport Based on Model 3. e: error (residual) term.
Figure 2. Standardized Parameter Estimates of the RESTQ-Sport Based on Model 3. e: error (residual) term.
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Table 1. Descriptive statistics and Internal Consistencies (n = 394).
Table 1. Descriptive statistics and Internal Consistencies (n = 394).
ScalesMSDSKα
1-GS7.544.830.660.050.81
2-ES8.154.140.380.080.79
3-SS8.054.520.530.060.80
4-C/P10.254.420.38−0.190.70
5-F10.324.680.47−0.250.75
6-LE8.654.200.500.310.74
7-PC7.714.230.670.120.73
8-S12.464.110.26−0.070.70
9-SR12.704.700.21−0.510.74
10-PR11.243.900.32−0.030.72
11-GWB12.324.150.18−0.360.78
12-SQ10.974.960.21−0.400.70
13-DB7.164.330.37−0.470.75
14-EE6.154.410.62−0.0090.73
15-I9.844.590.43−0.030.70
16-BS12.824.680.06−0.270.81
17-PA11.244.570.410.120.70
18-SE12.104.660.190.060.82
19-Self-R12.744.680.03−0.210.72
M: mean; SD: standard deviation; S: skewness; K: kurtosis; α: Cronbach alpha. GS: general Stress; ES: emotional Stress; SS: social Stress; C/P: conflicts/pressure; F: fatigue; LE: lack of energy; PC: physical complaints; S: success; SR: social recovery; PR: physical recovery; GWB: general well-being; SQ: sleep quality; DB: disturbed breaks; EE: emotional exhaustion; I: injury (I), BS: being in shape; PA: personal accomplishment; SE: self-efficacy; Self-R: self-regulation.
Table 2. Overview of four factors.
Table 2. Overview of four factors.
Higher-Order FactorAbbreviationSubscales IncludedNumber of SubscalesItems per SubscaleTotal Items
General StressGSGeneral Stress (GS); Emotional Stress (ES); Social Stress (SS); Conflicts/Pressure (C/P); Fatigue (F); Lack of Energy (LE); Physical Complaints (PC)7428
General RecoveryGRSuccess (S); Social Recovery (SR); Physical Recovery (PR); General Well-Being (GWB)4416
Sport-Specific StressSSDisturbed Breaks (DB); Emotional Exhaustion (EE); Injury (I)3412
Sport-Specific RecoverySSRBeing in Shape (BS); Personal Accomplishment (PA); Self-Efficacy (SE); Self-Regulation (Self-R)4416
Table 3. Goodness-of-fit indices for the SEM.
Table 3. Goodness-of-fit indices for the SEM.
Absolute FitIncremental FitParsimonious Fit
ModelModificationRMSEAGFIAGFITLICFINFIχ2/df
M1Initial model0.0990.8500.8010.8710.8910.8674.85
M2M1 + correlated errors of Emotional Stress and Social Stress0.090.8680.8240.8930.9100.8864.20
M3M2 + correlated errors of Fatigue and Physical Complaints0.0890.8720.8270.8960.9140.8894.11
Criterion for goodness of fit≤0.08≥0.90≥0.85≥0.90≥0.90≥0.90<5
RMSEA: root mean square of approximation; GFI: goodness of fit index; AGFI: adjusted goodness of fit index; TLI: Tucker–Lewis index; CFI: comparative fit index; NFI: normed fit index.
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MDPI and ACS Style

Boobani, B.; Grants, J.; Vazne, Ž.; Volgemute, K.; Astafičevs, A.; Leja, R.; Brūvere, D.D.; Licis, R.; Saulite, S.; Litwiniuk, A. Preliminary Latvian RESTQ-76 for Athletes: A Tool for Recovery–Stress Monitoring and Health Promotion. Sci 2026, 8, 6. https://doi.org/10.3390/sci8010006

AMA Style

Boobani B, Grants J, Vazne Ž, Volgemute K, Astafičevs A, Leja R, Brūvere DD, Licis R, Saulite S, Litwiniuk A. Preliminary Latvian RESTQ-76 for Athletes: A Tool for Recovery–Stress Monitoring and Health Promotion. Sci. 2026; 8(1):6. https://doi.org/10.3390/sci8010006

Chicago/Turabian Style

Boobani, Behnam, Juris Grants, Žermēna Vazne, Katrina Volgemute, Aleksandrs Astafičevs, Rihards Leja, Daido Dagne Brūvere, Renars Licis, Sergejs Saulite, and Artur Litwiniuk. 2026. "Preliminary Latvian RESTQ-76 for Athletes: A Tool for Recovery–Stress Monitoring and Health Promotion" Sci 8, no. 1: 6. https://doi.org/10.3390/sci8010006

APA Style

Boobani, B., Grants, J., Vazne, Ž., Volgemute, K., Astafičevs, A., Leja, R., Brūvere, D. D., Licis, R., Saulite, S., & Litwiniuk, A. (2026). Preliminary Latvian RESTQ-76 for Athletes: A Tool for Recovery–Stress Monitoring and Health Promotion. Sci, 8(1), 6. https://doi.org/10.3390/sci8010006

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