Joint moderating role of resilience and hope on the stress–burnout relationship in elite athletes: implications for burnout prevention

Abstract

Objective

Although resilience and hope have each been linked to reduced burnout risk, no studies have examined their joint moderating role on the stress–burnout relationship in elite athletes. This study addresses this gap using the framework of the cognitive-affective model of athletic burnout.

Methods

A total of 756 elite athletes completed surveys using the Perceived Stress Scale, Athlete Burnout Questionnaire, Connor–Davidson Resilience Scale, and Trait Hope Scale. Data were processed and analyzed using SPSS 27.0 and AMOS 27.0.

Results

Using hierarchical linear regression and controlling for gender and age, the study found that stress contributed to an escalation in athlete burnout (β = 0.537, p < 0.001). The interaction between stress and resilience significantly weakened the positive relationship between stress and burnout (β = -0.086, p < 0.01), as did the interaction between stress and hope (β = -0.070, p < 0.01). Additionally, resilience and hope jointly moderated the stress–burnout relationship (β = -0.060, p < 0.01).

Conclusions

Overall, perceived stress was associated with a higher risk of burnout among elite athletes. Resilience and hope are crucial protective factors that can help mitigate the negative impact of stress on burnout. However, the cross-sectional nature of the data precludes causal inference among the observed variables. Future research should expand on existing theories and empirical evidence by using longitudinal samples to investigate causal relationships.

Introduction

Athlete burnout is a temporary physical and mental stress response experienced by athletes; it occurs when situational demands significantly exceed an athlete’s available resources [1]. Athlete burnout, a symptom of physical and mental dysfunction, is mainly characterized by emotional and physical exhaustion, a reduced sense of achievement, and devaluation [1, 2]. Evidence indicates that long-term training and competition lead to notable changes in athletes’ physical and mental well-being, and such exposure may subject athletes to various stressors stemming from biological, psychological, and social factors; these stressors can arise from training intensity, injuries, social pressures, fear of failure, coach-athlete relationships, cyberbullying, and family conflicts [3, 4]. The cumulative effect of these stresses significantly increases the likelihood of burnout [5].

According to the cognitive-affective model of athletic burnout proposed by Smith [6], burnout is conceptualized as a stress response. Its development is closely linked to an individual’s cognitive, emotional, physiological, and behavioral responses when encountering stressful situations. This process consists of four main stages. The first stage begins with the athlete’s perception of situational demands, such as intense training and external pressures, which may exceed their personal resources and coping abilities, resulting in burnout. In the second stage, athletes assess the demands of the situation to determine whether they can handle the challenge. If athletes perceive these demands as threatening and feel unable to cope, burnout may progress to the third stage. This stage is marked by maladaptive psychological and physiological reactions, including anxiety, tension, insomnia, and weakened immune function. Finally, in the fourth stage, these psychological and physiological reactions manifest at the behavioral level, resulting in decreased motivation, reduced performance, and ultimately withdrawal from sports [7]. Burnout is a dynamic process influenced by various factors, including cognitive appraisal, psychological and physiological reactions, and behavioral coping. Stress plays a central role in driving this process.

Multiple studies have validated the effectiveness of cognitive-affective model of athletic burnout in explaining the stress–burnout relationship. For example, a cross-sectional study of 453 Spanish athletes by De Francisco, et al. [8] revealed that perceived stress was a reliable predictor of burnout, with higher levels of perceived stress increasing the likelihood of experiencing burnout. Gustafsson, et al. [9] conducted interviews with 10 Swedish athletes who had quit sports due to burnout, and the results indicated that psychological stressors, such as overtraining, lack of recovery, and high expectations, were leading causes. Similarly, Cresswell and Eklund [10] conducted interviews with 15 New Zealand athletes. They discovered that pressure to comply with demands, pressure to perform, and external expectations were all antecedents of athletes experiencing burnout. These findings suggest that stress plays an important role in athlete burnout.

Although previous research has provided evidence supporting the stress–burnout relationship, not all athletes experience significant burnout. Some athletes are more sensitive in stressful situations, making their psychological states and behavioral patterns more susceptible to stress. Conversely, others can actively utilize their physical and mental resources to effectively cope with stress, thereby displaying lower levels of burnout. Empirical research on sport-related stress explains this phenomenon by suggesting that resilient athletes can better cope with and overcome adversity and stress in competitive sports [3, 11–14].

Resilience refers to an athlete’s ability to evaluate and regulate their thoughts, feelings, and behaviors during sport-related adversity [15]. It stimulates athlete’s potential, invigorates their emotions, and improves their health [16]. The resilience meta-model suggests that specific psychological resources can buffer the negative impact of stressors on athletes’ physical and mental well-being. These resources act as filters and buffers during the experience of stressors [16, 17]. For example, a cross-sectional study of 506 young athletes by Wu, et al. [18] confirmed that those with higher levels of resilience reported lower levels of perceived stressors and burnout. Furthermore, as resilience levels increased, the likelihood of stressors contributing to burnout decreased. By contrast, athletes with lower resilience were more likely to quit sports and experience more severe burnout. Similarly, a cross-sectional study of 372 young athletes by Wagstaff, et al. [19] also supported this finding. The study indicated that resilience was a salient individual-difference variable that acts as a buffer against potential negative outcomes [20].

While resilience primarily buffers stress through enhanced adaptive coping, hope functions by maintaining goal-directed motivation during the stress-coping process. Hope involves individuals engaging in a cognitive process during goal attainment. This process includes setting a meaningful and clear goal, generating motivation and strategies based on the goal, and ultimately achieving the goal successfully [21]. Hope consists of two key components: agency, which involves goal-directed determination, and pathways, which involves planning ways to achieve those goals. Agency encompasses the determination and motivation an individual applies to achieve their goals. In contrast, the pathway relates to individual’s perceived ability to generate and implement effective strategies to achieve their goals. According to the hope theory [22], individuals with high hope levels, who exhibit strong agency and pathways thinking in the stress-coping process, tend to view stressors as challenges and take proactive actions to address them, making them less likely to experience the negative impact of stress and less prone to burnout [23, 24]. The relationship between hope and burnout has been examined in only three studies. A recent cross-sectional study of 483 active Chinese athletes confirmed that higher levels of hope hope help athletes maintain agency and pathway thinking, which assists them to proactively address and alleviate psychological distress in the face of adversity and stress, thereby reducing the manifestation of burnout [25]. The two remaining studies reported a significant negative correlations between hope and all dimensions of burnout; athletes with higher levels of hope also reported lower levels of stress and burnout [24, 26].

The evidence above suggests that athletes experience different adversities and stressors during their careers. Burnout may not be readily apparent in some athletes due to their resilience and hope, which help them adapt to and cope with challenges. According to the resources and perception model, psychological resources regulate individual’s subjective perception of stressors or threats through interaction, thereby facilitating effective coping, with a degree of substitutability existing among these resources [27]. Empirical research on sport-stress shows that the interactions among psychological factors can affect how athletes respond to stress in difficult situations [11, 13]. While resilience and hope have each been linked to reduced burnout risk, no studies to date have examined their joint moderating role on the stress–burnout relationship in elite athletes. The lack of such research limits our understanding of athletes’ psychological states and behavioral patterns. Based on the suggestion of Smith, et al. [28], this study extends prior research by examining not only the individual moderating role of resilience and hope but also their joint moderating role on the stress–burnout relationship, thereby providing a more comprehensive investigation of athletes’ stress-coping mechanisms. Based on preceding arguments, hypotheses 1–4 were developed. Since significant differences exist in athlete burnout levels across gender [29] and age [30], these variables were controlled for in the analysis. The proposed hypothesized model is presented in Fig. 1.

Fig. 1.

Proposed hypothesized model

• H1: Perceived stress significantly positively predicts athlete burnout.

• H2: Resilience moderates the stress–burnout relationship.

• H3: Hope moderates the stress–burnout relationship.

• H4: Resilience and hope jointly moderate the stress–burnout relationship, as evidenced by a significant three-way interaction (Stress × Resilience × Hope).

Methods

Participants and procedure

A priori power analysis was conducted using G*Power 3.1 to determine the minimum sample size required for the planned hierarchical linear regression analyses. The results indicated a minimum required sample size of 166 participants to achieve adequate statistical power. To minimize potential interference caused by training- or competition-related stress, all questionnaires were completed before athletes’ training sessions. Only athletes who were engaged in regular training and free from injury—as confirmed through brief consultations with the athletes and their coaches—were included in this study.

Using cluster sampling, elite athletes were recruited from professional sports teams and universities in Beijing, Jiangsu, Sichuan, Chongqing, and Jiangxi. Elite athletes were defined as individuals who compete at a national or international level of performance in their respective sports [31]. A total of 829 questionnaires were distributed. After excluding invalid responses, 756 valid questionnaires were retained, resulting in an effective response rate of 91.2%. The sample included 399 male (52.8%) and 357 female athletes (47.2%). The mean age of the athletes was 20.06 years, with an average training duration of 7.63 years. Informed consent was obtained from all participants prior to participation. Ethical approval was obtained from the Institutional Review Board of the School of Physical Education, Southwest University (ethical Approval Number: SWU20180601). All procedures involving human participants were conducted in accordance with the Declaration of Helsinki.

Instrument development

To ensure linguistic and conceptual equivalence with the original English instruments, this study followed a standardized translation and back-translation procedure. First, two bilingual experts independently translated the instruments into Chinese. Then, a professional translator back-translated the instruments into English to verify semantic equivalence and cultural appropriateness. The translated instruments demonstrated good reliability, validity and model fit indices. Detailed psychometric properties are presented in Table 1.

Table 1.

Psychometric properties of the measurement instruments

Instrument	Reliability, validity and model fit indices
	Cronbach’s α	Factor loadings	CR	AVE	χ2/df	RMSEA	SRMR	CFI	NFI	IFI	GFI
1. PSS	0.82	0.45–0.80	0.931	0.515	4.491	0.068	0.057	0.953	0.941	0.953	0.957
2. ABQ	0.93	0.41–0.91	0.932	0.526	4.559	0.069	0.04	0.979	0.973	0.979	0.967
3. CD-RISC	0.97	0.73–0.86	0.976	0.632	4.769	0.071	0.023	0.948	0.935	0.948	0.897
4. THS	0.92	0.62–0.87	0.929	0.622	3.934	0.062	0.016	0.989	0.985	0.989	0.980

Note: PSS Perceived Stress Scale, ABQ Athlete Burnout Questionnaire, CD-RISC Connor–Davidson Resilience Scale, THS Trait Hope Scale, CR Composite Reliability, AVE Average Variance Extracted

Perceived stress scale

The Perceived Stress Scale (PSS), developed by Cohen, et al. [32], was used to assess perceived stress across two dimensions: tension and loss of control. The PSS comprises 14 items, with items 4, 5, 6, 7, 9, 10, and 13 reverse scored. Responses were rated on a 5-point Likert scale, where 1 indicates “almost never” and 5 indicates “almost always.” Higher score reflects a greater level of perceived stress. The PSS has been validated as reliable and valid across multiple previous studies involving Chinese samples (e.g., Huang, et al. [33]). During validity and reliability testing in this study, item 12 (“How often have you found yourself thinking about things that you have to accomplish?”) was excluded due to a factor loading below 0.4.

Athlete burnout questionnaire

The Athlete Burnout Questionnaire (ABQ), developed by Raedeke and Smith [34], was used to assess athlete burnout across three dimensions: emotional and physical exhaustion, reduced sense of achievement, and devaluation. The ABQ comprises 15 items, with items 1 and 14 reverse scored. Responses were rated on a 5-point Likert scale, where 1 indicates “almost never” and 5 indicates “almost always.” Higher score reflects a greater level of athlete burnout. The ABQ has been validated as reliable and valid across multiple previous studies involving Chinese samples (e.g., Liu, et al. [35]). During validity and reliability testing in this study, items 1 (“I am accomplishing many worthwhile things in sport”) and 14 (“I feel successful at sport”) were excluded due to factor loadings below 0.4.

Connor–Davidson resilience scale

The Connor–Davidson Resilience Scale (CD-RISC), developed by Connor and Davidson [36], was used to assess resilience across five dimensions: personal competence, stress reaction, positive adaptation, perceived control, and spiritual influence. The CD-RISC comprises 25 items rated on a 5-point Likert scale, with 0 representing “not true at all” and 4 representing “true nearly all of the time.” Higher score reflects a greater level of resilience in the athlete. Permission to use the CD-RISC was obtained from the copyright holder. The CD-RISC has been validated as reliable and valid across multiple previous studies involving Chinese samples (e.g., Wu, et al. [37]). During the validity and reliability testing in this study, item 20 (“Have to act on a hunch”) was excluded due to a factor loading below 0.4.

Trait hope scale

The Trait Hope Scale (THS), developed by Snyder, et al. [21], was used to assess hope across two dimensions: agency and pathways. The THS comprises 12 items, with items 3, 5, 7, and 11 serving as filler items. Responses were rated on a 5-point Likert scale, where 1 signifies “definitely false” and 5 signifies “definitely true.” Higher score reflects a greater level of hope in the athlete. The THS has been validated as reliable and valid across multiple previous studies involving Chinese samples (e.g., Chen, et al. [38]).

Statistical analysis

To provide a robust foundation for testing interaction effects, hierarchical linear regression was used to establish the unique and incremental contributions of resilience and hope in predicting athlete burnout. The same method was used to examine the individual and joint moderating role of resilience and hope in the stress–burnout relationship. Hierarchical linear regression was preferred over other methods (e.g., PROCESS macro) because it enabled clear delineation of the unique explanatory contribution of each added interaction term, thereby directly mapping onto the hypothesized moderation sequence. Predictor variables were standardized prior to calculating two-way and three-way interaction terms to reduce multicollinearity. Simple slope analyses were conducted when interaction terms significantly predicted the dependent variable. A significance level of 0.05 was used for all statistical analyses. Data were processed and analyzed using SPSS 27.0 and AMOS 27.0.

Results

Common method bias test

Common method bias was mitigated by ensuring anonymity and confidentiality, and by employing standardized measurement procedures during data collection. An exploratory factor analysis using Harman’s single-factor test revealed that eight principal components had eigenvalues exceeding 1. The first principal component explained only 31.154% of the total variance, which is below the commonly accepted threshold of 40%. Notably, reliance on Harman’s single-factor test provides only limited evidence, given its well-documented lack of sensitivity. Although procedural controls were implemented during data collection, these results should be interpreted with caution.

Descriptive statistics and correlation matrix of the research variables

The means, standard deviations, and correlation coefficients of the research variables are presented in Table 2. Gender was significantly negatively correlated with resilience. Perceived stress was significantly positively correlated with athlete burnout but significantly negatively correlated with resilience and hope. Athlete burnout was significantly negatively correlated with resilience and hope. Resilience was significantly positively correlated with hope. All correlation coefficients were significant at levels ranging from p < 0.01 to p < 0.001.

Table 2.

Descriptive statistics and correlation matrix of athlete variables (N = 756)

Variable	M	SD	1	2	3	4	5	6
1. Gender	0.49	0.50	1.00
2. Age	20.06	2.19	-0.07	1.00
3. Perceived stress	2.76	0.53	-0.01	-0.06	1.00
4. Athlete burnout	2.59	0.76	0.06	0.02	0.53***	1.00
5. Resilience	2.99	0.53	-0.18***	0.02	-0.56***	-0.49***	1.00
6. Hope	3.73	0.82	-0.05	0.03	-0.62***	-0.44***	0.69***	1.00

Note: * p < 0.05, ** p < 0.01, *** p < 0.001, all values are rounded to two decimal places

Hierarchical linear regression analysis

The results of the hierarchical linear regression analysis regarding incremental contributions of resilience and hope are presented in Table 3. The maximum variance inflation factor (VIF) value in each model was below the critical threshold of 5, indicating no serious multicollinearity. The hierarchical linear regression results from Models 3 and 4 indicated that controlling for gender, age, and perceived stress, both resilience (β = -0.104, p < 0.01) and hope (β = -0.176, p < 0.001) served as independent predictors of athlete burnout. However, when both variables were included in Model 5, the independent effect of resilience was no longer significant (β = -0.023, p > 0.05), whereas hope remained a strong predictor (β = -0.163, p < 0.001). This pattern suggests that the impact of resilience and hope on burnout prevention is not merely additive but interdependent; that is, the protective effect of one resource may be contingent upon the level of the other. This evidence provides conceptual justification for examining the joint moderating role of resilience and hope in the stress–burnout relationship.

Table 3.

Hierarchical linear regression analysis predicting athlete burnout: incremental contributions of resilience and hope

Variable	Dependent variable: Athlete burnout (standardized β)
	Model 1	Model 2	Model 3	Model 4	Model 5
Control variable
Gender	-0.038	-0.030	-0.043	-0.041	-0.043
Age	0.028	0.062*	0.059	0.059	0.059
Independent variable
Perceived stress		0.537***	0.479***	0.428***	0.423***
Predictor
Resilience			-0.104**		-0.023
Hope				-0.176***	-0.163***
Model statistics
R 2	0.002	0.290	0.297	0.309	0.309
ΔR 2	0.002	0.288	0.295	0.307	0.307
F	0.892	102.326***	79.367***	83.802***	67.030***
VIF (Maximum)	1.004	1.008	1.481	1.647	2.268

Note: *p < 0.05, **p < 0.01, ***p < 0.001, all values are rounded to three decimal places. Model 1 included control variables only (gender, age). Model 2 included the main effect of perceived stress. Model 3 added resilience to Model 2 to test its incremental contribution. Model 4 added hope to Model 2 to test its incremental contribution. Model 5 added both resilience and hope to Model 2 to test their combined incremental contribution

The results of the hierarchical linear regression analysis regarding individual and joint moderating role of resilience and hope are presented in Table 4. The hierarchical linear regression results for the main effect indicated that controlling for gender and age, perceived stress significantly positively predicted athlete burnout (β = 0.537, p < 0.001), confirming H1. The hierarchical linear regression results for the individual moderating role indicated that perceived stress continued to significantly positively predict athlete burnout after inclusion of the mediators (resilience: β = 0.495, p < 0.001; hope: β = 0.440, p < 0.001). The interaction between stress and resilience significantly weakened the positive relationship between stress and burnout (β = -0.086, p < 0.01), as did the interaction between stress and hope (β = -0.070, p < 0.01), confirming H2 and H3. The corresponding simple slope tests are presented in Fig. 2. The results indicated that the strength of the positive association between perceived stress and athlete burnout gradually diminished as resilience increased, although the effect size remained significant (from β = 0.581, p < 0.001 to β = 0.408, p < 0.001). Similarly, the strength of the positive association between perceived stress and athlete burnout gradually diminished as hope increased, although the effect size remained significant (from β = 0.510, p < 0.001 to β = 0.370, p < 0.001). The hierarchical linear regression results for the joint moderating role indicated that the three-way interaction among perceived stress, resilience, and hope significantly predicted athlete burnout (β = -0.060, p < 0.01), confirming H4. The corresponding simple slope tests are presented in Fig. 3. The results indicated that the weakest positive association between perceived stress and burnout was found among athletes with high levels of resilience and hope. In contrast, the strongest positive association was found among athletes with low levels of resilience and hope. Athletes with low resilience and high hope exhibited a weaker positive association between perceived stress and burnout than athletes with high resilience and low hope.

Table 4.

Hierarchical linear regression analysis predicting athlete burnout: individual and joint moderating role of resilience and hope

Variable	Dependent variable: Athlete burnout (standardized β)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Control variable
Gender	-0.038	-0.030	-0.032	-0.031	-0.019	-0.027
Age	0.028	0.062*	0.060*	0.062*	0.066*	0.050*
Independent variable
Perceived stress		0.537***	0.495***	0.440***	0.528***	0.389***
Moderator
Resilience			-0.095*
Hope				-0.144***
Two-way interaction
Perceived stress × Resilience			-0.086**		0.003
Perceived stress × Hope				-0.070**	-0.124*
Resilience × Hope						-0.089**
Three-way interaction
Perceived stress × Resilience × Hope						-0.060**
Model statistics
R 2	0.002	0.290	0.306	0.316	0.304	0.306
ΔR 2	0.002	0.288	0.304	0.314	0.302	0.304
F	0.892	102.326***	66.289***	69.293***	65.598***	66.049***
VIF (Maximum)	1.004	1.008	1.492	1.777	2.268	2.791

Note: *p < 0.05, **p < 0.01, ***p < 0.001, all values are rounded to three decimal places. Model 1 included control variables only (gender, age). Model 2 included the main effect of perceived stress. Model 3 included resilience as an individual moderator. Model 4 included hope as an individual moderator. Model 5 included the two-way interaction (Stress × Resilience and Stress × Hope). Model 6 included the three-way interaction (Stress × Resilience × Hope)

Fig. 2.

Individual moderating role of resilience and hope on the stress–burnout relationship

Fig. 3.

Joint moderating role of resilience and hope on the stress–burnout relationship

Discussion

From the theoretical standpoint of the cognitive-affective model of athletic burnout, the present study employed hierarchical linear regression to examine the joint moderating role of resilience and hope on the stress–burnout relationship. Perceived stress had a direct impact on athlete burnout, and both the individual and joint effects of resilience and hope moderated this relationship. These findings have important theoretical and practical implications for understanding of the stress–burnout relationship and for using positive psychological resources to prevent and address athlete burnout.

As suggested by Smith, et al. [28], a individual moderation method has certain limitations in explaining the complexity of athletes’ psychological states and behavioral patterns and may overlook the influence of other moderators in this process. Therefore, utilizing a joint moderation method to investigate the impact of resilience and hope on the stress–burnout relationship helps clarify their interactive mechanisms and inform the development of psychological intervention strategies. This is especially important for enhancing athletes’ physical and mental well-being. This study supported a positive association between stress and burnout [8–10, 30, 39–41], as well as negative association between resilience and stress-induced maladaptive outcomes [18–20, 42–46], and between hope and stress-induced maladaptive outcomes [24–26, 47].

This study first established the unique and incremental contributions of resilience and hope in explaining athlete burnout beyond perceived stress. This foundational finding supports the theoretical premise that resilience and hope are distinct yet potent psychological resources, each contributing independently to burnout prevention. However, when their combined incremental contribution was examined, the protective effects were not merely additive, suggesting the presence of a more complex, interdependent relationship between them. Building on this, the present study further demonstrated that resilience and hope jointly moderated the stress–burnout relationship, superseding their individual moderation. This finding aligns with the resilience meta-model and hope theory, indicating that positive psychological resources can protect athletes from the negative impact of stressors and reduce the risk of burnout [16, 22]. Notably, the emergence of the significant three-way interaction (Stress × Resilience × Hope) in the final model, accompanied by the non-significance of the individual Stress × Resilience interaction, suggests that the protective effect of resilience depends on the level of hope (and vice-versa). This supports the core argument that joint moderation supersedes simple individual moderation in this model. Previous research consistently indicates that resilience reduces stress-related burnout [42, 48–50], perceived pain [51], suicidal ideation [52], depression, and anxiety [53, 54], whereas hope reduces stress-related depression and anxiety [55–57]. According to the literature, athletes with high levels of resilience and hope tend to view stressors as challenges and opportunities for development. This mindset can motivate athletes adapt to and cope with stressful situations, thereby reducing the risk of burnout [18, 19, 22]. Interestingly, athletes with low resilience and high hope exhibited a weaker positive association between perceived stress and burnout than those with high resilience and low hope. This pattern suggests that hope—particularly its agency component—may partially compensate for limited resilience, whereas high resilience without goal-directed motivation (hope) may be insufficient to buffer burnout under chronic stress. For athletes exposed to multiple stressors, effectively utilizing positive psychological resources to optimize stress-coping mechanisms is particularly crucial. The findings expand current insights into the role of resilience and hope in athletes’ stress management.

To apply these findings in sports practice, sports organizations and relevant departments are encouraged to implement target specific psychological intervention (e.g., hope-building programs such as goal mapping or resilience training through stress-inoculation protocols) to develop athletes’ positive psychological resources. Although some interventions such as stress management interventions [58, 59] and cognitive-behavioral therapies [60, 61], show promise for developing resilience and hope, their applicability and effectiveness in athlete populations require further investigation. Drawing from theories of stress inoculation [62], it has been suggested that moderate exposure to adversity can help individuals cope with and overcome future stressful situations more effectively. Therefore, interventions that enhance resilience and hope in moderately stressful contexts may yield better outcomes. Athletes can gradually accumulate experience and build confidence by simulating and adapting to competitive pressure, enabling them to effectively mobilize positive psychological resources in future stressful situations. When developing intervention strategies, strengthening resilience and hope may reduce stress-induced maladaptive outcomes. For example, protective factors of resilience, including positive personality, motivation, confidence, focus, and social support, help athletes adapt more effectively to stress, reduce its negative impact on physical and mental well-being, and promote positive recovery and growth in sports-related adversity [11].

Limitations and future directions

The findings of this study have several limitations. First, the selection of variables in this study was based on the resilience meta-model and hope theory. However, situational factors that could influence the stress–burnout relationship were considered. This suggests that the interplay between individual and situational factors may shape the stress–burnout relationship. Future research should explore the impact of situational factors on the relationship between stress and athletes’ maladaptive psychological states and behavioral patterns to provide a more comprehensive analysis of athletes’ stress-coping mechanisms. Second, although this study identified relationships between stress, burnout, resilience, and hope, these relationships were observed in cross-sectional samples, making it challenging to determine causal relationships between the variables. Future research should build on existing theories and empirical evidence by using longitudinal samples to investigate causal relationships—especially since burnout is often conceptualized as a longitudinal process. Third, all variables were measured using self-report instruments, which may not fully capture athletes’ true psychological states and behavioral patterns. Although self-report instruments are common in large-scale survey research, future studies could integrate ecological momentary assessment to capture dynamic fluctuations in stress and burnout. More importantly, future research should incorporate certain physiological indicators (e.g., heart rate variability, cortisol levels) to capture athletes’ stress-coping processes more accurately. For instance, monitoring such indicators can objectively quantify autonomic nervous system activity and hypothalamic-pituitary-adrenal axis responses during the stress-coping process. This approach provides biological validation for self-reported stress and burnout, facilitating a more comprehensive examination of the stress–burnout relationship. Finally, the generalizability and applicability of the findings may be constrained by the use of a primarily Chinese sample and by potential restricted score variability (e.g., ceiling/floor effects) common among elite athletes. Future research should further explore the stress–burnout relationship through cross-disciplinary and cross-population comparisons to understand how it varies across different cultural contexts and population characteristics.

Conclusions

Perceived stress was associated with a higher risk of burnout among elite athletes. At the same time, resilience and hope serve as crucial protective factors that can help mitigate the negative impact of stress on burnout. These findings have important theoretical and practical implications for understanding the stress–burnout relationship and using positive psychological resources to prevent and address athlete burnout.

Abbreviations

PSS

Perceived Stress Scale

ABQ

Athlete Burnout Questionnaire

CD-RISC

Connor–Davidson Resilience Scale

THS

Trait Hope Scale

Authors’ contributions

Z.Y.M and S.L conceived and designed the research. Z.Y.M, C.Y.C, and S.L conducted the data collection. Z.Y.M, H.C.J, and C.F.L conducted the data analysis. Z.Y.M and C.Y.C drafted the manuscript. H.C.J, C.F.L, and T.F.W reviewed and revised the manuscript. All authors have contributed to the manuscript and approved the submitted version.

Funding

This work was funded by the National Social Science Fund of China (project 24BTY098).

Data availability

Data and materials in this work will be made available on request.

Declarations

Ethics approval and consent to participate

Ethical approval was obtained from the Institutional Review Board of the College of Physical Education of Southwest University (ethical approval number: SWU20180601). All procedures conducted in this work involving human participants adhered to the Declaration of Helsinki. Informed consent was obtained from all participants included in this work.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.