Mindfulness Facets, Sport Anxiety, and Psychological Outcomes in Ultra-Trail Runners: A Pre-Competition Study

Mindfulness Facets, Sport Anxiety, and Psychological Outcomes in Ultra-Trail Runners: A Pre-Competition Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mindfulness Facets, Sport Anxiety, and Psychological Outcomes in Ultra-Trail Runners: A Pre-Competition Study Pierrick Laulan, Jérôme Cuadrado, Roberta Antonini Philippe, Ulrike Rimmele This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8649683/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Objectives Ultra-trail runners face sustained psychological demands during pre-competition preparation, yet little is known about factors associated with mental health in this population. Guided by Monitor and Acceptance Theory (MAT) as a heuristic process framework, this study examined associations between mindfulness facets, sport anxiety, and psychological outcomes in ultra-trail runners. Method Participants were 216 ultra-trail runners (86.6% men; M age = 41.3 years, SD = 8.6) assessed 6–8 weeks before a major competition. Measures included the Five Facet Mindfulness Questionnaire, Sport Anxiety Scale-2, Athlete Burnout Questionnaire, Chalder Fatigue Scale, and WHO-5 Well-Being Index. Indirect effects were tested using bootstrapped confidence intervals. Results Non-judging and Acting with Awareness showed consistent negative associations with burnout ( β = − .25 to − .30), fatigue ( β = − .20 to − .24), and positive associations with well-being ( β = .15 to .27). Observing showed null or marginally positive associations with burnout. Sport anxiety showed a statistically significant indirect association in the Non-judging–burnout link (27.8% of the total effect). Notably, parallel mediation models revealed that indirect pathways via cognitive anxiety were substantially stronger (37.1%) than via somatic anxiety (2.0%). Exploratory analyses suggested a small, marginal Observing × Non-judging pattern, whereby Observing was positively associated with burnout only at low levels of Non-judging. Conclusions Acceptance-related mindfulness facets were associated with lower burnout in ultra-trail runners, with statistical indirect associations via cognitive anxiety stronger than via somatic arousal. The cross-sectional design precludes causal inference; however, these associations may help inform hypotheses for future longitudinal and intervention studies examining whether acceptance-focused mindfulness training and cognitive decentering reduce pre-competition cognitive anxiety and burnout risk in ultra-endurance athletes. mindfulness ultra-trail running athlete burnout sport anxiety cognitive anxiety Monitor and Acceptance Theory Figures Figure 1 Background Ultra-trail running and other ultra-endurance events impose sustained physiological and psychological demands that extend over months of preparation and hours of competition. Beyond the physiological strain of prolonged training, ultra-endurance runners face cumulative psychosocial demands arising from high training volumes, occupational responsibilities, relationship pressures, and the inherent challenges of balancing elite sport pursuits with daily life (Niering et al., 2024 ; Thuany et al., 2023 ). Recent work has underscored that mental health concerns in ultra-endurance populations may be more prevalent than previously assumed, with some athletes reporting elevated levels of stress, mood disturbances, and psychological fatigue in the lead-up to major competitions (Gameiro et al., 2023 ; Roebuck et al., 2018 ). Athlete burnout has emerged as a central construct in understanding psychological maladjustment in sport. In ultra-endurance contexts, prolonged exposure to high training loads, performance pressure, and limited recovery windows may render athletes particularly vulnerable to burnout symptoms (Gucciardi et al., 2021 ). Burnout is typically conceptualized as a cognitive-affective syndrome characterized by emotional and physical exhaustion, a reduced sense of athletic accomplishment, and sport devaluation (Gustafsson et al., 2017 ; Raedeke & Smith, 2001 ). Smith's (1986) cognitive-affective stress model posits that burnout develops through a transactional process in which chronic stressors interact with cognitive appraisals and coping resources, ultimately leading to maladaptive outcomes when demands consistently exceed perceived resources. Complementary accounts also frame athlete burnout within self-determination theory (SDT), emphasizing that satisfaction of basic psychological needs (autonomy, competence, relatedness) supports more self-determined motivation and is associated with lower burnout, whereas more controlled forms of motivation are linked to higher burnout risk (Lonsdale et al., 2009 ). SDT research further highlights that need-thwarting interpersonal climates can undermine well-being and contribute to maladaptive outcomes in sport (Bartholomew et al., 2011 ). In parallel, work integrating motivational regulation and training strain suggests that symptoms of overtraining and less self-determined motivation are independently associated with burnout indicators (Lemyre et al., 2007 ). Together, these frameworks underscore that burnout is shaped by both chronic demands and the motivational–social context in which athletes pursue their sport. Alongside burnout, fatigue has emerged as a distinct yet related concern in high-performance sport. Fatigue in athletic populations encompasses both mental and physical dimensions: mental fatigue refers to a psychobiological state induced by prolonged cognitive effort, characterized by subjective tiredness and impaired cognitive performance (Van Cutsem et al., 2017 ), whereas physical or general fatigue reflects broader perceptions of exhaustion related to training load and recovery status (Chalder et al., 1993 ). Importantly, experimental and longitudinal work demonstrates that fatigue impairs endurance performance, decision-making, and motivation, making it a critical variable to monitor during intensive training periods (Russell et al., 2019 ; Wu et al., 2024 ). In ultra-trail runners, accumulated fatigue in the weeks preceding a major event may compromise both performance readiness and psychological well-being. The final mesocycles before a target competition represent a particularly salient window for psychological assessment. This period typically involves peak training loads followed by a taper phase designed to optimize physiological readiness while allowing accumulated fatigue to dissipate (Le Meur et al., 2012 ; Mujika & Padilla, 2003 ). However, psychological research suggests that this period may paradoxically heighten vulnerability to negative psychological states: anticipatory anxiety about the upcoming event, uncertainty regarding fitness and preparation, and the accumulated psychological cost of months of demanding training may converge to increase risk for burnout symptoms, elevated fatigue, and compromised well-being (Bali, 2015 ; Raglin & Morris, 1994 ). Despite its theoretical importance, relatively little empirical work has systematically examined psychological functioning in ultra-trail runners during this critical pre-competition window. One promising factor in this context is trait mindfulness. Dispositional mindfulness refers to an inherent capacity to attend to present-moment experience with openness, curiosity, and non-judgment (Kabat-Zinn, 2003 ). In sport psychology, mindfulness-based interventions have shown beneficial effects on performance, anxiety reduction, and psychological well-being across various athletic populations (Bühlmayer et al., 2017 ; Noetel et al., 2019 ; Sappington & Longshore, 2015 ). In long-distance running specifically, mindfulness-based programs such as Mindful Sport Performance Enhancement (MSPE) have been examined in runners (De Petrillo et al., 2009 ) and synthesized in a dedicated systematic review (Corbally et al., 2020 ) and a narrative review (Laulan et al., 2026). A systematic review and meta-analysis focusing specifically on athlete burnout further indicates that mindfulness is negatively associated with burnout, while emphasizing that intervention evidence remains comparatively limited and heterogeneous (Li et al., 2019 ). However, most research has treated mindfulness as a unitary construct, potentially obscuring differential associations between specific mindfulness facets and psychological outcomes. The Monitor and Acceptance Theory (MAT; Lindsay & Creswell, 2017 ) provides a useful framework for understanding how different components of mindfulness may relate to psychological adjustment. MAT proposes that mindfulness comprises two partially dissociable processes: attention monitoring, i.e. the capacity to observe and track ongoing experience, and acceptance, i.e. an orientation of openness and non-judgment toward that experience. Importantly, MAT proposes that enhancing attention monitoring in the absence of acceptance skills can actually amplify distress, because greater awareness of negative internal states is not accompanied by the regulatory resources needed to process them adaptively. Conversely, when attention monitoring is coupled with an attitude of acceptance, characterized by openness and non-judgment toward experience, MAT predicts reduced elaborative processing of aversive experiences and, in turn, lower negative emotional reactivity (Lindsay & Creswell, 2017 ; Simione & Saldarini, 2023 ). Although MAT was originally articulated to specify putative mechanisms of mindfulness training, it has also been used as a process framework to interpret individual differences in trait mindfulness in cross-sectional work (see Burić et al., 2024 ; Simione et al., 2021 ). The Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., 2006 ) operationalizes trait mindfulness through five empirically derived facets: Observing (noticing internal and external stimuli), Describing (labeling experiences with words), Acting with Awareness (attending to present activities rather than operating on autopilot), Non-judging (refraining from evaluative responses to thoughts and feelings), and Non-reactivity (allowing thoughts and feelings to come and go without becoming entangled in them). The FFMQ was originally developed by factor-analysing items pooled from five existing mindfulness questionnaires, which yielded these partially overlapping but distinguishable components of dispositional mindfulness (Baer et al., 2006 ). Subsequent work has supported the five-facet structure and its construct validity in both meditating and non-meditating samples, reinforcing the use of the FFMQ as the dominant multidimensional measure of trait mindfulness (Baer et al., 2008 ). Within a MAT-informed perspective, the Observing facet is typically taken as an index of attention monitoring, whereas Non-judging and Non-reactivity capture acceptance processes (Lindsay & Creswell, 2017 ; Simione & Saldarini, 2023 ). However, the operational mapping of FFMQ facets onto MAT processes, particularly for Observing, has been debated in the trait literature (Simione & Saldarini, 2023 ). Consistent with this concern, Baer et al. ( 2008 ) reported that the relationships between Observing and indices of psychological adjustment varied as a function of meditation experience. Moreover, in endurance contexts, attentional monitoring of task-relevant internal (and external) cues has been described as central to pacing regulation and coping with sustained strain (Brick et al., 2014 ; Vitali et al., 2019 ). Acting with Awareness reflects the capacity to remain attentive to present activities rather than operating on “autopilot” and has shown consistent associations with lower psychological symptoms and higher well-being, suggesting a role in adaptive self-regulation that may be particularly relevant during demanding training periods (Baer et al., 2006 , 2008 ). Describing occupies a more intermediate position: the ability to label internal experiences with words can simultaneously enhance monitoring (by increasing awareness and differentiation of internal states) and support regulatory processing (by facilitating more reflective engagement with emotions; Baer et al., 2006 ; Desrosiers et al., 2013 ). Examining all five facets simultaneously therefore allows for a comprehensive examination of MAT-consistent predictions about monitoring and acceptance, while avoiding the inferential limitations that arise when only a subset of facets is analysed (Lindsay & Creswell, 2017 ; Simione & Saldarini, 2023 ). A key question concerns the pathways through which mindfulness facets relate to psychological outcomes in athletes. Sport anxiety is typically conceptualized as a tendency to perceive competitive situations as threatening and to respond with apprehension, worry, and physiological arousal (Amaro et al., 2023; Martens et al., 1990 ; Smith et al., 2006 ). The Sport Anxiety Scale-2 (SAS-2; Smith et al., 2006 ) assesses this construct by distinguishing between cognitive anxiety (worry and concentration disruption) and somatic anxiety (physiological symptoms), both of which have been linked to impaired performance and reduced well-being in competitive sport (Grossbard et al., 2009 ). Distinguishing between these anxiety components may reveal which specific processes account for the mindfulness-burnout relationship. If acceptance facets primarily reduce ruminative worry rather than physiological arousal, stronger indirect effects through cognitive anxiety would be expected. From a MAT perspective, acceptance-related facets such as Non-judging and Non-reactivity are thought to buffer affective reactivity to stressors (Lindsay & Creswell, 2017 ). Consistent with this view, these facets show robust negative associations with worry, rumination, and anxiety symptoms in non-sport samples (Desrosiers et al., 2013 , 2014 ). Given that chronic stress and negative affect are key antecedents of athlete burnout (Goodger et al., 2007 ; Gustafsson et al., 2017 ), it is plausible that acceptance-related mindfulness may protect against burnout and fatigue by dampening anxious reactivity to competitive demands. Individual differences in sex and training experience may further influence these associations. Research consistently indicates that female athletes report higher levels of sport anxiety than male athletes (Correia & Rosado, 2019 ; Howle et al., 2022 ), suggesting that sex should be controlled when examining anxiety-related pathways. Training volume and competitive experience represent additional relevant factors: more experienced athletes may have developed adaptive coping strategies that buffer against anxiety and burnout, although some evidence suggests that prolonged exposure to high training demands may conversely increase burnout risk through accumulated strain (Gustafsson et al., 2011 ). Understanding how mindfulness facets relate to outcomes across different levels of training experience can inform targeted intervention development. Despite converging theoretical rationale, no study has comprehensively examined the associations between all five FFMQ facets, sport anxiety, and multiple psychological outcomes in ultra-trail runners during the pre-competition period. In ultra-endurance, existing work has concentrated mainly on performance-related psychological characteristics, particularly mental toughness and resilience (Roebuck et al., 2018 ; Méndez-Alonso et al., 2021 ; Gameiro et al., 2023 ). By contrast, large-scale studies on athlete mental health have predominantly focused on team sports and Olympic disciplines, with ultra-endurance athletes largely absent from major reviews and consensus statements (Rice et al., 2016 ; Reardon et al., 2019 ; but see also Thuany et al., 2023 ). Using MAT (Lindsay & Creswell, 2017 ) as a heuristic process framework, the present study had four aims. First, we sought to characterize levels of burnout, fatigue, sport anxiety, and psychological well-being in a sample of ultra-trail runners assessed approximately six to eight weeks before a major competition, thereby extending emerging work on mental health in ultra-endurance athletes to this under-studied preparatory window. Second, we examined whether specific mindfulness facets, particularly those reflecting acceptance (Non-judging, Non-reactivity) and present-moment attention (Acting with Awareness), would show stronger negative associations with adverse psychological outcomes than facets primarily reflecting monitoring (Observing). Third, we tested whether sport anxiety would account for the associations between mindfulness facets and outcomes, with particular attention to the differential roles of cognitive versus somatic anxiety components. Fourth, we examined sex differences in sport anxiety and controlled for training characteristics in all analyses. Hypotheses Based on MAT (Lindsay & Creswell, 2017 ) and prior work on mindfulness facets and athlete mental health, we formulated the following a priori hypotheses. H1 (confirmatory). Acceptance-related facets (Non-judging, Non-reactivity) and Acting with Awareness were expected to show the strongest associations with psychological adjustment: they should relate to lower burnout and fatigue and higher well-being, over and above demographic and training variables (Baer et al., 2008 ; Desrosiers et al., 2013 ; Goodger et al., 2007 ; Gustafsson et al., 2017 ). H2 (confirmatory). Because Observing is commonly used as a proxy for attention monitoring in trait mindfulness research (although this operational mapping remains debated), and MAT predicts that monitoring is beneficial primarily when combined with acceptance (Lindsay & Creswell, 2017 ; Simione & Saldarini, 2023 ), we expected Observing to show weaker or null associations with outcomes than acceptance-related facets (Baer et al., 2008 ; Desrosiers et al., 2014 ). Exploratorily, we examined whether Observing might be positively related to burnout at low acceptance, by testing an Observing × Non-judging interaction, consistent with the idea that monitoring without acceptance can amplify distress (Lindsay & Creswell, 2017 ; Simione & Saldarini, 2023 ). H3 (confirmatory). We hypothesized that higher mindfulness, especially acceptance-related facets and Acting with Awareness, would be associated with lower sport anxiety, in line with evidence that mindfulness is linked to reduced competitive anxiety in athletes (Scott-Hamilton & Schutte, 2016; Josefsson et al., 2019 ; Amaro & Brandão, 2023 ; Yu et al., 2024 ). H4 (confirmatory). We further expected sport anxiety to partially account for associations between mindfulness facets and psychological outcomes, such that higher mindfulness would relate to lower burnout and better well-being via lower sport anxiety (Desrosiers et al., 2013 ; Lindsay & Creswell, 2017 ; Goodger et al., 2007 ; Gustafsson et al., 2017 ). Because fatigue may be more directly influenced by training load, we anticipated weaker indirect effects for fatigue than for burnout and well-being. In line with multidimensional anxiety theory, we also hypothesized that cognitive anxiety would show stronger indirect effects than somatic anxiety, given the central role of worry and self-focused concern (Martens et al., 1990 ; Grossbard et al., 2009 ). H5 (confirmatory). Finally, we hypothesized that women would report higher pre-competition sport anxiety than men, consistent with prior work on sex differences in competitive anxiety (Grossbard et al., 2009 ; Amaro & Brandão, 2023 ). Training volume and years of ultra-trail experience were treated as covariates; given mixed findings, we did not specify directional hypotheses for these control variables (Gustafsson et al., 2017 ; Lundqvist & Gustafsson, 2022). In addition to these a priori hypotheses, we conducted a small number of clearly labelled exploratory analyses, which we interpret cautiously. Method Participants Participants were ultra-trail runners registered for the Grand Raid des Pyrénées, a major ultra-endurance event in southwestern France offering three race distances beyond 80 km: 80 km (approximately 5,000 m elevation gain), 120 km (approximately 7,500 m elevation gain), and 160 km (approximately 10,000 m elevation gain). Recruitment occurred via email invitation sent to registered participants in late June to early July, six to eight weeks before the competition scheduled for late August. The study was approved by the institutional ethics committee of the University of Geneva, and all participants provided informed consent prior to completing the online survey. The final sample comprised 216 participants who provided complete data on all study variables (one participant was excluded due to missing data). The sample included 187 men (86.6%) and 29 women (13.4%), with a mean age of 41.3 years ( SD = 8.6, range = 24–67). Participants reported an average of 5.1 years of ultra-trail experience ( SD = 4.0, range = 0–26) and trained an average of 8.6 hours per week ( SD = 3.0, range = 2–20). Race registration was distributed across the 80 km ( n = 77, 35.6%), 120 km ( n = 55, 25.5%), and 160 km ( n = 84, 38.9%) events. Measures Mindfulness Trait mindfulness was assessed using the French version of the Five Facet Mindfulness Questionnaire-Short Form (FFMQ-15; Baer et al., 2012 ; French validation: Heeren et al., 2011 ). We used the FFMQ-15 to reduce participant burden during a demanding pre-competition period. The FFMQ-15 comprises 15 items (3 per facet) rated on a 5-point Likert scale (1 = never or very rarely true to 5 = very often or always true ). The five facets are Observing, Describing, Acting with Awareness, Non-judging, and Non-reactivity. Subscale scores were computed as the mean of the three items per facet. Although not developed specifically for sport, the FFMQ is among the most frequently used self-report measures of mindfulness in mindfulness-based sport interventions (Solé et al., 2020) and has also been used in distance-running research (see Corbally et al., 2020 ). Sport-specific dispositional mindfulness measures are also available (e.g., the Mindfulness Inventory for Sport; Thienot et al., 2014 ; the Athlete Mindfulness Questionnaire; Zhang et al., 2017 ), but they do not provide an FFMQ-like five-facet profile, which constrained their use for the present facet-level approach. Internal consistency in the present sample was as follows: Observing (α = .68), Describing (α = .78), Acting with Awareness (α = .71), Non-judging (α = .85), and Non-reactivity (α = .72). Internal consistency was acceptable for most facets; Observing showed slightly lower reliability, suggesting that associations involving this facet should be interpreted with some caution. Sport Anxiety Competitive anxiety was measured using the French version of the Sport Anxiety Scale-2 (SAS-2; Smith et al., 2006 ; French validation: Fournier et al., 2017 ). Instructions were modified to assess anticipatory anxiety specific to the upcoming competition rather than general trait competitive anxiety: participants were asked to indicate how they typically feel "before the upcoming competition" rather than "generally during competition." The SAS-2 comprises 15 items rated on a 4-point Likert scale (1 = not at all to 4 = very much ). Items assess cognitive anxiety (worry and concentration disruption) and somatic anxiety (physiological symptoms). A total sport anxiety score was computed as the mean of all 15 items, and subscale scores for cognitive and somatic anxiety were computed separately for supplementary analyses. Internal consistency was adequate: total scale (α = .90), cognitive anxiety (α = .87), and somatic anxiety (α = .86). Athlete Burnout Burnout was assessed using the French version of the Athlete Burnout Questionnaire (ABQ; Raedeke & Smith, 2001 ; French validation: Isoard-Gautheur et al., 2010 ). The ABQ comprises 15 items rated on a 5-point Likert scale (1 = almost never to 5 = almost always ) assessing three dimensions: emotional/physical exhaustion, reduced sense of accomplishment, and sport devaluation. A global burnout score was computed as the mean of all 15 items. Internal consistency in the present sample was good (α = .87). Fatigue General fatigue was assessed using the Chalder Fatigue Scale (Chalder et al., 1993 ), a widely used measure of physical and mental fatigue. The scale comprises 10 items assessing symptoms such as problems with tiredness, need for rest, sleepiness, difficulty starting or completing tasks, lack of energy, muscle weakness, and concentration difficulties. Items are rated on a 4-point Likert scale (0 = less than usual to 3 = much more than usual ). A total fatigue score was computed as the mean of all items, with higher scores indicating greater fatigue. Internal consistency was adequate (α = .84). Psychological Well-Being Well-being was assessed using the World Health Organization Well-Being Index (WHO-5; Topp et al., 2015 ), a brief measure of subjective well-being. Although not sport-specific, the WHO-5 provides a brief index of general psychological well-being with extensive validation and is commonly used as a screening tool (Topp et al., 2015 ). The WHO-5 comprises 5 items rated on a 6-point Likert scale (0 = at no time to 5 = all of the time ) assessing positive mood and vitality over the past two weeks. Raw scores were transformed to a 0-100 scale, with higher scores indicating greater well-being. A score below 50 indicates impaired well-being warranting clinical attention (Topp et al., 2015 ). Internal consistency was good (α = .84). Covariates Demographic and training variables assessed as potential covariates included age (years), sex (0 = female, 1 = male), years of ultra-trail experience, and weekly training hours. Statistical Analysis All analyses were conducted using R version 4.3.1 (R Core Team, 2023 ). Descriptive statistics were computed using the psych package (Revelle, 2023 ). Effect sizes were calculated using the effectsize package (Ben-Shachar et al., 2020 ). Multicollinearity was assessed via Variance Inflation Factors using the car package (Fox & Weisberg, 2019 ). Indirect effects were tested using structural equation modeling with the lavaan package (Rosseel, 2012 ). Indirect effects were estimated using bootstrap confidence intervals with 5,000 resamples, with significance determined by 95% CIs excluding zero. In the parallel mediation models, we tested whether the indirect effect via cognitive anxiety differed from that via somatic anxiety using a bootstrapped contrast (ab_cog - ab_som). It is important to note that these cross-sectional mediation analyses test whether the data are consistent with the hypothesized indirect pathways, but cannot establish causal mediation (Maxwell & Cole, 2007 ). Sensitivity analyses for robustness to unmeasured confounding were conducted using the mediation package (Tingley et al., 2014 ). Simple slopes for interaction effects were computed using the emmeans package (Lenth, 2023 ). Statistical significance was set at p < .05 (two-tailed) for confirmatory analyses. For exploratory analyses, effects with p < .10 were flagged as trends warranting discussion. Effect sizes were interpreted according to Cohen's (1988) guidelines. Sensitivity Analyses Sensitivity analyses for statistical power were conducted using the pwr package (Champely, 2020 ). Given N = 216 and nine predictors in the full regression models (five mindfulness facets and four covariates), the analyses indicated that the design had 80% power to detect an overall effect size of approximately f ² = 0.08, corresponding to R² ≈ .07. With the observed imbalance in group sizes for sex (29 women, 187 men), the analyses showed that we had 80% power to detect sex differences in sport anxiety of about d ≈ 0.56; smaller group differences may therefore have gone undetected. For the Observing × Non-judging interaction, sensitivity analysis indicated that we had 80% power to detect an incremental effect of about f ² ≈ 0.04 ( ΔR ² ≈ .04). For the mediation models, statistical power depends on the magnitude of both the a path (mindfulness → sport anxiety) and the b path (sport anxiety → outcomes). Simulation studies on mediation indicate that sample sizes around N ≈ 200 provide adequate power to detect indirect effects when both paths are at least medium in size, but substantially lower power when one or both paths are small (Fritz & MacKinnon, 2007 ). Thus, the present design is well suited to detecting indirect effects of at least moderate magnitude, whereas smaller mediated effects and subtle differences between parallel mediators (cognitive vs. somatic anxiety) may have gone undetected. These sensitivity thresholds are broadly consistent with typical effect sizes reported in the literature. Meta-analyses indicate that dispositional mindfulness tends to show small-to-moderate associations with motivation and mental health indicators (| r | ≈ .20–.35; Enkema et al., 2020 ; Li et al., 2023 ), whereas more proximal constructs such as sport-specific stress and burnout or burnout and anxiety often correlate at moderate-to-large levels ( r ≈ .40–.50; Glandorf et al., 2023 ; Lin et al., 2022 ). Thus, the present design is well suited to detecting the magnitude of effects typically observed between mindfulness facets and psychological outcomes, while very small associations or subtle differences between pathways may remain undetected. Results Preliminary Analyses Descriptive Statistics Descriptive statistics for all psychological variables are presented in Table 1. Mindfulness facets showed adequate variability, with means ranging from 2.83 ( SD = 0.89) for Observing to 3.53 ( SD = 0.79) for Acting with Awareness on the 1–5 scale. Sport anxiety levels were relatively low ( M = 2.00, SD = 0.58), with cognitive anxiety ( M = 2.20, SD = 0.74) slightly higher than somatic anxiety ( M = 1.84, SD = 0.59). Burnout levels were low to moderate ( M = 2.20, SD = 0.54), fatigue was low ( M = 1.26, SD = 0.37), and well-being was moderate ( M = 59.41, SD = 16.37). All variables showed acceptable skewness and kurtosis for parametric analyses (|skew| < 1, |kurtosis| < 1). Clinical Prevalence Despite generally positive mean levels, a notable proportion of participants showed elevated symptoms. Approximately one quarter of participants (23.6%, n = 51) reported impaired well-being (WHO-5 < 50), while 7.9% ( n = 17) showed elevated burnout symptoms (ABQ ≥ 3) and 4.2% ( n = 9) reported high fatigue levels. Sex Differences Independent-samples t -tests revealed significant sex differences in sport anxiety. Women reported higher total sport anxiety than men ( M = 2.28, SD = 0.62 vs . M = 1.95, SD = 0.56), t (214) = 2.87, p = .007, d = 0.57. This difference was observed for both cognitive anxiety ( d = 0.38, p = .045) and somatic anxiety ( d = 0.64, p = .009). No significant sex differences emerged for burnout, fatigue, well-being, or mindfulness facets (all p s > .05). These findings support H5 and justify including sex as a covariate in subsequent analyses. Given the small number of women in the sample (n = 29), these comparisons should be interpreted cautiously, and smaller sex differences may have gone undetected. Race Distance Differences One-way ANOVAs revealed no significant differences across race distances for any psychological variable (all p s > .05). However, race distance was associated with years of experience, F (2, 213) = 13.64, p < .001, and weekly training hours, F (2, 213) = 3.16, p = .045, with longer distances associated with greater experience and training volume. Zero-Order Correlations Zero-order correlations among study variables are presented in Table 2. Consistent with expectations, Non-judging showed significant negative correlations with burnout ( r = − .36), fatigue ( r = − .31), and sport anxiety ( r = − .36), and a positive correlation with well-being ( r = .35). Acting with Awareness showed a similar pattern, with notable associations with burnout ( r = − .36) and fatigue ( r = − .24). Non-reactivity was associated with well-being ( r = .28) and sport anxiety ( r = − .29). In contrast, Observing showed near-zero correlations with all outcomes ( r s = − .04 to .06). Sport anxiety was significantly correlated with burnout ( r = .39), fatigue ( r = .22), and well-being ( r = − .33). Notably, years of experience showed a small but significant positive correlation with burnout ( r = .15, p = .026). Primary Analyses: Mindfulness Facets and Psychological Outcomes (H1, H2) Multiple regression analyses tested the unique associations between the five FFMQ facets and each outcome, controlling for age, sex, years of experience, and weekly training hours. All five facets were entered simultaneously. Burnout The overall model significantly predicted burnout, F (9, 206) = 8.00, p < .001, R ² = .259. Acting with Awareness showed the strongest negative association ( B = -0.21, SE = 0.05, β = − .30, p < .001), followed by Non-judging ( B = -0.15, SE = 0.04, β = − .25, p < .001). Non-reactivity showed a trend (β = − .12, p = .082). Observing showed a trend toward a positive association ( β = .11, p = .083). Among covariates, years of experience was positively associated with burnout ( β = .16, p = .025). Fatigue The model significantly predicted fatigue, F (9, 206) = 5.15, p < .001, R ² = .184. Non-judging ( β = − .24, p < .001) and Acting with Awareness ( β = − .20, p = .006) were significant predictors. Weekly training hours were negatively associated with fatigue ( β = − .15, p = .018). Well-Being The model significantly predicted well-being, F (9, 206) = 5.56, p < .001, R ² = .196. Three facets emerged as significant predictors: Non-judging (β = .27, p < .001), Non-reactivity ( β = .20, p = .003), and Acting with Awareness ( β = .15, p = .030). Summary of H1 and H2 Results provided strong support for H1: Non-judging and Acting with Awareness were consistently associated with lower burnout and fatigue and higher well-being, with medium effect sizes ( β = .20-.30). Non-reactivity was additionally associated with well-being. Regarding H2, Observing showed null or marginally positive associations with outcomes, consistent with the mixed evidence on the Observing facet in trait mindfulness research and with MAT’s emphasis that monitoring processes may be most adaptive when accompanied by acceptance. Multicollinearity was not a concern (all VIF < 1.35). As a robustness check, we also estimated single-facet models (each mindfulness facet entered separately, controlling for covariates); patterns were broadly similar, though coefficients for some facets were attenuated in the full model, consistent with shared variance among facets (see Supplementary Table S1 ). Mindfulness Facets and Sport Anxiety (H3) A multiple regression model tested associations between FFMQ facets and total sport anxiety, F (9, 206) = 6.91, p < .001, R ² = .232. Non-judging was the strongest predictor ( β = − .25, p < .001), followed by Non-reactivity ( β = − .19, p = .005). These results support H3. Supplementary analyses examining cognitive and somatic anxiety separately revealed that Non-judging was particularly strongly associated with cognitive anxiety ( β = − .35, p < .001) compared to somatic anxiety ( β = − .10, p = .145). Non-reactivity was associated with both cognitive ( β = − .15, p = .023) and somatic anxiety ( β = − .18, p = .009). These differential patterns suggest that Non-judging is primarily associated with reduced cognitive worry, with only a weak and non-significant association with somatic symptoms of anxiety. Indirect Effects Through Sport Anxiety (H4) Simple Indirect Effects: Non-judging to Sport Anxiety to Outcomes Burnout. The indirect effect model showed significant paths: Non-judging was negatively associated with sport anxiety (path a : B = -0.162, 95% CI [-0.254, -0.072]), and sport anxiety was positively associated with burnout (path b : B = 0.259, 95% CI [0.142, 0.376]). The indirect effect was significant ( ab = -0.042, 95% CI [-0.077, -0.015]), suggesting that sport anxiety shows a meaningful statistical indirect association in the Non-judging–burnout link. The proportion of the total effect represented by this indirect pathway was 27.8%. The direct effect remained significant ( c' = -0.109, p = .007), consistent with a partial statistical mediation pattern. Well-being. Sport anxiety also showed a significant indirect association in the link between Non-judging and well-being. The indirect effect was significant ( ab = 1.057, 95% CI [0.326, 1.999]), with 21.4% of the total effect going through this pathway. Fatigue. For fatigue, the indirect effect was not significant ( ab = -0.013, 95% CI [-0.035, 0.002]), despite significant total and direct effects. This pattern suggests that sport anxiety does not play a substantial indirect role in the mindfulness–fatigue association, consistent with our prediction that fatigue is more directly influenced by training load. Parallel Indirect Effects: Cognitive vs. Somatic Anxiety A parallel mediation model tested whether cognitive and somatic anxiety carried distinct components of the Non-judging–burnout association (Table 4; Fig. 1). Non-judging was strongly associated with lower cognitive anxiety (path a1: B = -0.283, SE = 0.060, 95% CI [-0.403, -0.170], p < .001) but showed a weaker, non-significant association with somatic anxiety (path a2: B = -0.067, SE = 0.046, 95% CI [-0.159, 0.022], p = .144). Cognitive anxiety, in turn, was positively associated with burnout (path b1: B = 0.197, SE = 0.064, 95% CI [0.059, 0.320], p = .003), whereas somatic anxiety was not (path b2: B = 0.044, SE = 0.074, 95% CI [-0.098, 0.192], p = .558). The direct effect of Non-judging on burnout remained significant when both mediators were included (c': B = -0.092, SE = 0.043, 95% CI [-0.178, -0.008], p = .033). Consistent with these paths, the total indirect effect in the parallel mediation model was B = -0.059 ( SE = 0.021, 95% CI [-0.106, -0.021], p = .006; Table 4), slightly larger in magnitude than the indirect effect observed in the model using total sport anxiety (ab = -0.042). The indirect effect through cognitive anxiety was significant (ab_cog = -0.056, SE = 0.022, 95% CI [-0.107, -0.017], p = .015), whereas the indirect effect through somatic anxiety was not (ab_som = -0.003, SE = 0.006, 95% CI [-0.025, 0.005], p = .641). A bootstrapped contrast indicated that the indirect effect via cognitive anxiety was larger in magnitude than the indirect effect via somatic anxiety (ab_cog - ab_som = -0.053, 95% CI [-0.110, -0.009], p = .041). These indirect components represented 37.1% and 2.0% of the total Non-judging–burnout effect, respectively. This pattern supports H4’s prediction that statistical indirect associations via cognitive anxiety would be stronger than via somatic anxiety and is consistent with the idea that Non-judging is more strongly related to burnout through reduced cognitive worry than through somatic symptoms of anxiety, while recognizing that these cross-sectional data do not permit causal conclusions. Sensitivity Analysis Sensitivity analysis assessed the robustness of the indirect effect to unmeasured confounding. The correlation between residuals (ρ) at which the indirect effect would equal zero was 0.30, indicating moderate robustness to potential confounding. This suggests that a moderately strong unmeasured confounder would be required to nullify the observed indirect effect. Additionally, we examined whether prior relaxation training experience ( n = 26, 12.0%) influenced the main findings. When included as an additional covariate, relaxation training did not significantly predict burnout ( B = -0.10, p = .32), fatigue ( B = -0.04, p = .63), or well-being ( B = 3.27, p = .31), and all FFMQ facet coefficients remained virtually unchanged (all Δβ < .01, ΔR² < .004). Exploratory Analyses Observing × Non-judging Interaction Based on MAT, we examined whether Non-judging moderated the association between Observing and burnout. The Observing × Non-judging interaction was small and marginal ( B = -0.081, SE = 0.042, p = .057), accounting for an additional 1.3% of variance. To describe this pattern, we probed conditional associations at ± 1 SD of Non-judging. At low Non-judging (− 1 SD ), higher Observing was associated with higher burnout ( B = 0.149, SE = 0.058, t = 2.59, p = .010), whereas at high Non-judging (+ 1 SD), Observing was not associated with burnout ( B = 0.003, p = .954). Given the marginal interaction and the limited power to detect small moderation effects, this pattern should be interpreted as exploratory and in need of replication. Experience and Burnout An unexpected finding was the positive association between years of experience and burnout. Controlling for age and training volume, years of experience remained a significant predictor ( B = 0.025, p = .018). This effect was particularly evident for sport devaluation ( r = .19). Testing for curvilinearity, the quadratic term was not significant ( p = .148), indicating a linear relationship. However, the effect size was small ( r = .15), and this cross-sectional association should be interpreted cautiously. Several mechanisms may explain this pattern, including accumulated strain, elevated expectations, or selection effects, but longitudinal research is needed to understand this relationship. Discussion The present study examined associations between mindfulness facets, sport anxiety, and psychological outcomes in ultra-trail runners during the pre-competition period. Drawing on MAT (Lindsay & Creswell, 2017 ), we examined whether acceptance-related mindfulness facets would show stronger associations with mental health than attention monitoring, and whether sport anxiety, particularly cognitive worry, would statistically account for these associations. Overall, the pattern of results was broadly compatible with these expectations and extends our understanding of mindfulness in athlete mental health to an under-studied population assessed during a theoretically important preparatory window. Acceptance-related facets and Acting with Awareness showed the strongest links with mental health; Observing played a limited and context-dependent role; and sport anxiety, particularly its cognitive component, showed indirect statistical associations with the links between Non-judging and both burnout and well-being, whereas sex differences were limited, noting the small number of women in the sample. Sample Characteristics and Mental Health Status The demographic profile of our sample, predominantly male, middle-aged, and moderately experienced, closely mirrors the broader ultra-endurance population described in recent surveys (Hoffman & Fogard, 2012 ; Knechtle et al., 2021 ; Thuany et al., 2023 ). Assessed six to eight weeks before competition, participants were navigating the demanding final mesocycles of preparation characterized by high training volumes, occupational and family responsibilities, and anticipatory concerns about the upcoming event (Bali, 2015 ; Niering et al., 2024 ). This timing is particularly relevant because the pre-competition period may paradoxically heighten vulnerability to negative psychological states: athletes must balance peak training demands with the accumulated psychological costs of months of intensive preparation while managing uncertainty about their readiness (Raglin & Morris, 1994 ). A notable finding concerns the prevalence of psychological difficulties despite generally positive mean scores. Nearly one quarter of participants reported well-being below clinical thresholds, suggesting that a meaningful proportion of ultra-trail runners experience compromised mental health during preparation. This aligns with emerging evidence that mental health concerns in ultra-endurance athletes may be more common than previously recognized (Gameiro et al., 2023 ; Niering et al., 2024 ), and underscores the value of examining psychological resources that may support adaptation during this demanding phase. Differential Associations of Mindfulness Facets In line with MAT’s emphasis on acceptance-related processes, Non-judging and Acting with Awareness emerged as the facets most consistently associated with favorable outcomes. These findings extend prior research identifying Non-judging as particularly relevant for athlete adjustment (Josefsson et al., 2017 ; Kinnunen et al., 2020 ) to the ultra-trail context. The pattern is theoretically coherent: athletes who refrain from harsh self-evaluation of internal experiences (Non-judging) and who maintain attentional engagement with present activities rather than drifting into rumination or worry (Acting with Awareness) may be better equipped to navigate the psychological demands of intensive training periods without developing burnout symptoms or compromised well-being. Acting with Awareness showed associations comparable in magnitude to Non-judging, which warrants interpretation. During demanding training phases, athletes face continuous decisions about pacing, recovery, and effort allocation. The capacity to remain attentively engaged with these moment-to-moment demands—rather than operating on autopilot or becoming absorbed in performance-related worries—may support more adaptive self-regulation. This interpretation aligns with broader evidence that Acting with Awareness is among the FFMQ facets most consistently linked to reduced psychological symptoms across populations (Carpenter et al., 2019 ). Non-reactivity showed a more selective pattern, predicting well-being but not burnout or fatigue in multivariate models. This facet—allowing thoughts and feelings to arise and pass without becoming entangled—may be particularly relevant for maintaining positive psychological states. During intensive preparation, negative thoughts and doubts are likely common; the capacity to observe these experiences without elaborative engagement may preserve well-being without necessarily reducing the exhaustion or devaluation components of burnout. Observing showed null to marginally positive associations with burnout, consistent with debates about this facet's role in psychological adjustment (Baer et al., 2008 ; Lilja et al., 2013 ). The exploratory interaction analysis suggested that Observing may relate to higher burnout specifically when Non-judging is low. Although this conditional pattern is compatible with MAT’s moderation hypothesis, the interaction was marginal and should be interpreted cautiously. More broadly, this result is best viewed as hypothesis-generating, given ongoing debates about the operationalization of monitoring via Observing and the limited power to detect small moderation effects in the present sample. Such moderation patterns have been proposed and examined in other contexts (e.g., Lindsay et al., 2019), warranting replication in sport samples. Cognitive Anxiety as an Indirect Pathway A central contribution of this study concerns the differential roles of cognitive vs . somatic anxiety. Parallel indirect models indicated that cognitive anxiety was associated with a larger proportion of the Non-judging–burnout association than somatic anxiety, which contributed negligibly; a bootstrapped contrast supported this difference between indirect effects. This asymmetry suggests that the association between Non-judging and burnout may be more closely tied to reduced ruminative worry than to lower physiological arousal. This finding has both theoretical and practical implications. Theoretically, it is consistent with a plausible cognitive pathway linking acceptance-related mindfulness to athlete burnout: by reducing harsh evaluation of internal experiences, Non-judging may attenuate the self-critical rumination and performance concerns that characterize competitive anxiety, thereby reducing downstream risk for emotional exhaustion and sport devaluation. This interpretation is consistent with evidence that cognitive emotion-regulation processes such as worry and rumination can statistically mediate associations between mindfulness and anxiety symptoms (Desrosiers et al., 2013 ), suggesting that mindfulness-related skills may be linked to athlete burnout partly through reduced cognitive overengagement. Practically, these findings tentatively suggest that interventions targeting cognitive worry through acceptance-based techniques, such as cognitive defusion or decentering, may be more relevant for burnout prevention than approaches focused on somatic relaxation, although longitudinal and experimental confirmation is needed. Notably, sport anxiety did not account for the mindfulness–fatigue association. Fatigue during intensive training is likely more directly tied to physiological load, recovery, and sleep than to cognitive worry, which may explain why anxiety does not serve as an indirect pathway for this outcome. This pattern is consistent with work highlighting the predominant role of training load, recovery, and non-functional overreaching in the development of athlete fatigue, relative to purely cognitive-emotional factors (Meeusen et al., 2013 ; Schwellnus et al., 2016 ). Sex Differences and Experience-Related Patterns Consistent with prior sport psychology research (Correia & Rosado, 2019 ; Grossbard et al., 2009 ), women reported higher pre-competition anxiety than men. Importantly, however, no sex differences emerged for burnout, fatigue, or well-being, suggesting that elevated anxiety does not automatically translate into differential mental health outcomes—possibly because other resources buffer its downstream effects. Given the marked underrepresentation of women in ultra-endurance research, this finding highlights the importance of attending to sex-specific experiences while avoiding assumptions about differential vulnerability. An unexpected finding was the positive association between years of experience and burnout, particularly sport devaluation. Although the effect was small, it persisted after controlling for age and training volume. This pattern contrasts with intuitions about the protective role of expertise and aligns with accumulated strain models of burnout (Gustafsson et al., 2011 ). Experienced runners may face rising expectations, chronic exposure to demanding preparation cycles, or selection effects whereby highly motivated individuals persist despite symptoms. Whatever the mechanism, this finding suggests that experience alone does not confer psychological resilience, and that even veteran athletes may benefit from monitoring and support. Practical Implications Several practical considerations emerge, though they warrant cautious interpretation pending experimental evidence. First, the prevalence of compromised well-being suggests that routine screening during pre-competition phases may be valuable; brief tools such as the WHO-5 could be incorporated into athlete monitoring. Second, the consistent associations between acceptance-related facets and favorable outcomes suggest that interventions emphasizing Non-judging and Acting with Awareness (e.g., Mindfulness-Acceptance-Commitment; Gardner & Moore, 2004 , 2012 ; MSPE; Kaufman et al., 2009 ) could be prioritized for evaluation in ultra-endurance contexts. Third, the specificity of cognitive anxiety as an indirect association suggests that techniques targeting ruminative worry (e.g., cognitive defusion, decentering) may be particularly relevant targets to examine in future burnout prevention research. Finally, practitioners should be attentive to burnout signs among experienced athletes, who may be at elevated risk despite their accumulated expertise. Limitations and Future Directions Several limitations warrant acknowledgment. Most importantly, the cross-sectional design precludes causal inference. Although SAS-2 (Smith et al., 2006 ) instructions were framed to the upcoming competition, the instrument was originally developed to assess dispositional competitive anxiety; thus, the psychometric implications of this contextual framing warrant replication using repeated assessments closer to race day. Although indirect effect analyses suggest that anxiety statistically accounts for part of the mindfulness–burnout association, temporal precedence cannot be established. Cross-sectional mediation can yield biased estimates of longitudinal processes (Maxwell & Cole, 2007 ), and sensitivity analyses indicated only moderate robustness to unmeasured confounding. Stable personality traits such as neuroticism (Hanley & Garland, 2019 ) and contextual factors such as social support (Luo et al., 2025 ) could plausibly influence both mindfulness and outcomes. Longitudinal designs tracking athletes across the pre-competition period are needed to establish temporal ordering. In addition, because recruitment relied on volunteers responding to an online invitation, participants may differ from non-responders (e.g., in psychological openness or current mental health status). This self-selection limits the generalizability of the findings to all ultra-trail runners registered for the event. Finally, all variables were assessed via self-report questionnaires administered in a single online session, raising the possibility of common method variance and self-report biases (Podsakoff et al., 2003 ). Incorporating behavioral or physiological indicators of anxiety and regulatory processes (e.g., heart rate variability, sleep, or training-load metrics) alongside self-reported mindfulness and burnout would help to reduce shared method variance and provide a more multi-dimensional picture of mental health in ultra-trail runners (Matsuura et al., 2023 ; Charest et al., 2022 ; Thuany et al., 2023 ). Conclusion This study provides a comprehensive examination of mindfulness facets, sport anxiety, and psychological outcomes in ultra-trail runners during the pre-competition period. Acceptance-related mindfulness facets, particularly Non-judging and Acting with Awareness, showed consistent associations with lower burnout and fatigue and higher well-being. Cognitive anxiety showed a specific statistical indirect association in the Non-judging–burnout link, whereas somatic anxiety played a negligible role. Although the cross-sectional design precludes causal inference, these findings are consistent with the possibility that acceptance-focused mindfulness training and cognitive decentering may be promising targets for future longitudinal and intervention studies in ultra-endurance athletes.x Declarations Ethical Principles This study was approved by the Commission Universitaire de Recherche Éthique de Genève (CUREG 2.0), University of Geneva (reference number: CUREG-20250423-421-2, approved 12 June 2025). The research was conducted in accordance with the ethical principles of the Declaration of Helsinki. Prior to completing the online survey, all runners received detailed information about the study purpose and procedures, participant rights (including the voluntary nature of participation and the right to withdraw at any time without consequence), and the measures implemented to protect confidentiality. Electronic informed consent was obtained before participation. Data were handled anonymously (or de-identified) and treated as confidential throughout the research process, and participants were informed that the collected data would be used solely for scientific purposes. Consent for publication Not applicable. Funding This research was supported by the Swiss National Science Foundation (PCEFP1_186911). Acknowledgments We thank Steeve Azevedo, Bhavya Jain, Charlotte Mancini, and Joao Marcos for their assistance with protocol implementation and data collection. We also gratefully acknowledge the Grand Raid des Pyrénées organization for allowing us to conduct this study as part of their event and for their support with participant recruitment. CRediT Author Statement PL: conceptualization, study design, data collection coordination, statistical analysis, tables and figure, writing—original draft and writing—review & editing. JC: study design and writing—review & editing. RAP: writing—review & editing. UR: supervision and writing—review & editing. 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Action monitoring through external or internal focus of attention does not impair endurance performance. Front Psychol. 2019;10:535. https://doi.org/10.3389/fpsyg.2019.00535 . Wu CH, Zhao YD, Yin FQ, Yi Y, Geng L, Xu X. Mental fatigue and sports performance of athletes: Theoretical explanation, influencing factors, and intervention methods. Behav Sci. 2024;14(12):1125. Yu MG, Dou GB, Gong C. Effects of mindfulness intervention on competition state anxiety in sprinters—a randomized controlled trial. Front Psychol. 2024;15:1418094. https://doi.org/10.3389/fpsyg.2024.1418094 . Zhang C-Q, Chung P-K, Si G. Assessing acceptance in mindfulness with direct-worded items: The development and initial validation of the Athlete Mindfulness Questionnaire. J Sport Health Sci. 2017;6(3):311–20. https://doi.org/10.1016/j.jshs.2015.09.010 . Tables Table 1 Descriptive Statistics for Psychological Variables (N = 216) Variable Scale M SD Min Max α Observing 1-5 2.83 0.89 1.00 5.00 0.68 Describing 1-5 2.88 0.83 1.00 4.67 0.78 Acting with Awareness 1-5 3.53 0.79 1.00 5.00 0.71 Non-judging 1-5 3.51 0.91 1.00 5.00 0.85 Non-reactivity 1-5 2.92 0.76 1.00 5.00 .72 Sport Anxiety (total) 1-4 2.00 0.58 1.00 3.56 .90 Cognitive anxiety 1-4 2.20 0.74 1.00 4.00 .87 Somatic anxiety 1-4 1.84 0.59 1.00 3.67 .86 Burnout 1-5 2.20 0.54 1.13 4.20 .87 Fatigue 0-3 1.26 0.37 0.20 2.70 .84 Well-being 0-100 59.41 16.37 4.00 88.00 .84 Note. FFMQ = Five Facet Mindfulness Questionnaire; Sport anxiety assessed with SAS-2; Burnout assessed with ABQ; Fatigue assessed with Chalder Fatigue Scale; Well-being assessed with WHO-5. Table 2 Zero-Order Correlations Among Study Variables (N = 216) Variable 1 2 3 4 5 6 7 8 9 10 11 12 1. Observing — 2. Describing .24 *** — 3. Acting Aware .14 * .37 *** — 4. Non-judging -.11 .09 .24 *** — 5. Non-reactivity .13 .11 .03 .32 *** — 6. Sport Anxiety .02 -.16 * -.22 ** -.36 *** -.29 *** — 7. Burnout .06 -.14 * -.36 *** -.36 *** -.20 ** .39 *** — 8. Fatigue .06 -.09 -.24 *** -.31 *** -.14 * .22 ** .51 *** — 9. Well-being -.04 .02 .18 ** .35 *** .28 *** -.33 *** -.45 *** -.48 *** — 10. Age -.04 .07 .07 .11 -.06 -.09 .04 -.07 -.09 — 11. Experience -.08 .01 -.01 .04 -.08 -.09 .15 * .10 -.05 .46 *** — 12. Training h/wk .04 .12 .05 -.05 .02 .04 -.06 -.14 * .04 .02 .07 — Note . * p < .05, ** p < .01, *** p < .001 Table 3 Multiple Regression Results: FFMQ Facets Predicting Psychological Outcomes Burnout Fatigue Well-being Predictor β p β p β p Observing .11 .083 .08 .210 -.05 .451 Describing -.01 .849 .03 .683 -.08 .252 Acting with Awareness -.30 *** <.001 -.20 ** .006 .15 * .030 Non-judging -.25 *** <.001 -.24 *** <.001 .27 *** <.001 Non-reactivity -.12 .082 -.07 .296 .20 ** .003 R ² .259 .184 .196 F (9, 206) 8.00 *** 5.15 *** 5.56 *** Note. Standardized coefficients (β) reported. Models control for age, sex, years of experience, and weekly training hours. * p < .05, ** p < .01, *** p < .001. Table 4 Parallel Indirect Effects: Cognitive vs. Somatic Anxiety in the Non-judging–Burnout Association Path B SE 95% CI p a 1: NJ → Cognitive anxiety -0.283 0.060 [-0.403, -0.170] <.001 a 2: NJ → Somatic anxiety -0.067 0.046 [-0.160, 0.020] .145 b 1: Cognitive anxiety → Burnout 0.197 0.064 [0.073, 0.324] .002 b 2: Somatic anxiety → Burnout 0.044 0.074 [-0.107, 0.185] .554 c' : Direct effect -0.092 0.043 [-0.178, -0.009] .034 Indirect via cognitive -0.056 0.022 [-0.105, -0.018] .012 Indirect via somatic -0.003 0.006 [-0.018, 0.009] .640 Total indirect -0.059 0.021 [-0.103, -0.021] .005 Total effect -0.151 0.041 [-0.232, -0.072] <.001 Note. NJ = Non-judging. Unstandardized coefficients reported. Bootstrap 95% confidence intervals based on 5,000 resamples. Proportion of total effect via cognitive anxiety = 37.1%; via somatic anxiety = 2.0%. Model controls for all other FFMQ facets, age, sex, years of experience, and training hours. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1APA.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 27 Jan, 2026 Submission checks completed at journal 23 Jan, 2026 First submitted to journal 23 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8649683","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":579476200,"identity":"6e872361-77eb-4669-a2ec-6f73b9252d3d","order_by":0,"name":"Pierrick Laulan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYDACZhBhAITsQPoBA4McAwNjA0gsgbAWZogyY8JaoACuJbEBKoJTizk787HPFQV2xgzMzM8kEmrupG+43dz84gODXR4uLZbNbMkzzxgkmzEws5lJJBx7lrvhzsE2yxkMycU4HXSYx5ixweCADdBhQC1sh3M33EhsM+ZhOAB3IaYW/s9QLezfJBL+HU43AGn5g1cLDzNIC9BhPGYSiW2HE4Bamh8z4NEC9AvIYcnGbMw8xRaJfYcNZwJtYewxSMapxZz/8GPGhj92hv3s7RtvfPh2WJ7vRvrjDz8q7HA7DMZgQxJkk0CI49GCDJg/4NYwCkbBKBgFIxAAAI5OVIqJTtCGAAAAAElFTkSuQmCC","orcid":"","institution":"University of Geneva","correspondingAuthor":true,"prefix":"","firstName":"Pierrick","middleName":"","lastName":"Laulan","suffix":""},{"id":579476201,"identity":"0bf4484a-be46-4620-95fe-a5f9fe496c02","order_by":1,"name":"Jérôme Cuadrado","email":"","orcid":"","institution":"Catholic University of Toulouse","correspondingAuthor":false,"prefix":"","firstName":"Jérôme","middleName":"","lastName":"Cuadrado","suffix":""},{"id":579476203,"identity":"0338ff3b-8a12-4669-a4dd-a3e85c1ab807","order_by":2,"name":"Roberta Antonini Philippe","email":"","orcid":"","institution":"University of Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Roberta","middleName":"Antonini","lastName":"Philippe","suffix":""},{"id":579476206,"identity":"9b03aee3-1925-40a3-a24b-5b35133ac9e9","order_by":3,"name":"Ulrike Rimmele","email":"","orcid":"","institution":"University of Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Ulrike","middleName":"","lastName":"Rimmele","suffix":""}],"badges":[],"createdAt":"2026-01-20 13:35:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8649683/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8649683/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101214594,"identity":"53273919-c6eb-47b4-ad48-5337c37a19f5","added_by":"auto","created_at":"2026-01-27 10:35:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":65740,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eParallel mediation model: Cognitive and somatic anxiety as potential mediators of the Non-judging–burnout association.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Unstandardized coefficients are shown. Solid lines indicate significant paths; dashed lines indicate non-significant paths. The indirect effect through cognitive anxiety represented 37.1% of the total effect, whereas the indirect effect through somatic anxiety represented only 2.0% (non-significant). Model controls for other FFMQ facets, age, sex, years of experience, and training hours. Bootstrap 95% confidence intervals based on 5,000 resamples. * \u003cem\u003ep\u003c/em\u003e \u0026lt; .05, ** \u003cem\u003ep\u003c/em\u003e\u0026lt; .01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; .001.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8649683/v1/af911e35171e812192ae15c2.png"},{"id":101942788,"identity":"7e7fcffe-676e-4a67-8dc8-bd69128643cb","added_by":"auto","created_at":"2026-02-05 09:37:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1535115,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8649683/v1/c1ad9b9f-4f67-4a67-a7c8-998fa252af77.pdf"},{"id":101214595,"identity":"1b65fa3a-c861-4b74-8ce9-5022010be20b","added_by":"auto","created_at":"2026-01-27 10:35:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37924,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1APA.docx","url":"https://assets-eu.researchsquare.com/files/rs-8649683/v1/8112bfc937bc43b1d6777e2c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mindfulness Facets, Sport Anxiety, and Psychological Outcomes in Ultra-Trail Runners: A Pre-Competition Study","fulltext":[{"header":"Background","content":"\u003cp\u003eUltra-trail running and other ultra-endurance events impose sustained physiological and psychological demands that extend over months of preparation and hours of competition. Beyond the physiological strain of prolonged training, ultra-endurance runners face cumulative psychosocial demands arising from high training volumes, occupational responsibilities, relationship pressures, and the inherent challenges of balancing elite sport pursuits with daily life (Niering et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Thuany et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Recent work has underscored that mental health concerns in ultra-endurance populations may be more prevalent than previously assumed, with some athletes reporting elevated levels of stress, mood disturbances, and psychological fatigue in the lead-up to major competitions (Gameiro et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Roebuck et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAthlete burnout has emerged as a central construct in understanding psychological maladjustment in sport. In ultra-endurance contexts, prolonged exposure to high training loads, performance pressure, and limited recovery windows may render athletes particularly vulnerable to burnout symptoms (Gucciardi et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Burnout is typically conceptualized as a cognitive-affective syndrome characterized by emotional and physical exhaustion, a reduced sense of athletic accomplishment, and sport devaluation (Gustafsson et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Raedeke \u0026amp; Smith, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Smith's (1986) cognitive-affective stress model posits that burnout develops through a transactional process in which chronic stressors interact with cognitive appraisals and coping resources, ultimately leading to maladaptive outcomes when demands consistently exceed perceived resources. Complementary accounts also frame athlete burnout within self-determination theory (SDT), emphasizing that satisfaction of basic psychological needs (autonomy, competence, relatedness) supports more self-determined motivation and is associated with lower burnout, whereas more controlled forms of motivation are linked to higher burnout risk (Lonsdale et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). SDT research further highlights that need-thwarting interpersonal climates can undermine well-being and contribute to maladaptive outcomes in sport (Bartholomew et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In parallel, work integrating motivational regulation and training strain suggests that symptoms of overtraining and less self-determined motivation are independently associated with burnout indicators (Lemyre et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Together, these frameworks underscore that burnout is shaped by both chronic demands and the motivational–social context in which athletes pursue their sport.\u003c/p\u003e \u003cp\u003eAlongside burnout, fatigue has emerged as a distinct yet related concern in high-performance sport. Fatigue in athletic populations encompasses both mental and physical dimensions: mental fatigue refers to a psychobiological state induced by prolonged cognitive effort, characterized by subjective tiredness and impaired cognitive performance (Van Cutsem et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), whereas physical or general fatigue reflects broader perceptions of exhaustion related to training load and recovery status (Chalder et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Importantly, experimental and longitudinal work demonstrates that fatigue impairs endurance performance, decision-making, and motivation, making it a critical variable to monitor during intensive training periods (Russell et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In ultra-trail runners, accumulated fatigue in the weeks preceding a major event may compromise both performance readiness and psychological well-being.\u003c/p\u003e \u003cp\u003eThe final mesocycles before a target competition represent a particularly salient window for psychological assessment. This period typically involves peak training loads followed by a taper phase designed to optimize physiological readiness while allowing accumulated fatigue to dissipate (Le Meur et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Mujika \u0026amp; Padilla, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). However, psychological research suggests that this period may paradoxically heighten vulnerability to negative psychological states: anticipatory anxiety about the upcoming event, uncertainty regarding fitness and preparation, and the accumulated psychological cost of months of demanding training may converge to increase risk for burnout symptoms, elevated fatigue, and compromised well-being (Bali, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Raglin \u0026amp; Morris, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Despite its theoretical importance, relatively little empirical work has systematically examined psychological functioning in ultra-trail runners during this critical pre-competition window.\u003c/p\u003e \u003cp\u003eOne promising factor in this context is trait mindfulness. Dispositional mindfulness refers to an inherent capacity to attend to present-moment experience with openness, curiosity, and non-judgment (Kabat-Zinn, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In sport psychology, mindfulness-based interventions have shown beneficial effects on performance, anxiety reduction, and psychological well-being across various athletic populations (Bühlmayer et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Noetel et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sappington \u0026amp; Longshore, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In long-distance running specifically, mindfulness-based programs such as Mindful Sport Performance Enhancement (MSPE) have been examined in runners (De Petrillo et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and synthesized in a dedicated systematic review (Corbally et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and a narrative review (Laulan et al., 2026). A systematic review and meta-analysis focusing specifically on athlete burnout further indicates that mindfulness is negatively associated with burnout, while emphasizing that intervention evidence remains comparatively limited and heterogeneous (Li et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, most research has treated mindfulness as a unitary construct, potentially obscuring differential associations between specific mindfulness facets and psychological outcomes.\u003c/p\u003e \u003cp\u003eThe Monitor and Acceptance Theory (MAT; Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) provides a useful framework for understanding how different components of mindfulness may relate to psychological adjustment. MAT proposes that mindfulness comprises two partially dissociable processes: attention monitoring, i.e. the capacity to observe and track ongoing experience, and acceptance, i.e. an orientation of openness and non-judgment toward that experience. Importantly, MAT proposes that enhancing attention monitoring in the absence of acceptance skills can actually amplify distress, because greater awareness of negative internal states is not accompanied by the regulatory resources needed to process them adaptively. Conversely, when attention monitoring is coupled with an attitude of acceptance, characterized by openness and non-judgment toward experience, MAT predicts reduced elaborative processing of aversive experiences and, in turn, lower negative emotional reactivity (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although MAT was originally articulated to specify putative mechanisms of mindfulness training, it has also been used as a process framework to interpret individual differences in trait mindfulness in cross-sectional work (see Burić et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Simione et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) operationalizes trait mindfulness through five empirically derived facets: Observing (noticing internal and external stimuli), Describing (labeling experiences with words), Acting with Awareness (attending to present activities rather than operating on autopilot), Non-judging (refraining from evaluative responses to thoughts and feelings), and Non-reactivity (allowing thoughts and feelings to come and go without becoming entangled in them). The FFMQ was originally developed by factor-analysing items pooled from five existing mindfulness questionnaires, which yielded these partially overlapping but distinguishable components of dispositional mindfulness (Baer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Subsequent work has supported the five-facet structure and its construct validity in both meditating and non-meditating samples, reinforcing the use of the FFMQ as the dominant multidimensional measure of trait mindfulness (Baer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Within a MAT-informed perspective, the Observing facet is typically taken as an index of attention monitoring, whereas Non-judging and Non-reactivity capture acceptance processes (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the operational mapping of FFMQ facets onto MAT processes, particularly for Observing, has been debated in the trait literature (Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consistent with this concern, Baer et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) reported that the relationships between Observing and indices of psychological adjustment varied as a function of meditation experience. Moreover, in endurance contexts, attentional monitoring of task-relevant internal (and external) cues has been described as central to pacing regulation and coping with sustained strain (Brick et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Vitali et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Acting with Awareness reflects the capacity to remain attentive to present activities rather than operating on “autopilot” and has shown consistent associations with lower psychological symptoms and higher well-being, suggesting a role in adaptive self-regulation that may be particularly relevant during demanding training periods (Baer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Describing occupies a more intermediate position: the ability to label internal experiences with words can simultaneously enhance monitoring (by increasing awareness and differentiation of internal states) and support regulatory processing (by facilitating more reflective engagement with emotions; Baer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Desrosiers et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Examining all five facets simultaneously therefore allows for a comprehensive examination of MAT-consistent predictions about monitoring and acceptance, while avoiding the inferential limitations that arise when only a subset of facets is analysed (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA key question concerns the pathways through which mindfulness facets relate to psychological outcomes in athletes. Sport anxiety is typically conceptualized as a tendency to perceive competitive situations as threatening and to respond with apprehension, worry, and physiological arousal (Amaro et al., 2023; Martens et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Smith et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The Sport Anxiety Scale-2 (SAS-2; Smith et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) assesses this construct by distinguishing between cognitive anxiety (worry and concentration disruption) and somatic anxiety (physiological symptoms), both of which have been linked to impaired performance and reduced well-being in competitive sport (Grossbard et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Distinguishing between these anxiety components may reveal which specific processes account for the mindfulness-burnout relationship. If acceptance facets primarily reduce ruminative worry rather than physiological arousal, stronger indirect effects through cognitive anxiety would be expected. From a MAT perspective, acceptance-related facets such as Non-judging and Non-reactivity are thought to buffer affective reactivity to stressors (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Consistent with this view, these facets show robust negative associations with worry, rumination, and anxiety symptoms in non-sport samples (Desrosiers et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Given that chronic stress and negative affect are key antecedents of athlete burnout (Goodger et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Gustafsson et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), it is plausible that acceptance-related mindfulness may protect against burnout and fatigue by dampening anxious reactivity to competitive demands.\u003c/p\u003e \u003cp\u003eIndividual differences in sex and training experience may further influence these associations. Research consistently indicates that female athletes report higher levels of sport anxiety than male athletes (Correia \u0026amp; Rosado, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Howle et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), suggesting that sex should be controlled when examining anxiety-related pathways. Training volume and competitive experience represent additional relevant factors: more experienced athletes may have developed adaptive coping strategies that buffer against anxiety and burnout, although some evidence suggests that prolonged exposure to high training demands may conversely increase burnout risk through accumulated strain (Gustafsson et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Understanding how mindfulness facets relate to outcomes across different levels of training experience can inform targeted intervention development.\u003c/p\u003e \u003cp\u003eDespite converging theoretical rationale, no study has comprehensively examined the associations between all five FFMQ facets, sport anxiety, and multiple psychological outcomes in ultra-trail runners during the pre-competition period. In ultra-endurance, existing work has concentrated mainly on performance-related psychological characteristics, particularly mental toughness and resilience (Roebuck et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Méndez-Alonso et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gameiro et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). By contrast, large-scale studies on athlete mental health have predominantly focused on team sports and Olympic disciplines, with ultra-endurance athletes largely absent from major reviews and consensus statements (Rice et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Reardon et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; but see also Thuany et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUsing MAT (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) as a heuristic process framework, the present study had four aims. First, we sought to characterize levels of burnout, fatigue, sport anxiety, and psychological well-being in a sample of ultra-trail runners assessed approximately six to eight weeks before a major competition, thereby extending emerging work on mental health in ultra-endurance athletes to this under-studied preparatory window. Second, we examined whether specific mindfulness facets, particularly those reflecting acceptance (Non-judging, Non-reactivity) and present-moment attention (Acting with Awareness), would show stronger negative associations with adverse psychological outcomes than facets primarily reflecting monitoring (Observing). Third, we tested whether sport anxiety would account for the associations between mindfulness facets and outcomes, with particular attention to the differential roles of cognitive versus somatic anxiety components. Fourth, we examined sex differences in sport anxiety and controlled for training characteristics in all analyses.\u003c/p\u003e\n\u003ch3\u003eHypotheses\u003c/h3\u003e\n\u003cp\u003eBased on MAT (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and prior work on mindfulness facets and athlete mental health, we formulated the following a priori hypotheses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1 (confirmatory).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAcceptance-related facets (Non-judging, Non-reactivity) and Acting with Awareness were expected to show the strongest associations with psychological adjustment: they should relate to lower burnout and fatigue and higher well-being, over and above demographic and training variables (Baer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Desrosiers et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Goodger et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Gustafsson et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2 (confirmatory).\u003c/b\u003e Because Observing is commonly used as a proxy for attention monitoring in trait mindfulness research (although this operational mapping remains debated), and MAT predicts that monitoring is beneficial primarily when combined with acceptance (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), we expected Observing to show weaker or null associations with outcomes than acceptance-related facets (Baer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Desrosiers et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExploratorily, we examined whether Observing might be positively related to burnout at low acceptance, by testing an Observing × Non-judging interaction, consistent with the idea that monitoring without acceptance can amplify distress (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3 (confirmatory).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe hypothesized that higher mindfulness, especially acceptance-related facets and Acting with Awareness, would be associated with lower sport anxiety, in line with evidence that mindfulness is linked to reduced competitive anxiety in athletes (Scott-Hamilton \u0026amp; Schutte, 2016; Josefsson et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Amaro \u0026amp; Brandão, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eH4 (confirmatory).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe further expected sport anxiety to partially account for associations between mindfulness facets and psychological outcomes, such that higher mindfulness would relate to lower burnout and better well-being via lower sport anxiety (Desrosiers et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Goodger et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Gustafsson et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Because fatigue may be more directly influenced by training load, we anticipated weaker indirect effects for fatigue than for burnout and well-being. In line with multidimensional anxiety theory, we also hypothesized that cognitive anxiety would show stronger indirect effects than somatic anxiety, given the central role of worry and self-focused concern (Martens et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Grossbard et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eH5 (confirmatory).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFinally, we hypothesized that women would report higher pre-competition sport anxiety than men, consistent with prior work on sex differences in competitive anxiety (Grossbard et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Amaro \u0026amp; Brandão, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Training volume and years of ultra-trail experience were treated as covariates; given mixed findings, we did not specify directional hypotheses for these control variables (Gustafsson et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lundqvist \u0026amp; Gustafsson, 2022).\u003c/p\u003e \u003cp\u003eIn addition to these a priori hypotheses, we conducted a small number of clearly labelled exploratory analyses, which we interpret cautiously.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e\n\n\n\n \n\n\n\n "},{"header":"Method","content":"\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eParticipants were ultra-trail runners registered for the Grand Raid des Pyrénées, a major ultra-endurance event in southwestern France offering three race distances beyond 80 km: 80 km (approximately 5,000 m elevation gain), 120 km (approximately 7,500 m elevation gain), and 160 km (approximately 10,000 m elevation gain). Recruitment occurred via email invitation sent to registered participants in late June to early July, six to eight weeks before the competition scheduled for late August. The study was approved by the institutional ethics committee of the University of Geneva, and all participants provided informed consent prior to completing the online survey.\u003c/p\u003e\u003cp\u003eThe final sample comprised 216 participants who provided complete data on all study variables (one participant was excluded due to missing data). The sample included 187 men (86.6%) and 29 women (13.4%), with a mean age of 41.3 years (\u003cem\u003eSD\u003c/em\u003e = 8.6, range = 24–67). Participants reported an average of 5.1 years of ultra-trail experience (\u003cem\u003eSD\u003c/em\u003e = 4.0, range = 0–26) and trained an average of 8.6 hours per week (\u003cem\u003eSD\u003c/em\u003e = 3.0, range = 2–20). Race registration was distributed across the 80 km (\u003cem\u003en\u003c/em\u003e = 77, 35.6%), 120 km (\u003cem\u003en\u003c/em\u003e = 55, 25.5%), and 160 km (\u003cem\u003en\u003c/em\u003e = 84, 38.9%) events.\u003c/p\u003e\u003ch3\u003eMeasures\u003c/h3\u003e\u003ch2\u003eMindfulness\u003c/h2\u003e\u003cp\u003eTrait mindfulness was assessed using the French version of the Five Facet Mindfulness Questionnaire-Short Form (FFMQ-15; Baer et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; French validation: Heeren et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). We used the FFMQ-15 to reduce participant burden during a demanding pre-competition period. The FFMQ-15 comprises 15 items (3 per facet) rated on a 5-point Likert scale (1 = \u003cem\u003enever or very rarely true\u003c/em\u003e to 5 = \u003cem\u003every often or always true\u003c/em\u003e). The five facets are Observing, Describing, Acting with Awareness, Non-judging, and Non-reactivity. Subscale scores were computed as the mean of the three items per facet. Although not developed specifically for sport, the FFMQ is among the most frequently used self-report measures of mindfulness in mindfulness-based sport interventions (Solé et al., 2020) and has also been used in distance-running research (see Corbally et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Sport-specific dispositional mindfulness measures are also available (e.g., the Mindfulness Inventory for Sport; Thienot et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; the Athlete Mindfulness Questionnaire; Zhang et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), but they do not provide an FFMQ-like five-facet profile, which constrained their use for the present facet-level approach. Internal consistency in the present sample was as follows: Observing (α = .68), Describing (α = .78), Acting with Awareness (α = .71), Non-judging (α = .85), and Non-reactivity (α = .72). Internal consistency was acceptable for most facets; Observing showed slightly lower reliability, suggesting that associations involving this facet should be interpreted with some caution.\u003c/p\u003e\u003ch3\u003eSport Anxiety\u003c/h3\u003e\u003cp\u003eCompetitive anxiety was measured using the French version of the Sport Anxiety Scale-2 (SAS-2; Smith et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; French validation: Fournier et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Instructions were modified to assess anticipatory anxiety specific to the upcoming competition rather than general trait competitive anxiety: participants were asked to indicate how they typically feel \"before the upcoming competition\" rather than \"generally during competition.\" The SAS-2 comprises 15 items rated on a 4-point Likert scale (1 = \u003cem\u003enot at all\u003c/em\u003e to 4 = \u003cem\u003every much\u003c/em\u003e). Items assess cognitive anxiety (worry and concentration disruption) and somatic anxiety (physiological symptoms). A total sport anxiety score was computed as the mean of all 15 items, and subscale scores for cognitive and somatic anxiety were computed separately for supplementary analyses. Internal consistency was adequate: total scale (α = .90), cognitive anxiety (α = .87), and somatic anxiety (α = .86).\u003c/p\u003e\u003ch2\u003eAthlete Burnout\u003c/h2\u003e\u003cp\u003eBurnout was assessed using the French version of the Athlete Burnout Questionnaire (ABQ; Raedeke \u0026amp; Smith, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; French validation: Isoard-Gautheur et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The ABQ comprises 15 items rated on a 5-point Likert scale (1 = \u003cem\u003ealmost never\u003c/em\u003e to 5 = \u003cem\u003ealmost always\u003c/em\u003e) assessing three dimensions: emotional/physical exhaustion, reduced sense of accomplishment, and sport devaluation. A global burnout score was computed as the mean of all 15 items. Internal consistency in the present sample was good (α = .87).\u003c/p\u003e\u003ch3\u003eFatigue\u003c/h3\u003e\u003cp\u003eGeneral fatigue was assessed using the Chalder Fatigue Scale (Chalder et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), a widely used measure of physical and mental fatigue. The scale comprises 10 items assessing symptoms such as problems with tiredness, need for rest, sleepiness, difficulty starting or completing tasks, lack of energy, muscle weakness, and concentration difficulties. Items are rated on a 4-point Likert scale (0 = \u003cem\u003eless than usual\u003c/em\u003e to 3 = \u003cem\u003emuch more than usual\u003c/em\u003e). A total fatigue score was computed as the mean of all items, with higher scores indicating greater fatigue. Internal consistency was adequate (α = .84).\u003c/p\u003e\u003ch3\u003ePsychological Well-Being\u003c/h3\u003e\u003cp\u003eWell-being was assessed using the World Health Organization Well-Being Index (WHO-5; Topp et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), a brief measure of subjective well-being. Although not sport-specific, the WHO-5 provides a brief index of general psychological well-being with extensive validation and is commonly used as a screening tool (Topp et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The WHO-5 comprises 5 items rated on a 6-point Likert scale (0 = \u003cem\u003eat no time\u003c/em\u003e to 5 = \u003cem\u003eall of the time\u003c/em\u003e) assessing positive mood and vitality over the past two weeks. Raw scores were transformed to a 0-100 scale, with higher scores indicating greater well-being. A score below 50 indicates impaired well-being warranting clinical attention (Topp et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Internal consistency was good (α = .84).\u003c/p\u003e\u003ch2\u003eCovariates\u003c/h2\u003e\u003cp\u003eDemographic and training variables assessed as potential covariates included age (years), sex (0 = female, 1 = male), years of ultra-trail experience, and weekly training hours.\u003c/p\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll analyses were conducted using R version 4.3.1 (R Core Team, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Descriptive statistics were computed using the \u003cem\u003epsych\u003c/em\u003e package (Revelle, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Effect sizes were calculated using the \u003cem\u003eeffectsize\u003c/em\u003e package (Ben-Shachar et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Multicollinearity was assessed via Variance Inflation Factors using the \u003cem\u003ecar\u003c/em\u003e package (Fox \u0026amp; Weisberg, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIndirect effects were tested using structural equation modeling with the lavaan package (Rosseel, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Indirect effects were estimated using bootstrap confidence intervals with 5,000 resamples, with significance determined by 95% CIs excluding zero. In the parallel mediation models, we tested whether the indirect effect via cognitive anxiety differed from that via somatic anxiety using a bootstrapped contrast (ab_cog - ab_som). It is important to note that these cross-sectional mediation analyses test whether the data are consistent with the hypothesized indirect pathways, but cannot establish causal mediation (Maxwell \u0026amp; Cole, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Sensitivity analyses for robustness to unmeasured confounding were conducted using the mediation package (Tingley et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Simple slopes for interaction effects were computed using the emmeans package (Lenth, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStatistical significance was set at \u003cem\u003ep\u003c/em\u003e \u0026lt; .05 (two-tailed) for confirmatory analyses. For exploratory analyses, effects with \u003cem\u003ep\u003c/em\u003e \u0026lt; .10 were flagged as trends warranting discussion. Effect sizes were interpreted according to Cohen's (1988) guidelines.\u003c/p\u003e\u003ch2\u003eSensitivity Analyses\u003c/h2\u003e\u003cp\u003eSensitivity analyses for statistical power were conducted using the \u003cem\u003epwr\u003c/em\u003e package (Champely, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Given N = 216 and nine predictors in the full regression models (five mindfulness facets and four covariates), the analyses indicated that the design had 80% power to detect an overall effect size of approximately \u003cem\u003ef\u003c/em\u003e² = 0.08, corresponding to \u003cem\u003eR²\u003c/em\u003e ≈ .07. With the observed imbalance in group sizes for sex (29 women, 187 men), the analyses showed that we had 80% power to detect sex differences in sport anxiety of about d ≈ 0.56; smaller group differences may therefore have gone undetected. For the Observing × Non-judging interaction, sensitivity analysis indicated that we had 80% power to detect an incremental effect of about \u003cem\u003ef\u003c/em\u003e² ≈ 0.04 (\u003cem\u003eΔR\u003c/em\u003e² ≈ .04).\u003c/p\u003e\u003cp\u003eFor the mediation models, statistical power depends on the magnitude of both the a path (mindfulness → sport anxiety) and the b path (sport anxiety → outcomes). Simulation studies on mediation indicate that sample sizes around N ≈ 200 provide adequate power to detect indirect effects when both paths are at least medium in size, but substantially lower power when one or both paths are small (Fritz \u0026amp; MacKinnon, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Thus, the present design is well suited to detecting indirect effects of at least moderate magnitude, whereas smaller mediated effects and subtle differences between parallel mediators (cognitive vs. somatic anxiety) may have gone undetected.\u003c/p\u003e\u003cp\u003eThese sensitivity thresholds are broadly consistent with typical effect sizes reported in the literature. Meta-analyses indicate that dispositional mindfulness tends to show small-to-moderate associations with motivation and mental health indicators (|\u003cem\u003er\u003c/em\u003e| ≈ .20–.35; Enkema et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), whereas more proximal constructs such as sport-specific stress and burnout or burnout and anxiety often correlate at moderate-to-large levels (\u003cem\u003er\u003c/em\u003e ≈ .40–.50; Glandorf et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lin et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, the present design is well suited to detecting the magnitude of effects typically observed between mindfulness facets and psychological outcomes, while very small associations or subtle differences between pathways may remain undetected.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePreliminary Analyses\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eDescriptive Statistics\u003c/h2\u003e \u003cp\u003eDescriptive statistics for all psychological variables are presented in Table\u0026nbsp;1. Mindfulness facets showed adequate variability, with means ranging from 2.83 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89) for Observing to 3.53 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.79) for Acting with Awareness on the 1\u0026ndash;5 scale. Sport anxiety levels were relatively low (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.00, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.58), with cognitive anxiety (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.20, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.74) slightly higher than somatic anxiety (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.84, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.59). Burnout levels were low to moderate (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.20, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.54), fatigue was low (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.26, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37), and well-being was moderate (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;59.41, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;16.37). All variables showed acceptable skewness and kurtosis for parametric analyses (|skew| \u0026lt; 1, |kurtosis| \u0026lt; 1).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eClinical Prevalence\u003c/h2\u003e \u003cp\u003eDespite generally positive mean levels, a notable proportion of participants showed elevated symptoms. Approximately one quarter of participants (23.6%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;51) reported impaired well-being (WHO-5\u0026thinsp;\u0026lt;\u0026thinsp;50), while 7.9% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17) showed elevated burnout symptoms (ABQ\u0026thinsp;\u0026ge;\u0026thinsp;3) and 4.2% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9) reported high fatigue levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSex Differences\u003c/h2\u003e \u003cp\u003eIndependent-samples \u003cem\u003et\u003c/em\u003e-tests revealed significant sex differences in sport anxiety. Women reported higher total sport anxiety than men (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.28, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.62 \u003cem\u003evs\u003c/em\u003e. \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.95, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.56), \u003cem\u003et\u003c/em\u003e(214)\u0026thinsp;=\u0026thinsp;2.87, \u003cem\u003ep\u003c/em\u003e = .007, \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.57. This difference was observed for both cognitive anxiety (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.38, \u003cem\u003ep\u003c/em\u003e = .045) and somatic anxiety (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.64, \u003cem\u003ep\u003c/em\u003e = .009). No significant sex differences emerged for burnout, fatigue, well-being, or mindfulness facets (all \u003cem\u003ep\u003c/em\u003es \u0026gt; .05). These findings support H5 and justify including sex as a covariate in subsequent analyses. Given the small number of women in the sample (n\u0026thinsp;=\u0026thinsp;29), these comparisons should be interpreted cautiously, and smaller sex differences may have gone undetected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eRace Distance Differences\u003c/h2\u003e \u003cp\u003eOne-way ANOVAs revealed no significant differences across race distances for any psychological variable (all \u003cem\u003ep\u003c/em\u003es \u0026gt; .05). However, race distance was associated with years of experience, \u003cem\u003eF\u003c/em\u003e(2, 213)\u0026thinsp;=\u0026thinsp;13.64, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, and weekly training hours, \u003cem\u003eF\u003c/em\u003e(2, 213)\u0026thinsp;=\u0026thinsp;3.16, \u003cem\u003ep\u003c/em\u003e = .045, with longer distances associated with greater experience and training volume.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eZero-Order Correlations\u003c/h2\u003e \u003cp\u003eZero-order correlations among study variables are presented in Table\u0026nbsp;2. Consistent with expectations, Non-judging showed significant negative correlations with burnout (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.36), fatigue (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.31), and sport anxiety (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.36), and a positive correlation with well-being (\u003cem\u003er\u003c/em\u003e = .35). Acting with Awareness showed a similar pattern, with notable associations with burnout (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.36) and fatigue (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.24). Non-reactivity was associated with well-being (\u003cem\u003er\u003c/em\u003e = .28) and sport anxiety (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.29). In contrast, Observing showed near-zero correlations with all outcomes (\u003cem\u003er\u003c/em\u003es\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.04 to .06). Sport anxiety was significantly correlated with burnout (\u003cem\u003er\u003c/em\u003e = .39), fatigue (\u003cem\u003er\u003c/em\u003e = .22), and well-being (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.33). Notably, years of experience showed a small but significant positive correlation with burnout (\u003cem\u003er\u003c/em\u003e = .15, \u003cem\u003ep\u003c/em\u003e = .026).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Analyses: Mindfulness Facets and Psychological Outcomes (H1, H2)\u003c/h2\u003e \u003cp\u003eMultiple regression analyses tested the unique associations between the five FFMQ facets and each outcome, controlling for age, sex, years of experience, and weekly training hours. All five facets were entered simultaneously.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eBurnout\u003c/h2\u003e \u003cp\u003eThe overall model significantly predicted burnout, \u003cem\u003eF\u003c/em\u003e(9, 206)\u0026thinsp;=\u0026thinsp;8.00, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eR\u003c/em\u003e\u0026sup2; = .259. Acting with Awareness showed the strongest negative association (\u003cem\u003eB\u003c/em\u003e = -0.21, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05, β = \u0026minus;\u0026thinsp;.30, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), followed by Non-judging (\u003cem\u003eB\u003c/em\u003e = -0.15, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04, β = \u0026minus;\u0026thinsp;.25, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Non-reactivity showed a trend (β = \u0026minus;\u0026thinsp;.12, \u003cem\u003ep\u003c/em\u003e = .082). Observing showed a trend toward a positive association (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.11, \u003cem\u003ep\u003c/em\u003e = .083). Among covariates, years of experience was positively associated with burnout (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.16, \u003cem\u003ep\u003c/em\u003e = .025).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eFatigue\u003c/h2\u003e \u003cp\u003eThe model significantly predicted fatigue, \u003cem\u003eF\u003c/em\u003e(9, 206)\u0026thinsp;=\u0026thinsp;5.15, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eR\u003c/em\u003e\u0026sup2; = .184. Non-judging (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.24, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) and Acting with Awareness (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.20, \u003cem\u003ep\u003c/em\u003e = .006) were significant predictors. Weekly training hours were negatively associated with fatigue (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.15, \u003cem\u003ep\u003c/em\u003e = .018).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eWell-Being\u003c/h2\u003e \u003cp\u003eThe model significantly predicted well-being, \u003cem\u003eF\u003c/em\u003e(9, 206)\u0026thinsp;=\u0026thinsp;5.56, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eR\u003c/em\u003e\u0026sup2; = .196. Three facets emerged as significant predictors: Non-judging (β\u0026thinsp;=\u0026thinsp;.27, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), Non-reactivity (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.20, \u003cem\u003ep\u003c/em\u003e = .003), and Acting with Awareness (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.15, \u003cem\u003ep\u003c/em\u003e = .030).\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eSummary of H1 and H2\u003c/h2\u003e \u003cp\u003eResults provided strong support for H1: Non-judging and Acting with Awareness were consistently associated with lower burnout and fatigue and higher well-being, with medium effect sizes (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.20-.30). Non-reactivity was additionally associated with well-being. Regarding H2, Observing showed null or marginally positive associations with outcomes, consistent with the mixed evidence on the Observing facet in trait mindfulness research and with MAT\u0026rsquo;s emphasis that monitoring processes may be most adaptive when accompanied by acceptance. Multicollinearity was not a concern (all VIF\u0026thinsp;\u0026lt;\u0026thinsp;1.35). As a robustness check, we also estimated single-facet models (each mindfulness facet entered separately, controlling for covariates); patterns were broadly similar, though coefficients for some facets were attenuated in the full model, consistent with shared variance among facets (see Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eMindfulness Facets and Sport Anxiety (H3)\u003c/h2\u003e \u003cp\u003eA multiple regression model tested associations between FFMQ facets and total sport anxiety, \u003cem\u003eF\u003c/em\u003e(9, 206)\u0026thinsp;=\u0026thinsp;6.91, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eR\u003c/em\u003e\u0026sup2; = .232. Non-judging was the strongest predictor (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.25, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), followed by Non-reactivity (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.19, \u003cem\u003ep\u003c/em\u003e = .005). These results support H3.\u003c/p\u003e \u003cp\u003eSupplementary analyses examining cognitive and somatic anxiety separately revealed that Non-judging was particularly strongly associated with cognitive anxiety (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.35, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) compared to somatic anxiety (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.10, \u003cem\u003ep\u003c/em\u003e = .145). Non-reactivity was associated with both cognitive (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.15, \u003cem\u003ep\u003c/em\u003e = .023) and somatic anxiety (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.18, \u003cem\u003ep\u003c/em\u003e = .009). These differential patterns suggest that Non-judging is primarily associated with reduced cognitive worry, with only a weak and non-significant association with somatic symptoms of anxiety.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eIndirect Effects Through Sport Anxiety (H4)\u003c/h2\u003e \u003cdiv id=\"Sec28\" class=\"Section4\"\u003e \u003ch2\u003eSimple Indirect Effects: Non-judging to Sport Anxiety to Outcomes\u003c/h2\u003e \u003cp\u003e \u003cb\u003eBurnout.\u003c/b\u003e The indirect effect model showed significant paths: Non-judging was negatively associated with sport anxiety (path \u003cem\u003ea\u003c/em\u003e: \u003cem\u003eB\u003c/em\u003e = -0.162, 95% CI [-0.254, -0.072]), and sport anxiety was positively associated with burnout (path \u003cem\u003eb\u003c/em\u003e: \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.259, 95% CI [0.142, 0.376]). The indirect effect was significant (\u003cem\u003eab\u003c/em\u003e = -0.042, 95% CI [-0.077, -0.015]), suggesting that sport anxiety shows a meaningful statistical indirect association in the Non-judging\u0026ndash;burnout link. The proportion of the total effect represented by this indirect pathway was 27.8%. The direct effect remained significant (\u003cem\u003ec'\u003c/em\u003e = -0.109, \u003cem\u003ep\u003c/em\u003e = .007), consistent with a partial statistical mediation pattern.\u003c/p\u003e \u003cp\u003e \u003cb\u003eWell-being.\u003c/b\u003e Sport anxiety also showed a significant indirect association in the link between Non-judging and well-being. The indirect effect was significant (\u003cem\u003eab\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.057, 95% CI [0.326, 1.999]), with 21.4% of the total effect going through this pathway.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFatigue.\u003c/b\u003e For fatigue, the indirect effect was not significant (\u003cem\u003eab\u003c/em\u003e = -0.013, 95% CI [-0.035, 0.002]), despite significant total and direct effects. This pattern suggests that sport anxiety does not play a substantial indirect role in the mindfulness\u0026ndash;fatigue association, consistent with our prediction that fatigue is more directly influenced by training load.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eParallel Indirect Effects: Cognitive vs. Somatic Anxiety\u003c/h2\u003e \u003cp\u003eA parallel mediation model tested whether cognitive and somatic anxiety carried distinct components of the Non-judging\u0026ndash;burnout association (Table\u0026nbsp;4; Fig.\u0026nbsp;1). Non-judging was strongly associated with lower cognitive anxiety (path a1: \u003cem\u003eB\u003c/em\u003e = -0.283, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.060, 95% CI [-0.403, -0.170], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) but showed a weaker, non-significant association with somatic anxiety (path a2: \u003cem\u003eB\u003c/em\u003e = -0.067, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.046, 95% \u003cem\u003eCI\u003c/em\u003e [-0.159, 0.022], \u003cem\u003ep\u003c/em\u003e = .144). Cognitive anxiety, in turn, was positively associated with burnout (path b1: \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.197, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.064, 95% CI [0.059, 0.320], \u003cem\u003ep\u003c/em\u003e = .003), whereas somatic anxiety was not (path b2: \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.044, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.074, 95% \u003cem\u003eCI\u003c/em\u003e [-0.098, 0.192], \u003cem\u003ep\u003c/em\u003e = .558). The direct effect of Non-judging on burnout remained significant when both mediators were included (c': \u003cem\u003eB\u003c/em\u003e = -0.092, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043, 95% \u003cem\u003eCI\u003c/em\u003e [-0.178, -0.008], \u003cem\u003ep\u003c/em\u003e = .033). Consistent with these paths, the total indirect effect in the parallel mediation model was \u003cem\u003eB\u003c/em\u003e = -0.059 (\u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021, 95% \u003cem\u003eCI\u003c/em\u003e [-0.106, -0.021], \u003cem\u003ep\u003c/em\u003e = .006; Table\u0026nbsp;4), slightly larger in magnitude than the indirect effect observed in the model using total sport anxiety (ab = -0.042).\u003c/p\u003e \u003cp\u003eThe indirect effect through cognitive anxiety was significant (ab_cog = -0.056, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022, 95% \u003cem\u003eCI\u003c/em\u003e [-0.107, -0.017], \u003cem\u003ep\u003c/em\u003e = .015), whereas the indirect effect through somatic anxiety was not (ab_som = -0.003, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006, 95% \u003cem\u003eCI\u003c/em\u003e [-0.025, 0.005], \u003cem\u003ep\u003c/em\u003e = .641). A bootstrapped contrast indicated that the indirect effect via cognitive anxiety was larger in magnitude than the indirect effect via somatic anxiety (ab_cog - ab_som = -0.053, 95% \u003cem\u003eCI\u003c/em\u003e [-0.110, -0.009], \u003cem\u003ep\u003c/em\u003e = .041). These indirect components represented 37.1% and 2.0% of the total Non-judging\u0026ndash;burnout effect, respectively. This pattern supports H4\u0026rsquo;s prediction that statistical indirect associations via cognitive anxiety would be stronger than via somatic anxiety and is consistent with the idea that Non-judging is more strongly related to burnout through reduced cognitive worry than through somatic symptoms of anxiety, while recognizing that these cross-sectional data do not permit causal conclusions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSensitivity Analysis\u003c/h3\u003e\n\u003cp\u003eSensitivity analysis assessed the robustness of the indirect effect to unmeasured confounding. The correlation between residuals (ρ) at which the indirect effect would equal zero was 0.30, indicating moderate robustness to potential confounding. This suggests that a moderately strong unmeasured confounder would be required to nullify the observed indirect effect. Additionally, we examined whether prior relaxation training experience (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;26, 12.0%) influenced the main findings. When included as an additional covariate, relaxation training did not significantly predict burnout (\u003cem\u003eB\u003c/em\u003e = -0.10, \u003cem\u003ep\u003c/em\u003e = .32), fatigue (\u003cem\u003eB\u003c/em\u003e = -0.04, \u003cem\u003ep\u003c/em\u003e = .63), or well-being (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.27, \u003cem\u003ep\u003c/em\u003e = .31), and all FFMQ facet coefficients remained virtually unchanged (all \u003cem\u003eΔβ\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01, \u003cem\u003eΔR\u0026sup2;\u003c/em\u003e \u0026lt; .004).\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eExploratory Analyses\u003c/h2\u003e \u003cdiv id=\"Sec32\" class=\"Section3\"\u003e \u003ch2\u003eObserving \u0026times; Non-judging Interaction\u003c/h2\u003e \u003cp\u003eBased on MAT, we examined whether Non-judging moderated the association between Observing and burnout. The Observing \u0026times; Non-judging interaction was small and marginal (\u003cem\u003eB\u003c/em\u003e = -0.081, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042, \u003cem\u003ep\u003c/em\u003e = .057), accounting for an additional 1.3% of variance. To describe this pattern, we probed conditional associations at \u0026plusmn;\u0026thinsp;1 \u003cem\u003eSD\u003c/em\u003e of Non-judging. At low Non-judging (\u0026minus;\u0026thinsp;1 \u003cem\u003eSD\u003c/em\u003e), higher Observing was associated with higher burnout (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.149, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.058, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.59, \u003cem\u003ep\u003c/em\u003e = .010), whereas at high Non-judging (+\u0026thinsp;1 SD), Observing was not associated with burnout (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003ep\u003c/em\u003e = .954). Given the marginal interaction and the limited power to detect small moderation effects, this pattern should be interpreted as exploratory and in need of replication.\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section4\"\u003e \u003ch2\u003eExperience and Burnout\u003c/h2\u003e \u003cp\u003eAn unexpected finding was the positive association between years of experience and burnout. Controlling for age and training volume, years of experience remained a significant predictor (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025, \u003cem\u003ep\u003c/em\u003e = .018). This effect was particularly evident for sport devaluation (\u003cem\u003er\u003c/em\u003e = .19). Testing for curvilinearity, the quadratic term was not significant (\u003cem\u003ep\u003c/em\u003e = .148), indicating a linear relationship. However, the effect size was small (\u003cem\u003er\u003c/em\u003e = .15), and this cross-sectional association should be interpreted cautiously. Several mechanisms may explain this pattern, including accumulated strain, elevated expectations, or selection effects, but longitudinal research is needed to understand this relationship.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study examined associations between mindfulness facets, sport anxiety, and psychological outcomes in ultra-trail runners during the pre-competition period. Drawing on MAT (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), we examined whether acceptance-related mindfulness facets would show stronger associations with mental health than attention monitoring, and whether sport anxiety, particularly cognitive worry, would statistically account for these associations. Overall, the pattern of results was broadly compatible with these expectations and extends our understanding of mindfulness in athlete mental health to an under-studied population assessed during a theoretically important preparatory window. Acceptance-related facets and Acting with Awareness showed the strongest links with mental health; Observing played a limited and context-dependent role; and sport anxiety, particularly its cognitive component, showed indirect statistical associations with the links between Non-judging and both burnout and well-being, whereas sex differences were limited, noting the small number of women in the sample.\u003c/p\u003e\n\u003ch3\u003eSample Characteristics and Mental Health Status\u003c/h3\u003e\n\u003cp\u003eThe demographic profile of our sample, predominantly male, middle-aged, and moderately experienced, closely mirrors the broader ultra-endurance population described in recent surveys (Hoffman \u0026amp; Fogard, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Knechtle et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Thuany et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Assessed six to eight weeks before competition, participants were navigating the demanding final mesocycles of preparation characterized by high training volumes, occupational and family responsibilities, and anticipatory concerns about the upcoming event (Bali, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Niering et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This timing is particularly relevant because the pre-competition period may paradoxically heighten vulnerability to negative psychological states: athletes must balance peak training demands with the accumulated psychological costs of months of intensive preparation while managing uncertainty about their readiness (Raglin \u0026amp; Morris, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA notable finding concerns the prevalence of psychological difficulties despite generally positive mean scores. Nearly one quarter of participants reported well-being below clinical thresholds, suggesting that a meaningful proportion of ultra-trail runners experience compromised mental health during preparation. This aligns with emerging evidence that mental health concerns in ultra-endurance athletes may be more common than previously recognized (Gameiro et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Niering et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and underscores the value of examining psychological resources that may support adaptation during this demanding phase.\u003c/p\u003e\n\u003ch3\u003eDifferential Associations of Mindfulness Facets\u003c/h3\u003e\n\u003cp\u003eIn line with MAT\u0026rsquo;s emphasis on acceptance-related processes, Non-judging and Acting with Awareness emerged as the facets most consistently associated with favorable outcomes. These findings extend prior research identifying Non-judging as particularly relevant for athlete adjustment (Josefsson et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kinnunen et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to the ultra-trail context. The pattern is theoretically coherent: athletes who refrain from harsh self-evaluation of internal experiences (Non-judging) and who maintain attentional engagement with present activities rather than drifting into rumination or worry (Acting with Awareness) may be better equipped to navigate the psychological demands of intensive training periods without developing burnout symptoms or compromised well-being.\u003c/p\u003e \u003cp\u003eActing with Awareness showed associations comparable in magnitude to Non-judging, which warrants interpretation. During demanding training phases, athletes face continuous decisions about pacing, recovery, and effort allocation. The capacity to remain attentively engaged with these moment-to-moment demands\u0026mdash;rather than operating on autopilot or becoming absorbed in performance-related worries\u0026mdash;may support more adaptive self-regulation. This interpretation aligns with broader evidence that Acting with Awareness is among the FFMQ facets most consistently linked to reduced psychological symptoms across populations (Carpenter et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNon-reactivity showed a more selective pattern, predicting well-being but not burnout or fatigue in multivariate models. This facet\u0026mdash;allowing thoughts and feelings to arise and pass without becoming entangled\u0026mdash;may be particularly relevant for maintaining positive psychological states. During intensive preparation, negative thoughts and doubts are likely common; the capacity to observe these experiences without elaborative engagement may preserve well-being without necessarily reducing the exhaustion or devaluation components of burnout.\u003c/p\u003e \u003cp\u003eObserving showed null to marginally positive associations with burnout, consistent with debates about this facet's role in psychological adjustment (Baer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Lilja et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The exploratory interaction analysis suggested that Observing may relate to higher burnout specifically when Non-judging is low. Although this conditional pattern is compatible with MAT\u0026rsquo;s moderation hypothesis, the interaction was marginal and should be interpreted cautiously. More broadly, this result is best viewed as hypothesis-generating, given ongoing debates about the operationalization of monitoring via Observing and the limited power to detect small moderation effects in the present sample. Such moderation patterns have been proposed and examined in other contexts (e.g., Lindsay et al., 2019), warranting replication in sport samples.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eCognitive Anxiety as an Indirect Pathway\u003c/h2\u003e \u003cp\u003eA central contribution of this study concerns the differential roles of cognitive \u003cem\u003evs\u003c/em\u003e. somatic anxiety. Parallel indirect models indicated that cognitive anxiety was associated with a larger proportion of the Non-judging\u0026ndash;burnout association than somatic anxiety, which contributed negligibly; a bootstrapped contrast supported this difference between indirect effects. This asymmetry suggests that the association between Non-judging and burnout may be more closely tied to reduced ruminative worry than to lower physiological arousal.\u003c/p\u003e \u003cp\u003eThis finding has both theoretical and practical implications. Theoretically, it is consistent with a plausible cognitive pathway linking acceptance-related mindfulness to athlete burnout: by reducing harsh evaluation of internal experiences, Non-judging may attenuate the self-critical rumination and performance concerns that characterize competitive anxiety, thereby reducing downstream risk for emotional exhaustion and sport devaluation. This interpretation is consistent with evidence that cognitive emotion-regulation processes such as worry and rumination can statistically mediate associations between mindfulness and anxiety symptoms (Desrosiers et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), suggesting that mindfulness-related skills may be linked to athlete burnout partly through reduced cognitive overengagement. Practically, these findings tentatively suggest that interventions targeting cognitive worry through acceptance-based techniques, such as cognitive defusion or decentering, may be more relevant for burnout prevention than approaches focused on somatic relaxation, although longitudinal and experimental confirmation is needed.\u003c/p\u003e \u003cp\u003eNotably, sport anxiety did not account for the mindfulness\u0026ndash;fatigue association. Fatigue during intensive training is likely more directly tied to physiological load, recovery, and sleep than to cognitive worry, which may explain why anxiety does not serve as an indirect pathway for this outcome. This pattern is consistent with work highlighting the predominant role of training load, recovery, and non-functional overreaching in the development of athlete fatigue, relative to purely cognitive-emotional factors (Meeusen et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Schwellnus et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eSex Differences and Experience-Related Patterns\u003c/h2\u003e \u003cp\u003eConsistent with prior sport psychology research (Correia \u0026amp; Rosado, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Grossbard et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), women reported higher pre-competition anxiety than men. Importantly, however, no sex differences emerged for burnout, fatigue, or well-being, suggesting that elevated anxiety does not automatically translate into differential mental health outcomes\u0026mdash;possibly because other resources buffer its downstream effects. Given the marked underrepresentation of women in ultra-endurance research, this finding highlights the importance of attending to sex-specific experiences while avoiding assumptions about differential vulnerability.\u003c/p\u003e \u003cp\u003eAn unexpected finding was the positive association between years of experience and burnout, particularly sport devaluation. Although the effect was small, it persisted after controlling for age and training volume. This pattern contrasts with intuitions about the protective role of expertise and aligns with accumulated strain models of burnout (Gustafsson et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Experienced runners may face rising expectations, chronic exposure to demanding preparation cycles, or selection effects whereby highly motivated individuals persist despite symptoms. Whatever the mechanism, this finding suggests that experience alone does not confer psychological resilience, and that even veteran athletes may benefit from monitoring and support.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003ePractical Implications\u003c/h2\u003e \u003cp\u003eSeveral practical considerations emerge, though they warrant cautious interpretation pending experimental evidence. First, the prevalence of compromised well-being suggests that routine screening during pre-competition phases may be valuable; brief tools such as the WHO-5 could be incorporated into athlete monitoring. Second, the consistent associations between acceptance-related facets and favorable outcomes suggest that interventions emphasizing Non-judging and Acting with Awareness (e.g., Mindfulness-Acceptance-Commitment; Gardner \u0026amp; Moore, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; MSPE; Kaufman et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) could be prioritized for evaluation in ultra-endurance contexts. Third, the specificity of cognitive anxiety as an indirect association suggests that techniques targeting ruminative worry (e.g., cognitive defusion, decentering) may be particularly relevant targets to examine in future burnout prevention research. Finally, practitioners should be attentive to burnout signs among experienced athletes, who may be at elevated risk despite their accumulated expertise.\u003c/p\u003e \u003cdiv id=\"Sec40\" class=\"Section3\"\u003e \u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e \u003cp\u003eSeveral limitations warrant acknowledgment. Most importantly, the cross-sectional design precludes causal inference. Although SAS-2 (Smith et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) instructions were framed to the upcoming competition, the instrument was originally developed to assess dispositional competitive anxiety; thus, the psychometric implications of this contextual framing warrant replication using repeated assessments closer to race day. Although indirect effect analyses suggest that anxiety statistically accounts for part of the mindfulness\u0026ndash;burnout association, temporal precedence cannot be established. Cross-sectional mediation can yield biased estimates of longitudinal processes (Maxwell \u0026amp; Cole, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and sensitivity analyses indicated only moderate robustness to unmeasured confounding. Stable personality traits such as neuroticism (Hanley \u0026amp; Garland, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and contextual factors such as social support (Luo et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) could plausibly influence both mindfulness and outcomes. Longitudinal designs tracking athletes across the pre-competition period are needed to establish temporal ordering. In addition, because recruitment relied on volunteers responding to an online invitation, participants may differ from non-responders (e.g., in psychological openness or current mental health status). This self-selection limits the generalizability of the findings to all ultra-trail runners registered for the event. Finally, all variables were assessed via self-report questionnaires administered in a single online session, raising the possibility of common method variance and self-report biases (Podsakoff et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Incorporating behavioral or physiological indicators of anxiety and regulatory processes (e.g., heart rate variability, sleep, or training-load metrics) alongside self-reported mindfulness and burnout would help to reduce shared method variance and provide a more multi-dimensional picture of mental health in ultra-trail runners (Matsuura et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Charest et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Thuany et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides a comprehensive examination of mindfulness facets, sport anxiety, and psychological outcomes in ultra-trail runners during the pre-competition period. Acceptance-related mindfulness facets, particularly Non-judging and Acting with Awareness, showed consistent associations with lower burnout and fatigue and higher well-being. Cognitive anxiety showed a specific statistical indirect association in the Non-judging\u0026ndash;burnout link, whereas somatic anxiety played a negligible role. Although the cross-sectional design precludes causal inference, these findings are consistent with the possibility that acceptance-focused mindfulness training and cognitive decentering may be promising targets for future longitudinal and intervention studies in ultra-endurance athletes.x\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Principles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Commission Universitaire de Recherche \u0026Eacute;thique de Gen\u0026egrave;ve (CUREG 2.0), University of Geneva (reference number: CUREG-20250423-421-2, approved 12 June 2025). The research was conducted in accordance with the ethical principles of the Declaration of Helsinki. Prior to completing the online survey, all runners received detailed information about the study purpose and procedures, participant rights (including the voluntary nature of participation and the right to withdraw at any time without consequence), and the measures implemented to protect confidentiality. Electronic informed consent was obtained before participation. Data were handled anonymously (or de-identified) and treated as confidential throughout the research process, and participants were informed that the collected data would be used solely for scientific purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Swiss National Science Foundation (PCEFP1_186911).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Steeve Azevedo, Bhavya Jain, Charlotte Mancini, and Joao Marcos for their assistance with protocol implementation and data collection. We also gratefully acknowledge the Grand Raid des Pyr\u0026eacute;n\u0026eacute;es organization for allowing us to conduct this study as part of their event and for their support with participant recruitment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT Author Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePL: conceptualization, study design, data collection coordination, statistical analysis, tables and figure, writing\u0026mdash;original draft and writing\u0026mdash;review \u0026amp; editing. JC: study design and writing\u0026mdash;review \u0026amp; editing. RAP: writing\u0026mdash;review \u0026amp; editing. UR: supervision and writing\u0026mdash;review \u0026amp; editing. All authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report there are no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003cbr\u003e\u003c/strong\u003eDeidentified data and analysis code are available on the Open Science Framework at https://osf.io/uc7hf/?view_only=0efb487e03c449b7ba14ddf1f8450dec\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmaro R, Brand\u0026atilde;o T. Competitive anxiety in athletes: Emotion regulation and personality matter. Kinesiology. 2023;55(1):108\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaer RA, Smith GT, Hopkins J, Krietemeyer J, Toney L. Using self-report assessment methods to explore facets of mindfulness. 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style=\"width: 11px;\"\u003e\n \u003cp\u003eScale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026alpha;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eObserving\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eDescribing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eActing with Awareness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eNon-judging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eNon-reactivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eSport Anxiety (total)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Cognitive anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Somatic anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eBurnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eWell-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e59.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e16.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e88.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eFFMQ = Five Facet Mindfulness Questionnaire; Sport anxiety assessed with SAS-2; Burnout assessed with ABQ; Fatigue assessed with Chalder Fatigue Scale; Well-being assessed with WHO-5.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"116%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eZero-Order Correlations Among Study Variables (N = 216)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1. Observing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e2. Describing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e3. Acting Aware\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.37\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4. Non-judging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e5. Non-reactivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e6. Sport Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.16\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.22\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e7. Burnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.39\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e8. Fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.22\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.51\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e9. Well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.33\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.45\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e10. Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e11. Experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.15\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.46\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e12. Training h/wk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. * \u003cem\u003ep\u003c/em\u003e \u0026lt; .05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; .01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eMultiple Regression Results: FFMQ Facets Predicting Psychological Outcomes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBurnout\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFatigue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWell-being\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eObserving\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.451\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eDescribing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eActing with Awareness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.30\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.15\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eNon-judging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.25\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.27\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eNon-reactivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e(9, 206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e8.00\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e5.15\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e5.56\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eStandardized coefficients (\u0026beta;) reported. Models control for age, sex, years of experience, and weekly training hours. * \u003cem\u003ep\u003c/em\u003e \u0026lt; .05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; .01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; .001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eParallel Indirect Effects: Cognitive vs. Somatic Anxiety in the Non-judging\u0026ndash;Burnout Association\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cem\u003ea\u003c/em\u003e1: NJ \u0026rarr; Cognitive anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.403, -0.170]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cem\u003ea\u003c/em\u003e2: NJ \u0026rarr; Somatic anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.160, 0.020]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e1: Cognitive anxiety \u0026rarr; Burnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[0.073, 0.324]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e2: Somatic anxiety \u0026rarr; Burnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.107, 0.185]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cem\u003ec\u0026apos;\u003c/em\u003e: Direct effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.178, -0.009]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eIndirect via cognitive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.105, -0.018]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eIndirect via somatic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.018, 0.009]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.640\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eTotal indirect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.103, -0.021]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eTotal effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e[-0.232, -0.072]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eNJ = Non-judging. Unstandardized coefficients reported. Bootstrap 95% confidence intervals based on 5,000 resamples. Proportion of total effect via cognitive anxiety = 37.1%; via somatic anxiety = 2.0%. Model controls for all other FFMQ facets, age, sex, years of experience, and training hours.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"mindfulness, ultra-trail running, athlete burnout, sport anxiety, cognitive anxiety, Monitor and Acceptance Theory","lastPublishedDoi":"10.21203/rs.3.rs-8649683/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8649683/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eUltra-trail runners face sustained psychological demands during pre-competition preparation, yet little is known about factors associated with mental health in this population. Guided by Monitor and Acceptance Theory (MAT) as a heuristic process framework, this study examined associations between mindfulness facets, sport anxiety, and psychological outcomes in ultra-trail runners.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eParticipants were 216 ultra-trail runners (86.6% men; \u003cem\u003eM\u003c/em\u003e age\u0026thinsp;=\u0026thinsp;41.3 years, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.6) assessed 6\u0026ndash;8 weeks before a major competition. Measures included the Five Facet Mindfulness Questionnaire, Sport Anxiety Scale-2, Athlete Burnout Questionnaire, Chalder Fatigue Scale, and WHO-5 Well-Being Index. Indirect effects were tested using bootstrapped confidence intervals.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNon-judging and Acting with Awareness showed consistent negative associations with burnout (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.25 to \u0026minus;\u0026thinsp;.30), fatigue (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;\u0026thinsp;.20 to \u0026minus;\u0026thinsp;.24), and positive associations with well-being (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.15 to .27). Observing showed null or marginally positive associations with burnout. Sport anxiety showed a statistically significant indirect association in the Non-judging\u0026ndash;burnout link (27.8% of the total effect). Notably, parallel mediation models revealed that indirect pathways via cognitive anxiety were substantially stronger (37.1%) than via somatic anxiety (2.0%). Exploratory analyses suggested a small, marginal Observing \u0026times; Non-judging pattern, whereby Observing was positively associated with burnout only at low levels of Non-judging.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAcceptance-related mindfulness facets were associated with lower burnout in ultra-trail runners, with statistical indirect associations via cognitive anxiety stronger than via somatic arousal. The cross-sectional design precludes causal inference; however, these associations may help inform hypotheses for future longitudinal and intervention studies examining whether acceptance-focused mindfulness training and cognitive decentering reduce pre-competition cognitive anxiety and burnout risk in ultra-endurance athletes.\u003c/p\u003e","manuscriptTitle":"Mindfulness Facets, Sport Anxiety, and Psychological Outcomes in Ultra-Trail Runners: A Pre-Competition Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-27 10:35:49","doi":"10.21203/rs.3.rs-8649683/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-27T15:17:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-23T15:54:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2026-01-23T15:42:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bce1d876-56a6-495d-a6b3-311d771adb6a","owner":[],"postedDate":"January 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-28T18:23:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-27 10:35:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8649683","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8649683","identity":"rs-8649683","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}