Modelling perception-action coupling in the phenomenological experience of “hitting the wall” during long-distance running with exercise induced muscle damage in highly trained runners
Venhorst et al. Sports Medicine - Open
Modelling perception-action coupling in the phenomenological experience of “hitting the wall” during long-distance running with exercise induced muscle damage in highly trained runners
Andreas Venhorst 0
Dominic P. Micklewright 1
Timothy D. Noakes 0
0 Department of Human Biology, Division of Exercise Science and Sports Medicine, University of Cape Town , Newlands 7725 , South Africa
1 School of Sport, Rehabilitation and Exercise Sciences, University of Essex , Colchester CO4 3SQ , UK
Background: “Hitting the wall” (HTW) can be understood as a psychophysiological stress process characterised by (A) discrete and poignant onset, (B) dynamic interplay between physiological, affective, motivational, cognitive, and behavioural systems, and (C) unintended alteration of pace and performance. A preceding companion article investigated the psychophysiological responses to 20-km self-paced treadmill time trials after producing exercise-induced muscle damage (EIMD) via a standardised muscle-lengthening contraction protocol. Methods: A 5-step procedure was applied determining the extent to which the observed data fit the hypothesised causeeffect relationships. Running with EIMD negatively impacts performance fatigability via (A) amplified physiological responses and a non-adaptive distress response and (B) deterioration in perceived fatigability: increase in perceived physical strain precedes decrease in valence, which in turn precedes increase in action crisis, eventually dissolving the initially aspired performance goal. Results: First, haematological indicators of EIMD predicted increased blood cortisol concentration, which in turn predicted increased performance fatigability. Second, perceived physical strain explained 44% of the relationship between haematological indicators of EIMD and valence, which in turn predicted increased action crisis, which in turn predicted increased performance fatigability. The observed data fitted the hypothesised dual-pathway model well with good model-fit indices throughout. Conclusions: The hypothesised interrelationships between physiological strain, perception, and heuristic and deliberative decision-making processes in self-regulated and goal-directed exercise behaviour were applied, tested, and confirmed: amplified physiological strain and non-adaptive distress response as well as strain-perception-thinking-action coupling impact performance fatigability. The findings provide novel insights into the psychophysiological processes that underpin the phenomenological experience of HTW and alteration in pacing behaviour and performance.
Structural equation modelling; Mediation analysis; Pacing behaviour; Perceived fatigability; Performance fatigability; Central regulation; Decision-making
“Hitting the wall” (HTW) can be understood as a
psychophysiological stress process characterised by
(A) discrete and poignant onset, (B) dynamic interplay
between physiological, affective, motivational, cognitive,
and behavioural systems, and (C) unintended alteration
of pace and performance.
Running with EIMD causes (A) amplified
physiological responses and a non-adaptive
endocrinological distress response and (B)
increase in perceived physical strain, which
in turn mediates decrease in valence, which
in turn predicts increase in action crisis; and
both physiological and perceptual effects predict
increase in performance fatigability.
The findings provide novel insights into the
psychophysiological processes that underpin the
phenomenological experience of HTW under the
constraint of amplified physical duress.
Structural equation modelling and the applied
three-dimensional framework of perceived fatigability
comprehensively address pressing questions about
how hypothesised cause-effect relationships come to
be and how strain-perception-thinking-action
coupling determines the observed alteration in pacing
behaviour and endurance performance.
The “hitting the wall” (HTW) phenomenon is a much
talked about but poorly understood phenomenological
experience that regularly occurs in prolonged endurance
exercise. HTW can be understood as a psychophysiological
stress process characterised by (A) discrete and poignant
onset and duration, (B) dynamic and complex interplay
between physiological, affective, motivational, cognitive,
and behavioural systems, and (C) unintended alteration of
pacing behaviour and performance deterioration [
The sheer physicality of endurance sports, particularly
long-distance running, ensures that HTW is tightly
coupled to stimulus-driven processes resulting from
extreme physical duress. The most popular physiological
explanation for HTW is skeletal muscle glycogen
depletion and hypoglycaemia [
]. However, a
computational study by Rapoport [
] showed that glycogen
storage capacity is only a performance-limiting factor in
runners with low and moderate aerobic capacities, but
may not constrain performances of highly trained
long-distance runners. An alternative determinant of
HTW is exercise-induced muscle damage (EIMD)
caused by muscular exertion of unaccustomed exercise
duration and/or intensity, especially when involving
muscle lengthening contractions [
]. This notion is
supported by length of longest training run predicting the
likelihood of HTW [
] and correlations between
deterioration in marathon running pace and indirect
haematological markers of muscle damage .
The performance level-dependent nature of HTW [
] points towards the importance of salient primary
appraisals of physiological sensations. However, the large
context-dependent intra- and inter-individual variability
in subsequent psychophysiological responses necessitates
the integration of sentient secondary appraisals of
psychophysiological perceptions into a more holistic
multi-dimensional framework .
Buman et al. [
] investigated the phenomenological
characteristics of HTW in marathon runners and
observed escalating generalised fatigue accompanied by
unintentional slowing of running pace, increased desire to
walk, and a shift from initially set performance goals to
desire just finishing the race. Furthermore, runners
experiencing HTW felt more negatively impacted by these
events, and the authors interpreted the renegotiation of
race aspirations as an adaptive behavioural response to
exhaustion and performance deterioration as it did not
per se increase the likelihood of race drop-out [
In a subsequent study, Buman et al. [
explored the psychological and behavioural experiences of
HTW. Raw data were thematised into five higher-order
themes: (A) affective (e.g. frustration), (B) behavioural (e.g.
pace disruption), (C) cognitive (e.g. changing goals), (D)
motivational (e.g. desire to quit), and (E) physiological (e.g.
generalised and leg-related fatigue). As expected,
physiological descriptors were reported most frequently [
but the authors concluded that the complex interactions of
physiological, affective, motivational, cognitive, and
behavioural perceptions truly underpin the goal-disengagement
impulse associated with the HTW phenomenon .
Goal-related cost-benefit thinking in goal-striving
consistently peaks around the 32-km mark during a marathon
before resolving closer to the finish line [
5, 8, 15
non-linear dynamics of a psychological crisis concord with
linear dynamics of a physiological crisis during HTW, but
can dissociate thereafter. More importantly, deliberating
anew the desirability and feasibility of the initially aspired
performance goal during a marathon independently
predicted increased performance fatigability, thereby
providing a psychobiological link between a mindset-shift in
goal-striving and performance degradation [
5, 16, 17
However, the above studies relied on correlational study
designs, recreational runners, and low temporal resolution
in perceptual and performance measures. These studies
therefore provide limited information on pressing
questions about (A) how hypothesised cause-effect
relationships determining endurance performance come to be
] and (B) how perception-action coupling underpins
self-regulation and decision-making in pacing behaviour
and endurance performance [
A recently proposed three-dimensional framework of
centrally regulated and goal-directed exercise behaviour [
was therefore applied to investigate the alterations in pacing
behaviour and endurance performance in highly trained
long-distance runners during a self-paced 20-km treadmill
time trial after inducing EIMD by means of a standardised
drop-jump protocol [
]. The preceding companion article
showed dynamic changes and interdependencies in
physiological and perceptual effects on pacing behaviour and
performance fatigability that are in full agreement with the
defining characteristics of the phenomenological experience
of HTW described previously. An accepted approach to
lend credibility to the hypothesised cause-effect relationships
is to statistically test the integrity of the hypothesised model
structure in relation to observed data.
Structural equation modelling (SEM) is a causal inference
method that combines testable causal hypotheses based on
scientific knowledge and empirical data as input, and
produces quantitative causal claims, conditional on the input
assumptions, as output [
]. The statistical inference is
based on a simultaneous analysis of the entire system of
variables determining the extent to which the observed data
fit the hypothesised a priori specifications [
]. It thereby
provides a higher-level perspective to the analysis and
evaluation of entire models. Another key component to
theory development is mediation analysis, which aims to
clarify how cause-effect relationships come to be, [
which are therefore theoretical formulations for
unidirectional relationships [
]. Thus, specifically when used in
conjunction with an experimental design, the capabilities to
formalise and implement causal inference makes SEM an
indispensable tool in causal hypothesis testing and
mediation analysis; its potential for theory development is even
Here, SEM was applied to test the extent to which the
observed data fit the hypothesised cause-effect relationships
of the dual-pathway model outlined below and which are
described in detail in the preceding companion article [
Due to the limited sample size, a simplified version was
tested that focused on the haematological indicators of
EIMD and thus the muscle damage component rather than
the combined effects of locomotor muscle fatigue and
EIMD. Differential responses in haematological indicators
of EIMD are hypothesised to precede (1) amplified
physiological and non-adaptive endocrinological distress response
(indicated by blood cortisol concentrations) and (2)
increase in perceived physical strain, which in turn mediates
a decrease in valence, which in turn precedes an increase in
action crisis, and both physiological and perceptual effects
precede performance fatigability.
Twenty-two (11 females) highly trained (performance
level 4) runners completed two maximal self-paced
20 km treadmill time trials over a simulated profiled
course in a counterbalanced crossover design: (A) in a
tapered condition and (B) with EIMD produced by a
standardised drop-jump protocol. Indicators of muscle
damage, muscle metabolic strain, and endocrinological
stress were assessed to investigate the physiological
effects, and a three-dimensional framework of perceived
fatigability emphasising the distinct contributions of
sensory, affective, and cognitive processes was applied to
investigate the perceptual effects of running with EIMD
on performance fatigability.
The methods and results of preliminary and
experimental procedures as well as the outcome of
conventional statistical analyses have been described in detail in
the preceding companion article [
]. A 5-step procedure
was applied to ascertain that the theorised relationships
were statistically robust enough for the structural
modelling process [
In step one, conventional statistical analyses and visual
inspection of data took place. Main study variables that
showed significant treatment × time interaction or main
treatment effects were considered potential explanatory
moderators and mediators of defended regulatory
variables and observed trial-related differences in
performance fatigability. To overcome discrepancies in temporal
dynamics and sampling points as well as non-linearity in
psychophysiological responses, trial-related differences
in area under the curve1 (Δ AUC) were calculated for
each main study variable before proceeding with
correlation and regression analyses.
In step two, zero-order correlations and linear
regressions were computed. Zero-order correlations were
calculated between Δ AUC in main study variables
determining the strength of association between each
variable pair. Significant correlations between variable
pairs were followed-up with linear regression analyses,
thereby allowing predictions to be made.
In step three, mediation analysis was conducted when
a predictor variable was correlated to the proposed
outcome variable and another dependent variable.
Mediation analysis measures the significance of the indirect
effect and the extent to which the mediator variable
accounts for the relationship between the predictor and
the outcome variable. Mediation analysis is particularly
appropriate to use when (A) the predictor variable is
experimentally manipulated and the mediator variable
measured and (B) the dynamic change in the predictor
variable precedes the dynamic change in the mediator
variable; and both precede the outcome variable [
In step four, multiple hierarchical regression analyses
were conducted between pairs of study variables
hypothesised to be linked in a temporal order and
separate for each pathway hypothesised to impact
performance fatigability2: Path one: (A) blood leucocyte count
and blood cortisol concentration, (B) blood neutrophil
count and blood cortisol concentration, and (C) blood
cortisol concentration and performance fatigability. Path
two: (D) blood leucocyte count and perceived physical
strain, (E) blood neutrophil count and perceived physical
strain, (F) perceived physical strain and valence, (G)
valence and action crisis, and (H) action crisis and
performance fatigability. Every variable pair was analysed by
means of stepwise longitudinal regression analysis to
ensure that the relationship between the direct predictor
and outcome variable in each pairwise comparison was
independent of descriptor and training variables as well
as conventional predictors of endurance performance.
Age and weight were entered in step one. Weekly
mileage and volume of other aerobic training were
entered in step two. VO2peak relative to body mass and
running economy (i.e. energy cost of running) were
entered in step three. Lastly, the direct predictor of the
outcome variable of interest was entered in step four.
In step five, main study variables were fitted into a
singular structural path model. Despite the small sample
size (n = 22), SEM was deemed appropriate as the
variables included in the tested model: (A) showed
significant interaction or main treatment effects in
conventional statistical analyses, (B) showed significant
zero-order correlations, (C) showed inter-individual
homogeneity in responses, (D) showed trial-dependent
changes that were in full agreement with the theoretical
predictions, and lastly (E) as a result of the relatively low
complexity level of the tested model [
All conventional statistical analyses were conducted with
IBM® SPSS® (Version 24.0, Chicago, IL, USA). Slopes
and AUC were calculated using GRAPHPAD PRISM®
(Version 6.00 for Windows, GraphPad Software, La Jolla,
CA, USA). Mediation analysis and structural equation
modelling was performed using IBM® SPSS® Amos
(Version 24.0, Chicago, IL, USA). Model fits were estimated
using the maximum likelihood method, and results are
represented as standardised estimates. Significance of
the indirect effect within mediation analysis was
estimated by means of bootstrap sampling and
bias-corrected 95% confidence intervals based on 2.000
bootstrap samples [
]. Statistical significance was
accepted at p < 0.05 (2-tailed).
Step 1: Visual inspection and conventional statistical analyses
Trial-related differences in main study variables showing
significant treatment × time interaction or main
treatment effects are shown in Fig. 1.
Step 2: Correlation and linear regression
Zero-order correlations among the major study variables
are provided in Table 1.
Significant linear relationships were found between
haematological indicators of EIMD (i.e. Δ AUC in blood
leucocyte and neutrophil count) and Δ AUC in blood
cortisol concentration, which in turn showed a significant
linear relationship with performance fatigability (β = 0.51; p
= 0.015). However, Δ AUC in haematological indicators of
EIMD also showed significant linear relationships with Δ
AUC in perceived physical strain, valence, and action crisis
(although only weakly with the latter). Furthermore, there
were significant linear relationships in the hypothesised
temporal order between the Δ AUC in perceived physical
strain and valence (β = − 0.78; p = < 0.001), valence and
action crisis (β = − 0.51; p = 0.015), and action crisis and
performance fatigability (β = 0.57; p = 0.006). The
simultaneous significant linear relationships between Δ
AUC in haematological indicators of EIMD, perceived
physical strain, and valence required the examination of a
potential indirect effect of perceived physical strain on the
relationship between haematological indicators of EIMD
Step 3: Mediation analysis
In full agreement with our theory-driven approach, Δ AUC
in perceived physical strain was a significant mediator as it
explained 44% of the relationship between Δ AUC in
haematological indicators of EIMD and valence. The significant
total effect c (standardised estimate = − 0.68**, p < 0.001)
between Δ AUC in haematological indicators of EIMD and
valence was reduced by a non-trivial amount to a
significant direct effect c’ (standardised estimate = − 0.38**, p =
0.001) after controlling for the significant indirect effect
a × b (standardised estimate = − 0.24, p = 0.025). Statistical
details are provided in Fig. 2 and Table 2.
Step 4: Multiple hierarchical regression analyses
None of the control variables (i.e. age, weight, weekly
mileage, other training, VO2peak, and energy cost of
running) significantly predicted any of the main study
outcome variables (i.e. blood cortisol concentration,
perceived physical strain, valence, action crisis, and
performance fatigability). More importantly, all direct
predictors (i.e. blood leucocyte count, blood neutrophil
count, blood cortisol concentration, perceived physical
strain, valence, and action crisis) continued to
significantly predict the respective outcome variable (i.e. blood
cortisol concentration, perceived physical strain, valence,
action crisis, and performance fatigability) after
controlling for anthropometric and training variables as well as
conventional predictors of endurance performance. The
results of the seven stepwise regression analyses are
summarised in Table 3.
Step 5: Structural equation modelling
Details of the full structural equation model are provided in
Fig. 3. The dual-pathway model hypothesised to underpin
increased performance fatigability in response to running
with EIMD entails: (1) debilitative physiological effects
characterised by amplified physiological demand and
non-adaptive endocrinological distress response and (2)
debilitative perceptual effects characterised by deterioration in
sensory, affective, and cognitive processes hypothesised to
underpin perceived fatigability.
First, an increase in Δ AUC in haematological
indicators of EIMD significantly predicted non-adaptive
endocrinological distress response indicated by an excessive
increase in Δ AUC in blood cortisol concentrations
(standardised estimate = 0.69**; p < 0.01) despite reduced
performance, which in turn significantly predicted
increased performance fatigability (standardised
estimate = 0.38*; p < 0.05).
Second, besides the significant mediatory role of
perceived physical strain in the relationship between
haematological indicators of EIMD and valence discussed
previously, an increase in Δ AUC in haematological
indicators of EIMD significantly predicted an increase in Δ
AUC in perceived physical strain (standardised estimate
= 0.52*; p < 0.05). An increase in Δ AUC in perceived
physical strain significantly predicted a decrease in Δ
AUC in valence (standardised estimate = − 0.47*; p <
0.05). A decrease in Δ AUC in valence significantly
predicted an increase in Δ AUC in perceived action crisis
(standardised estimate = − 0.51**; p < 0.01), and an
increase in Δ AUC in perceived action crisis significantly
predicted an increase in performance fatigability
(standardised estimate = 0.46**; p < 0.01).
The observed data fitted the hypothesised dual-pathway
model well with good model fit indices throughout and a
78% probability that the observed data fit the hypothesised
cause-effect relationships: χ2 = 7.277, p = .776, χ2/11 = .662,
NFI = .949, CFI = 1.000, RMSEA = .000 (95%CI = [.000,
.156]; PCLOSE = .806), AIC = 55.277, SRMR = .068) [
The present research applied SEM to measure the extent
to which the observed data of the preceding companion
] fit the previously outlined psychophysiological
cause-effect relationships hypothesised to shape the
HTW phenomenon by combining causal (i.e. formalising
and implementing testable causal hypotheses in an
experimental design) and statistical (i.e. assessing the
extent to which the experimental data fitted the
hypothesised model) inference. Good model fit indices
confirmed the credibility of the hypothesised model
structure. The main findings were (A) discrete and
poignant event onset, (B) differential responses in
haematological indicators of amplified muscular strain and
non-adaptive endocrinological distress response, (C)
sensory-discriminatory, affective-motivational, and
cognitive-evaluative processes indicative of deterioration
in perceived fatigability, and (D) unintended alteration of
pacing behaviour and performance fatigability.
First, the muscle lengthening contraction protocol
caused a large 11% decrease in power output generating
capacity of the knee extensors, medium increases in
haematological indicators of EIMD, and large increases
in symptoms of delayed onset of muscular soreness in
highly trained runners; collectively confirming mild
EIMD (for details see preceding companion article) [
Still, strength loss was only about half of that observed
in similar studies using moderately trained cyclists [
]. Thus, given that highly trained runners are arguably
better adapted to mechanical strain through the
repeat-bout effect, this might explain why the current
study only observed trends towards significant
zero-order correlations between haematological
indicators of EIMD and performance fatigability.
However, the drop-jump protocol did induce medium
increases in absolute cardiovascular, respiratory, and
metabolic demands during the steady-state running
economy test preceding the time trials, thereby
indicating an increase in relative exercise intensity (for details,
see preceding companion article) [
]. Running with mild
EIMD therefore elicited a stressful physiological milieu
that is not conducive to high-performance. In support,
in the current study, differential responses in
haematological indicators of EIMD predicted non-adaptive
endocrinological distress response, which in turn predicted
increased performance fatigability. Thus, the escalating
leg-related and generalised fatigue experienced when
] are likely associated with greater accumulation
of EIMD, amplified physiological demands, and excessive
endocrinological distress response during the
second-half of marathons compared to half-marathons
]. This notion is consistent with observational data
showing correlations between greater decreases in
marathon running pace after ≈ 25 km and haematological
markers of muscle damage in moderately trained
runners who slowed down significantly more than those
who were able to maintain their running speed [
Second, the most prevalent cognitions described by
runners in response to challenging exercise [
perceptions of salient physiological disturbance, and this
particularly holds true under extreme physiological duress
as experienced when HTW . Another sentient
characteristic of the phenomenological experience of HTW is
that runners who HTW perceive these sensations to more
negatively impact on their performance than those who
do not, thereby becoming increasingly frustrated and
]. This attachment of valence to
homeostatic disturbance and perceived physical strain eventually
undermines effective goal-striving by promoting an urge
to disengage from further goal-pursuit [
support, in the current study, differential responses in
**Significant at the 0.01 level (2-tailed). *Significant at the 0.05 level (2-tailed)
haematological indicators of EIMD predicted an increase
in perceived physical strain as well as a decrease in
valence. Importantly, perceived physical strain was a
significant mediator explaining 44% of the relationship
between haematological indicators of EIMD and valence.
Thus, in full agreement with recent proposals of pacing
behaviour and performance regulation, [
stimulus-driven heuristic processes are hypothesised to
motivate the desire to walk and quit,3 thereby
necessitating the opposing recruitment of goal-driven volitional
processes in continued goal-striving.
Third, runners HTW have been found to renegotiate
their initially set performance aspirations and change their
goals to just finishing the race [
]. This closely
resembles an intra-psychic conflict between further goal-pursuit
and goal-disengagement resulting from negatively
valenced events in goal-striving—the hallmark of an action
]. During an action crisis, the cognitive
orientation shifts from an implemental mindset facilitating
volitional tasks such as goal-striving in the face of adversity
to a deliberative mindset facilitating motivational tasks
such as deliberating anew the desirability and feasibility of
the focal and alternative goals [
]. More specifically,
the experience of such a mindset-shift during a marathon
predicted and negatively impacted running performance
independently from the detrimental effects of the linearly
developing physiological crisis [
]. In support, in the
current study, a decrease in valence predicted an increase
in action crisis, which in turn predicted an increase in
performance fatigability, thereby suggesting heuristic and
deliberative antecedents in the goal-disengagement process.
In the academic domain, using cross-lagged panel path
analysis, Brandstätter and colleagues [
convincing evidence that an action crisis temporally
antecedes devaluation of goal-desirability and deterioration
in perceived goal-attainability. Similarly, recent
neuroeconomic research found that in a fatigued state, and
moderated by endurance capacity, anticipated costs of
future efforts are escalated, while the attractiveness of
anticipated rewards are discounted . During
psychophysiological crises, stimulus-driven reactive control
therefore seems to undermine goal-driven proactive
control and negatively impact on thinking-action
coupling in the self-regulatory control of goal-striving [
However, according to Brick et al. [
athletes can monitor and control their thoughts and actions
in self-regulated endurance performance through
metacognitive processes, albeit at the speculated cost of
accruing mental fatigue. Thus, the HTW phenomenon can
be understood as psychophysiological stress process
draining on fatigable and temporally limited
physiological and psychological resources, eventually leading to
the dissolution of the initially aspired performance goal.
Last, intriguing neurofunctional evidence for the above
outlined hypothesised dual-pathway model has been
provided by Maier et al. [
], who showed that acute
stress biased decision-making and self-regulatory control
via two parallel but distinguishable neuroanatomical
pathways: (1) endocrinological distress (indicated by
salivary cortisol concentration) increased connectivity with
limbic system structures suggestive of augmented salient
motivating stimuli (e.g. thereby facilitating the
motivational desire to slow down) and (2) perceived stress
levels decreased connectivity with prefrontal cortex
structures suggestive of attenuated volitional
goal-maintenance (e.g. thereby debilitating the volitional
drive to attain the initially set performance goal).
Limitations and future directions
First, a limitation of the current study is the sample size.
The current findings therefore prevent the generalisation
of findings beyond the specific context in which this
study was conducted. However, the findings do lend
credibility to the hypothesised cause-effect relationships
and provide researchers with valuable information to
drive further theory development and research design in
strain-perception-thinking-action coupling during
prolonged endurance exercise.
Second, to reduce data volume and simplify the
modelling process, we focussed on action crisis to indicate the
shift from an implemental to a deliberative mindset.
However, the preceding companion article also showed
mirror-like responses in flow state [
]. Thus, although
model fit indices throughout were slightly better for action
crisis compared to flow state (Δ AIC = 2.755), both
measures seem valid indicators of a shift from an
implemental mindset cognitively tuned towards the “how” of
behaviour to a deliberative mindset cognitively tuned towards
the “why” of behaviour (for statistical details see
Additional file 1). This may provide the opportunity to also
investigate facilitative effects of cognitive-evaluative
processes in the regulation of pacing behaviour and endurance
Third, given the significant zero-order correlation
between blood cortisol concentration and valence, the fit
of a theoretically equally feasible model with an
additional unidirectional pathway from valence to blood
cortisol concentration was explored. The alternative and
more restrictive model showed slightly worse model fit
indices (statistical results are not shown, but available
from the first author upon request). Given the observed
data, the initially hypothesised model is more
parsimonious and therefore it is to be preferred based on this
By combining causal and statistical inference, the
present article demonstrates that dynamic and complex
interdependencies in physiological and perceptual effects
determine the phenomenological experience of HTW
and the behavioural outcome of observed pacing
behaviour and performance fatigability during long-distance
running with EIMD. More specifically, it contributes to
a better understanding of how relationships come to be
and how strain-perception-thinking-action coupling
underpins observed pacing behaviour and performance
fatigability. Differential responses in haematological
indicators of EIMD predicted (1) amplified physiological
strain and a non-adaptive endocrinological distress
response and (2) increase in perceived physical strain,
which in turn mediated a decrease in valence, which in
turn predicted an increase in action crisis; and both
physiological and perceptual effects predicted
performance fatigability. The findings are in full agreement with
recent theoretical developments in centrally regulated
and goal-directed exercise behaviour and provide novel
insights into the psychophysiological processes that (A)
shape the phenomenological experience of HTW and
(B) determine the poignant and unintended alterations
in pacing behaviour and performance fatigability.
1To reflect the lag period in haematological indicators
of EIMD and endocrinological strain, areas under the
curve of haematological variables were integrated
from pre-time trial to post-recovery period.
2The direct predictive effects of blood leucocyte and
neutrophil count on blood cortisol concentration and
perceived physical strain were assessed separately due
3Critically, the desire to walk and quit must be
understood as a motivational drive as the vast majority of
recreational runners HTW do not actually quit. [
Similarly, the experience of an action crisis is not a
binary event inevitably leading to self-regulatory
failure, but constitutes an antecedent in the
goal-disengagement process and does not necessarily
imply that athletes let go of their goals entirely. [
Additional file 1: Supplementary material contains graphical and
tabular information on the 5-step structural equation modelling
procedure using differential responses in flow state instead of action crisis: (1)
trial-related differences in main study variables in response to running
with exercise-induced muscle damage, (2) zero-order correlations
between trial-related differences in area under the curve of main study
variables, (3) multiple hierarchical regression analyses of control variables,
direct predictor variables, and main study outcome variables, and (4)
structural equation model of physiological and percpetual effects on
performance fatigability. (PDF 452 kb)
Δ AUC: Trial-related differences in area under the curve; AIC: Akaike information
criterion; CFI: Comparative fit index; CI: Confidence interval; CTRL: Control
condition; CTT: Control time trial; DJ: Drop-jump protocol; EIMD: Exercise-induced
muscle damage; HTW: “Hitting the wall”; ITT: Intervention time trial; NFI: Normed
fit index; PCLOSE: p close of fit; RE: Running economy; RMSEA: Root mean square
error of approximation; SEM: Structural equation modelling; VO2peak: Peak oxygen
consumption; SRMR: Standardised root mean square residual.
We would like to acknowledge (A) the reviewers for their constructive
criticism and insightful comments and (B) all our participants for their time
The study has been funded by the National Research Foundation of South
Africa (443920 HUB 1138) awarded to Prof. Timothy D. Noakes. Dr. Venhorst
has been supported by a scholarship from the German Academic Exchange
Service (DAAD). The funding body played no roles in the design of the study
and collection, analysis, and interpretation of data and in writing the
Availability of data and materials
Additional data are provided in supplementary material. Please contact first
author for any further data requests.
AV designed the study, collected the data, analysed the data, and compiled
the first draft of the manuscript. AV, DPM, and TDN contributed to the
revision and final approval of the manuscript.
Ethics approval and consent to participate
The study was approved by the Human Research Ethics Committee of the
University of Cape Town (reference number 092/2016). All participants
signed appropriate informed consent forms and the study was performed in
accordance with the standards of ethics outlined in the Declaration of
Consent for publication
Andreas Venhorst, Dominic P. Micklewright, and Timothy D. Noakes declare
that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
1. Buman MP , Brewer BW , Cornelius AE , Van Raalte JL , Petitpas AJ . Hitting the wall in the marathon: phenomenological characteristics and associations with expectancy, gender, and running history . Psychol Sport Exerc . 2008 ; 9 : 177 - 90 .
2. Buman MP , Omli JW , Giacobbi PR , Brewer BW . Experiences and coping responses of “hitting the wall” for recreational marathon runners . J Appl Sport Psychol . 2008 ; 20 : 282 - 300 .
3. Coyle EF . Physiological regulation of marathon performance . Sport Med . 2007 ; 37 : 306 - 11 .
4. Stevinson CD , Biddle SJ . Cognitive orientations in marathon running and “hitting the wall” . Br J Sports Med . 1998 ; 32 : 229 - 234 -235.
5. Schüler J , Langens TA . Psychological crisis in a marathon and the buffering effects of self-verbalizations . J Appl Soc Psychol . 2007 ; 37 : 2319 - 44 .
6. Rapoport BI . Metabolic factors limiting performance in marathon runners . PLoS Comput Biol . 2010 ; 6 : e1000960 .
7. Venhorst A , Micklewright D , Noakes TD . The psychophysiological regulation of pacing behaviour and performance fatigability during long-distance running with locomotor muscle fatigue and exercise-induced muscle damge in highly trained runners . Sport. Med . - Open. 2018 . https://doi.org/ 10.1186/s40798-018-0143-2.
8. Buman MP , Brewer BW , Cornelius AE . A discrete-time hazard model of hitting the wall in recreational marathon runners . Psychol Sport Exerc Elsevier Ltd . 2009 ; 10 : 662 - 6 .
9. Del Coso J , Fernandez D , Abian-Vicen J , Salinero JJ , Gonzalez-Millan C , Areces F , et al. Running pace decrease during a marathon is positively related to blood markers of muscle damage . PLoS One . 2013 ; 8 : 1 - 7 .
10. Morgan WP , Pollock ML . Psychologic characterization of the elite distance runner . Ann N Y Acad Sci . 1977 ; 301 : 382 - 403 .
11. Manuel MA . Toward an understanding of marathon induced fatigue and, the phenomenological motives and meanings of perseverance under duress [dissertation] . Miami: Carlos Albizu University; 2000 . p. 195 . Carlos Albizu University
12. Lazarus R . How emotions influence performance in competitive sports . Sport Psychol . 2000 ; 14 : 229 - 52 .
13. Morgan WP. The mind of the marathoner . Psychol Today . 1978 ; 11 : 38 - 49 .
14. Tenenbaum G , Fogarty G , Stewart E , Calcagnini N , Kirker B , Thorne G , et al. Perceived discomfort in running: scale development and theoretical considerations . J Sports Sci . 1999 ; 17 : 183 - 96 .
15. Brandstätter V , Schüler J . Action crisis and cost-benefit thinking: a cognitive analysis of a goal-disengagement phase . J Exp Soc Psychol Elsevier Inc . 2013 ; 49 : 543 - 53 .
16. Brandstätter V , Herrmann M , Schüler J. The struggle of giving up personal goals: affective, physiological, and cognitive consequences of an action crisis . Personal Soc Psychol Bull . 2013 ; 39 : 1668 - 82 .
17. Venhorst A , Micklewright D , Noakes TD . Modelling the process of falling behind and its psychophysiological consequences . Br J Sports Med . 2017 ; 0 : 1 - 6 .
18. McCormick A , Meijen C , Marcora S . Psychological determinants of wholebody endurance performance . Sport Med . 2015 ; 45 : 997 - 1015 .
19. Smits BLM , Pepping G-J , Hettinga FJ . Pacing and decision making in sport and exercise: the roles of perception and action in the regulation of exercise intensity . Sports Med . 2014 ; 44 : 763 - 75 .
20. Venhorst A , Micklewright D , Noakes TD . Towards a three-dimensional framework of centrally regulated and goal-directed exercise behaviour: a narrative review . Br J Sports Med . 2017 ; 0 : 1 - 12 .
21. Pearl J. The causal foundations of structural equation modeling . In: Hoyle RH, editor. Handb. Struct. Equ. Model . New York: Guilford Press; 2012 . p. 68 - 91 .
22. Kline RB . In: Kline RB, editor. Principles and practice of structural equation modeling . 4th ed. New York: Guilford Press; 2015 .
23. Hayes AF , Gentry WA , Gilmore DC , Shuffler ML , Leslie JB , Gandz J , et al. Beyond baron and Kenny: statistical mediation analysis in the new millennium . Commun Monogr . 2009 ; 76 : 408 - 20 .
24. Wu AD , Zumbo BD . Understanding and using mediators and moderators . Soc Indic Res . 2008 ; 87 : 367 - 92 .
25. Bollen KA , Pearl J . Eight myths about causality and structural equation models . In: Morgan SL, editor. Handb. causal Anal. Soc. Res . Dordrecht: Springer; 2013 . p. 301 - 28 .
26. Preacher KJ , Hayes AF . SPSS and SAS procedures for estimating indirect effects in simple mediation models . Behav Res Methods Instrum Comput . 2004 ; 36 : 717 - 31 .
27. Iacobucci D. Structural equations modeling: fit indices, sample size, and advanced topics . J Consum Psychol Soc Consumer Psychol . 2010 ; 20 : 90 - 8 .
28. Efron B . Better bootstrap confidence intervals . J Am Stat Assoc . 1987 ; 82 : 171 - 85 .
29. Hooper D , Coughlan J , Mullen M. Structural equation modeling: guidelines for determining model fit . Electron J Bus Res Methods . 2008 ; 6 : 53 - 60 .
30. Marcora SM , Bosio A , de Morree HM . Locomotor muscle fatigue increases cardiorespiratory responses and reduces performance during intense cycling exercise independently from metabolic stress . Am J Physiol Regul Integr Comp Physiol . 2008 ; 294 : R874 - 83 .
31. de Morree HM , Marcora SM . Effects of isolated locomotor muscle fatigue on pacing and time trial performance . Eur J Appl Physiol . 2013 ; 113 : 2371 - 80 .
32. Reihmane D , Jurka A , Tretjakovs P , Dela F. Increase in IL-6, TNF-α, and MMP9, but not sICAM-1, concentrations depends on exercise duration . Eur J Appl Physiol . 2013 ; 113 : 851 - 8 .
33. Cabanac M. Pleasure : the common currency . J Theor Biol . 1992 ; 4 : 173 - 200 .
34. Cabanac M. Sensory pleasure optimizes muscular work . Clin Investig Med . 2006 ; 29 : 110 - 6 .
35. Cabanac M. Exertion and pleasure from an evolutionary perspective . In: Acevedo EO , Ekkekakis P , editors. Psychobiol. Phys. Act . Champaign: Human kinetics; 2006 . p. 79 - 89 .
36. Renfree A , Martin L , Micklewright D , St Clair Gibson A. Application of decision-making theory to the regulation of muscular work rate during selfpaced competitive endurance activity . Sports Med . 2014 ; 44 : 147 - 58 .
37. Brick N , MacIntyre T , Campbell M. Metacognitive processes in the selfregulation of performance in elite endurance runners . Psychol Sport Exerc Elsevier Ltd . 2015 ; 19 : 1 - 9 .
38. Micklewright D , Kegerreis S , Raglin J , Hettinga F . Will the conscioussubconscious pacing quagmire help elucidate the mechanisms of selfpaced exercise? New opportunities in dual process theory and process tracing methods . Sports Med . 2017 ; 47 : 1231 - 9 .
39. Gollwitzer P. Action phases and mind-sets . In: Higgins T , Sorrentine R , editors. Handb. Motiv. Cogn. Found. Soc. Behav . New York: The Guilford Press; 1990 . p. 53 - 92 .
40. Gollwitzer P. Mindset theory of action phases . In: van Lange PA, editor. Handb. Theor. Soc. Psychol . 1st ed. Los Angeles: Sage; 2012 . p. 526 - 45 .
41. Ghassemi M , Bernecker K , Herrmann M , Brandstätter V. The process of disengagement from personal goals: reciprocal influences between the experience of action crisis and appraisals of goal desirability and attainability . Personal Soc Psychol Bull . 2017 ; 43 : 524 - 37 .
42. Iodice P , Calluso C , Barca L , Bertollo M , Ripari P , Pezzulo G . Fatigue increases the perception of future effort during decision making . Psychol. Sport Exerc . 2017 ; 33 : 150 - 60 .
43. Rhoden CL , West J , Renfree A , Corbett M , St Clair Gibson A. Adaptive selfregulation in cycle time trials: goal pursuit, goal disengagement and the affective experience . J Sci Cycl . 2015 ; 4 : 44 - 52 .
44. Brick NE , MacIntyre TE , Campbell MJ . Thinking and action: a cognitive perspective on self-regulation during endurance performance . Front Physiol . 2016 ; 7 : 1 - 7 .
45. Maier SU , Makwana AB , Hare TA . Acute stress impairs self-control in goaldirected choice by altering multiple functional connections within the brain's decision circuits . Neuron. Elsevier Inc . 2015 ; 87 : 621 - 31 .
46. Herrmann M , Baur V , Brandstätter V , Hänggi J , Jäncke L . Being in two minds: the neural basis of experiencing action crises in personal long-term goals . Soc Neurosci . 2014 ; 9 : 1 - 14 .