798  |    
 
Scand J Med Sci Sports. 2022;32:798–806.
wileyonlinelibrary.com/journal/sms
Received: 15 October 2021  |  Revised: 15 December 2021  |  Accepted: 9 January 2022
DOI: 10.1111/sms.14129  
O R I G I N A L  A R T I C L E
Disturbance of desire- goal motivational dynamics during 
different exercise intensity domains
Ian M. Taylor
 |   Summer Whiteley |   Richard A. Ferguson
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided 
the original work is properly cited.
© 2022 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd.
School of Sport, Exercise & Health 
Sciences, Loughborough University, 
Leicestershire, United Kingdom
Correspondence
Ian M. Taylor, School of Sport, Exercise 
& Health Sciences, Loughborough 
University, Leicestershire, United 
Kingdom.
Email: i.m.taylor@lboro.ac.uk
Abstract
Purpose: The  desire- goal  motivational  conflict  helps  explain  endurance  per-
formance; however, the physiological concomitants are unknown. The present 
study  examined  disturbances  in  desire  to  reduce  effort  and  performance  goal 
value across moderate, heavy, and severe exercise intensity domains, demarcated 
by the first (LT1) and second (LT2) lactate thresholds. In addition, the within- 
person relationships among blood lactate concentration, heart rate, and desire- 
goal conflict were examined.
Methods: Thirty participants (53% female, Mage = 21.03 years; SD = 2.06 years) 
completed an incremental cycling exercise test, in which work rate was increased 
by 25 watts every four minutes, until voluntary exhaustion or sufficient data from 
the severe intensity domain had been collected. Desire to reduce effort, perfor-
mance  goal  value,  blood  lactate  concentration  (for  determination  of  LT1  and 
LT2), and heart rate were measured at the end of each stage and analyzed using 
multilevel models.
Results: The desire to reduce effort increased over the exercise test with addi-
tional shifts and accelerations after each lactate threshold. The performance goal 
did not show general declines, nor did it shift at LT1. However, the performance 
goal value shifted at LT2, and the rate of change increased at both thresholds. 
Within- person variation in blood lactate concentration positively correlated with 
the desire to reduce effort and negatively correlated with the performance goal. 
Within- person variation in heart rate correlated with desire to reduce effort but 
not the performance goal.
Conclusion: Transitioning through both lactate thresholds is important phases 
for motivation during progressive exercise, particularly for the desire to reduce 
effort. Within- person variation in blood lactate concentration is more influential 
for motivation, compared with heart rate.
K E Y W O R D S
desire- goal conflict, exercise domains, lactate threshold, motivation, self- control
   | 799
TAYLOR et al.
1  |  INTRODUCTION
The ability to endure discomfort is critical in sport and 
many  other  areas  of  human  performance,  such  as  the 
military and survival in extreme circumstances. It is un-
surprising,  therefore,  that  endurance  is  a  popular  topic 
of  investigation  in  the  sport,  exercise,  and  performance 
sciences.  Having  been  dominated  by  physiological  per-
spectives,  our  understanding  of  human  endurance  has 
benefited recently from researchers integrating psycholog-
ical and physiological perspectives to offer more compre-
hensive models of human endurance.1,2 Building on this 
trend, the present study investigates the potential physi-
ological underpinnings of motivational processes during 
an  endurance  task.  Rather  than  defining  endurance  in 
terms of time or distance, as is done in applied contexts, 
we refer to an endurance act as requiring persistence in 
the  face  of  psychological  and  physiological  difficulties. 
This definition, therefore, can be applied to many scenar-
ios beyond “endurance” classified events (e.g., 10 000 m 
athletics event).
Endurance  in  performance  contexts  requires  consid-
erable  tolerance  and  management  of  psychophysiolog-
ical  discomfort.  Afferent  signals  (i.e.,  sensory  impulses 
transferred from parts of the body to the central nervous 
system) associated with physiological responses (includ-
ing those associated with exercise) are affectively labeled3 
and  integrated  into  a  collective  representation  of  the 
current  physiological  condition  compared  with  homeo-
stasis.4 This  depiction  subsequently  emerges  as  a  single 
conscious,  motivational  state,5  which  becomes  increas-
ingly aversive as a function of exercise intensity.6 Hence, 
a desire to reduce effort will evolve because humans have 
a proclivity to avoid discomfort7 and maintain homeosta-
sis.8 This proximal desire vies with the distal goal of suc-
cessful performance. In endurance settings, the content of 
the goal may vary, for example, winning a race, achieving 
a pre- specified time, or exerting a specific amount of effort 
during the task. This content is less important, compared 
with the motivational strength of the goal and its conflict 
with the desire to reduce effort. Such desire- goal conflicts 
represent  a  central  aspect  of  all  self- control  dilemmas9 
and  provide  an  empirically  supported  framework  to  in-
vestigate endurance performance.10,11 For example, lower 
desire to reduce effort at the beginning of a cycling time 
trial and slower reductions in goal importance across the 
trial have been found to be characteristic of better perfor-
mance12 Measures of the desire and goal value at the mid-
point of a cycling trial also predicted cycling performance 
at a high intensity.12
Within  this  desire- goal  conflict  model  of  endurance, 
it is assumed that the underlying basis for the desire to 
reduce  effort  is  hedonic  and  stems  from  basic  drives  to 
maintain  homeostasis.10  This  implies  that  the  desire  to 
reduce  effort  may  have  significant  physiological  under-
pinnings. In contrast, the value of the performance goal 
is primarily underpinned by internal (e.g., improvement 
and personal value) and external (squad selection, prize 
money) incentive structures, and physiological responses 
to exercise are less influential. Nonetheless, this assump-
tion remains to be empirically tested until now.
Broadly  speaking,  the  physiological  foundation  of 
motivation  during  endurance  acts  is  not  a  new  area  of 
research.  Endeavors  have  typically  focused  on  the  rela-
tionship between physiological responses to exercise and 
perceived exertion or effort.2 Responses include heart rate, 
oxygen  uptake,  respiratory  rate,  and  blood  lactate  con-
centration, yet no single parameter consistently explains 
feelings of exertion.13 The psychobiological model of en-
durance proposes that afferent signals from physiological 
perturbances have little motivational value because they 
are independent of perceived effort.1 This body of work, 
therefore, implies that physiological responses to exercise 
may have little influence on motivational processes during 
endurance. By focusing on perceived effort; however, an 
incomplete portrayal of motivation and its physiological 
concomitants is presented. Physiological responses to ex-
ercise and their generalized core affective labels (i.e., states 
that vary simply on pleasantness and activation) are mo-
tivationally salient because they form the basis of desires 
that  are  often  contrary  to  valued  goals.14,15  Indeed,  the 
central purpose of affect associated with afferent bodily 
signals is to motivate action.4,16 The desire- goal conflict is 
a motivational framework that can assimilate this psycho-
physiological knowledge.
The  physiological  response  to  exercise  varies  as 
a  function  of  the  intensity  at  which  it  is  performed.17 
These responses have been characterized into exercise 
intensity domains,17,18 which are delineated by specific 
physiological  thresholds.  The  moderate  intensity  do-
main refers to intensities below the so- called first lactate 
threshold, defined as the intensity after which there is a 
sustained increase in blood lactate concentration above 
resting values (LT1).19,20 This domain is characterized by 
a steady state cardiopulmonary response and little or no 
sustained  increase  in  blood  lactate  concentration. The 
heavy intensity domain refers to intensities above LT1, 
but below critical power, which is analogous to the so- 
called second lactate threshold when there is a second 
rise  in  blood  lactate  concentration  above  resting  lev-
els (LT2).21 This domain is characterized by a delayed 
steady state and emergence of a V̇O2 slow- component, 
which eventually stabilizes after 20– 30 minutes, as well 
as a sustained but gradual increase in blood lactate con-
centration. During severe domain exercise (at intensities 
above LT2), no steady state is achieved, V̇O2 progresses 
800 |   
TAYLOR et al.
to  reach  V̇O2max,  and  blood  lactate  concentration  in-
creases  progressively.  Evaluation  of  these  domains  is 
possible via a progressive exercise test in which blood 
lactate  concentration  is  regularly  measured.  This  al-
lows estimation of the two primary physiological (lac-
tate) thresholds that delineate the moderate- heavy, and 
heavy- severe  boundaries,  respectively,  as  well  as  the 
subsequent  progression  through  each  of  the  domains. 
As  such,  these  two  thresholds  represent  an  opportu-
nity to analyze disruptions to the desire- goal conflict at 
points when broad metabolic and cardiopulmonary sys-
tem responses to exercise become unstable.
Complementary  to  inspecting  specific  thresholds 
and  domains,  it  is  worth  establishing  whether  the 
desire- goal  conflict  is  sensitive  to  continuous  changes 
in  metabolic  and  cardiopulmonary  responses  over  the 
course  of  an  endurance  act.  Comparing findings  from 
the  two  approaches  will  establish  whether  the  desire- 
goal  conflict  is  sensitive  to  general  micro- fluctuations 
(i.e.,  within- person  variation)  in  physiological  motiva-
tional inputs or stronger macro- fluctuations (i.e., lactate 
thresholds) are required to disrupt the desire- goal con-
flict. In addition to repeated measurements of blood lac-
tate concentration as a metabolic response to exercise, 
cardiopulmonary responses are also likely to influence 
motivational states.22 Heart rate, for example, is known 
to produce interoceptive information that informs emo-
tional  states.23,24  During  treadmill  exercise,  heart  rate, 
unlike other respiratory factors (e.g., V̇O2 and respira-
tory exchange ratio), remains stable when perceptions 
of effort are fixed,25 albeit the relationship between HR 
and  effort  is  likely  correlational  rather  than  causal.13 
Collectively,  this  research  implies  that  heart  rate  may 
be  an  underlying  input  to  motivational  states  during 
exercise.
In  sum,  recent  work  has  established  the  desire- goal 
conflict as an important framework to study human en-
durance.10- 12 The present study aims to build on this work 
by  investigating  the  physiological  concomitants  of  the 
desire- goal conflict during progressive exercise. It was hy-
pothesized that the trajectories of the desire to reduce ef-
fort and performance goal value would be disrupted when 
participants  transition  through  relevant  physiological 
thresholds from the moderate to heavy intensity domain 
(hypothesis 1a and 1b), and from heavy to severe intensity 
domain (hypothesis 2a and 2b). Specifically, the desire to 
reduce effort was expected to shift and/or accelerate pos-
itively, whereas the performance goal value was expected 
to shift and/or accelerate negatively. Moreover, it was hy-
pothesized that within- person variation in blood lactate 
and heart rate would positively predict the desire to re-
duce effort (hypothesis 3a and 3b) and negatively predict 
the performance goal value (hypothesis 4a and 4b).
2  |  MATERIALS & METHODS
2.1  |  Participants
Thirty 
participants 
(14 
males, 
16 
females, 
Mage  =  21.03  years;  SD  =  2.06  years)  were  recruited 
through a university scheme in which students can partic-
ipate in studies for course credit, as well as adverts placed 
with university triathlon and cycling teams. Participants 
were  required  to  be  18– 35  years  old,  physically  active 
(i.e., a minimum of 30 minutes moderate intensity activ-
ity three days a week for three months) and free of pre- 
existing medical conditions or family history that made 
high  intensity  exercise  potentially  unsafe.  Sample  size 
targets were based on a minimum of 30 level- 2 units (i.e., 
participants  in  the  present  study)  required  for  minimal 
bias in statistical parameters, when combined with at least 
five level- 1 units (i.e., measurement points in the present 
study) for multilevel modeling.26
2.2  |  Procedure
All experimental procedures were approved by a univer-
sity ethics approvals committee and conformed with the 
Declaration of Helsinki. Participants were fully informed 
of study details and the risks and discomforts associated 
with all experimental trials. It was clarified that participa-
tion was voluntary, data would be stored anonymously, 
and they had a right to withdraw at any point during the 
study without consequences. Participants provided writ-
ten informed consent and completed questionnaires to es-
tablish that they met the inclusion criteria (i.e., they were 
generally healthy and physically active). Participants were 
initially instructed that the goal of the session was to place 
as high as possible on a leaderboard containing all partici-
pants’ performance scores and, to enhance the meaning-
fulness of the goal, they were to set a target position on 
the leaderboard. Leaderboards are commonly used to set 
meaningful goals in psychology research, especially when 
the goal is difficult.27
Participants  performed  an  incremental  cycling  test 
on  an  electronically  braked  cycle  ergometer  (Lode 
Excalibur Sport, Lode B.V. Gronigen, The Netherlands). 
Ergometer saddle and handlebar dimensions were setup 
to  suit  individual  specifications.  Participants  cycled  at 
a freely chosen pedal rate at an initial work rate of ei-
ther  50  or  100  watts  (W)  depending  on  personal  pref-
erence  and  experience  (e.g.,  cyclist/triathlete).  This 
flexibility was permitted because we were not interested 
in performance data (e.g., time to exhaustion), only un-
derlying psychological and physiological data during ex-
ercise. Work rate was increased by 25 W at four- minute 
   | 801
TAYLOR et al.
intervals. Visual  information  regarding  pedal  rate  and 
workload was obscured to avoid participants using this 
information to regulate their performance. During the 
third  minute  of  each  four- minute  stage,  participants 
were presented with measures of their desire to reduce 
effort and performance goal value. During the last thirty 
seconds of each stage, capillary blood samples were ob-
tained for the immediate measurement of blood lactate 
concentration.  Heart  rate  was  recorded  at  the  end  of 
each stage. The test continued until voluntary exhaus-
tion or when two stages had been completed in which 
a  clear  increase  in  blood  lactate  concentration  above 
4 mmol.L−1 had occurred (to obtain data in the severe 
intensity domain), whichever came first. We did not ask 
participants to continue beyond two stages in the severe 
domain  because  this  was  not  necessary  to  answer  the 
research questions.
2.3  |  Measures
Desire and goal value. The desire to reduce effort was 
measured by verbal responses to the instruction “Please 
rate to what extent do you want to reduce your effort” on 
a 20- point scale, ranging from 1 (not wanting to reduce 
effort at all) to 20 (definitely want to reduce effort imme-
diately). The value of the performance goal was measured 
by responding to the instruction “Please rate how impor-
tant is it to achieve your goal” on a 20- point scale, ranging 
from 1 (not important at all) to 20 (extremely important). 
Similar  scales  have  demonstrated  predictive  and  nomo-
logical validity in previous work.12
Blood lactate concentration, lactate thresholds, 
and establishment of exercise domains. Capillary blood 
samples  were  taken  from  the  earlobe  and  immediately 
analyzed  for  blood  lactate  concentration  (Lactate  Pro 
2,  Arkray,  Japan).  A  blood  lactate/work  rate  curve  was 
modelled  for  each  participant  using  publicly  available 
software.28 The work rate corresponding to an initial in-
crease of 1 mmol.L−1 above baseline concentration during 
the initial stage of the exercise test, and fixed blood lac-
tate  concentration  of  4  mmol.L−1  were  defined  as  LT1 
and  LT2,  respectively,  and  were  used  to  demarcate  the 
moderate, heavy, and severe domains of exercise. Blood 
lactate  concentration  is  a  reliable  method  to  determine 
exercise intensity,29 generally superior to heart rate30 and 
circumvents the need to assess expired gases for V̇O2.
Heart rate. Heart rate was continually monitored (T31 
transmitter  and  FT1  watch,  Polar  Electro  Oy,  Kempele, 
Finland).
2.4  |  Data analysis
MLwiN  software  (version  3.0531)  was  used  to  construct 
multilevel models to test study hypotheses. This method 
was used because of the hierarchical structure of the data 
with each measurement of desire, goal value, blood lactate 
concentration, and heart rate (Level- 1 time- varying units) 
nested within each participant (Level- 2 units32). First, un-
conditional  means  models  (i.e.,  no  predictor  variables) 
were formed to describe the variance of study variables 
associated  with  level- 1  (i.e.,  within- person)  and  level- 2 
errors (i.e., between- person). To test hypothesis 1 and 2, 
two multilevel growth models (for desire and goal value, 
respectively)  were  constructed  by  simultaneously  add-
ing a linear time predictor variable (each time point was 
coded as 1, 2, 3, etc.), two dichotomous “threshold” pre-
dictor variables indexing pre- (coded as 0) to post- (coded 
as 1) LT1 and LT2 threshold measures, respectively. In ad-
dition, two higher order interaction terms between each 
threshold variable and linear time were included. These 
models estimate a) the degree of linear change in desire 
and goal value over the course of the trial, b) the change 
in mean levels as a function of the respective thresholds, 
and c) the alterations in rate of change as a function of the 
thresholds.
To examine hypotheses 3 and 4, two multilevel models 
without time and threshold variables included, but with 
lactate concentration and heart rate as predictor variables 
of desire and goal value. The predictor variables were cen-
tered around each participant's unique mean (i.e., group 
mean centered), therefore, the models estimated whether 
within- person variation (as opposed to individual differ-
ences) in blood lactate or heart rate predicted desire to re-
duce effort and performance goal value.
Variable
Lactate Threshold 1
Lactate threshold 2
Mean (SD)
Range
Mean (SD)
Range
Desire to reduce effort
4.67 (3.60)
1– 15
7.04 (4.80)
1– 18
Performance goal value
14.67 (4.55)
3– 20
14.22 (4.76)
3– 20
Heart rate (beats.min−1)
151 (14)
119– 175
165 (14)
133– 186
Power (Watts)
155.56 (58.56)
75– 300
184.26 (56.82)
75– 325
TABLE 1  Descriptive statistics of 
study variables
802 |   
TAYLOR et al.
3  |  RESULTS
3.1  |  Descriptive Statistics
Descriptive  statistics  for  the  study  variables  at  LT1  and 
LT2  can  be  found  in  Table  1.  On  average,  participants 
completed 7.57 stages (SD = 1.74), which are equivalent 
to approximately 30 minutes of work. Twenty- eight par-
ticipants cycled until voluntary exhaustion, and two par-
ticipants were stopped twice by an investigator because 
two stages in the severe intensity domain had been com-
pleted. Average heart rate at LT1 and LT2 was 83 percent 
and 91 percent, respectively, of participants’ heart rate at 
task cessation. Average workload at LT1 and LT2 was 68 
percent and 81 percent, respectively, of participants’ peak 
workload. Unconditional means models revealed that 20 
percent of the variance in performance goal value was at-
tributable to within- person variation, and 80 percent at-
tributable to individual variation. In contrast, 85 percent 
of the variance in desire to reduce effort was attributable 
to within- person variation, and 15 percent was attribut-
able to individual variation.
3.2  |  Trajectories of desire to reduce 
effort and performance goal value across 
intensity domains (hypotheses 1 and 2)
In Table 2, multilevel growth model 1 describes the trajec-
tory of the desire to reduce effort over the trial, therefore, 
investigating hypotheses 1a and 2a. The model indicated 
that the desire to reduce effort generally increased over 
the course of the trial (linear time coefficient), shifted at 
LT1  and  LT2  (threshold  coefficients),  and  accelerated 
after each threshold (interaction terms). This pattern in 
desire to reduce effort is illustrated in Figure 1, which de-
scribes predicted trajectories in desire and goal value over 
time and when participants transition through LT1 and 
LT2. Variance terms indicated that the linear increase and 
the shift at the LT2 varied in magnitude across individu-
als, but the shift at the LT1 did not. When allowing the 
interaction terms to vary across individuals the model did 
not converge; hence, these parameters are not reported.
Model 2 describes the trajectory of performance goal 
value  over  the  trial,  therefore,  investigating  hypotheses 
1b and 2b. The model revealed that the performance goal 
value did not linearly decline over the course of the trail 
(linear time coefficient), nor did it shift at LT1 (threshold 
coefficient). However, the performance goal value shifted 
at LT2 (threshold coefficient), and the rate of change was 
disturbed  at  both  thresholds  (interaction  terms).  This 
pattern in goal value across the course of the trial is illus-
trated in Figure 1. Variance terms indicated that the linear 
change, but not the shift at LT2, significantly varied across 
individuals. When allowing the remaining effects to vary 
across  individuals,  the  model  did  not  converge;  hence, 
these parameters are not reported.
3.3  |  Within- person variation of 
blood lactate concentration and heart 
rate predicting desire and goal value 
(hypotheses 3 and 4)
Multilevel  models  revealed  that  within- person  varia-
tion  in  blood  lactate  concentration  positively  correlated 
with the desire to reduce effort (b = 0.69, p < .001) and 
negatively  correlated  with  the  performance  goal  value 
(b = −0.15, p = .02). A small positive correlation between 
within- person variation in heart rate and desire to reduce 
effort (b = 0.05, p < .001) was observed, but no significant 
relationship  between  heart  rate  and  performance  goal 
value (b = 0.00, p = .37).
4  |  DISCUSSION
The  desire- goal  conflict  has  been  proposed  as  a  valid 
framework to study motivational dynamics during en-
durance  performance,10  but  potential  underpinning 
TABLE 2  Multilevel growth models describing desire to reduce 
effort and performance goal value across LT1 and LT2 thresholds
Outcome
Desire to reduce 
effort (model 1)
Goal value 
(model 2)
Fixed Effects (SE in parentheses)
Intercept
−0.37 (0.37)
14.84 (0.99)
Linear time
1.09 (0.21)
0.01 (0.14)
LT1 threshold
−3.50 (0.99)
1.21 (0.80)
Time ×LT1 threshold
0.84 (0.20)
−0.40 (0.16)
LT2 threshold
−5.26 (1.34)
2.08 (1.01)
Time ×LT2 threshold
1.04 (0.22)
−0.39 (0.18)
Variance Terms
Intercept
1.20 (0.84)
27.92 (7.49)
Linear time
0.85 (0.30)
0.39 (0.13)
LT1 threshold
1.21 (1.34)
Time ×LT1 threshold
LT2 threshold
5.31 (2.40)
1.76 (1.03)
Time ×LT2 threshold
Note: Bold figures indicate statistical significance (p ≤ .05). Exact values can 
be calculated from the Z scores (b/SE for the fixed effects). Variance terms 
are not reported in instances when the predictor variable was not permitted 
to vary across individuals to aid convergence of models. LT = Lactate 
Threshold.
   | 803
TAYLOR et al.
physiological  concomitants  were  unknown  until  now. 
Two different blood lactate thresholds were inspected to 
observe changes in the desire to reduce effort and value 
of a performance goal at these periods, which are char-
acterized by physiological instability. Moreover, within- 
person  variation  in  blood  lactate  concentration  and 
heart rate was examined as correlates of the desire and 
performance goal value. Results indicated that progres-
sion from the moderate through to the heavy and severe 
domains of exercise by transitioning through LT1 and 
LT2, respectively, are points in which motivational dy-
namics are perturbed, particularly the desire to reduce 
effort. Variation in blood lactate concentrations was a 
stronger correlate of the desire to reduce effort and per-
formance goal value, compared with variation in heart 
rate.
In  any  activity  requiring  self- control,  the  desire  to 
stop will increase as a function of time.33 Unsurprisingly, 
therefore, a general increase in the desire to reduce effort 
was observed in the present study. As expected, however, 
this desire deviated from its trajectory and began to ac-
celerate when the LT1 occurred, and participants entered 
the heavy exercise domain. The same picture is presented 
regarding LT2 and entry into the severe exercise domain. 
At this point, the desire to reduce effort shifts again and 
further  accelerates.  Previous  research  has  not  modeled 
changes in motivational factors as a function of these two 
physiological thresholds. Nonetheless, core affect has been 
shown to be stable below the ventilatory threshold (which 
typically occurs at a similar exercise intensity as the LT113) 
but  become  increasingly  negative  after  it.34  Our  results 
align with the idea that hedonic motivational factors that 
encourage avoidance of unpleasant states, such as nega-
tive affect and desire to reduce effort, become increasingly 
powerful when aversive physiological responses accumu-
late. The causal pathway linking physiological responses 
and generalized core affective labels,3 which subsequently 
manifest into a motivational state,5 were not investigated 
here but seems the most plausible explanation for this pat-
tern of findings.
Both  physiological  thresholds  also  have  implications 
for the value of performance goal. The value of the goal 
did not shift at LT1; however, after a period of stability it 
began to significantly decline at this point. LT2 (and entry 
into the severe intensity domain) coincided with a shift 
in level and a change in rate of decline. The smaller re-
gression coefficients compared with the desire to reduce 
effort imply that underlying physiological responses con-
tribute less to the performance goal value. Nonetheless, it 
may be inaccurate to suggest that the performance goal 
value  is  entirely  underpinned  by  more  stable  reflective 
factors,  such  as  internal  and  external  incentives.10  The 
lactate thresholds may signify that goal achievement is be-
coming increasingly difficult, therefore, reductions in goal 
value may occur to protect self- worth (i.e., defensive pes-
simism35). The comparable (albeit in opposing directions) 
disturbances of desire and goal value at the two lactate 
thresholds imply that they are not isolated motivational 
components  with  distinct  concomitants,  but  they  share 
some physiological correlates during progressive exercise.
The primary aim of some types of endurance training 
is to delay reaching the lactate thresholds and associated 
physiological consequences resulting in fatigue. The col-
lective findings of the present study imply that achieving 
this  aim  also  has  important  motivational  ramifications. 
These  physiological  thresholds  are  associated  with  in-
creases in the motivational potency of the desire to reduce 
effort and simultaneous decreases in the value of the per-
formance goal. As such, the relative weight of each moti-
vational component shifts in favor of the proximal desire, 
and diminished endurance performance occurs.12 Positive 
motivational consequences can, therefore, be added to the 
list of benefits resulting from delayed lactate thresholds.
In  addition  to  the  examination  of  physiological 
thresholds  and  intensity  domains,  the  results  demon-
strated  that  within- person  variation  in  blood  lactate 
FIGURE 1 
Illustrative trajectories of 
desire and performance goal value during 
the cycling trial
804 |   
TAYLOR et al.
concentration  was  positively  associated  with  the  de-
sire to reduce effort and negatively associated with the 
performance goal value. The relationship was stronger 
with the desire to reduce effort, compared with the per-
formance goal value, again implying that blood lactate 
concentration is more salient for the hedonic desire to 
reduce  effort  than  the  performance  goal  value.  A  rel-
atively  smaller  positive  correlation  between  within- 
person variation in heart rate and desire to reduce effort 
was observed, and no significant relationship between 
heart rate and performance goal value. Hence, the mag-
nitude  of  the  regression  coefficients  suggests  that  the 
relationship between lactate and motivation is stronger 
than heart rate and motivation. Previous work offers no 
definitive conclusion regarding the relative coupling of 
heart rate and lactate with motivational factors. Some 
evidence  suggest  perceived  exertion  is  correlated  to  a 
greater  extent  with  heart  rate  compared  with  lactate 
concentrations.36 However, the present analysis focuses 
on within- person variation, rather than absolute levels, 
which  makes  comparison  with  previous  research  dif-
ficult. It is likely that deviations of physiological state 
within  an  individual  are  more  likely  to  stimulate  mo-
tivational  responses  (within- person  variation),  as  op-
posed to individual differences leading to corresponding 
differences in motivation (between- person differences). 
The impact of lactate concentration on motivational fac-
tors is likely not direct, of course, but indirect via pH 
changes  associated  with  lactic  acid  production.37  The 
affective sensation associated with this process may be 
more potent, given that heart rate interoceptive signals 
can be easily suppressed in favor of alternative stimuli.38
4.1  |  Limitations and Future 
Research Directions
Future research should experimentally manipulate un-
derpinning  physiological  states  to  establish  causal  ef-
fects  on  the  desire- goal  conflict.  This  can  be  achieved 
acutely through, for example, nutritional supplementa-
tion  such  as  prior  ingestion  of  sodium  bicarbonate  or 
ammonium  chloride  to  induce  metabolic  alkalosis  or 
acidosis, respectively,39 or chronically through exercise 
training. A familiarization trial would be necessary to 
include in this type of experiment, which did not occur 
in  the  present  study.  In  addition,  a  measure  of  affect 
alongside  the  desire  to  reduce  effort  would  provide  a 
more detailed examination of the assumed relationship 
between  affective  responses  and  the  desire  to  reduce 
effort. Third, our healthy and active sample may limit 
the generalizability of some of the findings in the study. 
For example, participants with experience of strenuous 
activity  may  appraise  the  associated  sensations  of  lac-
tate accumulation less negatively, compared with an un-
healthy and inactive sample.
The prevailing method of analyzing physiological re-
sponses to exercise is to treat each response as a directly 
observed  variable  working  independently.  Instead,  each 
physiological  parameter  can  be  used  as  a  composite  la-
tent variable describing overall homeostatic disturbance. 
That is, each individual parameter contributes to a higher 
order construct, but they do not cause any motivational 
disturbances on their own. This latent factor approach is 
common in psychology but would be physiologically inno-
vative and align with the idea that system- wide responses 
to exercise manifest into an overall gauge of homeostatic 
integrity.5
Future research should also examine how to delay the 
desire- goal  conflict,  particularly  when  the  desire  begins 
to  overcome  the  performance  goal  value.  Delay  can  be 
achieved by lowering the desire to reduce effort, increasing 
the magnitude of the performance goal value, or a com-
bination of these strategies. Existing work has suggested 
that enhancing the congruence between the performance 
goal and one's identity12 can disturb the desire- goal con-
flict favorably. This approach fits with other motivational 
frameworks, such as the identity- value model40 and self- 
determination  theory.41  Other  strategies  have  potential, 
such as enhancing the congruence between actively man-
aging discomfort and the performance goal (i.e., means- 
end fusion42).
4.2  |  Perspective
The  desire- goal  conflict  is  a  recently  applied  motiva-
tional framework that helps explain endurance perfor-
mance.10,12 Unlike most other models of endurance that 
considers  motivation  as  a  unidimensional  construct,1 
motivation  is  viewed  as  a  network  of  constructs  and 
related processes. Moreover, it has the potential to rec-
oncile  different  physiological  and  psychological  ideas, 
such as the role of physiological responses to exercise 
and their affective labels in shaping motivational pro-
cesses.3,4 Overall, the present study represents the first 
analysis of how the desire- goal conflict is disturbed by 
two  physiological  thresholds  (i.e.,  LT1  and  LT2,  and 
how  these  delineate  fundamental  exercise  intensity 
domains).  These  thresholds,  therefore,  represent  im-
portant  points  when  motivational  factors  become  in-
creasingly detrimental to performance and intervention 
is required. In addition, analyzing within- person varia-
tion in blood lactate and heart rate may portray a clearer 
picture of their relationship with motivation constructs, 
compared with absolute levels.
   | 805
TAYLOR et al.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are avail-
able from the corresponding author (IT), upon reasonable 
request.
ORCID
Ian M. Taylor 
 https://orcid.org/0000-0001-6291-4025 
Richard A. Ferguson 
 https://orcid.
org/0000-0002-2508-8358 
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How to cite this article: Taylor IM, Whiteley S, 
Ferguson RA. Disturbance of desire- goal 
motivational dynamics during different exercise 
intensity domains. Scand J Med Sci Sports. 
2022;32:798– 806. doi:10.1111/sms.14129

Disturbance of desire-goal motivational dynamics during different exercise intensity domains.
Taylor, Ian M,Whiteley, Summer,Ferguson, Richard A