Psychology
2014. Vol.5, No.1, 78-89
Published Online Janu ary 201 4 in Sci R es (http://www.scirp.org/journal/psych) http://dx.doi.org/10.4236/psych.2014.51013
Stress Management Based on Trait-Anxiety Levels and Sleep
Quality in Middle-Aged Employees Confronted with Psychosocial
Chronic Stress
Marion Troussela rd1*, Dominique Steiler2, Angelique Lebreton1, Pascal Van Beers1,
Catherine D rogout1, Josi ane Denis1, Mounir Chennaoui1, Frédéric Canini1
1Département des Environnement Opérationnels, IRBA-CRSSA, La Tronch e, France
2Département Management et Comportements, Grenoble Ecole de Management, Grenoble, France
Received July 24th, 2013; revised October 26th, 2013; accepted December 2nd, 2013
Copyright © 2014 Marion Trousselard et al. This is an open access article d istributed under the Creative Com-
mons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, pro-
vided the original work is prop erly cited. In accordance of the Creative Commons Attributio n License all Copy-
rights © 2014 are reserved for SCIRP and the owner of the intellectual property Marion Trousselard et al. All
Copyright © 2014 a re guarded by law and by SCIRP as a guardian.
A stress management program using cardiac coherence was implemented after an organizational down-
sizing. The study was conducted in nine voluntary workers in order to evaluate the efficiency of the pro-
gram. A baseline evaluation was conducted on psychological variables (anxiety, perceived-stress, well-
being and sleep), endocrine assessments (urinary cortisol excretion, alpha-amylase and salivary concen-
trations) and physiological recordings (sleep and heart rate variability). The low number of participants
was due to the intrusive approach in collecting physiological and endocrine variables. The program con-
sisted of ten sessions of cardiac coherence training during a 3-month follow-up period. At the end of the
training sequence, subjects were once again exposed to the same evaluation battery. A decrease in per-
ceived stress and a subsequent increase in well-being were observed. Sleep quality improved as suggested
by the results of the subjective and objective measurements. For the entirety of the results, improvements
were higher in subjects with high vs. low trait-anxiety scoring. The pattern of results for subjects prone to
a high level of trait-anxiety suggested that stress and sleep are related to each other in a bidirectional way:
increased anxiety is associated to poor sleep and stress reduction improves both anxiety and sleep. On the
basis of these results, we suggest that trait-anxiety can be used as an indicator of which employees should
be given priority for stress management intervention. We will also highlight the interest of operationally
physiological recordings, used outside the laboratory, for measuring objective improvements due to this
stress management intervention, as quality of sleep.
Keywords: Anxiety; Work Stress; Sleep; Stress Management
Introduction
A growing body of evidence indicates that downsizing and
its related forms of organisational restructuring can have pro-
found adverse effects on worker safety, health and well-being
through stress (Bourbonnais et al., 2005; Kalimo et al., 2003;
Kang et al, 2004; Vahtera et al., 2004).
The reaction of individuals to chronic stress is theorized in
the general alarm syndrome and allostasis theories (Sterling &
Eyer, 1988), conducting to high biological cost featuring the
allostatic load (Chrousos, 2009). Stress underpins a number of
disturbances often found in a psychosocial stress context. Psy-
chosocial stressor exposure is associated with an enhanced
Hypothalamo-Pituitary-Adrenal (HPA) axis as shown by the
increase in cortisol reaction (Biondi & Picardi, 1999; Chida &
Hamer, 2008; Chida & Steptoe, 2009).
The Autonomic Nervous System (ANS) with its two sympa-
thetic and parasympathetic branches is also activated in stress-
ful conditions with an increased sympathetic tonus, a decrease
in parasympathetic tonus and reduced heart rate variability
(HRV) (Friedman & Thayer, 1998; Porges, 1995). Such a pa-
ttern is also observed in psychosocial strain situation (Horsten
et al., 1999; Ohira et al., 2008). An appropriate vagal response
therefore involves high vagal flexibility that both allows sym-
pathetic activity to occur and limits its activation to the period
of stressors presence. Consequently, healthy physiology could
be features of high levels of adaptative variability (Lucini et al.,
2002; Porges, 1995).
Subjects exposed to psychosocial stressors also experienced
emotional disturbance centered by anxiety levels (Lazarus,
1993; Poleshuck et al., 2009). This anxiety is both the conse-
quence of previous stressor exposures (Haftgoli et al., 2010;
Poleshuck et al., 2009) and a factor of vulnerability for future
stressor exposures (Hanson & Chen, 2010; Boyce & Ellis,
2005). Subjects with high levels of trait-anxiety typically res-
pond to stress with greater elevations of cognitive and physio-
logical arousal, impairment of motor performance, and health
*
Corresponding author.
78

M. TROUSSELARD ET AL.
disorders compared with subjects who have low levels of trait-
anxiety (DeMo ja & DeMoja, 1986; Grillon et al., 1993; Haft-
goli et al., 2010; Sade et al., 1990; Poleshuck et al., 2009). The
negative effects of trait-anxiety (TA) may be attributed to the
tendency to respond fearfully to a wide variety of unspecific
stressors, and the need for both security and cognitive control
(Fales et al., 2008; Spielberger, 1966, 1970, 1975). In this way,
state-anxiety could correspond exactly to mood variations
(Bolmont & Abraini, 2001). Presumably people are always ex-
periencing a continuous stream of affects, manifesting itself in
some sort of mood, which provides a background to everyday
activities (Watson & Clark, 1994).
Then exposure to psychosocial stressors may also induce
sleep disorders as indicated by a growing amount of literature
on the associations between stressful workplace experiences
and sleep problems (Linton, 2004; Nakata et al., 2004; Kalimo
et al., 2000; Akerstedt et al., 2002; Marquie et al., 1999; Jac-
quinet-Salord et al., 1993). The inability to stop worrying about
work during free time may be an important link in the relation-
ship between stress and sleep (Akerstedt et al., 2002).
Pharmaceutical approaches have been developed to regulate
the endocrine and SNS imbalances and to therefore improve
health and quality of life for working people (Head & Kelly,
2009). A combination of certain attitudes and behaviour cons-
titutes a more natural approach based on physical training, sleep
rest strategies, or dietary and nutritional strategies. Other forms
of mental training, such as yoga, martial arts, meditation, and
creative courses are also in common use (Carlson & Garland,
2005). Education and training, as well as the use of external
information processing devices, may be labelled as “conven-
tional” means of reducing stress. They are often well establi-
shed and culturally accepted. Research exploring the impact of
the regulation of emotions on physiological processes is still
relatively scarce in the context of work restructuring (McCraty
et al., 2003). The capacity to both self-reduce negative emo-
tions and self-generate positive emotional states however, can
be developed confronting stress in changes at work and refined
through the use of practical tools and techniques quickly enhan-
cing a shift to a physiologically quiet state by increasing para-
sympathetic flexibility (Porges, 1995).
In line, techniques for enhancing heart/brain synchronization
(Heart Coherence, Cardiac Coherence (CC)), facilitating the
maintenance of a physiologically efficient and highly regene-
rative inner state, characterized by reduced nervous system
chaos and increased synchronization and harmony in system-
wide dynamics have been developed. This psychophysiological
mode, termed physiological coherence, is conducive to healing
and rehabilitation, emotional stability and optimal performance
(McCraty et al., 1995; McCraty et al., 1998). Recent research
has demonstrated that HRV dynamics are particularly sensitive
to changes to emotional state, and that positive and negative
emotions can be readily distinguished by changes in heart
rhythm patterns, which are independent to the heart rate (Mc-
Craty et al., 2003; McCraty et al., 1998). More specifically,
during the experience of negative emotions such as anger, frus-
tration, or anxiety, heart rhythms become more erratic or disor-
dered, indicating less synchronization in the reciprocal action
between the parasympathetic and sympathetic branches of the
autonomic nervous system. In contrast, sustained positive emo-
tions, such as appreciation, love, or compassion, are associated
with a highly ordered or coherent pattern in the heart rhythms,
reflecting greater synchronization between the two branches of
the autonomic (Tiller et al., 1996). An important reason that
this technology is effective is that it uses HRV feedback for
reflecting the activity of both the sympathetic and parasympa-
thetic branches of the autonomic nervous system and the syn-
chronization between them, and thus providing a window into
the dynamics of the system 2 as a whole. Compared to EEG
feedback, HRV feedback is also considerably simpler and more
straightforward to learn and use, which facilitates rapid im-
provement. Furthermore, because the instrumentation only uses
a simple pulse sensor that does not require an electrode hook-up,
it is extremely versatile and can be easily and effectively used
as an educational tool not only in clinical settings but also in
the home, workplace, schools, or even whilst traveling. Its
cost-effectiveness also makes it accessible to a greater number
of people and in a wide range of applications (McCraty et al.,
2003). In relation to other biofeedback modalities, HRV feed-
back also reflects changes in emotional/psychological state for
subjects (Lehrer et al., 2003; McCraty et al., 1998; Mc Craty &
Tomasino, 2004).
As reducing stress and increasing emotional stability and
quality of sleep are critical for dealing with organisational res-
tructuring, the aim of the present study is to evaluate the bene-
fits of the use of an intervention based on physiological coher-
ence in a sample of middle-aged workers confronted with or-
ganisational changes by answering four specific questions. The
first question concerns the physiological and psychological
stress level benefits of the intervention. How such an inter-
vention impacts the subjective and objective quality of sleep is
the second assessed question. Third, faced with the intervari-
ability observed in monitoring stressors, the third one ex-
amines how trait-anxiety modulates the stress and sleep res-
ponses to the intervention program. Finally, the last question
concerned testing the feasibility, as acceptance for subjects, and
the interest, of "light" physiological recordings used outside the
laboratory for evaluating benefits of such an intervention. We
assume that cardiac coherence training will increase the posi-
tive assessed outcomes and will reduce the negative assessed
outcomes. We also assume that the improvement of the emo-
tional functioning will be better for the more anxious subjects.
Finally, whether subjects accept the “light” physiological re-
cordings used outside the laboratory could depend on individu-
als.
Materials and Method
Parti cipants
A research laboratory, employing 160 personnel, submitted
to downsizing and related forms of organisational restructuring
in the following two years was contacted for the study. Indi-
viduals of the lab received a letter inviting men (90 subjects
from the research lab) to participate in the study. The letter was
supported by a covering letter from the management, and con-
tained three types of information. First, the main aim of the
study was noted as a psycho-physiological investigation based
on questionnaires about stress and physiological recordings,
with guidance for the protocol for the experiment. Second, the
desired criteria to be included in the study were defined as:
being male, not to be undergoing treatment and not to have
practiced stress intervention since the announcement of the
restructuration of the laboratory. Third, the protocol design was
clearly described (Figure 1). They were also informed that the
study was conducted in accordance with all applicable regu-
OPEN ACCESS 79

M. TROUSSELARD ET AL.
Figure 1.
The protocol design f or the baselin e, middle and end o f the training ti me points. Fo r the middle of the tr aining time po int, EE G was
not recorded and salivary alpha amylase was not collected.
latory requirements, including the 1996 version of the Helsinki
Declaration, and approved by the French Health Authorities.
Nine volunteers had given written consent to participate in the
study.
Materials
Psychological Assessments
All subjects completed a set of “paper and pencil” standar-
dized assessments including common socio-demographic data,
trait and state anxiety levels, the Cohen perceived stress scale,
the Buguet Sleep questionnaire, and the Activation-Deactiva-
tion Adjective Check List. The Socio-demographic and trait-
anxiety questionnaire were only completed at the baseline time-
point whereas the four other questionnaires were completed at
three time-points: a pre-intervention step (baseline), a middle
intervention step and an after the end of the intervention step.
Trait and state anxiety was assessed using the French version
of the Spielberger State-Trait-Anxiety Inventory (S-STAI). It is
a 40-item self-reported questionnaire (Spielberger, 1970, 1975;
Bruchon-Schweitzer & Paulhan, 1993; 10 min). The internal
consistency of the whole scale was very good (Cronbach’s
alpha = .80 to .92; Bruchon-Schweitzer & Paulhan, 1993). In
the state portion of the scale, 20 items ask subjects to report the
extent of their anxiety at particular moments. In the trait scale,
the remaining 20 items ask respondents to indicate the i ntensity
of their anxiety in general. Mean (SD) in a non-clinical sampl e
of middle-aged men were 35.55 (9.76) and 36.54 (10.22) for
trait a n d state anxie ty, respectively.
The Perceived Stress Scale (PSS; 5 min; Bruchon-Schweitzer,
2002; Cercle et al., 2008; Cohen et al., 1983) is a 14-item self-
reported scale designed to assess subjects’ appraisal of how
stressful their life situation feels to them. The Cronbach’s alpha
reliability estimate for this measure was .84 (Bruchon-Sch-
weitzer, 2002; Cohen et al., 1983). The PSS is recommended
for assessing non-specific appraisals because it is found to pre-
dict better stress-related psychological symptoms and physical
symptoms compared to commonly used life event scales
(Berghal & Berghal, 2002).
A subjective self-reported sleep questionnaire (5 min; Buguet
et al., 1981; Trousselard et al., 2009) was used to evaluate the
quality of the subjects’ sleep during the week before each ses-
sion. It consisted of two sleep items [i.e., restoration quality and
ease of falling asleep) featured by Visual Analogue Scales from
“−”on the left to “+” on the right. Three well-being items in-
vestigated physical, psychological mood and Joy of going to
work. The subjects “hooked” a cross on a scale using the pencil,
and dragged it to the appropriate location on the scale (12 cm
long). This questionnaire was filled on awakening during one
week at each of the steps of the e valuation sessions, leading to 7
daily questionnaires per time-point for each subject.
The Activation-Deactivation Adjective Check List (AD-ACL,
Thayer, 1979, 1989) is a multidimensional self-reported test
assessing various transitory arousal states. The 20 item-short
form evolved two bipolar dimensions titled Energetic-Arousal
and Tense-Arousal (Thayer, 1967, 1978, 1986, 1989; Thayer et
al., 1994). Energetic-Arousal contains both energy and sleep
items leading to General Activation (GA) and tiredness (Deac-
tivation-Sleep, DS) sub-factors. The tense-arousal contains both
emotional and quiet items leading to Tension (High Activation,
HA) and calmness (General-Deactivation, GD) sub-factors. The
reliability of the AD-ACL scale was estimated as .92 based on
communality results from a factor analysis (Thayer, 1978).
Physiological and Sleep Assessments
Physiological recordings used two Actiwave devices (Acti-
wave, Camntech Ltd.). They are a range of miniature solid-state
biosignal recorders which can be worn discreetly on the body
without the need for a large belt mounted recorder or lengthy
wires. They are reliable and record the same thing as existing
ECG/EEG/EOG/EMG capturing equipment under normal sleep
laboratory conditions (Elbaz et al., 2008). For one subject, elec-
trodes were placed at about 18h00, correct signal functioning
were controlled with a calibration procedure, and then the re-
cordings were programmed to record at 22h00, when the sub-
ject goes to bed. After the night at home, he returned to the lab
at around 8h00 the following morning and the devices were
removed to analyse the night’s recordings. Assessments were
applied at the baseline, and at the end of the training leading to
18 EEG and 18 HRV recordings.
An Actiwave Cardio was used for electrocardiogram re-
cording. It was digitalized with a 256-Hz sampling rate to ac-
curately detect R-wave peaks. Time intervals from ectopic
beats were detected and substituted by interpolated values of
normal RR intervals using an adaptive filtering method (avai-
lable on: http://tocsy.agnld.unipotsdam.de/) (Wessel et al.,
1990). Beat-to-beat time series (HRV signal) were analysed by
a produced and validated computer program (Niskanen, 2004).
Readings were done by an HRV analysis expert who had no
inclusion in the participants’ experimental sessions. All HRV
parameters were defined according to international measure-
ments standards (Malik et al., 1996). The HRV temporal analy-
80

M. TROUSSELARD ET AL.
sis of the night was carried out as requested for long recordings,
namely sleep (Burr, 2007). The following time-domain HRV
parameters were analysed: mean NN interval (mean NN), stan-
dard deviation of the NN intervals (SDNN), standard deviation
of the successive NN differences (SDSD), the square root of the
mean of the sum of successive NN differences (RMSSD), and
the percentage of adjacent pairs of RR intervals that differed by
more than 50 ms from each other (pNN50). SDNN is indicative
of overall HRV. SDSD, RMSSD and pNN50 evaluate beat-to-
beat fluctuations. Although all the indexes are influenced by
both sympathetic and parasympathetic activity, those extracted
from beat-to-beat variability are considered good estimators of
parasympathetic modulation of heart rate (Parati et al., 2006;
Sollers et al., 2007), whereas the variable expressing long term
HRV (SDNN) is dually influenced by cholinergic and adrener-
gic activities, as well as by other physiological inputs (Malik et
al., 1996). Calculations were done for the entire night’s study
(from 2300 h to 0600 h).
Another Actiwave module was used for the EEG recording. It
was digitalized with a 128 Hz sampling. Reference record- ings
were made using Compumedics Siesta/ProFusion equipment to
record EEG, EOG and EMG channels and these were used to
annotate sleep stages. EEG signals for “C3-A2” and “O1-A2”
were recorded using two channels of the Actiwave EEG chan-
nel device, the chin EMG signal was recorded using two EMG
channels, and the EOG was recorded using one channel. The
EEG and EMG electrodes for the Actiwaves and reference
systems were placed as close together as possible without con-
necting them together. In addition to the standard manual
AASM scoring and resulting hypnograms, automated spectral
analysis was used to quantify the power of each frequency band
in 15-minute epochs. The EEG signals were also analysed for
their spectral content in the Delta, Theta, Alpha and Beta bands
during each sleep epoch by a computer program produced and
validated [Somnologica].
Endocrine Assessments
All endocrine assessments concerning salivary enzyme al-
pha-amylase and salivary chromogranin A were carried out
between 15h30 and 18h00 in order to control circadian varia-
tion (Branderger, 1992; Den, 2007). Salivary chromogranin A
was collected at the baseline, middle-training and at the end of
the training leading to 27 samples from the nine subjects. Sali-
vary chromogranin A is a major protein in adrenal chromaffin
cells and adrenargic sensitive neurons and a substantial index
for psychosomatic stress (Nakane, 1998). Salivary enzyme
alpha-amylase was collected at the baseline and at the end of
the training leading to 18 samples from the nine subjects. Sali-
vary enzyme alpha-amylase is reported to have a reaction to
psychological stressors (Nater et al., 2005; Nater et al., 2006).
For each endocrine measure, a 5 mL saliva sample was col-
lected in Salivette tubes according to specification of the pro-
vider [Yanaihara Inst Inc and Salimetrics; Europe ltd., respect-
tively]. Two hours before each collection, eating, drinking or
smoking were not allowed. Once filled, the tubes were centri-
fuged, sampled into 1.5 mL aliquots stored at −80˚C until ana-
lysis. Salivary concentrations were analyzed using the enzyme-
link immunoabsorbant assay kits (ELISA; Kit Yanaihara Inst
Inc YK 070 and Kit Salimetrics 1-1902 respectively for the
chromogranin A and the alpha amylase). All samples were
analyzed in duplicate.
A 12h-night-cortisol excretion was assessed and collected at
the baseline, middle-training and at the end of the training.
Cortisol concentrations were measured using radioimmunoas-
say kits according to the protein concentration rates (Siemens
Healthcare Diagnostics, Germany). The urinary cortisol excre-
tion rates were calculated according to the diuresis and the
creatinine excretion rates. All samples were analyzed in dupli-
cate.
Procedure
The intervention program, so called Cardiac Coherence
Training (CCT), was derived from the ‘‘Power to Change Per-
formance program” developed by Institute of HeartMath (Boul-
der Creek, CA). More detailed descriptions of the techniques,
their conceptual basis, and their applications in organizational
settings can be found elsewhere (Childre & Cryer, 2000; Chil-
dre & Martin, 1999; Childre & Rozman, 2005). For the study,
the adapted program was centered on helping subjects to deal
with stress faced with job insecurity and work organisational
restructuring strains. It consisted of ten individual sessions of
one hour each week for a three-month duration, and daily regu-
lar exercises of few minutes. The full program contained three
modules whose progression was adjusted according to individ-
ual progression.
1) Risk factors: what they are, how to interpret them, and
how they relate to health and wellness.
2) Freeze-Frame: Freeze-Frame is a positive emotion refo-
cusing technique specifically designed to improve decision-
making, especially in stressful or challenging situations. The
technique is intended to enable individuals to intervene more
effectively when a stress reaction is triggered, and with practice,
to offset the harmful or depleting physiological aspects of the
stress response. In essence, the technique enables people to
consciously disengage from draining negative mental and emo-
tional reactions as they occur and to activate a neutral or posi-
tive emotional state before returning to address the stressor
from a more emotionally balanced perspective.
3) Power tools for inner quality: creating a caring culture and
increasing job satisfaction. The Power to Change Performance
intervention is based on the theory that the cumulative effect of
many employees self-regulating emotions more effectively and
communicating with each other in a more constructive and
caring fashion will bring about a positive change in the sur-
rounding organizational culture within which employees work.
This program module includes the following tools: the Heart
Lock-In technique—an emotional restructuring exercise de-
signed to reduce stress and increase psychophysiological co-
herence; Appreciation—taking time out in one’s day to notice
and be grateful for the positive aspects of one’s life; and Neu-
tral learning to neutralize distressing emotions.
Statistical Analyses
All data, expressed as mean (SD), were treated as ordinal
data except for educational levels, tobacco use and marital
status. The effect of the CCT was performed using separate
analyses of variance (ANOVA) with time-points (baseline,
middle-training and after the training) as within-subjects effect,
except for the EEG measures only recorded at the baseline and
post-training time-points, and the salivary alpha amylase only
collected at the baseline and post-training time-points. For sig-
nificant interaction between within- and between-subjects,
OPEN ACCESS 81

M. TROUSSELARD ET AL.
post-hoc analyses using Newman-Keuls were applied. Fur-
thermore, in order to evaluate the links between the psycho-
logical effects and endocrine effects separately, a delta value
(end of the training minus baseline value) expressed in % of
change was calculated for each variable. All comparisons be-
tween groups, according to the anxiety-trait level, were as-
sessed using nonparametric tests, due to the small size of the
groups.
All analyses were performed with SPSS 17.0 for Windows
(SPSS GmbH Software, Munich). We judged p < 0.05 as signi-
ficant. When p ≤ 0.1, results were expressed as a tendency to a
difference.
Results
Socio-Demographic Description
The mean age of the nine male respondents was 39.77 (6.45)
years with 7.9 ± 1.9 years of education above grade 7. 44.44%
were married. 33.33% were smokers. All subjects, except two
(22.22%), practiced sport regularly. None had any coaching
practice or a stress management program. Mean trait-anxiety
was 35.55 (9.08) with four subjects above the mean trait-anxi-
ety level (44.44%), the remaining above this mean cut-off. The
subjects’ adhesion to the protocol was good as all maintained
their participation for the complete duration of the study and no
training session absence was noted.
Effects of the Stress Training on Psychological
Assessments
For the state-anxiety assessment, the ANOVA showed no di-
fference between the three time-points (F(2.8) = 0.33, p =
0.723).
The ANOVA performed between the three steps on the per-
ceived stress showed a significant decrease on the score after
the training (F(2.8) = 8.12, p = 0.01). The post-hoc analysis
showed that the successful transformation was observed be-
tween baseline and both the middle- and end-steps’ assess-
ments.
The ANOVA performed between the three steps on the sleep
EVA variables showed a significant increase on the sleep res-
toration score quality after the training (F(2.8) = 6.32, p = 0.01).
This was associated with an increase in the facility of falling
asleep (F(2.8) = 4.54, p = 0.04). The post-hoc analysis showed
that the successful transformations were observed between the
baseline and end-steps assessments.
Concerning the well-being items of the sleep questionnaire
investigating physical, psychological well-being (mood and joy
of going to work), the separate ANOVA showed that the scores
increased for the physical score (F(2.8) = 7.89, p = 0.01). The
post-hoc analysis showed that the successful transformation
was observed between baseline and the end-steps assessments.
Tendencies were observed for the mood well-being (F(2.8) =
3.21, p = 0.08) and the joy of going to work (F(2.8) = 3.54, p =
0.06).
For the AD-ACL questionnaire, the ANOVAs performed
between the three steps on each sub-factor highlighted a sig-
nificant increase of the General Activation scores (F(2.8) = 6.85,
p = 0.01). The post-hoc analysis showed that the successful
transformation was observed between the baseline and both
middle- and end-steps’ assessment s.
Effects of Stress Tr ai n i ng on the Physiological
Assessments
The ANOVA that was performed between the three steps on
the SDNN showed a tendency to decrease between the time
points. No difference was found for the RMSSD, as for all
other ECG parameters (Table 1).
Table 2 shows the recorded sleep parameters and separate
ANOVAs applied to the parameters between the baseline and
the end of the training time-points. Results only showed a sig-
nificant increase of the time in REM as a % of sleep time. The
number of REM periods did not change between the two time-
points (t(1.8) = 0.22, p = 0.82) with 4(1.29) and 3.86(1.26)
mean number of REM periods during the recorded night, for
the baseline and the end of the training time-points respectively.
There was a tendency to a significant increase of the duration of
REM period at the end of the training compared to the duration
of REM period at the baseline was observed for the fourth
REM period of the night ((t(1.8) = 2.15, p = 0.06; Figure 2).
Effects of the Stress Training on the Endocrine
Assessments (Figure 3)
The ANOVA performed between the three steps on the sali-
vary enzyme alpha-amylase concentration showed a significant
decrease in concentration after the training (F(2.8) = 5.89, p =
0.04). The post-hoc analysis showed that the successful trans-
formation was observed between the baseline and both the
middle- and end-steps assessments.
The ANOVA performed between the two steps on the sali-
vary chromogranin A showed a tendency to a decrease in con-
centration of the salivary enzyme alpha amylase after the train-
ing (F(2.8) = 2.79, p = 0.08).
For the urinary cortisol excretion, the ANOVA performed
between the three steps showed no difference between time-
points (F(2.8) = 3.24, p = 0.16).
Impact of the Anxiet y-Trait Level on the Effects of
the Intervention
According to Spielberger’s norms (Spielberger, Gorsuch,
Lushene, Vagg, & Jacobs, 1983), the four subjects scoring
higher than the mean score were defined has the high trait-
anxiety group (GHTA), and the five subjects scoring lower than
the mean score were defined as the high trait-anxiety group
(GLTA). Trait-anxiety scores differed between group (H(1.9) =
6.05, p = .013). No significant difference for age (H(1.9) =
0.288, p = .591), educational level (H(1.N=9) = 0.388, p =
0.491), for matrimonial status (X2 = 4, p = 0.857) same for the
tobacco users (X2 = 3.5, p = 0.899) factors were observed be-
tween the GHTA and t he GLT A.
Table 3 depicted differences in baseline assessments be-
tween the two groups. The GHTA was higher in salivary chro-
mogranin A concentration, perceived stress score compared to
the GLTA. It also tended to be higher in the state-anxiety score
and the RMSS value. This was associated with a lower score in
the subjective sleep restoration quality, the joy of going to work,
the Energetic-Arousa l General Activation, and the % of time in
REM compared to the GLTA. Moreover, a tendency of a lower
efficiency in reference to sleep time was observed. In line with
such a pattern of baseline functioning, the GHTA differed from
the GLTA in the effects of the training (Table 4): For the
GHTA, higher increases were observed after the training for the
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M. TROUSSELARD ET AL.
Table 1.
Effects of the stress training on the HRV assessments according to the time-points.
Variables Time-point Mean Minimum Maximum Standard-deviation F p
Mean NN inte rval (ms)
Baseline 1025.24 931.13 1133.26 77.61
1.23 0.88
Middle 1031.74 738.26 1299.00 180.31
After 1037.25 870.32 1190.18 112.14
SDNN
Baseline 132.16 61.7 272.60 70.47
3.25 0.08 Middle 113.42 60.70 205.40 51.46
After 90.73 34.46 136.35 40.14
SDSS
Baseline 47.64 22.20 66.83 16.82
1.14 0.40 Middle 66.48 22.20 145.64 44.61
After 52.45 11.28 76.73 22.48
pNN50
Baseline 29.58 6.34 50.33 19.19
0.89 0.41 Middle 27.96 4.76 55.06 21.10
After 34.66 0.52 62.87 24.32
RMSS
Baseline 94.47 28.73 211.30 57.58
1.67 0.23 Middle 98.76 28.73 229.30 66.73
After 70.60 15.39 113.84 34.52
Table 2.
Effects of the stress training on the sleep assessments according to the time-points.
Variables Time-point Mean Minimum Maximum Standard-deviation F p
Number of arousals: Baseline 16.57 3.00 31.00 8.99 0.19 0.67
After 15.62 6.00 31.00 9.19
Total tim e analyzed: Baseline 431.07 340.00 564.00 75.64 0.024 0.88
After 446.81 319.50 491.50 55.73
Sleep Period: Baseline 425.71 337.50 558.50 76.26 0.027 0.87
After 442.06 318.50 489.00 54.11
Wake time during slee p period: Baseline 34.85 23.00 52.50 10.73 1.65 0.26
After 49.06 5.00 144.50 44.36
Total sleep time: Baseline 390.85 304.00 531.50 75.55 0.02 0.89
After 392.87 293.50 468.50 55.70
Sleep latency in first 60 seconds
of sleep:
Baseline 5.35 2.50 9.00 2.68 0.033 0.86
After 4.75 0.00 18.50 5.94
Sleep efficiency referred to sleep
period:
Baseline 0.91 0.88 0.95 0.020 1.66 0.26
After 0.93 0.75 0.98 0.08
Time in REM % of total sleep
time:
Baseline 0.17 0.14 0.23 0.03 24.18 0.001
After 0.20 0.16 0.25 0.02
Time in S1 % of total sleep
time:
Baseline 0.06 0.02 0.10 0.02 1.21 0.32
After 0.05 0.01 0.09 0.03
Time in S2 a % of total sleep
time:
Baseline 0.42 0.35 0.53 0.07 0.75 0.42
After 0.40 0.27 0.51 0.07
Time in S3 % of total sleep
time:
Baseline 0.32 0.20 0.45 0.09 0.15 0.71
After 0.31 0.13 0.53 0.12
OPEN ACCESS 83

M. TROUSSELARD ET AL.
Table 3.
Comparisons be tween groups according to the trait-anxiety scores for the psychological, physiological and endocrine variables.
Variables Group Mean SD Χ
2
values p
Endocrine
Salivary ChromograninA
(pm/ ml )
GLTA 3.41 2.30 4.86 0.027
GHTA 18.83 12.09
Salivary Amylase (U/ml)
GLTA
98.4
44.86
0.06 0.806
GHTA
117.83
48.25
Urinary cortisol excretion
(nM/L)
GLTA 120.06 51.08 0.96 0.327
GHTA 106.19 24.73
Psychological
State-anxiety GLTA 27.2 6.76 2.57 0.10
GHTA 41.37 10.25
Perceived stress GLTA 36.00 3.93 4.90 0.026
GHTA 44.75 4.5
Sleep restoration quality GLTA 5.72 0.85 6 0.014
GHTA 3.90 0.41
Easiness to go to sleep GLTA 5.73 1.15 2.16 0.141
GHTA
4.33
0.17
Joy of going to work GLTA 5.92 0.52 6 0.014
GHTA 3.84 0.70
Mood well-being GLTA 6.32 0.48 6.2 0.013
GHTA 3.83 0.74
Physical well-being GLTA 6.00 0.57 6.3 0.013
GHTA 3.86 0.41
General Activation GLTA 12.16 2.17 4.86 0.027
GHTA 7.77 2.48
Deactivation-Sleep
GLTA
10.1
1.92
0.54 0.462
GHTA
8.3
3.08
High Activation GLTA 4.72 0.70 0.06 0.805
GHTA 5.97 3.01
General Dea ctivation GLTA 13.86 1.96 6 0.14
GHTA 8.35 3.01
Physiological
Sleep efficiency referred to sleep
period
GLTA 0.92 0.02 3.09 0.07
GHTA 0.89 0.01
Time in REM % of total sleep
time:
GLTA 0.18 0.03 3.75 0.052
GHTA 0.14 0.01
SDNN
GLTA
103.66
48.44
1.8 0.179
GHTA 179.66 85.28
RMSSD GLTA 72.91 42.38 2.68 0.101
GHTA 130.41 70.11
Figure 2.
Effects of the stress training on the duration of REM periods. *Indi-
cating a tendency to a difference (p ≤ 0.1). For one subject with six
REM periods at baseline, the last one was not represented here.
mood well-being, and the time in REM as a % of sleep time and
greater decreases were found in the salivary chromogranin A
concentration, the Energetic-Arousal Deactivation-Sleep and
the Tense-Arousal High Activation.
Discussion
The aim of the present study concerned the evaluation of the
benefits of the use of an intervention based on physiological
coherence (CCT) in a sample of middle-aged workers con-
fronted to organisational changes. First, it must be noted a high
adhesion of the subjects to the experimental study: The inter-
vention program was conducted completely, miniature biosig-
nal recordings were well accepted without complaint or pain
during the home-night of the assessments.
Concerning the effects of the CCT on stress and well-being,
results showed fast successful effects after the intervention. The
84

M. TROUSSELARD ET AL.
Figure 3.
Effects of the stress training on the endocrine assessments. *Indicating a tendency to a difference (p ≤ 0.1) and **indicating a sig-
nificant difference (p < 0.05).
Table 4.
Comparisons be tween groups according to the trait-anxiety score for the % of changes in the psychological, physiological and endocrine variables.
Variables Group Mean SD Χ
2
values p
Endocrine
Salivary Cromogranin A
(pm/ ml )
GLTA 32.06 61.85 3.84 0.05
GHTA −56.66 45.76
Salivary Amylase (U/ml) GLTA −4.09 74.03 0.3 0.76
GHTA −15.81 16.20
Urinary cortisol excretion
(nM/L)
GLTA 20.62 146.93 0.54 0.46
GHTA 7.51 59.84
Psychological
State-anxiety GLTA −1.62 12.96 0.2 0.65
GHTA 1.86 17.40
Perceived stress GLTA −26.98 5.956 5 0.25
GHTA −12.49 5.673
Sleep restoration quality GLTA 5.93 10.34 0.11 0.91
GHTA 5.05 1.74
Easiness to go to sleep GLTA 12.16 11.39 2.4 0.12
GHTA 3.82 7.26
Joy in going to work GLTA −5.14 20.99 0.25 0.81
GHTA −0.56 22.84
Mood well-being GLTA 2.03 6.63 3.75 0.05
GHTA 16.27 3.58
Physical well-being GLTA 7.47 11.41 1.35 0.24
GHTA 15.36 9.91
General Activation GLTA 13.32 13.16 0.15 0.69
GHTA 11.33 2.34
Deactivation-Sleep GLTA 1.03 13.16 3.74 0.05
GHTA −19.07 2.34
High Activation GLTA 5.36 10.91 3.75 0.05
GHTA −48.33 25.92
General Dea ctivation GLTA 2.91 12.82 0.48 0.64
GHTA 7.62 1.86
Physiological
Sleep efficiency in reference to
sleep period
GLTA 1.14 4.33 0.21 0.64
GHTA 3.43 3.42
Time in REM % of total sleep
time:
GLTA 12.95 8.17 3.42 0.06
GHTA 30.52 2.32
SDNN GLTA −5.00 54.29 1.12 0.28
GHTA −45.54 26.40
RMSSD GLTA 9.70 74.09 1.16 0.29
GHTA −43.05 23.03
OPEN ACCESS 85

M. TROUSSELARD ET AL.
decrease in the perceived stress was associated with a subject-
tive benefit for the physique well-being and tendencies of the
increases in the subjective psychological well-being and a joy
of going to work. General Activation also increased after the
intervention. The AD-ACL, according to Thayer’s theory (Tha-
yer, 1987), contains related dimensions with the theoretical
assumption that a danger phenomenon has a greater psycho-
logical impact (greater tense arousal) when energy (General
Activation) is low, and a lesser impact when energetic arousal
is high. All together, these results indicated successful trans-
formations after the intervention for the subjective daily life
outcomes.
Furthermore, endocrine improvements were found in the
ANS functioning as suggested by the observed changes in the
salivary alpha amylase and chromogranin A concentrations
after the intervention. In accordance, the night sympathetic
activity decreased after the intervention. However, this impro-
vement towards a lower sympathetic activity was not associated
with an improvement of the HPA axis functioning.
Concerning the effects of the intervention on subjective sleep
quality, results found both a subjective improvement of the
quality of sleep associated with an increase in the facility to fall
asleep. Moreover, objective assessments showed an increase in
REM time referred to the % of sleep. Human data from litera-
ture are abundant about stress effects on sleep changes for non-
clinical subjects. Summing up the main data in humans, REM
sleep increased several days after the subjects had been exposed
to intensely demanding and stressful events (Cartwright &
Wood, 1991; Sushecki et al., 2009). These REM rebounds are
understood as an important adaptive behaviour for recovery
following a stressful situation (Sushecki et al., 2009). Re-
searchers also found that subjects who were deprived of REM
sleep had trouble learning. It’s considered that if we don’t get
enough of it we may experience serious negative physical and
psychological changes (Sushecki et al., 2009; Vgontzas et al.,
2000). This may be considered as the body’s “Yellow Alert”
response to REM Sleep Deficit. It is a compensatory increase in
the percentage of sleep time devoted to REM sleep. Indeed,
after a period of deprivation, REM sleep can increase by 40%
for several days before returning to a normal level (Riemann et
al., 2001; Suchecki et al., 2009). Chronic stress has been clai-
med to be one of the triggering factors of emotional-related
sleep disorders, such as insomnia, depressive- and anxiety-
disorders. Thus, data from chronic stress comes from clinical
sample, namely depression or post-traumatic stress disorder and
showed that duration and repartition of REM were impaired
(Suchecki et al., 2009). More than 80% of slow wave sleep is
concentrated in the first half of the typical 8-h night, whereas
the second half of the night contains roughly twice as much
REM sleep as does the first half. For these clinical individuals,
time in REM was usually decreased with REM periods mainly
observed during the first part of the night (Suchecki et al.,
2009). Although the functional association between emotional
memory and REM-sleep electrophysiology remains unclear, the
role of REM-sleep was highlighted for both the regulation and
the consolidation of emotional human memories, findings that
have direct translational implications for affective psychiatric
and mood disorders (Nishida, 2008).
To our knowledge, less is known about how stress manage-
ment intervention deals with sleep for non-clinical individuals.
Referred to the role of REM-sleep for the regulation of emo-
tional human memories, the increase of REM time observed
after the stress management intervention, namely in the last part
of the night, suggests that the intervention mainly based on
emotional management may directly impact emotional memo-
ries during the night (Gais & Born, 2004; Plihal & Born, 1999).
The decrease in sympathetic activity during the night was in
accordance with the data showing that REM sleep occurs when
activity in the aminergic system has decreased enough to allow
the reticular system to escape its inhibitory influence (Hobson
et al., 1975, 1998; Payne & Nadel, 2004). Referring to our re-
sults, such a pattern appears to help subjects recover to cope
more efficiently with the daily stressful concerns of work. Fi-
nally, all the observed biopsychophysiological changes after the
intervention indicate a clear and rapid benefit of such a program
for subjects confronted with chronic stress due to downsizing
and organisational restructuring. In terms of allostasis, the pro-
gram appears to improve the process of achieving homeostasis
through physiological and behavioural changes faced with per-
ceived and/or anticipated d emand.
Considering the question of the inter-variability in monitor-
ing stressors, the baseline, like the outcomes, are dependent on
individual trait-anxiety levels. A clear opposite biopsycho-
physiological pattern was observed in the baseline data between
high and low levels of trait-anxiety. The subjects scoring high
on the trait-anxiety scale exhibited subjective stress, subjective
as objective impairment in sleep, low well-being outcomes, low
Energetic-Arousal General Activation, and Sympathetic Nerv-
ous System (SNS) imbalance (high chromogranin A concentra-
tion associated with a tendency to a higher night-time para-
sympathetic activity). Effects of the intervention program also
differed: compared to subjects low in trait-anxiety, subjects
prone to higher trait-anxiety exhibited higher increases after the
training for well-being outcomes, and time in REM as a % of
sleep time, and higher decreases for subjective stress, and the
SNS activation. Furthermore, based on the observation of self-
ratings of energy and tension at various time of days, Thayer’s
theory considered that arousal state modulates mood facing
personal problems: for example a mood pattern of low energy
and high tension predicts more negative problem perceptions,
such as worries and rumination, than a pattern of high energy
and low tension (Thayer, 1987, 1989). In accordance with such
an explanation, a logical pattern of successful transformations
after the intervention program can be considered for subjects
with high trait-anxi ety: the decrea se in Deactivation-Slee p, that
is a low Energetic-Arousal, was associated with a decrease in
High Activation, that is a low Tense-Arousal, and an increase in
well-being outcomes. Faced with an observed decrease in sym-
pathetic activity, and the increase in REM-sleep, one of the
major issues, however, concerns causality between the psycho-
logical improvements, the changes in energetic arousal, the de-
crease in salivary chromogranin A concentration and the in-
crease in REM-sleep time.
Whether the observations may indicate that stress programs
are all the more effective than anxious subjects, they also con-
fer more complexity to the stress-sleep relationship. Stress and
sleep appear related to each other in a bidirectional way. If on
the one hand poor or inadequate sleep should exacerbate emo-
tional, behavioural and stress-relat ed responses when trait-
anxiety is high, on the other hand stress reduction should in-
duce sleep rebound, most likely as a form to cope with the ad-
verse stimuli when trait-anxiety is high. Whether it is consid-
ered that increased sleep, especially the REM phase, following
a stressful situation is an important adaptive behaviour for re-
86

M. TROUSSELARD ET AL.
covery, this endogenous advantage appears to be impaired in
human beings that exhibit high levels of anxiety and anxiety-
like behaviour (Mellman & Uhde, 1989; Reynolds et al., 1983;
Spoormaker & van den Bout, 2005). Our data completed this
knowledge by highlighting that these subjects notably improved
with an adapted stress management program and that the suc-
cessful transformations linked to an increase in REM-sleep and
a decrease in emotional disturbances. The most important point
that the recent data highlighted is the impact of prolonged sleep
disruption, namely REM-sleep reduction, may affect neuro-
genesis (Lucassen et al., 2010; Meerlo et al., 2009).
There were several limitations to this study that preclude
firm conclusions. The first limitation is the sample’s small size.
Most notably, it can be assumed that this small size could ac-
count for the absence of a significant decrease in the urinary
cortisol excretion after the intervention. Furthermore, given the
number of statistical comparisons, the efficiency of the inter-
vention program should be accepted with caution. Results,
secondly, need further investigations, namely randomized con-
trolled studies. The third limitation concerns the duration of the
positive effects on the improvement of the outcomes, which
were not assessed. Another limitation concerns the absence of
data about dreams as recent studies clearly showed a relation-
ship between dreams, REM and memory consolidation (Baylor
& Cavallero, 2001; Hobson et al., 1998; Payne & Nadel, 2004).
Finally, mechanisms were not evaluated in this study, thus rela-
tionships between emotional processing, sleep regulation, SNS
balance and brain functioning before and after the intervention
need to be further investigated.
Conclusion
To sum up, our findings showed that such an intervention
approach appears to help subjects deal with stress faced with
insecurity and contingent work arrangements. Moreover, it may
appear to be more efficient when the subjects had a high level
of trait-anxiety. Sleep functioning, namely REM-sleep, appears
to be one of the main mechanisms of successful transformation.
It is to our knowledge the first proof of concept in non-clinical
samples of an ecological relationship between emotional stress
recovery and REM sleep. Such are these findings, even if they
need to be investigated further, may be considered as a poten-
tially low cost effective approach to the care of individuals
confronted with normal stress in their job. Finally, the impor-
tance must be highlighted, of miniature biosignal systems for
recording objective parameters in daily life to lead to the open-
ing up of ecological studies in psychophysiology.
Competing Interest
The authors declare that there are no competing interests
Acknowledgemen ts
This study is part of an ongoing project on military psychol-
ogy supported by the French ‘Service de Santé des Armées’.
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