The Version of Record of this manuscript has been published and is available in:
Schmid, R. F., & Thomas, J. (2020). Teachers’ ambulatory heart rate variability as an
outcome and moderating variable in the job demands-resources model. Anxiety, Stress,
& Coping, 33(4), 387–402. https://doi.org/10.1080/10615806.2020.1746286
This work is licensed under the Creative Commons AttributionNonCommercial-
NoDerivatives 4.0 License. For more information see
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© 2021 Regina Franziska Schmid
Catholic University of Eichstätt-Ingolstadt, Eichstätt, Germany
Department of Psychological Assessment and Intervention
Ostenstraße 25, D-85072 Eichstätt, Germany
E-mail: regina.schmid@ku.de
Phone: +49 8421 93 21 398
ORCID: https://orcid.org/0000-0001-9633-1522
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Teachers’ ambulatory heart rate variability as an outcome and moderating
variable in the job demands-resources model
Background and Objectives: According to the job demands-resources (JD-R) model,
strain reactions are based on the level of job demands and moderating resources. The
present study aims to contribute to psychophysiological research by integrating vagally
mediated heart rate variability (HRV) into the JD-R framework. Design and Methods:
Using a sample of school teachers, we conducted an ambulatory assessment study to
investigate HRV as (1) a state outcome measure of job demands and resources and (2) a
trait moderator in the relationship between job demands and emotional exhaustion. In
total, 101 participants wore an electrocardiogram device on two school days and rated
their level of job demands (emotional demands and time pressure), job resources
(control and support), and exhaustion six times a day. Based on 669 measurements,
multilevel models of the 5-minute state HRV measure and emotional exhaustion were
built. Results: The results supported the health-impairing effects of job demands on
emotional exhaustion but not state HRV. There was no evidence of the moderating
effects of job resources. Notably, the 48-hour trait HRV measure significantly buffered
the effect of emotional demands on exhaustion. Conclusions: These findings highlight
the stress-buffering potential of trait HRV as theoretical research extension and
practical intervention goal.
Keywords: job demands-resources model; heart rate variability; emotional exhaustion;
school teacher; ambulatory assessment
Introduction
Frequently encountering emotionally demanding student misbehaviors and classroom
disturbances, teachers are continuously under time pressure due to tight curricula (Dicke,
Stebner, Linninger, Kunter, & Leutner, 2018; Keller, Chang, Becker, Goetz, & Frenzel,
2014). It is well known that teachers are subjected to a substantial amount of job strain and
that teaching demands are associated with adverse affective adjustments (Dicke et al., 2018)
and changes in cardiac measures (Pieper, Brosschot, van der Leeden, & Thayer, 2010).
One of the most influential theories of job-related stress is the job demands-resources
(JD-R) model (Bakker & Demerouti, 2017; Demerouti, Bakker, Nachreiner, & Schaufeli,
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2001). The JD-R model distinguishes between two types of work characteristics. Job demands
represent toxic psychosocial or organizational conditions that may produce job strain, whereas
job resources refer to the positive aspects of the job that may help people cope with demands.
Consistent with the conservation of resources (COR) theory (Hobfoll, 1989), people strive to
deploy their resources, but when resources are lost due to exceeding demands, strain reactions
are likely. Accordingly, high demands seem to deplete resources and have detrimental effects
on mental and physical health, which is known as the health-impairment process (Bakker &
Demerouti, 2017). A well-studied outcome measure in the JD-R model is the level of
emotional exhaustion, which is defined as a central component of burnout and an indicator of
psychological strain, poor well-being, and low energy (e.g., Demerouti et al., 2001; Maslach
& Jackson, 1981). Many studies demonstrate that the model is also applicable to within-
person studies of situational fluctuations in emotional exhaustion (e.g., Riedl & Thomas,
2019). Directly related to the teaching context, numerous studies have examined the JD-R
model at both the between-subject (e.g., Dicke et al., 2018; Guglielmi, Panari, & Simbula,
2012) and within-subject (Garrick et al., 2014; Simbula, 2010; Tadić, Bakker, & Oerlemans,
2015) levels. Given the great variety of job demands, emotional demands and time pressure
seem to be particularly hazardous with respect to teachers’ health (Dicke et al., 2018;
Guglielmi et al., 2012; Sonnentag, 2001). According to the authors, emotional demands may
specifically occur in terms of disruptive students and interpersonal conflicts in the classroom,
while temporal constraints may be provoked mainly by means of timetables and curricula. An
additional assumption of the JD-R theory states that resources can buffer the detrimental
effects of job demands on health-related outcomes (Bakker & Demerouti, 2017). According to
this so-called stress-buffering hypothesis, resources render employees more resilient and less
vulnerable to stress, which may help them cope with stressors (Hobfoll, 1989). Reflecting
influence by Karasek (1979) and Johnson and Hall (1988), job control and social support are
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among the most prominent resources in the JD-R framework (Demerouti et al., 2001). The
buffering potentials of control and support have also been confirmed empirically in studies
related to teachers’ fatigue (Garrick et al., 2014) and positive affect (Tadić et al., 2015).
However, while flourishing research has investigated daily psychological strain
reactions (e.g., Keller et al., 2014; Simbula, 2010), fewer studies address daily physiological
pathways (Bakker & Demerouti, 2017). To date, the psychophysiological processes involved
in coping with job demands at the within-person level are not sufficiently understood. Of the
wide range of sympatho–adrenal and hypothalamic–pituitary–adrenal (HPA) biomarkers,
Chandola, Heraclides, and Kumari (2010) suggest that heart rate variability (HRV), which is
an indicator of the autonomic nervous system, is a particularly valid biological correlate of
workplace stressors. Consistently, reviews have provided evidence suggesting that heightened
job demands are closely related to decreased levels of HRV (Jarczok et al., 2013; Togo &
Takahashi, 2009). Specifically, HRV represents a measure of the irregularity of time between
consecutive heartbeats and is sensitive to both sympathetic and parasympathetic (vagal)
efferences (Jarczok et al., 2013; Malik, 1996). For example, HRV indexes the “contribution of
the parasympathetic nervous system to cardiac regulation” (Laborde, Mosley, & Thayer,
2017, p. 1) and has been associated with both physiological and psychological flexibility and
adaptability in response to different situations (Grossman & Taylor, 2007; Thayer & Lane,
2009; Togo & Takahashi, 2009). Notably, HRV can be investigated at the short-term phasic
level (state HRV) and long-term tonic level (trait HRV).
State HRV is thought to reflect mainly cardiac vagal activity and to be sensitive to
immediate changes in environmental requirements (Laborde et al., 2017; Thayer & Lane,
2009). For instance, studies have linked short-term vagal tone to state positive affect
(Schwerdtfeger & Gerteis, 2014), momentary resilience (Schwerdtfeger & Dick, 2019), acute
stressful events (Pieper, Brosschot, van der Leeden, & Thayer, 2007), and situational worry
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episodes (Pieper et al., 2010). It is important to note that some of the results remain equivocal,
e.g., the association between state HRV and positive affect apparently depended on the
arousal level (i.e., only deactivated, but not activated, positive affect was related to higher
HRV), and the negative relationship between state HRV and resilience somewhat contradicted
the hypotheses. However, empirical support for a demand-induced reduction in HRV was
found in ambulatory studies investigating the job demand-control model (e.g., Borchini et al.,
2015; Collins & Karasek, 2010), and even the deleterious combination of high demands and
low control or support was found to predict a decreased HRV (Borchini et al., 2015; Chandola
et al., 2010; Collins & Karasek, 2010). Nonetheless, evidence for the JD-R model is generally
mixed (Chandola et al., 2010), and only a few studies have investigated the relations between
acute teaching demands and HRV (Filaire, Portier, Massart, Ramat, & Teixeira, 2010).
In contrast, tonic HRV typically refers to resting or baseline measures collected over
longer periods (e.g., 24 h). Certainly, trait HRV is highly correlated with state HRV (Martens,
Greenberg, & Allen, 2008) but is mainly known to constitute the level at which
interindividual differences concerning adaptive and maladaptive vagal response patterns are
manifested (Laborde et al., 2017). For example, a higher trait HRV is positively associated
with health and resilience and negatively associated with chronic stress, depression, diseases,
and mortality (for an overview see Thayer, Åhs, Fredrikson, Sollers, & Wager, 2012).
Consistent with the neurovisceral integration model (Thayer & Lane, 2009) and the biological
behavioral model (Grossman & Taylor, 2007), which assume that vagally mediated cardiac
regulation is reflected in healthy self-regulation, tonic HRV has been previously considered
“a resource that enables cognitive and emotional regulation” (Martens et al., 2008, p. 377) and
“a functional energy reserve capacity from which the organism can draw during more active
states” (Grossman & Taylor, 2007, p. 279). Hence, studies have shown the potential of trait
HRV to moderate non-work-related stress- or threat-induced effects (Martens et al., 2008;
