Alexander Wettstein1*
Sandra Schneider1,2
Gabriel Jenni1
Martin grosse Holtforth2,3
Wolfgang Tschacher4
Roberto La Marca1,5,6- 1Department of Research and Development, University of Teacher Education Bern, Bern, Switzerland
- 2Department of Psychology, Clinical Psychology and Psychotherapy, University of Bern, Bern, Switzerland
- 3Department of Neurology, Psychosomatic Medicine, Bern University Hospital, Bern, Switzerland
- 4Experimental Psychology Division, University Clinic for Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- 5Centre for Stress-Related Disorders, Clinica Holistica Engiadina, Susch, Switzerland
- 6Department of Clinical Psychology and Psychotherapy, University of Zurich, Zürich, Switzerland
Introduction: Workaholism in teachers is characterized by the willingness to work until exhausted and may be associated with various adverse health outcomes as well as high economic costs. The present study examines the association between workaholism, vital exhaustion (VE), and hair cortisol concentration (HCC) as indicators of chronic stress. In addition, this study explores the moderating role of the personality trait neuroticism on the relationship between workaholism and chronic stress indicators, i.e., VE and HCC.
Methods: Forty-two Swiss teachers (28 females; Mage = 39.66, SD = 11.99) completed questionnaires assessing VE (Maastricht Vital Exhaustion Questionnaire), workaholism (Measure of Coping Capacity Questionnaire), and neuroticism (Big-Five Inventory). Together with VE, HCC was assessed twice, with a one year lag.
Results: Both workaholism and neuroticism were positively associated with VE at both time points but not with HCC. Moderation analyses revealed a positive relationship between workaholism and VE in teachers with high neuroticism, while no such association was observed in teachers with low neuroticism. No associations were found between self-reports and HCC.
Discussion: These findings emphasize the importance of considering individual characteristics when investigating VE. Further research is necessary to investigate the applicability of HCC as a biomarker of chronic stress in the context of work.
Introduction
In the teaching profession, the growing demands from policymakers and expectations from society, as well as the increasing number of tasks and bureaucratic work for which teachers lack time and resources, may lead to high external work pressure and chronic work overload, both during and after teachers’ workday (Apple, 1989; Kokkinos, 2007; Ballet and Kelchtermans, 2009; Isabel et al., 2021). When job demands exceed job resources, and certain individual predispositions are present, an obsessive need to work may occur, namely workaholism (Schaufeli, 2016; Tabak et al., 2021). Workaholism is characterized as a form of addiction that comprises the dimensions of affect (enjoying work but feeling guilty and anxious when not working), cognition (obsessing about work), and behavior (working excessive hours, even at home; Ng et al., 2007). The term workaholism was coined by Oates (1971), who described it as “the compulsion or the uncontrollable need to work incessantly” (p. 11), referring to the behavioral and cognitive components of alcoholism that may result in various stress-related health outcomes (Preckel et al., 2005; Clark et al., 2016).
Personality traits can influence how individuals perceive their work and how invested they become (Kokkinos, 2007; Schaufeli, 2016; Perera et al., 2018; Tabak et al., 2021). A growing body of research suggests that workaholism is positively related to neuroticism, as neuroticism may increase the risk of developing an obsessive need or dependence on work (Clark et al., 2016; Schaufeli, 2016). The Five-Factor Model (Costa and McCrae, 1992) describes neuroticism as being vulnerable to psychological stress, prone to unrealistic beliefs, and unable to control urges and successfully cope with stress. Furthermore, teachers with high neuroticism scores have been shown to be at higher risk for burnout based on situational anxiety related to challenging student behavior and classroom management, self-doubt, self-criticism, and work-related rumination (McIlveen and Perera, 2016).
Like neuroticism, workaholism was found to be positively related to burnout (Ng et al., 2007; Andreassen, 2014; Clark et al., 2016). A study by Nie and Sun (2016) found significant correlations between workaholism, job burnout, and depression in Chinese university teachers emphasizing how personal life and health can be affected when work becomes the priority in life. In addition, previous studies show an association between overcommitment to work (Preckel et al., 2005) and excessive workload (Schnorpfeil et al., 2002) with vital exhaustion (VE). The concept of VE has received increasing research attention for its adverse effects on health (Kop et al., 1996; Prescott et al., 2003; Balog and Konkolÿ, 2019). Characteristics of VE include excessive fatigue, lack of mental and physical energy, feelings of demoralization, and irritability (Appels and Mulder, 1989). Though the underlying causes of VE are still not fully known, it is thought that VE emerges when personal resources required to adapt to stress are depleted and can thus be considered a consequence of perceived chronic stress and burnout (Bellingrath et al., 2008; Schoch et al., 2018). Furthermore, VE has been shown to be a significant and independent risk factor for cardiovascular disease in men (Appels and Mulder, 1989). Kudielka et al. (2008) found a positive relation between VE and circulating fibrinogen levels in teachers. Increased circulating fibrinogen levels have been linked to higher cardiovascular mortality and morbidity. These findings suggest that dysregulated hemostasis may be a biological pathway through which chronic stress may negatively impact cardiovascular health in teachers (Kudielka et al., 2008).
Vital exhaustion can be assessed subjectively with the Maastricht Vital Exhaustion Questionnaire (MQ; Appels and Mulder, 1989). However, researchers have been urged to aim for multimethod approaches to assess chronic stress, to account for the distinction between self-reported and physiological chronic stress (Cohen, 1997). Self-reports may be influenced by various individual factors such as mood and personality traits like neuroticism (Christensen et al., 2019). In addition, some items used in neuroticism and subjective stress-related measures may be similar, resulting in common method variance and reduced discriminant validity. Physiological measures of stress over time, on the other hand, are generally less influenced by an individual’s immediate mood or personality and are not affected by recalling biases and social desirability (Gow et al., 2010; Stirratt et al., 2015; Christensen et al., 2019; Prado-Gascó et al., 2019). Hair cortisol concentration (HCC) analysis has been a valuable tool for chronic physiological stress measurement and has been increasingly used in the last decade (Russell et al., 2012; Stalder and Kirschbaum, 2012). Cortisol is the most common glucocorticoid (GC) in humans and an essential element of the hypothalamus-pituitary–adrenal (HPA) axis stress response. By driving the release of GCs, the HPA axis is a central player in maintaining homeostasis and alerting the organism to environmental changes (Herman and Cullinan, 1997). HCC provides a unique opportunity to quantify long-term systematic cortisol exposure retrospectively over several months (Gow et al., 2010; Stalder and Kirschbaum, 2012; Ullmann et al., 2016). Circadian rhythms and acute changes regulated by the HPA axis are thought to affect HCC less than salivary cortisol (Stalder and Kirschbaum, 2012), and several studies showed significantly higher HCC in chronically stressed individuals (Dettenborn et al., 2010; Manenschijn et al., 2011; Stalder et al., 2017; Brianda et al., 2020).
To the best of our knowledge, no study has investigated the relationship between workaholism and neuroticism with HCC in teachers. However, some studies have linked HCC to work stress, with inconsistent results (Steinisch et al., 2014; Gidlow et al., 2016; Janssens et al., 2017; Herr et al., 2018). Regarding neuroticism and cortisol, previous studies have found an association between neuroticism and higher salivary basal cortisol or area under the curve on one or more days (e.g., Nater et al., 2010; Garcia-Banda et al., 2011; Laceulle et al., 2015). In contrast to salivary cortisol, research on the relationship between neuroticism and HCC is still scarce, but with promising results: Rietschel et al. (2016) reported a modest positive association between neuroticism and long-term HCC over the past three months. A study by Engert et al. (2021) showed neuroticism predicted HCC in 1 cm hair segments. Similarly, Erickson et al. (2021) found that neuroticism predicted higher HCC over 2 months, even after controlling for other personality traits. These results support using HCC to investigate associations between chronic physiological stress indicators and traits like neuroticism.
The aim of this longitudinal study is twofold. First, we intend to examine the relationship between workaholism and teachers’ chronic stress indicators, that is, self-reported vital exhaustion (VE) and hair cortisol concentrations (HCC; measured over three-cm hair segments) at two time points 1 year apart. Second, we aim to test the moderating role of neuroticism on the relationship between workaholism and VE and workaholism and HCC. Teachers have been found to have high levels of occupational stress and are at increased risk for burnout syndrome (Gluschkoff et al., 2016; Richards et al., 2018; García-Carmona et al., 2019). Examining long-term relationships between individual teacher characteristics and chronic stress-related indicators may provide a better understanding of contributing factors to high stress levels and psychosomatic complaints among teachers.
To tackle the study’s main objectives, we tested the following four hypotheses: (H1) Workaholism and neuroticism are associated with VE at t1 and t2 1 year later. Studies have found associations between workaholism and adverse subjective health outcomes, especially burnout (Ng et al., 2007; Andreassen, 2014; Clark et al., 2016). As VE may be considered a consequence of chronic stress and burnout (Bellingrath et al., 2008; Schoch et al., 2018), it seems reasonable to expect a positive association between workaholism and VE at t1 and t2. Neuroticism is considered a risk factor for burnout (Schaufeli and Enzmann, 2020). Thus, we expect to see an association between neuroticism and VE at t1 and, since it is a relatively stable personality trait (Borkenau and Ostendorf, 1993), likewise with VE at t2 1 year later. (H2) Neuroticism moderates the relationship between workaholism and VE at t1 and t2. This hypothesis is based on the assumption that a workaholic teacher with high neuroticism may be more vulnerable to psychological stress (Costa and McCrae, 1992). Such a teacher may also experience more self-doubt, anxiety, and pressure to perform than a workaholic teacher with low neuroticism (Clark et al., 2016; Aziz et al., 2018) and may consequently be at higher risk of experiencing VE. (H3) Workaholism and neuroticism are positively associated with HCC at t1 and t2. Neuroticism and workaholism appear to be risk factors for chronic stress (Clark et al., 2016; Erickson et al., 2021), which in turn has been associated with higher HCC (Russell et al., 2012; Stalder and Kirschbaum, 2012). (H4) Neuroticism moderates the relationship between workaholism and HCC at t1 and t2. Based on the literature above, we assume that workaholic teachers with high levels of neuroticism may have higher HCC than those with low neuroticism.
Materials and methods
Participants
School administrations were informed via flyers and emails, and the consent of the participating teachers was obtained. The inclusion criterion for participation in the study was an occupation as a primary or secondary teacher in Switzerland and a workload of a minimum of 16 lessons per week (equivalent to at least a 60 percent occupation). Fourty-two apparently healthy teachers (28 females, Mage = 39.66, SD = 11.99) completed the first online questionnaire on workaholism, neuroticism, and vital exhaustion. On average, the 42 teachers came from 39 different schools within the canton of Bern, Switzerland and had 13.35 years of teaching experience (SD = 11.07, range = 1–40). Participants had completed teacher training and were regular classroom teachers, not gifted or special education teachers. The grade levels they taught ranged from kindergarten and elementary school (1st to 6th grade; n = 27) to secondary school (7th, 8th, and 9th grade; n = 12) and to high school and vocational school (10th, 11th, and 12th grade; n = 3).
Three participants were either bald or had too short hair to take a hair sample, resulting in 39 teachers providing physiological data at the first measurement. When reaching the follow-up measurement 1 year later (t2), three more teachers withdrew their participation due to moving abroad (n = 1) and pregnancy (n = 2), resulting in 39 teachers with a follow-up self-report and 36 teachers with a follow-up self-report as well as follow-up physiological data.
Procedure
All teachers were screened in a short interview to ensure that they met inclusion criteria. Participating teachers then signed informed consent. Subsequently, they completed online questionnaires on workaholism, neuroticism, and vital exhaustion and came to the University of Bern, Switzerland, where hair samples were taken at the beginning of 2020 before the COVID-19 Pandemic. One year after the first measurement (t2) during the COVID-19 Pandemic, participants completed another questionnaire on vital exhaustion and provided another hair sample. During data collection, teachers were teaching in their regular schools, not digitally.
The study was approved by the ethics committee of the canton of Bern and the Internal Review Board (IRB) of the University of Bern and was conducted in strict compliance with current data protection laws.
Materials
Workaholism
To assess workaholism, we used subscale three (“Willingness to work until exhausted”) of the established inventory AVEM in its original German version (Schaarschmidt and Fischer, 2008). The English version was named the Measure of Coping Capacity Questionnaire (MECCA). Participants rated the six items with a value between 1 = not at all and 5 = a lot, depending on how much the items applied to them. Sample items were “If necessary, I work until exhaustion,” “I probably work more than I should,” and “I tend to work beyond my strength.” This resulted in a total sum score ranging from 6 to 30 points. The reliability was α =0.84.
Neuroticism
Neuroticism was assessed with two items of the short version of the Big Five personality trait scale (BFI-10; Rammstedt and John, 2007) and two additional items with the highest factor loadings of the NEO-FFI (Borkenau and Ostendorf, 1993). The structure of the combined items was tested using exploratory factor analysis. Both Bartlett’s test (p < 0.001) and the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.675) indicate that the variables are suitable for factor analysis. Therefore, a Principal Component Analysis (PCA) with varimax rotation was performed. The one-factorial solution we obtained explained 56% of the variance. Participants indicated the extent to which each item described them, from 1 = not at all to 5 = a lot. Items were “I get depressed quickly, dejected” (NEO-FFI), “I worry a lot” (NEO-FFI), “I see myself as someone who is relaxed, handles stress well” (reversed item, BFI-10), and “I see myself as someone who gets nervous easily” (BFI-10). Mean values were calculated. The reliability of the four-item scale was α =0.73.
Vital exhaustion
VE was assessed at t1 and t2 (one-year follow-up) with the German translation (cf. Rau et al., 2010) of the Maastricht Vital Exhaustion Questionnaire (MQ; Appels and Mulder, 1989). The scale consists of 21 items assessing fatigue, difficulties falling asleep, general malaise, apathy, irritability, energy loss, depression, and waking up exhausted. Sample items were: “Do you sometimes feel as if your body is like a battery that is losing its power?,” “Do you have increasing difficulty in concentrating on a single subject for long?” “Do you often feel tired?.” Each of the 21 items could be rated on a three-point scale, from “statement is not true” (1) to “undecided” (2) or “true” (3). By summing the scores of each item, the total score could be calculated, with higher scores indicating increased vital exhaustion. The reliability was α =0.88 at t1 and α =0.88 at t2.
Hair cortisol concentration
Participants came to the University of Bern, where hair strands were cut from the posterior vertex as close to the scalp as possible. Hair cortisol concentrations were determined from the three-centimeter segment closest to the scalp. Given an average hair growth of 1 cm per month (Wennig, 2000), this segment represents the cumulative cortisol secretion over 3 months before sampling. The washing procedure and cortisol extraction followed the laboratory protocol described by Gao et al. (2013). All samples were analyzed by liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). This analysis’s lower limits of quantification (LOQ) were below 0.1 pg./mg for cortisol. The inter-and intra-assay coefficients of variance for cortisol were below 15% (Gao et al., 2013).
Data analyses
Descriptive statistics and bivariate correlations were computed to investigate the study’s variables. The moderations were tested with ordinary least square regression models using SPSS 28 with the macro PROCESS version 4.0 (Hayes, 2018). The Shapiro–Wilk test was used for each variable to test whether the data were normally distributed. HCC at t1 and t2 were log-transformed due to non-normal distribution. Therefore, all correlations and regressions involving these two variables were calculated and interpreted using this transformation. The interaction terms were computed as the product of the mean-centered variables (except sex) involved. Significant interaction terms were followed up by simple slope tests at low (16th), middle (50th), and high (84th) percentiles of the moderator (Hayes, 2018). Participants’ sex, years of work experience, and the number of lessons taught per week were controlled for in the models. Only sex was associated with the predicted outcomes. Because of the small sample size, we preferred a parsimonious model and presented the results only with the control variable sex.
Results
Associations between self-reports and hair cortisol concentration
Descriptive characteristics and intercorrelations between workaholism, neuroticism, VE (t1 and t2), HCC (t1 and t2), and the control variables are shown in Table 1. In our sample, female teachers reported more VE at t2 (r = −0.36, p = 0.023) and had fewer years of work experience than their male colleagues (r = 0.39, p = 0.010). Both workaholism and neuroticism correlated significantly positively with VE at t1 as well as t2. Self-reports were unrelated to HCC at t1 and t2.
Table 1. Descriptive statistics and intercorrelations of the study variables.
Prediction of vital exhaustion by workaholism and neuroticism
Table 2 shows the results of the multiple regression analysis predicting VE at t1 and t2.
Table 2. Results of the multiple regression analyses predicting vital exhaustion t1 (N = 42) and t2 (N = 39).
H1: Model 1 shows that both workaholism (β = 0.47, p < 0.001) as well as neuroticism (β = 0.46, p < 0.001) were positively associated with VE at t1 when controlling for the participants’ sex (β = −0.13, p = 0.156). Both predictors together explain 70% of the variance [F(3, 39) = 29.10, p < 0.001, R2 = 0.70]. Model 3 shows the results of the multiple linear regression predicting VE at t2. Both workaholism t1 (β = 0.09, p = 0.559) and neuroticism t1 [β = 0.23, p = 0.112] were not significantly associated with VE at t2, when controlling for prior VE [β = 0.50, p = 0.006; F(4, 34) = 19.61, p < 0.001, R2 = 0.70]. There was a significant effect of sex, with female teachers reporting higher degrees of VE at t2 than male teachers (β = −0.25, p = 0.014).
H2: Next, we analyzed the moderating role of neuroticism on the relationship between workaholism and VE at t1 and t2. The moderation model [model 2; F(4, 37) = 28.35, p < 0.001, R2 = 0.10] showed a significant interaction effect (β = 0.23, p = 0.006) when controlling for sex, which is shown in Figure 1. For teachers high in neuroticism, workaholism is positively associated with VE at t1 (simple slope: β = 0.62, SE = 0.11, p < 0.001), while for teachers low in neuroticism, there was no such association (simple slope: β = 0.16, SE = 0.15, p = 0.283).
Figure 1. Interaction between workaholism x neuroticism on vital exhaustion at t1, controlling for sex (N = 39).
Model 4 examined the interaction between workaholism and neuroticism on VE at t2 [F(5, 33) = 18.84, p < 0.001, R2 = 0.74]. When controlling for VE t1 and sex, the interaction effect was significant as well (β = 0.22, p = 0.026). Figure 2 shows that for teachers high in neuroticism, workaholism is trend wise positively associated with VE t2 (simple slope: β = 0.35, SE = 0.18, p = 0.056), while for teachers low in neuroticism, there was no such association (simple slope: β = −0.10, SE = 0.16, p = 0.520). One year later, high neuroticism in combination with high scores in workaholism predicted high VE as well.
Figure 2. Interaction between workaholism x neuroticism on vital exhaustion at t2, controlling for vital exhaustion at t1 and sex (N = 39).
Association of workaholism and neuroticism with hair cortisol concentration
H3: A multiple regression was conducted to predict HCC at t1 from workaholism and neuroticism (Table 3, model 1). The results show that neither workaholism (β = 0.22, p = 0.260) nor neuroticism (β = −0.00, p = 0.981) were significant predictors of HCC at t1, when controlling for gender (β = 0.19, p = 0.263; F(3, 35) = 0.95, p = 0.429, R2 = 0.08). The same multiple regression was calculated for HCC at t2 [model 3; F(4, 31) = 3.27, p < 0.05, R2 = 0.30]. Therefore, neither workaholism (β = 0.09, p = 0.661) nor neuroticism (β = −0.19, p = 0.316) were significant predictors of HCC 1 year later, when controlling for gender (β = 0.07, p = 0.677) and HCC at t1 (β = 0.52, p = 0.002).
H4: Models 2 and 4 explored whether there was a moderation of neuroticism on the association between workaholism and HCC at t1 and t2. However, no such effects were found.
Table 3. Results of the multiple regression analyses predicting hair cortisol (N = 39) and t2 (N = 36).
Discussion
The present study aimed to investigate the interaction between the two potential risk factors of workaholism and neuroticism as longitudinal predictors of vital exhaustion (VE) and hair cortisol concentration (HCC). Additionally, we explored the moderating role of neuroticism on the relationship between workaholism, VE, and HCC.
The results partly confirmed our first hypothesis (H1), which stated that workaholism and neuroticism were positively associated with VE at t1. Our findings are consistent with previous research suggesting that workaholism and neuroticism may be risk factors for adverse subjective health outcomes (Preckel et al., 2005; Ng et al., 2007; Andreassen, 2014; Clark et al., 2016). The association between workaholism and VE supports the assumption that the exhaustive and compulsive work-related behaviors of workaholism come at the expense of teachers’ health and well-being (Preckel et al., 2005; Nie and Sun, 2016). However, contrary to our expectation, workaholism and neuroticism were both unrelated to VE one year later at t2 when controlling for t1. VE showed a very high longitudinal stability of r = 0.79 over the year between the two measurements at t1 and t2. Thus, not much variance remained that other variables could explain. Direct analysis at t2 without controlling for t1 showed similar effects as at t1. Furthermore, our results showed sex differences in VE at t2. One explanation could be that women generally report higher VE than men, which may be due to psychological and physiological sex differences in the stress response (Frestad and Prescott, 2017). In addition, studies suggest that women had a more significant decrease in mental health during the COVID-19 lockdown than men (Adams-Prassl et al., 2020), which may also have influenced the sex differences in our sample, as the follow-up data collection 1 year later occurred during the pandemic.
The second hypothesis stated that neuroticism moderates the relationship between workaholism and VE at t1 and t2, which has been confirmed. One possible explanation for this finding may be that teachers with high neuroticism scores are more likely to push themselves to or beyond the limits of their work performance, which eventually results in higher VE. Several previous studies support this assumption that neuroticism positively relates to workaholism as it may create an obsessive need or dependence on work, which, in turn, can result in adverse health outcomes (Lahey, 2009; Clark et al., 2016; McIlveen and Perera, 2016; Schaufeli, 2016, Gillet et al., 2018). In addition, neuroticism was found to be associated with low self-esteem (Amirazodi and Amirazodi, 2011), and some researchers suggest that one driving force behind workaholic employees may be the desire for self-worth validation (Aziz et al., 2018). Workaholics who experience low self-esteem, high levels of guilt, anxiety, and excessively high expectations of themselves are also likely to experience high levels of work stress (Clark et al., 2016; Aziz et al., 2018). High work stress combined with neuroticism may cause teachers to devote even more effort and time to work, perpetuating the vicious cycle.
Regarding hair cortisol concentrations (HCC), no association was found with workaholism or neuroticism, neither at t1 nor t2 (H3). One possible explanation for the associations of workaholism and neuroticism with vital exhaustion but not with HCC could be a simple negativity effect, that is, individuals high in neuroticism do not necessarily feel more exhausted or experience more workaholism, but they may report their feelings as stronger. Previous work suggests that neuroticism is associated with increased reporting of somatic symptoms but not with increased experience of these symptoms (McCrae and Costa, 1986; Larsen, 1992). In addition, the relationship between HCC and subjective work stress has yielded contradictory results in the existing literature (Qi et al., 2014, 2015; Steinisch et al., 2014; Gidlow et al., 2016; Janssens et al., 2017; Herr et al., 2018). Possible reasons may be the heterogeneity of the study populations, different hair sample lengths, and different stress questionnaires for different periods (Staufenbiel et al., 2013; Gidlow et al., 2016). Finally, van der Meij et al. (2018) compared HCC in a high and a normal workload sample and found an association with HCC only in the high workload sample. These findings suggest that a certain stress threshold must be reached to cause changes in HCC. The teachers in our sample are in the middle range between mild and moderate VE levels. Therefore, another reasonable explanation for our null findings may be that our teacher sample did not reach the threshold of chronic stress exposure that was high enough to associate with HCC.
The present study has several limitations. First, due to the COVID-19 pandemic, there were changes in the everyday lives of our participants, such as lockdowns and adaptation to digital teaching, which may have affected the stress-related measurements at one-year follow-up. The first assessments were conducted before the pandemic. Second, the assessment of neuroticism can be criticized since we did not use the full 12-item scale of the NEO-FFI (Borkenau and Ostendorf, 1993) which may not capture neuroticism in its broader concept. Third, workaholism and neuroticism were measured only once, which does not allow an analysis of the constructs’ bidirectional associations. Fourth, studies that have examined the overlap between vital exhaustion and depression have yielded inconsistent results regarding the extent to which they reflect the same underlying mechanisms (van Diest and Appels, 1991; Kopp et al., 1998; Kudielka et al., 2004; Vroege et al., 2012). Though our sample consists of generally healthy teachers, we did not control for depression, which may be considered a limitation. Finally, the sample of this study is relatively small, limiting the generalizability of the results. The findings should be replicated in a large cohort study to determine the effect of workaholism and neuroticism on adverse health outcomes in the general population. This would also help determine under what circumstances a relationship between workaholism, personality traits, and hair cortisol concentrations does or does not exist. That said, this study also includes some considerable strengths. This study is (to the best of the authors’ knowledge) the first to examine workaholism and neuroticism in relation to long-term hair cortisol concentrations in teachers. The longitudinal design further underscores the value of the study’s results.
If replicated in future research, our results have practical implications. In particular, the finding that workaholism was positively associated with vital exhaustion in teachers with high levels of neuroticism may highlight the importance of raising teachers’ awareness of potential risk factors contributing to vital exhaustion. In regards to neuroticism, a meta-analysis (Jorm, 1989) has shown that rational-emotive and similar therapies can successfully reduce neuroticism levels despite the dispositional nature of neuroticism. Moreover, providing in-service training courses for teachers may help familiarize them with the concepts of work behaviors, vital exhaustion, and the role of their personality in these processes. Although such training alone is unlikely to be sufficient to ultimately reduce the burden on teachers, it may help develop an understanding of potential adverse individual and organizational consequences of maladaptive or dysfunctional behaviors and coping styles. Identifying coping styles and work behaviors that match their personality style may help teachers to achieve and obtain a more sustainable work-life balance.
Taken together, workaholism and neuroticism appear to be associated with vital exhaustion in teachers. The association was manifested in increased self-reported vital exhaustion but not in increased HCC. Our findings emphasize the importance of considering individual characteristics when investigating vital exhaustion in teachers. Furthermore, this study adds to the literature on the divergence between self-reports and HCC. Further research is necessary to investigate the applicability of HCC as a biomarker of chronic stress in the context of work.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving human participants were reviewed and approved by Ethics Committee of the Canton Bern (no. 2019–00787) Internal Review Board (IRB) of the University of Bern. The participants provided their written informed consent to participate in this study.
Author contributions
AW: conceptualization, methodology, formal analysis, and writing—review and editing. SS: conceptualization, investigation, and writing—original draft. GJ: formal analysis. MgH and WT: writing—review and editing. RLM: conceptualization, methodology, and writing—review and editing. All authors contributed to the article and approved the submitted version.
Funding
This work was supported by the Swiss National Science Foundation SNF, under Grant number 100019_185484, and the University of Teacher Education Bern, Grant number 16 w 0008 02.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Adams-Prassl, A, Boneva, T, Golin, M, and Rauh, C. (2020). The Impact of the Coronavirus Lockdown on Mental Health: Evidence from the US. Cambridge: University of Cambridge.
Amirazodi, F, and Amirazodi, M. (2011). Personality traits and self-esteem. Procedia Soc. Behav. Sci. 29:713–6. doi: 10.1016/j.sbspro.2011.11.296
Andreassen, C. S. (2014). Workaholism: an overview and current status of the research. J. Behav. Addict. 3, 1–11. doi: 10.1016/0022-3999(89)90088-3
Appels, A., and Mulder, P. (1989). Fatigue and heart disease. The association between ‘vital exhaustion’ and past, present and future coronary heart disease. J. Psychosom. Res. 33, 727–738. doi: 10.1016/0022-3999(89)90088-3
Apple, MW. (1989). Teachers and Texts: A Political Economy of Class and Gender Relations in Education. New York: Routledge 259.
Aziz, S., Zamary, S., and Wuensch, K. (2018). The endless pursuit for self-validation through attainment: an examination of self-esteem in relation to workaholism. Personal. Individ. Differ. 121, 74–79. doi: 10.1016/j.paid.2017.09.024
Ballet, K., and Kelchtermans, G. (2009). Struggling with workload: primary teachers’ experience of intensification. Teach. Teach. Educ. 25, 1150–1157. doi: 10.1016/j.tate.2009.02.012
Balog, P., and Konkolÿ, T. B. (2019). The role of vital exhaustion in predicting the recurrence of vascular events: a longitudinal study. Int. J. Clin. Health Psychol. 19, 75–79. doi: 10.1016/j.ijchp.2018.11.004
Bellingrath, S., Weigl, T., and Kudielka, B. M. (2008). Cortisol dysregulation in school teachers in relation to burnout, vital exhaustion, and effort–reward-imbalance. Biol. Psychol. 78, 104–113. doi: 10.1016/j.biopsycho.2008.01.006
Borkenau, P., and Ostendorf, F. (1993). NEO-Fünf-Faktoren Inventar (NEO-FFI) nach Costa und McCrae. Göttingen: Hogrefe. Z. für Klin. Psycholo. Psychother. 28, 145–146. doi: 10.1026//0084-5345.28.2.145
Brianda, M. E., Roskam, I., and Mikolajczak, M. (2020). Hair cortisol concentration as a biomarker of parental burnout. Psychoneuroendocrinology 117:104681. doi: 10.1016/j.psyneuen.2020.104681
Christensen, D. S., Dich, N., Flensborg-Madsen, T., Garde, E., Hansen, Å. M., and Mortensen, E. L. (2019). Objective and subjective stress, personality, and allostatic load. Brain Behav. 9:e01386. doi: 10.1002/brb3.1386
Clark, M. A., Michel, J. S., Zhdanova, L., Pui, S. Y., and Baltes, B. B. (2016). All work and no play? A meta-analytic examination of the correlates and outcomes of Workaholism. J. Manag. 42, 1836–1873. doi: 10.1177/0149206314522301
Cohen, S (ed.). (1997). Measuring Stress: A Guide for Health and Social Scientists. New York: Oxford University Press 236.
Costa, P. T., and McCrae, R. R. (1992). The five-factor model of personality and its relevance to personality disorders. J. Personal. Disord. 6, 343–359. doi: 10.1521/pedi.1992.6.4.343
Dettenborn, L., Tietze, A., Bruckner, F., and Kirschbaum, C. (2010). Higher cortisol content in hair among long-term unemployed individuals compared to controls. Psychoneuroendocrinology 35, 1404–1409. doi: 10.1016/j.psyneuen.2010.04.006
Engert, V., Blasberg, J. U., Köhne, S., Strauss, B., and Rosendahl, J. (2021). Resilience and personality as predictors of the biological stress load during the first wave of the Covid-19 pandemic in Germany. Transl. Psychiatry 11:443. doi: 10.1038/s41398-021-01569-3
Erickson, T. M., Jacobson, S. V., Banning, R. L., Quach, C. M., and Reas, H. E. (2021). Big five traits and interpersonal goals during stressors as predictors of hair cortisol. Compr. Psychoneuroendocrinol. 8:100084. doi: 10.1016/j.cpnec.2021.100084
Frestad, D., and Prescott, E. (2017). Vital exhaustion and coronary heart disease risk: a systematic review and meta-analysis. Psychosom. Med. 79, 260–272. doi: 10.1097/PSY.0000000000000423
Gao, W., Stalder, T., Foley, P., Rauh, M., Deng, H., and Kirschbaum, C. (2013). Quantitative analysis of steroid hormones in human hair using a column-switching LC–APCI–MS/MS assay. J. Chromatogr. B 928, 1–8. doi: 10.1016/j.jchromb.2013.03.008
Garcia-Banda, G., Servera, M., Chellew, K., Meisel, V., Fornes, J., Cardo, E., et al. (2011). Prosocial personality traits and adaptation to stress. Soc. Behav. Pers. 39, 1337–1348. doi: 10.2224/sbp.2011.39.10.1337
García-Carmona, M., Marín, M. D., and Aguayo, R. (2019). Burnout syndrome in secondary school teachers: a systematic review and meta-analysis. Soc. Psychol. Educ. 22, 189–208. doi: 10.1007/s11218-018-9471-9
Gidlow, C. J., Randall, J., Gillman, J., Silk, S., and Jones, M. V. (2016). Hair cortisol and self-reported stress in healthy, working adults. Psychoneuroendocrinology 63, 163–169. doi: 10.1016/j.psyneuen.2015.09.022
Gillet, N., Morin, A. J. S., Sandrin, E., and Houle, S. A. (2018). Investigating the combined effects of workaholism and work engagement: a substantive-methodological synergy of variable-centered and person- centered methodologies. J. Vocat. Behav. 109, 54–77. doi: 10.1016/j.jvb.2018.09.006
Gluschkoff, K., Elovainio, M., Kinnunen, U., Mullola, S., Hintsanen, M., Keltikangas-Järvinen, L., et al. (2016). Work stress, poor recovery and burnout in teachers. Occup. Med (Lond). 66, 564–570. doi: 10.1093/occmed/kqw086
Gow, R., Thomson, S., Rieder, M., Van Uum, S., and Koren, G. (2010). An assessment of cortisol analysis in hair and its clinical applications. Forensic Sci. Int. 196, 32–37. doi: 10.1016/j.forsciint.2009.12.040
Hayes, AF. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. 2nd. New York: Guilford Press. 692.
Herman, J. P., and Cullinan, W. E. (1997). Neurocircuitry of stress: central control of the hypothalamo–pituitary– adrenocortical axis. Trends Neurosci. 20, 78–84. doi: 10.1016/S0166-2236(96)10069-2
Herr, R. M., Almer, C., Loerbroks, A., Barrech, A., Elfantel, I., Siegrist, J., et al. (2018). Associations of work stress with hair cortisol concentrations – initial findings from a prospective study. Psychoneuroendocrinology 89, 134–137. doi: 10.1016/j.psyneuen.2018.01.011
Isabel, A., Lopes, J., and Oliveira, C. (2021). Burnout in Portuguese teachers: a systematic review. Eur. J. Educ. Res. 10, 693–703. doi: 10.12973/eu-jer.10.2.693
Janssens, H., Clays, E., Fiers, T., Verstraete, A. G., de Bacquer, D., and Braeckman, L. (2017). Hair cortisol in relation to job stress and depressive symptoms. Occup. Med. 67, 114–120. doi: 10.1093/occmed/kqw114
Jorm, A. F. (1989). Modifiability of trait anxiety and neuroticism: a meta-analysis of the literature. Aust. N. Z. J. Psychiatry 23, 21–29. doi: 10.3109/00048678909062588
Richards, K. A., Hemphill, M. A., and Templin, T. (2018). Personal and contextual factors related to teachers’ experience with stress and burnout. Teach. Teach. 24, 768–787. doi: 10.1080/13540602.2018.1476337
Kokkinos, C. M. (2007). Job stressors, personality and burnout in primary school teachers. Br. J. Educ. Psychol. 77, 229–243. doi: 10.1348/000709905X90344
Kop, W. J., Appels, A. P. W. M., de Leon, C. F. M., and Bar, F. W. (1996). The relationship between severity of coronary artery disease and vital exhaustion. J. Psychosom. Res. 40, 397–405. doi: 10.1016/0022-3999(95)00613-3
Kopp, M. S., Falger, P. R. J., Appels, A., and Szedmak, S. (1998). Depressive symptomatology and vital exhaustion are differentially related to behavioral risk factors for coronary artery disease. Psychosom. Med. 60, 752–758.
Kudielka, B. M., Bellingrath, S., and von Känel, R. (2008). Circulating fibrinogen but not D-dimer level is associated with vital exhaustion in school teachers. Stress 11, 250–258. doi: 10.1080/10253890701714831
Kudielka, B. M., von Känel, R., Gander, M. L., and Fischer, J. E. (2004). The interrelationship of psychosocial risk factors for coronary artery disease in a working population: do we measure distinct or overlapping psychological concepts? Behav. Med. 30, 35–44. doi: 10.3200/BMED.30.1.35-44
Laceulle, O. M., Nederhof, E., van Aken, M. A. G., and Ormel, J. (2015). Adolescent personality: associations with basal, awakening, and stress-induced cortisol responses: adolescent personality and cortisol. J. Pers. 83, 262–273. doi: 10.1111/jopy.12101
Lahey, B. B. (2009). Public health significance of neuroticism. Am. Psychol. 64, 241–256. doi: 10.1037/a0015309
Larsen, R. J. (1992). Neuroticism and selective encoding and recall of symptoms: evidence from a combined concurrent-retrospective study. J. Pers. Soc. Psychol. 62, 480–488. doi: 10.1037/0022-3514.62.3.480
Manenschijn, L., van Kruysbergen, R. G. P. M., de Jong, F. H., Koper, J. W., and van Rossum, E. F. C. (2011). Shift work at young age is associated with elevated long-term cortisol levels and body mass index. J. Clin. Endocrinol. Metabol. 96, E1862–E1865. doi: 10.1210/jc.2011-1551
McCrae, R. R., and Costa, P. T. (1986). Personality, coping, and coping effectiveness in an adult sample. J. Pers. 54, 385–404. doi: 10.1111/j.1467-6494.1986.tb00401.x
McIlveen, P., and Perera, H. N. (2016). Career optimism mediates the effect of personality on teachers’ career engagement. J. Career Assess. 24, 623–636. doi: 10.1177/1069072715616059
Nater, U. M., Hoppmann, C., and Klumb, P. L. (2010). Neuroticism and conscientiousness are associated with cortisol diurnal profiles in adults—role of positive and negative affect. Psychoneuroendocrinology 35, 1573–1577. doi: 10.1016/j.psyneuen.2010.02.017
Ng, T. W. H., Sorensen, K. L., and Feldman, D. C. (2007). Dimensions, antecedents, and consequences of workaholism: a conceptual integration and extension. J. Organ. Behav. 28, 111–136. doi: 10.1002/job.424
Nie, Y., and Sun, H. (2016). Why do workaholics experience depression? A study with Chinese university teachers. J. Health Psychol. 21, 2339–2346. doi: 10.1177/1359105315576350
Oates, W. (1971). Confessions of a workaholic: the facts about Work addiction. New York: World Publishing Co.
Perera, H. N., Vosicka, L., Granziera, H., and McIlveen, P. (2018). Towards an integrative perspective on the structure of teacher work engagement. J. Vocat. Behav. 108, 28–41. doi: 10.1016/j.jvb.2018.05.006
Prado-Gascó, V., de la Barrera, U., Sancho-Castillo, S., de la Rubia-Ortí, J. E., and Montoya-Castilla, I. (2019). Perceived stress and reference ranges of hair cortisol in healthy adolescents. PLoS One 14:e0214856. doi: 10.1371/journal.pone.0214856
Preckel, D., von Känel, R., Kudielka, B. M., and Fischer, J. E. (2005). Overcommitment to work is associated with vital exhaustion. Int. Arch. Occup. Environ. Health 78, 117–122. doi: 10.1007/s00420-004-0572-8
Prescott, E., Holst, C., Grønbæk, M., Schnohr, P., Jensen, G., and Barefoot, J. (2003). Vital exhaustion as a risk factor for ischaemic heart disease and all-cause mortality in a community sample. A prospective study of 4084 men and 5479 women in the Copenhagen City heart study. Int. J. Epidemiol. 32, 990–997. doi: 10.1093/ije/dyg235
Qi, X., Liu, Y., Zhang, J., Ji, S., Sluiter, J. K., Zhou, R., et al. (2015). Relationship between work strain, need for recovery after work and cumulative cortisol among kindergarten teachers. Int. Arch. Occup. Environ. Health 88, 1053–1059. doi: 10.1007/s00420-015-1033-2
Qi, X., Zhang, J., Liu, Y., Ji, S., Chen, Z., Sluiter, J. K., et al. (2014). Relationship between effort–reward imbalance and hair cortisol concentration in female kindergarten teachers. J. Psychosom. Res. 76, 329–332. doi: 10.1016/j.jpsychores.2014.01.008
Rammstedt, B., and John, O. P. (2007). Measuring personality in one minute or less: a 10-item short version of the big five inventory in English and German. J. Res. Pers. 41, 203–212. doi: 10.1016/j.jrp.2006.02.001
Rau, R., Gebele, N., Morling, K., and Rösler, U. (2010). Untersuchung arbeitsbedingter Ursachen für das Auftreten von Depressiven Störungen: Forschung Projekt F 1865. Dortmund: Bundesanstalt für Arbeitrschutz und Arbeitsmedizin.
Rietschel, L., Streit, F., Zhu, G., McAloney, K., Kirschbaum, C., Frank, J., et al. (2016). Hair Cortisol and Its Association With Psychological Risk Factors for Psychiatric Disorders: a Pilot Study in Adolescent Twins. Twin Res. Hum. Genet. 19, 438–446. doi: 10.1017/thg.2016.50
Russell, E., Koren, G., Rieder, M., and Van Uum, S. (2012). Hair cortisol as a biological marker of chronic stress: current status, future directions and unanswered questions. Psychoneuroendocrinology 37, 589–601. doi: 10.1016/j.psyneuen.2011.09.009
Schaarschmidt, U, and Fischer, A. (2008). AVEM–Arbeitsbezogenes Verhaltens-und Erlebensmuster. 3rd Frankfurt: Pearson.
Schaufeli, W. B. (2016). Heavy work investment, personality and organizational climate. J. Manag. Psychol. 31, 1057–1073. doi: 10.1108/JMP-07-2015-0259
Schaufeli, W, and Enzmann, D. (2020). The Burnout Companion to Study and Practice: A Critical Analysis. 1st Boca Raton, FL: CRC Press.
Schnorpfeil, P., Noll, A., Wirtz, P., Schulze, R., Ehlert, U., Frey, K., et al. (2002). Assessment of exhaustion and related risk factors in employees in the manufacturing industry - a cross-sectional study. Int. Arch. Occup. Environ. Health 75, 535–540. doi: 10.1007/s00420-002-0369-6
Schoch, J., Noser, E., and Ehlert, U. (2018). Do implicit motives influence perceived chronic stress and vital exhaustion? Front. Psychol. 9:1149. doi: 10.3389/fpsyg.2018.01149
Stalder, T., and Kirschbaum, C. (2012). Analysis of cortisol in hair--state of the art and future directions. Brain Behav. Immun. 26, 1019–1029. doi: 10.1016/j.bbi.2012.02.002
Stalder, T., Steudte-Schmiedgen, S., Alexander, N., Klucken, T., Vater, A., Wichmann, S., et al. (2017). Stress-related and basic determinants of hair cortisol in humans: a meta-analysis. Psychoneuroendocrinol. 77, 261–274. doi: 10.1016/j.psyneuen.2016.12.017
Staufenbiel, S. M., Penninx, B. W. J. H., Spijker, A. T., Elzinga, B. M., and van Rossum, E. F. C. (2013). Hair cortisol, stress exposure, and mental health in humans: a systematic review. Psychoneuroendocrinology 38, 1220–1235. doi: 10.1016/j.psyneuen.2012.11.015
Steinisch, M., Yusuf, R., Li, J., Stalder, T., Bosch, J. A., Rahman, O., et al. (2014). Work stress and hair cortisol levels among workers in a Bangladeshi ready-made garment factory – results from a cross-sectional study. Psychoneuroendocrinology 50, 20–27. doi: 10.1016/j.psyneuen.2014.08.001
Stirratt, M. J., Dunbar-Jacob, J., Crane, H. M., Simoni, J. M., Czajkowski, S., Hilliard, M. E., et al. (2015). Self-report measures of medication adherence behavior: recommendations on optimal use. Behav. Med. Pract. Policy Res. 5, 470–482. doi: 10.1007/s13142-015-0315-2
Tabak, F., Tziner, A., Shkoler, O., and Rabenu, E. (2021). The complexity of heavy work investment (HWI): a conceptual integration and review of antecedents, dimensions, and outcomes. Sustainability 13:7803. doi: 10.3390/su13147803
Ullmann, E., Barthel, A., Petrowski, K., Stalder, T., Kirschbaum, C., and Bornstein, S. R. (2016). Pilot study of adrenal steroid hormones in hair as an indicator of chronic mental and physical stress. Sci. Rep. 6:25842. doi: 10.1038/srep25842
van der Meij, L., Gubbels, N., Schaveling, J., Almela, M, and van Vugt, M. (2018). Hair cortisol and work stress: Importance of workload and stress model (JDCS or ERI). Psychoneuroendocrinol. 89, 78–85. doi: 10.1016/j.psyneuen.2017.12.020
van Diest, R., and Appels, A. (1991). Vital exhaustion and depression: a conceptual study. J. Psychosom. Res. 35, 535–544. doi: 10.1016/0022-3999(91)90048-S
Vroege, E. M., Zuidersma, M., and de Jonge, P. (2012). Vital exhaustion and somatic depression: the same underlying construct in patients with myocardial infarction? Psychosom. Med. 74, 446–451. doi: 10.1097/PSY.0b013e31825a7194
Keywords: workaholism, neuroticism, hair cortisol, vital exhaustion, teacher stress
Citation: Wettstein A, Schneider S, Jenni G, Holtforth Mg, Tschacher W and La Marca R (2022) Association between workaholism, vital exhaustion, and hair cortisol concentrations among teachers: A longitudinal study testing the moderation effect of neuroticism. Front. Psychol. 13:1046573. doi: 10.3389/fpsyg.2022.1046573
Edited by:
Changiz Mohiyeddini, Oakland University William Beaumont School of Medicine, United StatesReviewed by:
Roger Hagen, University of Oslo, NorwayFerda Alper Ay, Sivas Cumhuriyet University, Turkey
Valentina Mihaela Ghinea, Bucharest Academy of Economic Studies, Romania
Copyright © 2022 Wettstein, Schneider, Jenni, Holtforth, Tschacher and La Marca. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alexander Wettstein, YWxleGFuZGVyLndldHRzdGVpbkBwaGJlcm4uY2g=