Job Satisfaction Among Mental Health Workers: Associations With Respiratory Sinus Reactivity to, and Recovery From Exposure to Mental Stress William H. O’Brien, Paul W. Goetz, Heather McCarren, Eileen Delaney, William F. Morrison, Tanya S. Watford, and Kristin A. Horan

Job Satisfaction Among Mental Health Workers

Associations With Respiratory Sinus Reactivity to, and Recovery From Exposure to Mental Stress

William H. O’Brien, 1

Paul W. Goetz, 2

Heather McCarren, 3

Eileen Delaney, 4 William F. Morrison, 1

Tanya S. Watford, 1

and Kristin A. Horan 1

1

Bowling Green State University, Bowling Green, OH, USA 2

Division of Cardiac Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 3

VHA National Center for Organization Development, Cincinnati, OH, USA 4

Naval Center for Combat and Occupational Stress Control (NCCOSC), San Diego, CA, USA

Abstract: Work characteristics such as job satisfaction have been associated with mental and physical health outcomes in several crosssectional and longitudinal studies. However, meta-analytic reviews indicate that nearly all of the reported relationships between these two sets of constructs rely on self-report measures. Thus, the magnitude of the reported relationships may be inaccurate and inflated due to common method variance (mono-method bias) and negative affectivity. Respiratory sinus arrhythmia (RSA) is an objective measure of risk for adverse mental health and physical health outcomes. To our knowledge, there has been no investigation of the relationship between job satisfaction and respiratory sinus arrhythmia. In this investigation, 29 workers in mental health settings who experience higher than average levels of work stress due to the amount and unpredictability of workload completed sociodemographic measures and a job satisfaction measure. RSA was then collected during a resting baseline, a worry induction stressor condition where they were instructed to think about work stressors, and a post-stress recovery condition. RSA reactivity to the stressor was significantly greater for participants with low job satisfaction. The low job satisfaction participants also demonstrated less RSA recovery after the stressor ended. Alternatively, participants with higher job satisfaction reacted less and recovered more completely from the stressor.

Keywords: respiratory sinus arrhythmia, job satisfaction

Workers who provide services to persons with mental health problems such as intellectual disabilities (ID) can experience significant work stress and low levels of job satisfaction which have been linked to turnover rates and intent to quit (Gray-Stanley et al., 2010; Larson, Lakin, & Bruininks, 1998; Lunsky, Hastings, Hensel, Arenovich, & Dewa, 2014; Mutkins, Brown, & Thorsteinsson, 2011; Rose, Home, Rose, & Hastings, 2004). Workplace factors that have been linked to work stress and low job satisfaction among persons working with ID populations include problematic client behaviors (Mitchell & Hastings, 2001; Skirrow & Hatton, 2007), perceived lack of support (Rose, 1993), role ambiguity (Hatton, Rashes, Caine, & Emerson, 1995), and unpredictable workloads. Job satisfaction has been associated with adverse mental and physical health outcomes. For example, Faragher, Cass, and Cooper (2005) conducted a comprehensive metaanalysis of research investigating relationships between job

satisfaction and mental and physical health outcomes. Their meta-analysis provided important insights into this research domain. First, job satisfaction was moderately correlated with several self-reported mental health states such as burnout (overall unadjusted r = .409), depressed mood (overall unadjusted r= .366), and anxiety (overall unadjusted r = .354). Second, job satisfaction was correlated, to a lesser extent, with self-reported physical symptoms (overall unadjusted r = .235). Third, job satisfaction was very modestly correlated with more objective physical health outcomes such as cardiovascular disease (overall unadjusted r = .121) and musculoskeletal disease (overall unadjusted r = .078). Finally, their results indicated that the evaluation of relationships between job satisfaction and these outcomes overwhelmingly relied on self-report measures. As such, it is difficult to parse out the effects of method bias as well as negative affectivity in the existing literature. Nonetheless, it is important to note, as did Faragher et al. (2005), that job

satisfaction was the largest work-related predictor of mental health symptoms.

Considering this, the use of objective physiological measures to examine the impact of job satisfaction is warranted. Respiratory sinus arrhythmia (RSA), for example, is an index of parasympathetic influence on the heart (Porges, 2007). RSA has been associated with risk for a number of adverse health outcomes such as diabetes, obesity, and cardiovascular disease (Masi, Hawkley, Rickett, & Cacioppo, 2007). RSA has also been associated with work stress (Toivanen, Länsimies, Jokela, & Hänninen, 1993; Watanabe et al, 2002; Zanstra, Schellekens, Schaap, & Kooistra, 2006) and depression (Bylsma, Solomon, Taylor-Clifft, Morris, & Rottenberg, 2014; Yaptangco, Crowell, Baucom, Bride, & Hansen, 2015). In the aforementioned research, higher levels of RSA were typically associated with lower levels of risk for adverse outcomes.

Respiratory sinus arrhythmia may be particularly relevant in the study of job satisfaction. The detrimental effects of work stress, which has been associated with job satisfaction, have been associated with impaired parasympathetic functioning (Clays et al., 2011; Orsila et al., 2008; Vrijkotte, Van Doornen, & De Geus, 2000). Vrijkotte and colleagues (2000) suggested this may be due to the role of the parasympathetic system in recovery and restoration. For example, workers with poor RSA recovery after work stress exposure may also struggle to relax after work on a daily basis and, over time, may have a substantially higher risk for coronary heart disease (Suadicani, Hein, & Gyntelberg, 1993). A review by Jarczok and colleagues (2013) adduced the Neurovisceral Integration Model (Thayer & Lane, 2000) to explain the link between work stress exposure and cardiovascular risk. They proposed that work stress is associated with heart rate variability which, like RSA, is an index of parasympathetic functioning. The Neurovisceral Integration Model posits that RSA can be thought of as an index of cognitive and emotional processes in the cortical and subcortical brain areas. Further, this model suggests that RSA is an index, not only of heart function, but also the degree of integration between the central autonomic network and the peripheral nervous system. The integration of the central autonomic network and the peripheral nervous system provides an individual with the ability to flexibly respond, both psychologically and physiologically, to emotional experiences and to generate effective behavioral responses to address environmental demands (Thayer, Åhs, Fredrikson, Sollers, & Wager, 2012). In other words, parasympathetic functioning indexed by RSA partially reflects an individual’s ability to function in a complex environment (Jarczok et al., 2013). To our knowledge, however, there are no published investigations of the relationship between job satisfaction and RSA.

Given the paucity of research examining the relationship between job satisfaction and objective measures of health, in this exploratory study we evaluated the relationship between job satisfaction and RSA among workers in community agencies that provide services to persons with intellectual disabilities. We predicted that higher levels of job satisfaction would be associated with higher levels of RSA overall. We also predicted that higher levels of job satisfaction would be associated with lower levels of RSA reactivity to an acute stressor.

Method

Participants

Participants were recruited from two agencies that provide services to ID persons in Northwest Ohio. The participants were informed that the study involved an evaluation of work stress and cardiovascular reactivity to stress. A total of 29 workers participated in the study. The study participants were predominantly women (86%, n = 25) and Caucasian (97%, n = 28, one person reported African American ethnicity). The average age of participants was 42 years (range: 25–60; SD = 10.50). Most of the participants were full time employees (90%, n = 26) and they reported working an average of 41 hr per week (SD = 7.00). The job tenure was 6.9 years (SD = 4.40). Four (14%) participants obtained a postgraduate degree, 16 (55%) obtained an undergraduate degree, 7 (24%) completed some college, and 2 (7%) obtained a high school degree.

Procedure

Participants completed the work stress evaluation at their workplace during working hours. To accomplish this, the researchers set up the laboratory equipment in a private office in the organizations. Upon arrival, the project was described in detail. Participants then completed a written informed consent. Following this, participants completed self-report questionnaires and then underwent a stress reactivity protocol while RSA was recorded using portable cardiovascular measurement equipment.

The stress reactivity protocol consisted of three conditions: a 10-min resting Baseline condition, a 5-min Stress/ Worry condition, and a 10-min Recovery condition. During the Baseline condition, participants were asked to close their eyes and to relax and focus on their breathing. During the Stress/Worry condition, participants were instructed to pick a topic about which they are currently most stressed or worried and asked to focus on this topic as intensely as they

could. This stress/worry induction method has been widely used and accepted within the stress and worry literature (e.g., Behar, Vescio, & Borkovec, 2005; McLaughlin, Borkovec, & Sibrava, 2007). Finally, during the Recovery condition participants were asked to close their eyes, relax, and focus on their breathing. At the conclusion of the Recovery condition, electrodes were removed, and participants were debriefed.

Measures

Demographics An 11-item self-report inventory was used to assess demographic variables, illness variables (e.g., doctor visits and days of work missed due to illness), and work characteristics (job tenure, job title, hours worked per week).

Job Satisfaction Job satisfaction was measured using the abridged Job Descriptive Index (JDI; Stanton et al., 2002). This scale contains five subscales that measure satisfaction with five aspects of the job including work, pay, promotion opportunities, coworkers, and supervisor. Respondents are asked to indicate whether short phrases describe their job by checking “Yes,” “No,” or “? Cannot Decide.” The JDI is widely accepted as having sound psychometric properties and it has been noted that the abridged version retains the reliability, validity, and factor consistency of the full-length scale (Stanton et al., 2002). The Cronbach’s α for the total JDI was .89 in this sample (note that while the JDI has five subscales, our analyses indicated it could be treated as a global and unidimensional index of job satisfaction).

Thought Rating At the conclusion of the baseline, stress/worry, and recovery conditions, participants were asked to “briefly describe the thoughts you experienced during the last 5 min.” They were then asked to write the thoughts. Trained raters then read and assigned the following values: 0 = no worry-related content, 9 = minimal worry-related content, 2 = moderate worry-related content, and 3 = maximal worry-related content.

Inter-rater reliability of these worry ratings was high, r = .81, p < .001, with a 70% agreement rate. Differences between raters were resolved through discussion.

Respiratory Sinus Arrhythmia Allen, Chambers, and Towers (2007) reviewed methods for calculating RSA and noted that a separate measure of respiration is not needed because the interaction between heart rate variability and respiration occurs in specific

frequency band that ranges from .12 to .40 Hz. Allen et al. (2007) also developed a software approach that uses two programs to calculate RSA. The first program, the QRSTool, was used to detect R waves in ECG (electrocardiogram) collected from each participant. The QRSTool has an option that allowed us to manually detect and correct artifacts in ECG data. In most cases, this involved identifying points in an ECG where an R wave was not detected. When this occurred, we manually inserted a maker variable for the missed R wave. In some instances, such as movement artifacts or large T waves, we removed markers that the program misidentified as an R wave. After the R waves were marked using the QRSTool, the CMetX program was used to compute RSA. Using the CMetX program, the interbeat intervals between successive R waves were converted to a time series and then run through a .12–.40 Hz band-pass filter. The Allen et al. ( 2007) validation study of the CMetX program indicated that the .12–.40 range captured variation in respiration-related heart rate variability and parasympathetic activation. The resultant RSA values were then log transformed. Allen et al. (2007) tested the validity of their QRSTool and CMetX system with the MXedit system developed by Porges and Boher (1990). Using a sample of 96 undergraduate students, they found the correlations between the two systems exceeded .99 during resting and stressor conditions.

In terms of hardware, ECG data was collected using a Biopac Systems MP30 (Biopac Systems, Galeta, CA) with the Biopac version 3.7.2 analysis software. Three silver-silver chloride electrodes were positioned in a standard Lead II configuration (negative electrode on the right wrist, positive electrode on the left ankle, ground electrode on the right ankle ground) to record ECG. The ECG was sampled at a rate of 1,000 Hz which is well above recommended 500 Hz sampling rate needed to calculate RSA.

Data Reduction and Analysis

Missing values were replaced with an individual’s mean score of endorsed items on a self-report measure if less than 20% of measure items were missed. RSA scores were averaged across each condition of the experiment. Only the last 5 min of the Baseline condition and the first 5 min of the Recovery condition were used in computing RSA scores, to match the 5-min period of the Stress/Worry condition.

Results

All predictor and dependent measures were examined for measurement adequacy. Skewness ranged from
0.78 to 0.44 and kurtosis ranged from
1.04 to 0.88. Each

Baseline Stressor Recovery

Low JDI High JDI 35

Figure 1. RSA as a function of JDI and condition.

skewness and kurtosis statistic was divided by the standard error for each statistic in order to generate a z-score and the corresponding probability value associated with each z-score (e.g., Hopkins & Weeks, 1990). The skewness z-scores ranged from
1.24 to 0.50 (p = .22 to p = .62) and the kurtosis z-scores ranged from
1.23 to 0.58 (p = .22 to p = .56). Based on these analyses, none of the variables were characterized by significant skew or kurtosis. An examination of individual participant standardized scores indicated that there were no outliers using the recommended cutoff of 3.0. Finally, all of the analyses of variance (ANOVAs) and follow-up comparisons (described below) were tested for equality of variances and sphericity. None of the analyses indicated a significant violation of the normality assumption.

The mean, median, and standard deviation for the total JDI was calculated (M = 53.17, Mdn = 57, SD = 16.11) and found to be consistent with prior reports (Stanton et al., 2002). Participants were divided into high JDI and low JDI groups using a median split. Specifically, participants with JDI scores greater than 57 were assigned to the high group while participants with scores equal to or lower than 57 were assigned to the low JDI group). The two groups were compared on relevant sociodemographic and health variables. No significant differences (all p values were > .10 on t-tests for ratio and ordinal variables and Chi-Square tests for nominal variables) were observed between the two groups on the following measures: age, gender, race, marital status, educational attainment, job tenure, and hours worked. A 2  3 (high JDI, low JDI  Baseline, Stress/Worry, and Recovery conditions) repeated-measures ANOVA was then conducted using the thought rating as the dependent variable. A significant main effect was observed for condition, F(2, 26) = 86.66, p < .001, η p 2

= .870. Follow-up

comparisons of the main effect for condition indicated that the Baseline thought rating (M = 0.48, SD = 0.83) was significantly, F(1, 28) = 96.76, p < .001, η p 2

= .782, lower than the Stress/Worry thought rating (M = 2.35, SD = 0.77) but not significantly, F(1, 28) = 2.31, p = .14, η p 2

= .079, different from the Recovery thought rating (M = 0.21, SD = 0.41). Additionally, the Stress/Worry thought rating was significantly higher than the Recovery thought rating, F(1, 28) = 168.01, p < .001, η p 2

= .867. The main effect for JDI was nonsignificant, F(1, 27) = 1.32, p = .26, η p 2

= .045. Similarly, the interaction between JDI and condition was nonsignificant, F(2, 26)=.50, p = .61, η p 2

= .037. Using Cohen’s (1988) effect size classification scheme (i.e., η p 2

= .01, .06, and .14 are labeled small, medium, and large, respectively), the effect sizes for the condition main effect, the Baseline-Stress/Worry comparison, and the Stress/ Worry-Recovery comparison were all very large. This is because worrisome thoughts were virtually absent during the Baseline and Recovery conditions whereas they were quite common (as expected given instructions) during the Stress/Worry condition. The effect sizes for the JDI main effect, the interaction between the JDI and condition, and the Baseline-Recovery comparison were very small. A 2  3 (high JDI, low JDI  Baseline, Stress/Worry, Recovery) repeated-measures ANOVA was then conducted using the RSA as the dependent variable. A significant interaction between the JDI and condition was observed, F(2, 26) = 3.67, p < .04, η p 2

= .220. Figure 1 provides a graphic representation of the interaction. A significant main effect was also observed for condition, F(2, 26) = 5.28, p = .01, η p 2

= .289. Follow-up comparisons of the main effect for condition indicated that the Baseline RSA (M = 5.86, SD = 1.27) was significantly higher, F(1, 28) = 9.94, p = .004, η p 2

= .262, than the Stress/Worry RSA (M = 5.54, SD = 1.35) but not significantly higher, F(1, 28)=.383,

p = .54, η p 2

= .013, than the Recovery RSA (M = 5.91, SD = 1.18). Additionally, the Stress/Worry RSA was significantly lower than the Recovery RSA, F(1, 28) = 9.64, p = .004, η p 2

= .256. The main effect for JDI was nonsignificant, F(1, 27)=.06, p = .81, η p 2

= .002. The effect sizes for the JDI by condition interaction, the main effect for condition, the Baseline-Stress/Worry comparison, and the Stress/ Worry-Recovery comparison were all large. The effect sizes for the JDI main effect and the Baseline-Recovery comparison were very small.

Follow-up analyses of theinteraction between JDI and condition were conducted. First, a one-way repeated-measures ANOVA was conducted for each group separately. Following this, pairwise comparisons were conducted using the Bonferroni-corrected probability value (p = .02). For the low JDI group, the one-way repeated measures ANOVA was significant, F(2, 14) = 8.10, p = .005, η p 2

= .536. Follow-up pairwise comparisons indicated that the Baseline RSA (M = 5.91, SD = 1.30) was significantly higher than the Stress/Worry RSA (M = 5.46, SD = 1.22) but not the Recovery RSA (M = 5.78, SD = 1.18); F(1, 15) = 17.35, p = .001, η p 2

= .536 and F(1, 15) = 1.20, p = .29, η p 2

= .074, respectively. The comparison between the Stress/Worry RSA and recovery RSA was nonsignificant using the Bonferroni correction, F(1, 15) = 5.37, p = .04, η p 2

= .264. The effect sizes for the overall one-way ANOVA and the Baseline-Stress/ Worry comparison and Stress/Worry-Recovery comparison were large.

For the high JDI group, the one-way repeated-measures ANOVA was not significant F(2, 11) = 3.02, p = .09. Exploratory pairwise comparisons were conducted. These revealed that the Baseline RSA (M = 5.79, SD = 1.27) was not significantly different (using Bonferroni correction) from the Stress/Worry RSA (M = 5.64, SD = 1.54) or Recovery RSA (M = 6.07, SD = 1.20); F(1, 12) = 0.45, p = .40, η p 2

= .059 and F(1, 12) = 5.95, p = .03, η p 2

= .331 respectively. The comparison between the Stress/Worry RSA and Recovery RSA was also nonsignificant, F(1, 12) = 4.25, p = .06, η p 2

= .262. Note that the Baseline-Stress/Worry comparison and the Stress/Worry-Recovery comparison were significant using the conventional probability cutoff of .05 but not when the more conservative Bonferroni corrected cutoff was used. Additionally, both comparisons indicated that the Recovery RSA was higher. In sum, the high JDI participants did not show significant RSA reactivity to the stressor. Further, during the Post-Stress/Worry Recovery period, they demonstrated a higher RSA which indicated greater parasympathetic activation.

Because of the small sample size, nonparametric analyses were conducted examine the possibility that a few participants were driving the ANOVA results. The Friedman’s test of ranks was used to evaluate condition effects within each group. For the low JDI group, all comparisons were

similar with a single exception. Specifically, the Baseline RSA (Mean Rank = 1.81) was significantly higher than the Recovery RSA (Mean Rank = 1.18; w 2 (1) = 6.25, p = .01). This indicated that the low JDI participants did not fully recover from the stressor. For the high JDI participants, the nonparametric findings were equivalent to the ANOVA results. Bivariate correlations were conducted to further explore the relationship between the JDI and RSA. The relationship between the JDI and baseline levels of RSA was not significant, r(27) =
.152, p = .45. We then computed two RSA residual scores by: (a) regressing the Stressor/Worry RSA on the Baseline RSA and saving the standardized residual and (b) regressing the Recovery RSA on the Baseline RSA and saving the standardized residual. These residual scores provided indices of reactivity and recovery that were uncorrelated with Baseline levels of RSA. A significant correlation was observed between the JDI and the Stress/ Worry residual score, r(27)=.32, p = .05 and the Recovery residual score, r(27)=.56, p < .002. Together, these correlations indicated that lower levels of job satisfaction were associated with more reactivity to stress and less complete recovery from stress.

In summary, results indicated that the laboratory stressor was able to induce a significant increase in worry and RSA reactivity. Further, participants with lower job satisfaction scores showed great RSA reactivity to the stressor and did not fully recover from it. Alternatively, participants with higher job satisfaction scores did not show significant RSA reactivity to the stressor and their recovery was more complete.

Discussion

This investigation was designed to evaluate the relationship between job satisfaction and RSA among persons working in agencies that provide services to persons with ID. We predicted that higher levels of job satisfaction would be associated lower levels of reactivity to a stressor. Consistent with expectations, we found that higher levels of job satisfaction were associated with lower levels RSA reactivity to a stressor and better recovery from a stressor. Alternatively, persons with lower job satisfaction reacted more strongly to the stressor and recovered less completely. As noted in the Introduction, job satisfaction has been associated with mental and physical health using self-report measures. We thus predicted that job satisfaction would be associated with a healthier RSA response to stress. The finding of a relationship between job satisfaction and RSA reactivity results suggests that one mechanism through which job satisfaction may be linked to adverse health outcomes is through impaired parasympathetic functioning. This is consistent with the Neurovisceral Integration

Model (Thayer & Lane, 2000), which states that parasympathetic functioning indexed by RSA provides an individual with a better ability to function, both psychologically and physiologically, in a complex environment (Jarczok et al., 2013). Furthermore, according to the Polyvagal Theory forwarded by Porges (2007), higher levels of RSA reactivity would indicate the presence of poorer parasympathetic “braking.” Poorer parasympathetic braking, in turn, would cause a person to experience both higher and more prolonged cardiovascular reactivity to daily stressors. As outlined by the recurrent cardiovascular reactivity hypotheses (Chida & Steptoe, 2010; Schuler & O’Brien, 1997), this pattern of higher RSA reactivity and incomplete recovery could lead to the development of both adverse mental and physical health outcomes over time. According to this model, when a person generates higher levels of cardiovascular reactivity to daily stressors and/or experiences delayed recovery from these stressors, there is an accumulation of adverse physiological impact that promotes the development of atherosclerosis, hypertension, and cardiovascular disease.

There are three limitations that merit discussion. First, the sample size was small which limited our power to reject the null hypothesis with some of the follow-up pairwise comparisons which had Bonferroni adjusted alpha levels. Second, respiration was not measured or controlled for in the analyses. Thus, it is possible that the observed RSA effects stemmed not from variation in parasympathetic activation, but alteration in rates of breathing among the low JDI group relative to the high JDI group. Third, the measures were collected at a single point in time. Thus, it is not possible to rule out a reversed causal account for these findings. For example, it is possible that persons with higher levels of RSA were more able to tolerate work stress and/or view their work as more satisfying. Similarly, at a methodological level, completing questionnaires assessing job satisfaction could have primed persons with lower job satisfaction to generate more distressing thoughts during the worry induction. However, the thought sampling data indicated that participants rarely reported worrisome thoughts during the baseline period suggesting that this effect, if present, was modest. Further research controlling for respiration effects (e.g., instructing that participants do paced breathing or collect respiration measurement and use as a covariate), reactivity of measurement, using larger samples, and longitudinal designs would be beneficial in this research arena.

Regardless of the causal direction (i.e., job satisfaction > RSA or RSA > job satisfaction) the current findings are important because it is one of a very few published demonstrations of a reliable link between job satisfaction, physiological reactivity to stress, and risk for disease. As such, it is reasonable to argue, as did Faragher et al. (2005) that work

characteristics associated with, and/or work interventions targeting improvement of, job satisfaction can exert important salutatory effects on worker health and resilience.

Ethics and Disclosure Statements All participants of the study provided written informed consent and the study was approved by the Ethics Committee at Bowling Green State University.

All authors disclose no actual or potential conflicts of interest including any financial, personal, or other relationships with other people or organizations that could inappropriately influence (bias) their work.

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Received May 16, 2016 Accepted April 7, 2017 Published online November 21, 2017

William H. O’Brien Department of Psychology Bowling Green State University Bowling Green, OH 43403 USA wobrien@bgsu.edu