Introduction

In many ways, clergy and religious leaders (e.g., pastors, ministers) are an ignored yet high-risk population (Birk et al. 2001). In their efforts to ensure the spiritual well-being of their congregations, clergy frequently neglect their own well-being. This results in frequent stress, burnout, and other health-related impairments for members of this population (Halbesleben and Buckley 2004). This is bad enough, but the consequences of this lack of self-care can also extend to the families and congregations of clergy. Church members typically seek help from clergy to cope with the loss of loved ones, life crises, and other general life stressors.

A clergy member unable to cope with these same challenges in his or her own life may be ineffective at helping church members to cope with their stress. For this reason, Cunningham (2014) noted that the stress and well-being of clergy are psychological health and well-being issues that can inherently trigger negative ripple effects on the health and well-being of entire communities of religious and spiritual believers and practitioners. An implication of this is that to improve the health and well-being of clergy is potentially to indirectly improve the health and well-being of the vast numbers of people who are served or assisted in some way by clergy.

Recent theory and measure development efforts in this research space have led to several studies of specific occupational hazards or challenges faced by clergy. These challenges include managing high job demands, congregational criticism, lack of congregational support, and isolation (Frenk et al. 2013); achieving restoration following moral failures (e.g., alcohol abuse, adultery; Sutton and Jordan 2013); and resolving conflict among congregation members (Proeschold-Bell et al. 2014). Proeschold-Bell et al. (2011) proposed a holistic model of clergy health functioning, which includes specific occupational challenges and their detrimental effects on clergy health.

Unfortunately, the constructs in the Proeschold-Bell et al. (2011) model are more theoretical than operational. While such a model is useful for conceptualizing the factors that influence clergy health, it cannot be directly and comprehensively tested in an empirical way. Therefore, this model is of limited use for moving forward our understanding of the specific effects of occupational demands, and personal and job-related resources on the health of clergy. An operational model of clergy physical self-care is still needed to empirically test these effects. The purpose of the present study, therefore, was to develop and test such a model. The ultimate goal of this research is to offer a model and methodological approach that can help to better identify and address the health and well-being needs of clergy. The ultimate hope is that such work might lead to interventions that can help clergy to thrive in their roles to the betterment of their families and congregations. In the following subsections of this introduction, we outline our theoretical orientation for this work, review clergy job demands, and propose specific work-related and nonwork-related resources clergy may possess, culminating in our proposed conceptual model.

Theoretical Orientation

Two common models of job-related stress processes help to explain how job demands may be negatively associated with worker health and well-being. First, is the job demand-control-support (DCS) model proposed by Johnson and Hall (1988). This model was an expansion of the original job demand-control (DC) model work by Karasek (1979), which outlined how the combination of job demands and job control can predict a broad range of health and behavioral outcomes related to one’s work. Johnson and Hall noted that work-related social support buffers the impact of demands and control on outcome variables. An important nuance of this model, however, is the finding that those in occupations high in job demands and job control (i.e., active jobs), but low in work-related social support, suffer from elevated prevalence rates of job strain. Thus, Johnson and Hall theorized that “high levels of control may accentuate rather than reduce the impact of demands” (p. 1341).

Second, Bakker and Demerouti (2007), in the job demands-resources (JD-R) model, expanded further the theoretical reach of the DCS model to include all relevant job resources. According to the JD-R model, job control is one of several job-related resources (e.g., social support, technology, time) employees use to meet their job demands. This concept of resources is an extension of conservation of resources (COR) theory, which also recognizes the key role job control can play as a moderator between job demands and well-being (Hobfoll 1989). Bakker and Demerouti suggested that, while every occupation has its own unique set of risk factors associated with job strain, all these factors may be classified as either job demands or job resources, making the JD-R model appropriate to apply to any occupation.

Clergy often face consistently high levels of job-related demands. For example, clergy generally set and maintain high, often unrealistic expectations for themselves (e.g., constant availability, long work hours). These expectations are often enforced and sometimes enhanced by church members who expect their clergy to be constantly available (Birk et al. 2001), even to the point of discouraging clergy from taking vacations (Proeschold-Bell et al. 2011). As noted by Hill et al. (2003), clergy and their families often struggle with stress and strain associated with challenges of managing work and nonwork role demands and boundaries.

The demands of the clergy role persist beyond church facilities and clergy are often held to a higher standard than others and closely monitored by congregation members and the general community wherever they might be (Lee and Balswick 2006). In many respects, clergy members’ nonwork life and morality are important parts of their jobs from which they are never able to detach. As a common biblical standard for church leadership, a clergy member must “manage his own household competently and have his children under control with all dignity,” for, “If anyone does not know how to manage his own household, how will he take care of God’s church?” (1 Timothy 3:4–5, Christian Standard Bible).

Despite typically not having formal and comprehensive mental healthcare education, clergy often face similar job demands to those experienced by mental health professionals, including counseling individuals with severe mental illness and substance abuse (Young et al. 2003). Accordingly, Holaday et al. (2001) noted that clergy experience a similar level of stress to other mental health professionals. Indeed, counseling can take a physical and emotional toll on clergy and clergy who counsel trauma victims often experience a secondary cognitive and behavioral impact from the trauma (Hendron et al. 2012, 2014). Additionally, many clergy provide services in difficult situations involving crisis intervention and abuse, situations that can lead to high levels of clergy stress (Bledsoe et al. 2013). Moreover, clergy may be increasingly encountering these issues as some communities are seeing the transfer of psychiatric care to be primarily the concern of faith-based organizations, such as churches and church-supported non-profit organizations (Leavey et al. 2007).

These chronic and resource-intensive job-related demands impact clergy in many ways. These demands are compounded by the fact that clergy often suffer from high levels of job insecurity. Tanner et al. (2012) estimated that 28% of clergy in the USA will experience an involuntary termination at least once during their career. Because the work of clergy is highly relational and deeply personal, involuntary terminations in this occupation are uniquely devastating experiences that may lead clergy members and their families (if applicable) to relocate and completely “start over” in building relationships and a church community (Tanner 2015, 2016).

The consistently high levels of job demands and low levels of job security so common for clergy can lead to negative effects on clergy physical health, mental health, and spiritual well-being. Despite coverage of physical self-care in clergy education programs (Bopp and Baruth 2017), clergy suffer from disproportionately high chronic disease rates compared to the lay population (Proeschold-Bell and LeGrand 2010; Webb and Bopp 2017). As previously noted, due to the nature of their work, clergy frequently experience stressful situations (Proeschold-Bell et al. 2015). Ellison et al. (2010) suggested that the stressful life events clergy encounter may erode mental health by fostering an elevated sense of spiritual struggle (i.e., troubled relations with God, chronic religious doubts, negative interactions with congregation members). Based on this preceding background, we expected that:

H1

Clergy job demands are negatively correlated with clergy well-being, operationalized as general health perception, physical health, mental health, spiritual well-being, and quality of life.

Helpful Conditioning Factors: Job and Personal Resources

Despite the potentially detrimental effects high job demands can have on clergy health and well-being, a number of job-related and personal resources may moderate and buffer these effects, to the benefit of clergy. Please note that we use the word “condition” throughout this manuscript, where appropriate, as an inclusive term to describe variables that might moderate, mediate, or otherwise influence a relationship between two or more other variables (cf., Hayes 2018).

Job Resources

Job resources include physical, psychological, social, or organizational aspects of the job that may help employees achieve work goals; reduce job demands and their subsequent costs; and stimulate personal growth, learning, and development (Bakker and Demerouti 2007). For clergy, particularly pertinent and valuable job resources may include job control and work-related social support.

Job Control

Karasek and Theorell (1990) defined job control, or decision latitude, as the combination of skill discretion and decision authority. Skill discretion refers to the variety of job-related skills an employee can exercise and the learning of new skills, and decision authority refers to having control over meaningful job-related decisions. Job control may serve an important role in buffering the impact of high job demands on well-being. For example, Van Yperen and Hagedoorn (2003) found in their sample of nurses that job control in particular reduced fatigue in highly demanding jobs. Though clergy often feel pressured to meet the demands of church members and denominational leadership, there is evidence from at least one study that job control among clergy may be fairly high. Specifically, Sonnentag et al. (2010) found that their sample of Protestant clergy rated their amount of job control as high. This may be because most clergy have a relatively high degree of control over the day-to-day operations of their job, even when the broader direction of a clergy’s church is influenced by church members and denominational leadership.

Work-Related Social Support

While likely not always the case, clergy may often view church members, fellow clergy, other church staff, and denominational leadership less as demands and more as valuable job resources in their own right. For clergy, work-related social support (i.e., relying on and asking others for help) from members of their congregation, denominational leaders, and fellow clergy may serve as an important buffering resource that conditions the relationship between job demands and well-being. Proeschold-Bell et al. (2015) found that congregation support was significantly and positively related to mental health in their sample of United Methodist clergy in North Carolina. Similarly, Wells (2013) analyzed data from a nationwide sample of clergy and noted that support from both the congregation and the denomination moderates or lessens the negative effects of stress on clergy health.

Interestingly, Proeschold-Bell et al. (2011) noted that clergy may lack social support in certain congregations or choose not to discuss their personal lives with congregants and denominational leaders for fear of being seen as spiritually inadequate to fulfill their clergy role. That work-related social support may be absent for clergy is disturbing and concerning, especially given that the moderating effect of high job control on the relationship between high job demands and well-being may depend on the presence of work-related social support (Johnson and Hall 1988).

The evidence for this job demand × job control × work-related social support is a bit mixed and may depend on specific occupation, as identified by Häusser et al. (2010). That said, the occupation of clergy presents a situation in which we would expect these three factors to influence and support each other. Though clergy may generally perceive high levels of job control, it could be that this job resource is only useful when clergy also perceive that they have the work-related social support from church members and denominational leadership to exercise skill discretion and decision authority. In other words, though clergy work-related social support and job control individually may moderate the relationship between job demands and well-being, the strength of job control’s moderation effect may also be affected by work-related social support. This being the case, we expected that:

H2

Clergy work-related social support moderates the relationship between job demands and clergy mental health, such that clergy with higher levels of work-related social support experience less of a detrimental effect on their mental health from a high level of job demands.

H3

Clergy job control moderates the relationship between job demands and clergy mental health, such that clergy with higher levels of job control experience less of a detrimental effect on their mental health from a high level of job demands.

H4

Clergy work-related social support moderates the moderating relationship of clergy job control to job demands and clergy mental health, such that job control’s moderating effect is strongest in the presence of high levels of work-related social support.

Personal Resources

Personal resources can be thought of as aspects of the self that are typically linked to resiliency (Hobfoll et al. 2003). More specifically, Hobfoll (1989) defined resources as “those objects, personal characteristics, conditions, or energies that are valued by the individual or that serve as a means for attainment of these objects, personal characteristics, conditions, or energies” (p. 516). For clergy, relevant literature suggests that particularly important personal resources may include nonwork-related social support, and the ongoing and holistic self-care practices (including spiritual and physical elements).

Nonwork-Related Social Support

Clergy may receive social support (i.e., availability of help) from family and friends outside of their work-related constituents. Galek et al. (2011) found that social support, which they conceptualized to include work-related social support and support from friends and family, was negatively related to burnout and secondary traumatic stress in their sample of professional chaplains. Alternatively, Blanton and Morris (1999) found that stressors associated with a lack of social support, which they operationalized as the quantity and availability of friendships in a clergy’s or clergy spouse’s social context, were the strongest predictors of physical symptomatology and emotional well-being. Based on these findings and the general theory shared in the previous subsection regarding the role of social support, we expected that:

H5

Clergy nonwork-related social support moderates the relationship between job demands and clergy mental health, such that clergy with higher levels of nonwork-related social support experience less of a detrimental effect on their mental health from a high level of job demands.

Holistic Health Practices

Two types of holistic health practices, spiritual self-care practices and physical self-care practices, may serve as important moderators between job demands and well-being.

Spiritual Self-care Practices

Spiritual self-care practices, or the extent to which a clergy member engages in ongoing personal spiritual development, may be a form of behavioral resource or routine particularly relevant to the well-being of clergy (Bickerton et al. 2015). Spiritual self-care for Christian clergy is conceptualized as experiences in which one looks to God for renewal and recovery apart from one’s job duties. Hence, spiritual self-care may include prayer, listening to seminars or lessons from other speakers, or reading Scripture without the intention of preparing for a job-specific task, such as writing a sermon. Meisenhelder and Chandler (2001) found that, despite a lack of variation in both health and prayer in their sample of Presbyterian (USA) clergy, high frequency of prayer (an example of spiritual self-care) was significantly related to higher scores in vitality, general health, and mental health. Bickerton et al. (2015) surveyed clergy and found that spiritual resources positively predicted future work engagement, which then predicted reduced turnover intention. Extending from this background, we expected that:

H6

Clergy spiritual self-care practices moderate the relationship between job demands and clergy well-being, such that clergy who more frequently engage in spiritual self-care practices experience less of a detrimental effect on their well-being from a high level of job demands.

Physical Self-care Practices

Physical self-care practices, another form of behavioral resource or routine, may also serve as an important moderator between job demands and well-being. For example, Ferguson et al. (2015) found that American clergy who take a day off each week or are involved in a support group with other clergy are less likely to suffer from obesity. Additionally, United Methodist clergy in North Carolina reported spending time with God and taking a day off each week as important self-care practices (Proeschold-Bell et al. 2011). Other examples of physical self-care practices for clergy may include diet, weight control, exercise, and avoiding alcohol. Although the evidence base pertaining to this form of resource-building routine is relatively thin for our target population, the linkage to existing recovery and resource theories is clear (Hobfoll 1989). Based on all of this material considered together, we expected that:

H7

Clergy physical self-care practices moderate the relationship between job demands and clergy well-being, such that clergy who more frequently engage in physical self-care practices experience less of a detrimental effect on their well-being from a high level of job demands.

Our entire proposed conceptual model can be found in Fig. 1.

Fig. 1
figure 1

Theoretical model of proposed hypotheses

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Pertinent Covariates

As the purpose of the present study was to develop and test a model that ultimately may support the development of practical interventions for high-risk clergy, several demographic and environmental factors also needed to be considered. Such factors are likely to be extremely difficult or even impossible to change within this population. Including these factors as covariates in our analyses makes it possible to account for variance linked to these factors that is unlikely to be otherwise controlled or influenced through targeted intervention. This makes it possible to then focus more realistically on that which can be understood and potentially modified. The hypotheses stated in the previous subsections were, therefore, tested over and above the influence of the following demographic and environmental factors.

Demographic Factors

Many demographic differences have been shown to influence perceptions of work-related stress and personal health and well-being. Within the present sample, it was identified through preliminary analysis that age and gender were moderately to strongly associated with several of the core study variables. This is consistent with other research in this population (Ferguson et al. 2015; Wells 2013), so these two demographic variables were included as covariates in all analyses.

Environmental Factors

Differences in geographical location may impact the job demands placed on clergy, though existing empirical support for this possibility is inconclusive. Lewis et al. (2007), in reviewing clergy burnout studies, consistently found a high level of work-related burnout among samples of clergy, regardless of their religious denomination or country location. However, differences in regional location can relate to differences in income as well as prevalence of obesity and joint disease, and this may explain why Miles et al. (2011) found that physical health-related quality of life was significantly lower for rural clergy than for non-rural clergy. Hence, geographical location was included as a covariate in all analyses. Also, because differences in location may not represent differences in the broader community prevalence of the clergy’s denomination, prevalence of participants’ own denomination in the broader community was also controlled for.

Method

Participants and Procedure

As noted by Proeschold-Bell et al. (2011), interventions aimed at improving occupational health and well-being should take into consideration the beliefs and practices of the specific occupational group in question. For this reason, we focused this initial test of our clergy health model to Christian clergy. Specifically, the inclusion criteria was adherence to the basic Christian doctrines as stated in the Apostles’ Creed, one of the oldest and most universal statements of beliefs in the Christian tradition. This criterion is consistent with the traditional view of Christianity (Beck and Haugen 2013). Other inclusion criteria were that clergy had to be employed, either part-time or full-time, and compensated by a specific congregation or congregations, and associated with a specific denomination. Lay clergy and other individuals who responded, but did not fully meet these criteria were excluded from the data analyzed and reported here.

All procedures for this study were approved by the authors’ university Institutional Review Board (IRB). Data for this study were gathered from a targeted convenience sample. Potential participants were identified and contacted through email lists from denominational administrative offices and religious institutions. Additionally, participants were contacted through direct and indirect personal appeal through professional social networking groups (e.g., a private Facebook group). In these communications, participants were asked to send the survey to any other clergy they knew. A web-based, structured survey was administered to participants through the Qualtrics internet-survey system. As incentive to respond to the survey, participants had the opportunity to enter their email address into a drawing for one of 15, $50 Amazon.com gift cards (participation was not required to enter the drawing). These email addresses were separated from the survey data upon export from the Qualtrics system and kept separate from the survey data to facilitate confidential management of the data gathered for the actual study purposes.

A total of 546 participants at least partially responded to the survey. After filtering out any respondents who did not fully meet the inclusion rules, removing respondents who completed less than 50% of the survey, and excluding respondents who did not provide critical demographic information needed to establish whether inclusion criteria were met, the final sample for analysis included 418 mostly complete survey records. All reported statistics past this point are based on this final sample.

Respondents ranged in age from 21 to 84 years (M = 53.19, SD= 12.96). Male respondents constituted 71.5% of the sample. A majority of respondents identified their race as White (91.1%), followed by Black (5%), Asian (1.2%), Middle Eastern (1.2%), Multiracial (0.7%), and Hispanic (0.5%). A majority of respondents reported their highest level of completed education to be a Master’s degree (61.5%), followed by Doctoral degree (23%), some graduate school (5.5%), Bachelor’s degree (4.8%), Associate’s degree (1.2%), some college/university (3.3%), and high school diploma (0.7%). Religious denomination was identified for respondents’ personal and institutional affiliations. For personal denomination, most participants identified as United Methodist (79.7%), followed by Southern Baptist (14.6%), Catholic (1.4%), Presbyterian (PCA; 0.5%), Episcopalian (0.5%), Pentecostal (0.5%), Lutheran (0.2%), and Anglican (0.2%). For institutional denomination, most participants identified as United Methodist (80.6%), followed by Southern Baptist (14.1%), Catholic (1.4%), Presbyterian (PCA; 0.5%), Episcopal (0.5%), Lutheran (0.5%), Pentecostal (0.2%), and Anglican (0.2%). Participants reported their geographical location to be rural (40.7%), suburban (39%), or urban (20.3%). The vast majority of participants’ job titles included the term “pastor” (72.9%) or “minister” (24.4%). Respondents had worked in their current positions for an average of 5.58 years (SD= 6.54) and averaged 20.54 total years working in ministry (SD= 13.87). Participants had an average of 4.39 other clergy and workers on-staff at their church to help with their work-related duties (SD= 7.66).

Measures

The survey distributed to participants included the following measures, as ordered here.

Symptoms of Physical Health Problems

Symptoms of physical health problems were assessed using the 13-item Physical Symptoms Inventory (PSI; Spector and Jex 1998). Participants responded by indicating the frequency with which they have experienced various physical symptoms (e.g., backache, eye strain) over the past month on a five-point scale from not at all (1) to every day (5). Scores on this measure are totaled so that a score of 65 indicates the lowest health functioning and a score of 0 indicates the highest health functioning. Because the PSI is a causal indicator scale, internal consistency reliability cannot be properly established (Spector and Jex 1998). In the present study, PSI scores correlated significantly with general health perception (− 0.40), symptoms of mental health problems (0.46), and quality of life (− 0.51). As a second indicator of this construct, participants rated their overall perception of personal health relative to others their same age and in their same occupation (i.e., the general health perception mentioned in the previous sentence). Proeschold-Bell and LeGrand (2012) found that their sample of United Methodist clergy reported significantly better physical health scores compared to individuals of their same age and gender, despite suffering from an above average prevalence of disease. Our interest was in how clergy viewed their health compared to their age- and occupation-matched peers. Similar single item self-assessments have been frequently used in previous research (e.g., Haddock et al. 2006). Scores from this single item, ranging from 5 = excellent health to 1 = poor health, were analyzed separately from physical health scores on the PSI.

Symptoms of Mental Health Problems

Symptoms of mental health problems were assessed using the 12-item General Health Questionnaire (GHQ-12; Gao et al. 2004; current study α = 0.87). This measure includes items assessing perceptions of mental health functioning over the past few weeks. The GHQ-12 uses a four-point scale (from 0 to 3), and scores from individual items are combined to generate a total score ranging from 0 to 36, with higher scores indicating worse conditions.

Spiritual Well-Being

Spiritual well-being was assessed using the Clergy Spiritual Well-being Scale’s power and presence of God in daily life subscale (Proeschold-Bell et al. 2014; current study α = 0.88). This Clergy Spiritual Well-being Scale is a measure of closeness to God among Christian clergy. The power and presence of God in daily life subscale consists of six items, each of which assesses how frequently a respondent has encountered the power and presence of God in daily life during the past 6 months. Each item is rated on a five-point scale from never to always, and individual item scores are combined so that higher scores indicate higher levels of spiritual well-being and lower scores indicate lower levels of spiritual well-being. Total scores on this measure can range from 6 to 30.

Quality of Life

Quality of life (QoL) was assessed using the Psychological General Well-being Index short version (PGWB-S; Grossi et al. 2006; current study α = 0.86). PGWB-S items assess participants’ emotions during the past month (e.g., nervousness, vitality). Participants respond to items on a five-point scale, and individual item scores are totaled so that higher scores indicate higher levels of QoL and lower scores indicate lower levels of QoL. Total scores on this measure can range from 0 to 30.

Physical Self-care Practices

Physical self-care practices were assessed using five items from the Survey (2013) and one item from Proeschold-Bell et al. (2015). The five items from the U.S. Congregational Life Survey ask about hours spent in different activities (e.g., time with family, physical exercise) within the past 7 days. Instructions were adapted slightly to ask about time spent fully engaged in activities. The item from Proeschold-Bell et al. asked about the number of vacation days taken in the last 12 months, excluding holidays, intentional Sabbaths, and weekend days. The five items from the U.S. Congregational Life Survey were combined into a total number of hours spent in physical self-care activities. The item from Proeschold-Bell et al. was considered in analyses as a separate, single indicator. Because the items from both of these sources are causal indicator items, reliability cannot be properly established with an internal consistency reliability coefficient. In the present study, however, significant correlations were found between physical self-care practices (i.e., the five items from the U.S. Congregational Life Survey) and symptoms of mental health problems (− 0.12), spiritual well-being (0.20), and spiritual self-care (0.39).

Spiritual Self-care Practices

Spiritual self-care practices were assessed using three items from the U.S. Congregational Life Survey (2013). The instructions for these items were modified slightly to ask about hours spent fully engaged in prayer, Scripture reading and study, and other spiritual activities and/or traditions not for work purposes within the past 7 days. These three items were combined into a total number of hours spent in spiritual self-care practices. Because the items from both of these sources are causal indicator items, reliability cannot be properly established with an internal consistency reliability coefficient. In the present study, however, a significant correlation was found between spiritual self-care practices and spiritual well-being (0.38).

Job Demands

Two different measures were used to assess job demands. The Quantitative Workload Inventory (QWI; Spector and Jex 1998; current study α = 0.86) was used to assess job demands from a general perspective, as the items of this scale measure the frequency with which participants experience heavy workloads (e.g., working very fast, little time to get things done). Responses are made on a five-point scale of frequency, ranging from less than once per month or never to several times per day. Scores on this measure can range from 5 to 25, with higher scores indicating higher workloads.

As a more context-specific measure of job demands, the Clergy Occupational Distress Index (CODI; Frenk et al. 2013; current study α = 0.82) was also administered. The CODI measures the frequency with which clergy have experienced occupational distress over the past year. This measure includes five questions about perceptions of the work environment (i.e., congregational demands, congregational criticism, and feelings of isolation and loneliness at work), as well as perceptions of the impact of the workplace environment (i.e., critical congregation members and congregational challenges) on level of stress. These five items are assessed on a four-point scale ranging from never to very often. Scores on this measure can range from 5 to 20, with higher overall total scores indicating higher levels of clergy job demands.

Nonwork-Related Social Support

Nonwork-related social support was assessed using the Medical Outcomes Study Social Support Survey (mMOS-SS; Moser et al. 2012; current study α = 0.95). The mMOS-SS contains eight items asking participants about the availability of someone to take care of them if they needed it (e.g., confined to bed, unable to prepare meals). The instructions for this measure were modified for the present study to focus responses on availability of support outside of work. Participants respond on a five-point scale, from 1 (none of the time) to 5 (all of the time). Overall total scores can range from 8 to 40, with higher scores indicating higher levels of available nonwork-related social support.

Job Control

Job control was assessed using the Job Control Scale (current study α = 0.93), which was initially developed and validated by Van Veldhoven (1996), and further validated by Van Yperen and Hagedoorn (2003). This measure includes 11 items referring to timing control and method control over work. Participants respond to items on a four-point scale, from 1 (never) to 4 (always), and individual item scores are totaled so that higher scores indicate higher levels of job control. Scores on this measure can range from 11 to 44.

Work-Related Social Support

Work-related social support was assessed using an adapted version of the Job Social Support Scale (Van Yperen and Hagedoorn 2003; current study α = 0.81). The original measure consisted of four items addressing perceived support from participants’ immediate supervisors (two items) and co-workers (two items). These items were also adapted and repeated for the present research to assess perceived support from participant’s denominational leadership and congregation, bringing the total number of items in this measure to eight. For all items, “not applicable” was an option for participants who came from nondenominational churches or for clergy who did not have co-workers or an immediate supervisor. Participants responded on a four-point scale, and individual item scores were totaled so that higher scores indicated higher levels of work-related social support. Scores on this modified measure could range from 0 to 32.

Demographics

The following demographic information was gathered to fully understand and report on the sample: age, sex, race/ethnicity, highest level of completed education, denomination, job title, number of clergy or other staff at current church who help manage work-related responsibilities, congregation size (overall), total years working at current church, total years working in ministry, church location (rural, suburban, or urban), and prevalence of religious denomination in the broader community in which the clergy worked.

Results

The hypotheses for this study were tested using a combination of correlational and regression-based techniques in SPSS (v23). Where appropriate, the PROCESS macro tools (v3) developed by Hayes (2018) were also used. Note that all effects reported from the PROCESS analyses in this section are over and above the impact of the demographic and environmental covariates identified in the previous section. Descriptive statistics for all study variables are found in Table 1 (full table of bivariate correlations available upon request).

Table 1 Descriptive statistics for all study variables
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Hypothesis 1 was that clergy job demands are negatively correlated with clergy well-being. Well-being was more strongly correlated with perceived occupation-specific job demands than perceived general job demands. Given this and the general understanding that context-specific measures are likely to provide the most appropriate operationalizations of hypothesized constructs and their relationships in a particular occupation than non-contextualized measures, the remainder of the analyses focused on the occupation-specific measure of job demands.

With respect to this first hypothesis, perceived occupation-specific job demands were significantly correlated with all five indicators of well-being considered in this study: general health perception (− 0.32), symptoms of physical health problems (0.36), symptoms of mental health problems (0.44), spiritual well-being (− 0.26), and quality of life (− 0.52). These findings support Hypothesis 1.

Hypothesis 2 was that work-related social support moderates the relationship between job demands and mental health, such that clergy with higher levels of work-related social support experience a less negative relationship between perceived job demands and mental health. From the PROCESS results summarized in Table 2, this hypothesis was not supported, though the observed effect showed a trend toward significance (b = 0.1366, p = 0.0964).

Table 2 Output for Hypotheses 2–4 regarding mental health
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Hypothesis 3 was that job control moderates the relationship between job demands and mental health, such that clergy with higher levels of job control experience a less negative relationship between perceived job demands and mental health. This hypothesis was supported (b = 0.0938, p = 0.0167), in that the negative impact of perceived job demands on mental health was weaker for clergy with higher levels of job control.

Hypothesis 4 was an extension of Hypothesis 3, in which work-related social support was expected to moderate the moderating effect of perceived job control on the relationship between perceived job demands and mental health. The nature of this hypothesized effect was such that job control’s moderating effect was expected to be strongest in the presence of high levels of work-related social support. This hypothesis was also supported (b = − 0.0042, p = 0.0441). As illustrated in Figs. 2, 3 and 4 (which illustrate the complex effects observed in our tests of H3 and H4), the nature of this moderated moderation was that job control’s moderating effect was strongest in the presence of high perceived job demands and high work-related social support.

Fig. 2
figure 2

Relationship between job demands and symptoms of mental health problems, moderated by job control—shown for individuals low in work-related social support effects of job control and job demands on symptoms of mental health problems among individuals low in work-related social support

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Fig. 3
figure 3

Relationship between job demands and symptoms of mental health problems, moderated by job control—shown for individuals moderate in work-related social support

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Fig. 4
figure 4

Relationship between job demands and symptoms of mental health problems, moderated by job control—shown for individuals high in work-related social support

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Hypothesis 5 was that nonwork-related social support moderates the relationship between perceived job demands and mental health. The nature of this hypothesized effect was such that clergy with higher levels of nonwork-related social support were expected to experience a weaker negative effect of job demands on their mental health. This hypothesis was not supported (tables available upon request), though the observed effect showed a trend toward significance (b = 0.0150, p = 0.0590).

Hypothesis 6 was that spiritual self-care practices moderate the relationship between perceived job demands and well-being, such that clergy who more frequently engage in spiritual self-care practices experience less of a detrimental effect on their well-being from a high level of perceived job demands. This hypothesis was not supported for any of the well-being indicators, though for quality of life (b = 0.0064, p = 0.0740) this hypothesized moderation effect showed a trend toward significance.

Hypothesis 7 was that physical self-care practices moderate the relationship between perceived job demands and well-being, such that clergy who more frequently engage in physical self-care practices experience less of a detrimental effect on their well-being from a high level of perceived job demands. This hypothesis was not supported for any of the five outcome variables. It is important to note, however, that the negative effect of job demands on general health perceptions was different depending on number of vacation days taken. Specifically, the taking of more vacation days buffered the effects of low to moderate levels of job demands, but not high job demands (b = − 0.0032, p = 0.0030). Overall, though, this hypothesis was not clearly supported.

Discussion

The purpose of the present study was to offer and test a model and methodological approach that can be useful to those interested in better identifying and addressing the health and well-being needs of clergy. This population is in need of attention from occupational health professionals, given that when clergy thrive, so do their families, congregations, and communities. As discussed in this section, many of our hypothesized relationships between resources and outcomes emerged, providing support for the buffering effects of these resources on the relationship between perceived job demands and well-being.

The present study builds on previous related research by identifying factors that influence clergy well-being, especially mental health. Along these lines, the results from the present study support the demands-control-support model (Johnson and Hall 1988). Specifically, our findings pertaining to Hypotheses 2 through 4 showed significant effects for job control, and the interaction of job control and work-related social support, but not for work-related social support when predicting mental health.

Job control and work-related social support were also tested as single moderators in separate models. In these follow-up analyses, significant moderation for work-related social support was observed (b = − 0.0265, p = 0.0152; see Fig. 5), but not for job control (p = 0.7443).

Fig. 5
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Relationship between job demands and symptoms of mental health problems, moderated by work-related social support

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The overall implication of these findings, in line with the demands-control-support model (Johnson and Hall 1988), is that job control appears to only be a health-enhancing job resource in the presence of moderate to high levels of work-related social support. In other words, this finding suggests that clergy need work-related social support before they are most able to benefit from job control. An implication here is that clergy mental health may be improved by (a) increasing available work-related social support and (b) helping clergy identify and exercise control over their work when possible. Practically, this work-related social support could come from congregation members, denominational leadership, and other church staff members. This support could range from asking clergy about their personal lives to seeing if the clergy need any help with their work-related tasks (e.g., advice, mentoring, or help prioritizing).

In general, our findings corroborate the propositions outlined in our proposed framework and align with previous research that has highlighted the negative relationship between perceived job demands and well-being. That said, the present findings expand on previous research by identifying spiritual well-being as an important outcome that may be impacted by job-related demands (r = − 0.26). Specifically, this expands on findings by Ellison et al. (2010) that spiritual struggle partially mediates the negative relationship between the stressful life events clergy frequently encounter and their mental health. With support from the present findings, we propose that spiritual well-being may be an important well-being outcome in its own right. While the present findings support this proposition for clergy, future research should also consider spiritual well-being as a meaningful outcome for study in the more general (i.e., non-clergy) population. As Miller and Ewest (2015) noted, employees increasingly want to integrate their whole lives, including the integration of their faith if applicable, with their work. By considering spiritual well-being as a meaningful outcome for study, researchers will be able to view employees’ health and identities holistically.

The present findings also underscore the value of contextualized or occupation-specific measures, given the stronger correlations that were observed between the occupation-specific measure of perceived job demands than the general measure of perceived job demands (Proeschold-Bell et al. 2014). According to the matching hypothesis, specific stressors and specific resources should ideally match to show moderating effects in the prediction of strain (Cohen and Wills 1985; de Jonge and Dormann 2006). This hypothesis is supported by the present findings in that available resources (e.g., work-related social support) for clergy corresponded to existing stressors (e.g., emotionally taxing job duties) to mitigate the negative effects of those stressors on mental health. Taken together, these findings suggest that future research should include occupation-specific measures to zone in on resources which might be especially efficacious for mitigating the negative effects of stressors on health and well-being outcomes.

Three hypothesized moderation effects tested in the present study showed a trend toward significance and likely would have reached significance had we achieved a higher level of statistical power for these analyses. Future researchers are encouraged to plan accordingly when designing studies to examine similar phenomena to these three rather small magnitude effects. Specifically, larger sample sizes are needed when examining these types of complex, yet small moderation effects. These three effects are as follows.

First, the hypothesized moderating effect of clergy nonwork-related social support on the relationship between perceived job demands and well-being showed a trend toward significance (b = 0.0150, p = 0.0590). As Fig. 6 illustrates, it appears that clergy nonwork-related social support may buffer the impact of high perceived job demands on mental health, but that this buffering effect is rather small in terms of magnitude and therefore did not reach statistical significance in our study.

Fig. 6
figure 6

Relationship between job demands and symptoms of mental health problems, moderated by nonwork-related social support

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Second, significant results were also not found for the hypothesized moderating effect of spiritual self-care practices. However, the moderating effect of spiritual self-care practices for quality of life showed a trend toward significance (b = 0.0064, p = 0.0740). Clergy spiritual self-care practices may buffer the impact of high perceived job demands on quality of life. It is also important to note that spiritual self-care practices did have a significant direct effect on spiritual well-being (b = 0.1181, p = 0.0073), indicating that these practices are important for clergy experiencing the presence and power of God in their daily lives.

Third, significant results were not found for the moderating effect of physical self-care practices. However, as Fig. 7 illustrates, vacation-taking (i.e., the single physical self-care item asking about the quantity of vacation days taken in the last 12 months) was found to significantly moderate the impact of perceived job demands on general health perception (b = − 0.0032, p = 0.0030). This suggests that clergy taking time away from work is an important factor to their general health perceptions. However, the mitigating effect of vacation-taking seems to disappear in the presence of high job demands. This suggests that clergy may be unable to detach from high job demands, even when they spend time away from work. By implication, giving clergy more time away from work may not improve their general health perceptions. Instead, those who want to help clergy should focus their attention on lightening clergy job demands. This could be done by distributing job-related tasks among congregation members, denominational leadership, and other church staff. With lowered job demands, clergy would be able to better use their vacation-taking to detach from work.

Fig. 7
figure 7

Relationship between job demands and general health perception, moderated by vacation-taking

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Limitations and Future Directions

There were several limitations to this study. First, the vast majority of participants in this study identified with the United Methodist denomination. This is likely because the current study used a convenience sample drawn without the ability to calculate a response rate and therefore it is not possible to know how generalizable the findings are to various Christian clergy groups. As Proeschold-Bell et al. (2011) noted, United Methodist clergy are reassigned to different churches every several years by denominational leadership. This can make United Methodist clergy hesitant to rely on denominational leadership for support with their congregation, out of fear that the leadership will not promote them to a larger congregation, or that the leadership will rule that the clergy member is unfit for ministry. In other words, United Methodist clergy may fear that asking for help from denominational leadership will have negative ramifications on their career (e.g., reassignment, demotion of placement). Hence, denominational leadership may be a particularly important source of support, without fear of unfitting retaliation, for United Methodist clergy. However, future research should examine whether this is just as true for clergy from other denominations.

Additionally, results were likely affected by the cross-sectional nature of our data for this study. For example, more objective measures of well-being outcomes might have resulted in significant findings for physical and spiritual self-care practices. In other words, our nonsignificant findings were likely due to our admittedly crude operationalizations of these constructs for this preliminary test of this model. Future research should consider the type of physical and spiritual self-care practices. Specific examples of physical self-care practices for clergy may include diet, weight control, exercise, and avoiding alcohol. Clergy may also participate in mental health treatment for themselves (e.g., counseling, treatment of depression/anxiety) to help combat the secondary cognitive and behavioral impact from counseling that they may experience (Hendron et al. 2012, 2014). Furthermore, the physical self-care and spiritual self-care items asked about time spent in these various activities. However, inferences could not be drawn from these data about the quality of time spent in these practices. Future studies should examine not only the quantity, but also the quality of self-care practices. Moreover, we are unable to draw causal conclusions due to the cross-sectional nature of our data for this study. Future studies should use more robust methods such as prospective longitudinal observational studies and experimental studies testing interventions. Such studies are needed before interventions can be widely implemented with confidence as evidence based.

Similarly, this study lacked measures for the number of hours clergy worked and expectations from congregants, making findings about high workload churches really about perceptions of workload only. This limits the study in that job demands could be perceived and not real. If the problem turned out to be one of perception, then a different set of implications for action would arise. For example, instead of receiving help from denominational leadership and other sources, clergy might be better off learning to reframe job demands as a set of work that is achievable (e.g., peace or strength may be obtained through God’s grace). Nonetheless, whether workload is objectively high or just perceived as high is irrelevant if an individual does not believe they can handle the workload. Hence, future studies should consider both objective measures of workload and perceptions of workload, as both may influence clergy well-being.

It is also important to note that we did not include reward-related constructs and measures in the present study. We are aware that Proeschold-Bell et al. (2013) found that rewards such as ministry satisfaction and lack of financial stress relate to mental health in clergy. The concept of rewards within ministry-related occupations is very tricky to define and work with, so for the present study we focused on more clearly defined and measured constructs. However, future researchers are encouraged to consider how intrinsic and extrinsic rewards might affect the relationships studied here and potentially influence clergy mental health.

All significant results from this study applied directly to a clergy’s work and not their lives outside of work. This makes sense, given that the present study examined interactions between job demands and potential job resources for clergy. As the significant correlations between clergy well-being outcomes and nonwork-related social support, physical self-care practices, and spiritual self-care practices suggest, these constructs are still relevant for studying clergy health and should be considered when developing holistic approaches to clergy well-being.

Implications

In addition to implications and future research directions already noted in this Discussion, the present methods and findings have the potential to guide those interested in better identifying and addressing the health and well-being needs of clergy so that they may thrive in their roles to the betterment of their families and congregations. Specifically, those interested in addressing clergy well-being needs should focus their attention on the environments in which clergy work. Work-related social support from the congregation, denominational leadership, supervisors, and co-workers should be the first priority of those who wish to help clergy. Job control should only become a priority after addressing work-related social support. In other words, the present study suggests that clergy need to have the support of those in their work environment to be able to best utilize job control.

Furthermore, the present study suggests that clergy with low to moderate workloads should take time off work for vacation days for better perceived general health. Future research should examine practices during vacation days which best help these clergy to recover from their work. The present findings suggest that the situation is trickier for clergy with high workload. More research and clever ideas are needed for this subpopulation, as they also need time to recover from work, but paradoxically, taking this time is more difficult and may negatively impact well-being if not managed well. Our findings regarding the role of support may help here for starters. Specifically, job control’s moderating effect was strongest in the presence of high perceived job demands and high work-related social support. Hence, we recommend that in high demand situations, building a network of support among administrative assistants, other clergy, and members of the congregation may make it more possible for high demand clergy to take a break and not feel the pain later. Additionally, future research should examine mental health outcomes for clergy family members, who often experience high levels of stress due to demanding responsibilities and hectic schedules (Hill et al. 2003), and what resources mitigate the detrimental effects of clergy job demands on their health and well-being. Such work will potentially improve not only the health and well-being of clergy, but also likely the health and well-being of the vast numbers of people who are served or assisted in some way by clergy.