Abstract
The primary goal of this study was to examine the relations from counselors’ character strengths to burnout via the potential mediating effect of meaningful work. We also compared mean levels of counselors’ character strengths to population means and conducted regression analyses to examine which character strengths uniquely predicted meaningful work and burnout. Counselors in our sample reported significantly higher levels on 13 of the 24 character strengths compared to a normed sample, with strengths like love of learning, perspective, and social intelligence being particularly elevated. Additionally, regression analyses revealed that prudence and hope predicted both meaningful work and burnout; love, perspective, and zest predicted meaningful work; and forgiveness, honesty, and self-regulation predicted burnout. These character strengths were included in the final structural equation model. Partially supporting hypotheses, prudence, perspective, and zest were related to meaningful work, which were, in turn, negatively related to burnout.
Within the field of counseling, a strengths-based focus is a means to prevent problems, promote human growth, and maximize human potential (Gelso, Nutt-Williams, & Fretz, 2014; Gelso & Woodhouse, 2003; Lopez, 2008; Magyar-Moe, Owens, & Conoley, 2015). As research in the area of positive psychology has grown, encouraging clients to identify, use, and develop their strengths has become a more widespread practice (e.g., Conoley, Padula, Payton, & Daniels, 1994; Scheel, Klentz Davis, & Henderson, 2012; Smith, 2006; Wong, 2006). However, scholars are yet to examine which strengths are most prominent in counselors and how the presence of their strengths impacts their experience of work. Identifying these strengths may hold promise in addressing unique problems counselors face, such as burnout.
Occupational burnout has been a long-standing concern for a variety of health-care workers (e.g., Ackerley, Burnell, Holder, & Kurdek, 1988; Lee, Lim, Yang, & Lee, 2011; Leiter & Harvie, 1996), with up to 67% of mental health professionals experiencing burnout during their career (Morse, Salyers, Rollins, Monroe-DeVita, & Pfahler, 2012). Given the detriments of burnout and the high frequency among people in the field of mental health, considerable research has examined what may buffer, prevent, or contribute to its presence (e.g., Iverson, Olekalns, & Erwin, 1998; Maslach, Schaufeli, & Leiter, 2001; Rupert & Morgan, 2005). However, only recently has research examined how positive psychological variables may help alleviate burnout. Emergent research suggests that strengths contribute to meaningful work in the general population (Littman-Ovadia, Lavy, & Boiman-Meshita, 2016) and that within specific occupations meaningful work is negatively related to burnout (Heyns, Venter, Esterhuyse, Barn, & Odendaal, 2003; Tei et al., 2014). Therefore, the purpose of this study was to examine the relation from counselors’ character strengths to burnout via the potential mediating effect of meaningful work.
Theoretical Framework
Character strengths
While there is not a fully agreed-upon conceptualization of strengths (e.g., Louis & Lopez, 2014), and scholars debate the philosophical underpinnings and appropriateness of strengths classifications and strengths-based approaches (e.g., Fowers, 2008; Kristjánsson, 2010), the VIA Classification of Strengths and its corresponding VIA-Inventory of Strengths (VIA-IS) have strong support in the literature (see Harzer, 2016; Littman-Ovadia & Niemiec, 2016). Within this framework, character strengths are trait-like, moral characteristics that enable people to be virtuous (Peterson & Seligman, 2004). Peterson and Seligman (2004) conducted an extensive classification of character strengths to create the VIA-IS, which included strengths that are intrinsically valuable, morally based, and cross-culturally representative (Peterson & Seligman, 2004). They identified 24 character strengths and organized them within six core virtues: wisdom, courage, humanity, justice, temperance, and transcendence (Peterson & Seligman, 2004). Evidence has generally supported this classification system, although character strengths are not always representative across cultures (e.g., Biswas-Diener, 2006; Shimai, Otake, Park, Peterson, & Seligman, 2006).
Typically, studies involving character strengths examine either the presence of strengths (i.e., strength identification, level, or endorsement) and their relation to other variables of interest or interventions in which participants are asked to use one or more of their top strengths for a designated amount of time (i.e., strengths use; e.g. Gander, Proyer, Ruch, & Wyss, 2012; Seligman, Steen, Park, & Peterson, 2005). The presence of strengths is related to a number of positive outcomes. For instance, strengths are related to life satisfaction and positive affect (Littman-Ovadia & Lavy, 2012; Park & Peterson, 2009), academic achievement (Park & Peterson, 2009), and both physical and mental health (Leontopoulou & Triliva, 2012). In the work domain, character strengths correlate with job satisfaction and adaptive coping (Harzer & Ruch, 2015; Littman-Ovadia & Steger, 2010), and they buffer the effect of work-related stress on job satisfaction (Harzer & Ruch, 2015). People who use their strengths also experience a variety of positive outcomes, such as enhanced well-being (e.g., Quinlan, Swain, & Vella-Brodrick, 2012; Seligman et al., 2005), meaning in life (Littman-Ovadia & Steger, 2010), happiness (Gander et al., 2012), and positive affect (Littman-Ovadia & Lavy, 2012).
Strengths and Meaningful Work
Only two known studies have examined the relation of character strengths and meaningful work (Harzer & Ruch, 2013; Littman-Ovadia et al., 2016). Littman-Ovadia, Lavy, and Boiman-Meshita (2016) found that using strengths was associated with behavioral outcomes, namely, performance, organizational citizenship behavior, and lower counterproductive work behavior. Several specific character strengths (i.e., hope, love, gratitude, curiosity, and zest), that Littman-Ovadia et al. (2016) termed “happiness strengths,” were associated with psycho-emotional work-related outcomes: meaningful work, engagement, and job satisfaction. Moreover, research has demonstrated that the use of character strengths in the workplace resulted in the experience of greater job satisfaction, pleasure, engagement, and meaning (Harzer & Ruch, 2013).
In addition, given the strong relation between strengths and meaning in life, the presence of strengths may be associated with meaningful work as well (Littman-Ovadia & Steger, 2010; Peterson & Park, 2012; Peterson, Ruch, Beermann, Park, & Seligman, 2007). For instance, using Seligman’s (2002) authentic happiness orientations—the pleasurable, engaging, and meaningful existence—all 24 character strengths related to a more meaningful life (Brdar & Kashdan, 2010). In another study, curiosity, gratitude, hope, love, zest, spirituality, perspective, leadership, bravery, and social intelligence had strong correlations with life meaning (Peterson & Park, 2012).
Meaningful Work and Burnout
Burnout is a combination of emotional exhaustion, cynicism toward one’s work, and feelings of inefficiency (Maslach et al., 2001). It is related to a number of negative job outcomes, such as poorer performance, lower productivity, and feelings of incompetence (Maslach et al., 2001). On the other hand, those who experience less burnout are more likely to have greater job satisfaction (Baruch-Feldman, Brondolo, Ben-Dayan, & Schwartz, 2002) and life satisfaction (Heyns et al., 2003). Similarly, happier people tend to experience less burnout (Iverson et al., 1998; Wright & Cropanzano, 1998) and miss work less frequently (George, 1989; Gil et al., 2004).
In contrast to burnout, having meaningful work is related to a number of positive outcomes. For instance, people with meaningful work report greater levels of well-being (e.g., Arnold, Turner, Barling, Kelloway, & McKee, 2007; Steger, Dik, & Duffy, 2012), job satisfaction (Allan, Dexter, Kinsey, & Parker, 2018), and work centrality (Harpaz & Fu, 2002). However, there is limited research examining the impact of meaningful work on burnout, and to our knowledge, no research has examined the relation of meaningful work to mental health professionals’ experience of burnout. However, in medical professionals, meaningful work negatively predicts burnout (Tei et al., 2014; Shanafelt et al., 2009), and in a sample of nurses, sense of coherence, which is in part defined by the experience of meaningfulness, was negatively related to burnout (Heyns et al., 2003). In addition, employee engagement, essentially the opposite of burnout, is positively related to meaningful work (Ghadi, Fernando, & Caputi, 2013; May, Gilson, & Harter, 2004).
The Present Study
As noted earlier, a strengths-based focus is an important value in counseling; however, limited research has examined the relation of character strengths and work-related variables in counselors. Therefore, the goals of the present study were 3-fold. First, we aimed to identify which character strengths were most salient to counselors by comparing counselors’ character strength means to population means (Peterson et al., 2007). Because this was an exploratory question and approach, we did not form specific hypotheses about which strengths would be most salient. Second, we aimed to investigate which character strengths were most related to meaningful work and burnout among the counselor sample. We hypothesized that the “happiness strengths” (i.e., hope, love, gratitude, curiosity, and zest) would explain unique variance above and beyond the other strengths. As found in previous studies, these strengths have shown relations to socioemotional constructs, including meaningful work (Littman-Ovadia et al., 2016). The final goal of the present study was to examine the relations from counselors’ character strengths to work burnout by examining the potential mediating effect of meaningful work. Based upon past findings (Allan & Duffy, 2014; Littman-Ovadia et al., 2016; Tei et al., 2014), we hypothesized that the character strengths identified from Goal 2 would be associated with meaningful work, which in turn would be negatively related to burnout.
Method
Participants
The sample consisted of 324 counselors living and working in the United States. Participants ranged in age from 22 to 85 (M = 44.66, SD = 12.84) and self-identified as female (n = 259, 79.9%), male (n = 61, 18.8%), transgender (n = 2, 0.6%), and genderqueer (n = 2, 0.6%). In terms of race/ethnicity, participants mainly self-identified as White/European American/Caucasian (n = 273, 84.3%), with remaining participants identifying as African/African American (n = 26, 8.0%), Hispanic/Latina/Latino American (n = 9, 2.8%), Asian/Asian American (n = 6, 1.9%), multiracial (n = 5, 1.5%), Arab American/Middle Eastern (n = 1, 0.3%), and Other (n = 4, 1.2%). In terms of education, 4.3% (n = 14) had a college degree, 66.0% (n = 214) had a master’s degree, and 29.6% (n = 96) had a professional or doctoral degree. Participants also reported a wide range of income with a high average (M = US$92,220.99, SD = US$64,997.97); however, income was missing for 29.93% (n = 97) of participants, and the average was skewed with several participants at the high end of the distribution. The sample captured a wide range of counselors, including mental health counselors (n = 114, 35.2%), clinical social workers (n = 39, 12.0%), clinical psychologists (n = 36, 11.1%), marriage and family therapists (n = 32, 9.9%), licensed professional counselors (n = 27, 8.3%), counseling psychologists (n = 18, 5.5%), graduate students on practicum (n = 17, 5.2%), graduate students on internship (n = 16, 4.9%), and others (n = 25, 7.7%).
Instruments
Character strengths
To measure character strengths, participants completed the 120-item VIA-IS (Peterson & Seligman, 2004). This survey uses a 5-point scale (1 = very much unlike me to 5 = very much like me) and assesses people’s levels on the 24 character strengths. Sample items include “I am never too busy to help a friend” and “I always keep my promises.” Peterson, Ruch, Beermann, Park, and Seligman (2007) reported acceptable internal consistencies (α ≥ .70) and 4-month test–retest reliabilities (r > .70) for all 24 character strengths. In the current study, 18 of the character strengths had α reliabilities ≥.70; however, honesty (α = .63), kindness (α = .61), leadership (α = .65), love of learning (α = .69), social intelligence (α = .65), and teamwork (α = .55) did not. These were under the recommended threshold of .70 (Nunnally, 1978), but Cronbach’s α is a limited measure of reliability that has limited value for assessing validity (McCrae, Kurtz, Yamagata, & Terracciano, 2011). Moreover, higher αs can result from a large number of items, item redundancy, and narrowness of the construct (McCrae et al., 2011). Briggs and Cheek (1986) argued that optimal scale homogeneity occurs when the average interitem correlation among items is between r = .20 and r = .40. Therefore, we calculated the average interitem correlation for honesty (α = .25), kindness (r = .25), leadership (r = .28), love of learning (r = .24), social intelligence (r = .27), and teamwork (r = .22). All fell within the acceptable range. Therefore, we retained these variables for analysis.
Meaningful work
Meaningful work was measured with the 10-item Work as Meaning Inventory (WAMI; Steger et al., 2012). Steger, Dik, and Duffy (2012) found the scale to load onto three factors (i.e., positive meaning, meaning-making through work, and greater good motivations) that loaded onto a second-order meaningful work factor. Sample items include “I have found a meaningful career” and “The work I do serves a greater purpose.” Participants answered items on a 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree). Points from each item were summed to calculate a total score, with higher scores representing higher levels of meaningful work. In the instrument development study, Steger et al. (2012) found the scale to correlate in the expected direction with overlapping variables, such as career commitment, presence of life meaning, job satisfaction, and calling. Furthermore, Steger et al. (2012) found the WAMI to have high internal consistency (α =.93), and in the present study, the estimated internal consistency was α = .86.
Burnout
To measure burnout, participants completed the 10-item Burnout Measure, Short Version (Malach-Pines, 2005). Participants are presented with 10 feelings and asked how often they experience them on a 7-point scale (1 = never to 7 = always). Sample items include “tired” and “helpless.” Malach-Pines (2005) found a positive correlation with burnout and health problems, workplace stressors, and withdrawal intentions and a negative correlation with work satisfaction, performance, and importance placed on one’s job. The author also reported estimated internal consistencies ranging from α = .85 to α = .92 and a 3-month test–retest reliability of r = .74. The estimated internal consistency in the present study was α = .89.
Procedure
Counselors were recruited through listservs associated with counseling organizations, such as the American Counseling Association and the Society of Counseling Psychology. We also contacted university counseling centers and mental health facilities around the country to recruit counselors. A short paragraph invited people to join the study. If they agreed to participate, they followed a link to the informed consent document that, if agreed to, directed them to the survey. After completing informed consent, participants were redirected to the VIA Institute on Character website to complete the VIA-IS. After completing this measure, participants received descriptions of their top five strengths from the website. Participants then returned to the main survey to enter their signature strengths and complete the remaining questionnaires. The VIA Institute on Character website provided raw scores of the 24 character strengths, which we combined with our data set by using participant identification numbers.
The initial sample yielded 834 participants. However, 489 only completed the demographic section of the questionnaire, 15 participants wrote in their own strengths, rather than retrieving their VIA character strengths, and 6 participants were identified as outliers. All these cases were removed for a final sample size of 324.
Results
Preliminary Analyses
Three cases for meaningful work and three for burnout had extreme scores >3.5 SDs from the mean. These cases were removed. All character strengths and burnout had absolute values of skewness and kurtosis under one and appeared normally distributed on visually inspected histograms. However, meaningful work was negatively skewed (−1.15) and positively kurtotic (1.36), with most participants reporting high levels of meaningful work. To address nonnormality, we used robust maximum likelihood for the analyses, which is able to effectively handle nonnormal data (Muthén & Muthén, 2011). Following the recommendations of experts (e.g., Tabachnick & Fidell, 2013), we also used full information maximum likelihood (FIML) to generate estimates. FIML uses all available information to calculate estimates with added error so as to not bias estimates. Experts argue that FIML is superior to traditional techniques, such as listwise deletion and mean substitution, which tend to discard valuable information and bias estimates (Tabachnick & Fidell, 2013).
t Tests
We conducted a series of independent t tests comparing the averages of character strengths from this study to established norms in a sample of 2,573,338 American adults (VIA, 2017). As seen in Table 1, the averages of 13 character strengths were larger in the counselor sample, 2 were larger in the normed sample, and 9 did not differ between the two groups. The counselor group was especially higher on love of learning (d = .44), perspective (d = .43), social intelligence (d = .37), love (d = .35), and spirituality (d = .35). The normed sample was higher on self-regulation (d = .36) and teamwork (d = .42). Because the current study had a larger proportion of women, we tested gender differences between all character strengths. There were no gender differences in the counselor sample, except for appreciation of beauty and excellence, t(272) = −2.08, p < .05, and gratitude, t(272) = −2.30, p < .05. However, the counselor sample did not differ from the normed sample on either of these character strengths.
The t-Tests Comparing Counselor Character Strengths Means to Population Norms.
*p < .05. **p < .01.
Regressions
To obtain character strengths for the model, we first conducted two regressions with all character strengths. Five character strengths significantly predicted meaningful work: love (β = .20, SE = .07, p < .01), prudence (β = −.28, SE = .09, p < .01), hope (β = .27, SE = .09, p < .01), perspective (β = .28, SE = .08, p < .01), and zest (β = .27, SE = .10, p < .01). Five character strengths also significantly predicted burnout: prudence (β = .24, SE = .09, p < .01), forgiveness (β = −.15, SE = .08, p < .05), honesty (β = −.16, SE = .08, p < .05), hope (β = −.24, SE = .09, p < .01), and self-regulation (β = −.32, SE = .08, p < .001). Therefore, with overlap, eight character strengths predicted unique variance in meaningful work and burnout. We included these for model testing.
Model Testing
To evaluate the models, we used structural equation modeling in MPlus with robust maximum likelihood. Indices of fit that minimized the likelihood of Type I and Type II error were selected (Hu & Bentler, 1999). These were the chi-square test (χ2), the comparative fit index (CFI), the root mean square error of approximation (RMSEA), and the standardized root mean residual (SRMR). A significant χ2 can indicate a poor fitting model, but this test is not reliable in larger samples (Tabachnick & Fidell, 2013). Criteria for the CFI and RMSEA have ranged from less conservative (CFI ≥ .90; RMSEA ≤ .10, SRMR ≤ .10) to more conservative (CFI ≥ .95; RMSEA ≤ .08; SRMR ≤ .06; Hu & Bentler, 1999; Quintana & Maxwell, 1999; Weston & Gore, 2006). However, researchers should be cautious when using these criteria as strict cutoffs and should consider sample size and model complexity when judging the fit of models (Weston & Gore, 2006).
When conducting structural equation models with latent variables, the use of item parcels when compared to item-level data has many advantages, such as more precise parameter estimates, better model fit, less bias in estimates, increased reliability, and reduced levels of skewness and kurtosis (Dow, Jackson, Wong, & Leitch, 2008; Little, Cunningham, Shahar, & Widaman, 2002; Nasser & Wisenbaker, 2003). Therefore, we created three parcels each for the character strength variables, meaningful work, and burnout. To create parcels for meaningful work, we used the meaningful work subscales. For the character strengths and burnout, we conducted an exploratory factor analysis, and items were assigned to parcels in countervailing order according to the size of the factor loading so that the parcels would have approximately equivalent factor loadings (Weston & Gore, 2006).
Descriptive Statistics and Correlations
Before evaluating the structural models, we tested a measurement model to ensure latent constructs were measured adequately by items and parcels. This model had good fit to the data, χ2 (360) = 559.13, p < .001, CFI = .94, RMSEA = .04, 90% CI [.04, .05], and SRMR = .06, and all indicators loaded onto their respective factors at values of .48 or higher. Table 2 depicts the factor correlations and raw means and SDs for all study variables.
Descriptive Statistics and Factor Correlations Among Study Variables.
*p < .05. **p < .01.
Full Mediation Model
The full mediation model included the character strength variables predicting meaningful work, which in turn predicted burnout. The character strength variables were allowed to correlate with one another. The model had acceptable fit to the data, χ2 (368) = 606.92, p < .001, CFI = .92, RMSEA = .05, 90% CI [.04, .05], and SRMR = .07.
Partial Mediation Model
The partial mediation model was the same as the full mediation model, but it allowed direct effects from the character strength variables to burnout. This model represented an improvement over the previous model, χ2 (360) = 559.13, p < .001, CFI = .94, RMSEA = .04, 90% CI [.04, .05], and SRMR = .06, and the scaled χ2 difference was significant, Δχ2 (8) = 26.65, p < .001. To find the most parsimonious model and reduce multicollinearity, we removed the character strength variables that did not significantly predict meaningful work or burnout. This included love, hope, forgiveness, and honesty. Although the final model was no longer nested and could therefore no longer be directly compared to previous models, fit was similar, χ2 (120) = 224.33, p < .001, CFI = .94, RMSEA = .05, 90% CI [.04, .06], SRMR = .05, and the pattern of results was identical. We then deleted all nonsignificant paths unless they were close to significance (p < .06). The final model was not significantly different from the previous model, χ2 (123) = 226.32, p < .001, CFI = .94, RMSEA = .05, 90% CI [.04, .06], SRMR = .05, Δχ2 (3) = 1.99, p = .57, but we retained it for parsimony. Figure 1 displays the standardized regression weights for this final model. This model explained 52.6% of the variance in meaningful work and 33.1% of the variance in burnout.
Standardized parameter estimates for the paired, partial mediation model. Note. Errors and correlations among the strengths variables are not shown. *p < .05, **p < .01.
Covaried Model
Given the large proportion of women, people identifying as White, and older adults in our sample, we tested the final model with gender, race, and age as covariates. Race was dummy coded as White and non-White. This model had similar fit, χ2 (159) = 298.53, p < .001, CFI = .93, RMSEA = .05, 90% CI [.04, .06], SRMR = .05, and the pattern of results was not altered. Therefore, we retained the noncovaried model.
Indirect Effects
The indirect effects of prudence (95% CI [.02, .15]), perspective (95% CI [−.20, −.04]), and zest (95% CI [−.30, −.08]) to burnout via meaningful work were significant.
Discussion
The primary purpose of this study was to examine the relations from counselors’ core character strengths at work to burnout by examining the potential mediating effect of meaningful work. We also compared mean levels of counselors’ strengths to population means and conducted regression analyses to examine which character strengths uniquely predicted meaningful work and burnout. Building from previous work that examined the link between specific character strengths and meaningful work (Littman-Ovadia et al., 2016), we hypothesized that “happiness strengths” (e.g., hope, love) would explain unique variance in the prediction of meaningful work and burnout when compared with other strengths. Lastly, based on results of the regression analyses, we used structural equation modeling to investigate whether character strengths predicted meaningful work and, in turn, burnout. Based on past research (Allan & Duffy, 2014; Littman-Ovadia et al., 2016; Tei et al., 2014), we hypothesized that the character strengths found earlier would be associated with meaningful work, which would in turn be negatively related to burnout. Our findings partially supported our hypotheses.
Comparing mean levels of character strengths among our sample with general population means revealed that the counselors in our sample reported significantly higher levels across 13 of the 24 character strengths, several of which were particularly elevated: love of learning, perspective, social intelligence, love, spirituality, honesty, and judgment. This constellation of strengths fits well with the character strengths likely required to be an effective counselor. For example, social intelligence is an awareness of the feelings of others, love refers to the capacity to form close relationships, judgment reflects the tendency to carefully examine a problem from different viewpoints, and perspective is the ability to provide wise guidance to others (Peterson & Seligman, 2004). This pattern of strengths also mirrors many of the common factors (e.g., strong relationships, empathy) that contribute to positive outcomes in psychotherapy (Wampold, 2015). However, counselors also scored significantly lower on two strengths when compared to the general population: self-regulation and teamwork. These strengths are typically associated with discipline and internally regulating feelings and working as part of a team (Peterson & Seligman, 2004). It may be that such strengths are not as in line with the core themes of counseling and, therefore, are not endorsed as much by counselors. For example, although many counselors work in collective practices, counseling is typically one-on-one with clients.
In our regression analyses, prudence and hope significantly predicted both meaningful work and burnout. Love, perspective, and zest significantly predicted meaningful work, and forgiveness, honesty, and self-regulation significantly predicted burnout. These findings partially supported our hypothesis that “happiness strengths” would predict meaningful work and burnout; however, although hope, love, and zest were significant predictors, gratitude and curiosity were not. These patterns of strengths are congruent with what one might expect would promote a sense of meaningful work and a diminished sense of burnout. Specifically, the strengths that contributed to meaningful work represent a sense of optimism (hope), valuing close connections with others (love), being able to provide counsel to others (perspective), and approaching work with excitement and energy (zest; Peterson & Seligman, 2004), all of which may be relevant to providing psychotherapy. On the other hand, being able to approach work with optimism (hope), acceptance of others’ shortcomings (forgiveness), acting genuinely (honesty), and being able to control emotions (self-regulation) likely provide people with resources to combat the exhaustion and cynicism that typically comprise burnout (Maslach et al., 2001).
In contrast to the results discussed earlier, prudence—a strength associated with being overly cautious and careful at times—was negatively associated with meaningful work and positively associated with burnout, suggesting that the more a counselor endorses prudence, the less meaningful they find their work and the more burned out they feel. However, the zero-order correlations between prudence and meaningful work and burnout were nonsignificant and only turned significant when included in our final model with the strengths of perspective, self-regulation, and zest. This pattern of results represents a suppression effect and suggests that on its own prudence may not be harmful, but when accounting for the shared variance among other strengths, high levels of prudence may be detrimental. A possible explanation for these findings is that prudence involves being careful about choices and not taking risks. This may not be harmful in and of itself, but being overly fastidious in the absence of other character strengths, such as perspective and self-regulation, may decrease meaningful work and increase burnout. The presence of prudence among counselors might inhibit progress in that prudent counselors may not be willing to take risks with clients, which may account for the negative association with perceptions of meaningful work. However, given that this finding is new and could reflect a statistical artifact, it should be interpreted with caution.
Following the above regression analyses, we examined the degree to which the identified character strengths predicted meaningful work and burnout. Partially confirming our hypotheses, prudence, perspective, and zest were positively linked with meaningful work, which was, in turn, negatively related to burnout. Specifically, prudence had a significant positive indirect effect on burnout through meaningful work, whereas perspective and zest had significant negative indirect effects on burnout via meaningful work. This implies that prudence may be associated with greater levels of burnout due to a decreased sense that work is meaningful. The opposite can be said for perspective and zest: Greater levels of these strengths were associated with greater perceptions of meaningful work, which in turn predicted lower levels of burnout. Additionally, prudence and self-regulation had significant direct effects to burnout, which suggested partial mediation. This model explained significant amounts of variance in meaningful work and burnout, suggesting that the presence of these character strengths may play an important role in the vocational well-being of counselors. Our results suggest that meaningful work may be an important mechanism that helps to explain the link between character strengths and burnout at work.
Our finding that the presence of character strengths was associated with meaningful work is in line with results from various studies linking meaning in life with the presence of character strengths (Littman-Ovadia & Steger, 2010; Peterson & Park, 2012; Peterson et al., 2007). However, our finding that only one happiness strength (zest) versus two nonhappiness strengths (prudence and perspective) predicted meaningful work is contrary to our predictions, which were based on Littman-Ovadia et al.’s (2016) findings that the use of happiness strengths was a stronger predictor of meaningful work when compared to signature strengths use. There are at least two possible explanations of this finding. First, we did not measure happiness strengths use, only the presence of the happiness strengths. Therefore, it may be that the presence of happiness strengths must be accompanied by the use of these strengths in order to be a catalyst for perceiving work as meaningful. Second, differences in meaningful work measurement may be a factor. While Littman-Ovadia et al. (2016) used the Meaningful Work Scale (Schnell, Höge, & Pollet, 2013) which measured meaningful work as fulfilling, meaningful, or self-congruent, the present study used the WAMI (Steger et al., 2012) which defines meaningful work as being made up of three domains: positive meaning, meaning-making through work, and greater good motivations. These varying conceptualizations of meaningful work may have contributed to our contrasting results.
Our finding that meaningful work was negatively linked with burnout corroborates past results demonstrating this link among a sample of medical professionals (Tei et al., 2014) and other studies finding constructs analogous to meaningful work (e.g., calling, sense of coherence) and burnout (e.g., occupational withdrawal intentions) to be linked similarly (Duffy, Dik, & Steger, 2011; Gazica & Spector, 2015; Ghadi et al., 2013; May et al., 2004). These findings suggest that cultivating certain character strengths may contribute to a greater sense of meaningful work and reduced feelings of burnout.
Practical Implications
The findings from the present study contribute to the literature on burnout, a major issue among mental health professionals and counselors. In their review of burnout among mental health professionals, Morse, Salyers, Rollins, Monroe-DeVita, and Pfahler (2012) reported that 21–67% of mental health workers may suffer from high levels of burnout. Treating burnout is essential, given the finding that, if left untreated, levels of burnout tend to remain stable or even worsen (Burke & Richardsen, 1993) and can contribute to declines in job performance, productivity, and satisfaction with work and life (Baruch-Feldman et al., 2002; Maslach et al., 2001). Our findings offer possible implications to help address the high level of burnout and its deleterious effects experienced by counselors.
One area in which findings from the present study might be applied is clinical supervision. Supervisors can work to implement a strengths-focused supervision approach in order to help supervisees identify and implement their strengths in session. Supervisees may benefit from completing the VIA-IS (Peterson & Seligman, 2004) followed by reviewing video segments of their sessions and working with supervisors to highlight the presence of character strengths in session. One study of 14 counseling graduate students found that supervision had the potential to promote resilience and serve as a protective factor against burnout (Thompson, Frick, & Trice-Black, 2011). Additionally, age has been found to be negatively correlated with burnout (Lim, Kim, Kim, Yang, & Lee, 2010), such that younger counselors appear to experience greater levels of burnout, further suggesting that implementing a strengths-based approach to supervision might help combat and prevent burnout by contributing to a greater sense of meaningful work.
Findings from the present study also provide support for the idea of strengths-based psychoeducational workshops designed for counselors and other mental health professionals. Such workshops could provide an introduction to the benefits associated with character strengths and work to help participants identify strengths through an assessment such as the VIA-IS (Peterson & Seligman, 2004). An overview of burnout interventions found workshops to be effective at reducing the core symptom of burnout—exhaustion (Le Blanc & Schaufeli, 2008). Therefore, workshops targeted at helping counselors discover and implement strengths in a clinical fashion may directly and, via meaningful work, indirectly contribute to decreased burnout.
Limitations and Future Directions
The present study has some limitations, all of which provide directions for future research. To start, cross-sectional data prevent determinations of causal relations, and mediation analyses conducted with cross-sectional data may contribute to biased and inaccurate estimates (Maxwell & Cole, 2007). Second, we did not examine potential third variables or moderators related to work environment, which may have influenced some of our hypothesized links to burnout. For example, the VIA survey measures strengths in general, not in the work context. Therefore, a counselor may possess a high strength of honesty in general but not specifically in the workplace. Another limitation is that the present study consisted mainly of wealthy (mean income of US$92,220.99) participants who largely identified as female (79.9%) and White (84.3%), possibly the result of self-selection bias. Such biases might also have influenced some of our findings. For example, because women tend to score higher than men on certain strengths (e.g., love and kindness; Brdar, Anić, & Rijavec, 2011), some of the significant differences in strengths between our counselor sample—which was mostly female—and the general population may be due to this imbalance. Therefore, although the covaried model suggests the model may be generalizable, the pattern of strengths identified in the present study may only reflect a subset of counselors. Additionally, we were unable to identify how different activities that counselors participate in (e.g., counseling, supervision, and advocacy) may have specifically contributed to a sense of meaningful work and burnout. Finally, several of the character strengths had estimated reliability coefficients below .70. This may be because we used the shorter version of VIA Inventory, which researchers continue to refine. However, it may mean that some character strengths are unreliable or have different structures in counselors.
We believe the limitations presented above provide several avenues for future research. First, although the temporal positioning of constructs was based upon theoretical and empirical relations (e.g., Littman-Ovadia et al., 2016), future scholarship should examine the relations among character strengths, meaningful work, and burnout over time. Such studies should also include variables related to work environment as moderating variables. Regarding our sample, future studies should replicate and extend our results with different samples, and research conducted specifically among counselors should distinguish between the varying roles that counselors engage in. Finally, future studies could obtain informant reports of the presence of character strengths, perhaps from clients, colleagues, or supervisors, in order to more accurately determine the extent to which counselors possess specific character strengths. Such studies may also benefit from coding recordings of counseling sessions, similar to our suggestion that supervisors and supervisees review session recordings.
Conclusion
The present study sought to examine how mean levels of character strengths among counselors compared with those of the general population, examine which character strengths were associated with meaningful work and burnout among counselors, and examine meaningful work as a mediator of character strengths and burnout. Overall, the general population endorsed significantly greater levels of teamwork and self-regulation, and counselors reported significantly greater levels of love, creativity, curiosity, fairness, forgiveness, gratitude, honesty, judgment, learning, perspective, social intelligence, spirituality, and zest. Of the character strengths, prudence, perspective, self-regulation, and zest emerged as key strengths associated with meaningful work and burnout. As a whole, our findings provide a foundation for future studies to further examine how character strengths link with meaningful work and burnout. Given that the relative importance of specific character strengths may vary across professions, these results demonstrate the need to examine character strengths within specific work environments.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.