Examining Burnout and Engagement in Layoff Survivors

Abstract

This study investigates burnout and work engagement in layoff survivors. Layoff survivors are defined as individuals who remain working at organizations that have recently had layoffs. Job demands (job insecurity and work overload) and job and personal resources (social support, optimism, career adaptability, and career management self-efficacy) are examined as predictors of burnout and engagement. The sample consists of 203 adults currently working at organizations that downsized within the past year. As hypothesized, job demands had positive relationships with burnout, while social support, optimism, and career management self-efficacy had positive relationships with engagement. Contrary to hypotheses, career adaptability was not positively related to engagement. Engagement also mediated the relationships between several resources and burnout. This study makes a unique contribution to the literature, as little research has examined personal strengths of layoff survivors, in addition to job characteristics.

Keywords

layoffs career adaptability career management self-efficacy burnout engagement

Since 2007, the United States has experienced a recession that is widely considered to be the worst economic crisis since the Great Depression. An increase in organizational downsizing has been one seemingly inevitable consequence of this crisis. According to the U.S. Department of Labor (2009), the total number of initial layoff claims during the 15 months between December 2007 and February 2009 was 2,927,813. More recently, during the first quarter of 2011, 1,397 mass layoff events occurred involving 190,895 workers (U.S. Department of Labor, 2011). Research indicates that it is not only the individuals who lose their jobs that are affected by layoffs. Those who remain working, termed layoff survivors (Brockner, 1988), also experience a number of stressful outcomes postdownsizing (e.g., Kalimo, Taris, & Schaufeli, 2003; Kivimäki, Vahtera, Griffiths, Cox, & Thompson, 2000; Noer, 2009), and vocational psychologists should explore what factors predict better outcomes for these individuals. The present study examines job and personal variables that may be predictive of burnout and work engagement in individuals who remain working at an organization that had downsized within the past year.

Layoff Survivors

Research suggests that the mental health and well-being of workers may be strongly affected by surviving a layoff. Decreased job satisfaction, decreased job performance, higher rates of absences and sick days, lower levels of organizational commitment, poorer emotional well-being, and increased psychosomatic complaints are some of the negative outcomes associated with this group (Armstrong-Stassen, 1994; Brockner, Grover, Reed, & DeWitt, 1992; Burke & Greenglass, 2000; Kivimäki et al., 2000). Noer (2009) coined the term layoff survivor sickness to describe a distinct pattern of emotions and concerns survivors may experience, which often involves guilt, anxiety, depression, reduced motivation, distrust, and anger. These negative effects may be perpetuated by the fact that many organizations have no method for dealing with survivors. Robbins (1999) suggests that while organizations often put effort into assisting layoff victims with outplacement services, severance pay, or psychological counseling, very rarely do they consider services for the employees who are left behind to keep the organization afloat, often with increased workloads, feelings of sadness and guilt, and confusion over new roles.

The negative reactions so often experienced by layoff survivors appear quite similar to the construct of burnout, as defined by Maslach (2003). Burnout is a psychological syndrome that occurs in response to exposure to prolonged stressors on the job. Maslach, Jackson, and Leiter (1996) suggest it consists of three components: emotional exhaustion, cynicism, and reduced professional efficacy. Emotional exhaustion refers to the experience of feeling drained or depleted of one’s emotional resources. Cynicism refers to a detached, negative, or callous response to others. Reduced professional efficacy refers to a lack of confidence in one’s abilities at work or a sense of inadequacy. Past research indicates there is a clear relationship between the work stressors common to surviving a layoff and the experience of burnout (e.g., Hakanen, Bakker, & Schaufeli, 2006; Schaufeli & Bakker, 2004). The present study will examine the outcome of burnout directly within a sample of layoff survivors.

The majority of research on this population has focused on organizational factors that may account for the variance in layoff survivor reactions. For instance, the magnitude of the downsizing, the degree of information exchanged, the perceived fairness of the layoff process, and the loss of close friends at work are all examples of organizational factors that affect survivor outcomes (Brockner, DeWitt, Grover, & Reed, 1990; Cascio, 1993; Moore, Grunberg, & Greenberg, 2004; Parker, Chmiel, & Wall, 1997; Shah, 2000). However, given that a large portion of variance in layoff survivor outcomes remains unexplained, other factors, such as intrapersonal characteristics, should be researched. More research is particularly needed that focuses on factors related to the strength and resilience of layoff survivors. Optimism, for example, appears to be a promising personal strength in combating the negative effects associated with surviving a layoff (e.g., Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007), and researchers should examine more psychological strengths that may benefit survivors. In addition, very little of the extant research has examined positive outcomes in layoff survivors. If a goal of organizational and vocational researchers is for layoff survivors to flourish under adverse conditions, then positive experiences such as engagement must be researched in addition to negative outcomes. The present study will examine the outcome variable of engagement, which is defined as a work-related state of mind that is positive and fulfilling, and characterized by the qualities of vigor, dedication, and absorption (Schaufeli, Bakker, & Salanova, 2006).

Job Demands–Resources Model

The present study is grounded in the job demands–resources model (JD-R; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). This theory suggests that all jobs have their own specific factors that relate to individuals’ levels of burnout and engagement and that these factors can be categorized as either job demands or job resources. Bakker and Demerouti (2007) define job demands as, “those physical, psychological, social, or organizational aspects of the job that require sustained physical and/or psychological (cognitive and emotional) effort or skills and are therefore associated with certain physiological and/or psychological costs” (p. 312). Job resources are defined as physical, psychological, social, or organizational aspects of the job that are “either functional in achieving work goals, reduce job demands and the associated physiological and psychological costs” and/or “stimulate personal growth, learning, and development” (Bakker & Demerouti, 2007, p. 312). Recent research has extended the JD-R model to also examine personal resources that may be positively related to engagement (e.g., Xanthopoulou et al., 2007; Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2009). A major strength of the JD-R model is its applicability to various occupational settings, regardless of the specific demands and resources involved.

Present Study

Grounded in the JD-R model (Demerouti et al., 2001), this research examines how certain job demands, along with certain job and personal resources, may influence the outcomes of burnout and engagement in layoff survivors. Job insecurity and work overload have been selected as two salient job demands for survivors, per review of previous research on this population (e.g., Noer, 2009). Social support, a variable that has been identified by previous research as able to reduce the effects of certain work-related stressors (e.g., Carlson & Perrewe, 1999), has been selected as an important job resource to examine specifically in layoff survivors. The intrapersonal resources of career adaptability, optimism, and career management self-efficacy will also be examined as predictors of burnout and engagement. Career adaptability refers to the ability to cope with unpredictable changes in one’s work life (Savickas, 1997). Optimism refers to the tendency to take a positive outlook toward the future (Scheier & Carver, 1992). Career management self-efficacy refers to the confidence that one can manage one’s own career (Kossek, Roberts, Fisher, & DeMarr, 1998). Very few studies have taken personal strengths into account when examining layoff survivors; and the inclusion of these resources will provide a more comprehensive, strengths-based explanation of layoff survivors’ reactions. The researchers have a particular interest in career adaptability’s relationship to engagement, as research has linked this construct to both positive outcomes, such as life satisfaction (Hirschi, 2009), and more negative work-related outcomes, such as turnover intentions (Ito & Brotheridge, 2005).

This research also attempts to clarify the nature of the role of resources in the burnout and engagement process. The JD-R model depicts resources as moderating variables, suggesting that they serve to buffer the relationship between demands and burnout. While some studies have found support for this buffering hypothesis (e.g., Bakker, Demerouti, & Euwema, 2005) others have not (e.g., Bakker, Demerouti, & Verbeke, 2004), indicating that resources may be independent antecedents to burnout, separate from demands. The present study examines whether each of the resources may buffer the relationship between the demands and burnout.

It is also possible the engagement may play a mediating role between each of the resources and burnout. Salanova and Schaufeli (2008) found that engagement fully mediated the relationship between job resources and proactive behaviors in two independent samples of employees. Engagement has also been found to mediate the relationship between certain job characteristics and job-related consequences such as job satisfaction, organizational commitment, and intention to quit (Saks, 2006). Therefore, the present study will examine the possible mediating role of engagement between each of the resources and burnout.

Hypotheses

First, we hypothesize that work demands in the form of (a) job insecurity and (b) work overload will have a positive relationship with burnout. Second, we hypothesize that job resources comprising of (a) social support from supervisor and coworkers, and personal resources comprising of (b) career self-efficacy, (c) optimism, and (d) career adaptability will have a positive relationship with work engagement. Third, we hypothesize that job and personal resources will moderate the relationship between each of the work demands and burnout. Fourth, we hypothesize that engagement will mediate the relationship between each of the resources and burnout.

Method

Participants and Procedure

A priori power analyses suggested that a sample size of 122 was needed to examine the hypotheses, given up to nine predictors and a β of .2 (Tabatchnik & Fidell, 2007). This smaller sample size is in line with previous research on burnout, which has not uncommonly consisted of samples less than 250 (e.g., Bakker et al., 2004; Xanthopoulou et al., 2009). Participants included 203 layoff survivors who worked for a range of organizations that had downsized within the past year. The sample consisted of 86 men and 117 women, with an average age of 37.49 (SD = 9.03). The racial/ethnic breakdown of participants was as follows: 22 African American/Black, 18 Asian American, 13 Latino/Hispanic, 13 Native American, 132 White/Caucasian, 7 Biracial, and 2 Other. Regarding highest level of education, 26.11% of participants had a graduate degree, 22.17% had completed some graduate school, 46.8% had a bachelor’s degree, 3.94% had completed some college, and less than 1% had a high school diploma. Tenure at current position ranged from 0 to 34 years (M = 7.31, SD = 6.27), and job level included entry level (11.82%), nonsupervisory (46.31%), middle management (27.59%), senior management (12.32%), and executive level (1%). Participants were recruited through postings that included a link to the survey on social networking sites such as LinkedIn. Snowball sampling was used, as participants were encouraged to forward the survey link to other layoff survivors. A $5 Amazon gift card was offered as an incentive to increase participation. In order to receive the gift card, participants were asked to provide an e-mail address at the end of the survey where they would like the gift card sent.

Measures

Demographic questionnaire

Participants completed a questionnaire of demographic variables related to age, gender, race/ethnicity, education level, number of years of tenure in their organization, organization type, and current level of position within their organization.

Job insecurity scale (Kristensen, Hannerz, Høgh, & Borg, 2005)

This measure of perceived job insecurity is a subscale of the Copenhagen Psychosocial Questionnaire (COPSOQ). It contains 4 items (e.g., Are you worried about becoming unemployed?) that are rated on a 5-point Likert-type scale ranging from (100) to a very large extent to (0) to a very small extent. The subscales of the COPSOQ have been used extensively in both Danish and international studies to assess the psychosocial workplace environment, with evidence of criterion and construct validity (Nübling, Stößel, Hasselhorn, Michaelis, & Hofmann, 2006; Pejtersen, Kristensen, Borg, & Bjorner, 2010). Kristensen et al. report a Cronbach’s α coefficient of .61 for this subscale and suggest that its lower internal consistency can be attributed to its small number of items. Cronbach’s α coefficient for the current sample is .82.

Quantitative demands (Kristensen, Hannerz, Høgh, & Borg, 2005)

This measure of work overload consists of 4 items designed to assess an employee’s workload (e.g., How often do you not have time to complete all your tasks?) and is also a subscale of the COPSOQ. The items are rated on a 5-point Likert-type scale ranging from (100) always to (0) never/hardly ever. Kristensen et al. report a Cronbach’s α coefficient of .65. Cronbach’s α coefficient for the current sample is .74.

Social support scale (Caplan, Cobb, French, Van Harrison, & Pinneau, 1980)

This scale measures employees’ perceived amount of support received from a variety of sources. Responses are rated on a 5-point Likert-type scale ranging from (4) very much to (0) don’t have any such person. Evidence of the scale’s convergent and discriminant validity has been established through past research (e.g., Kaufman & Beehr, 1989; Lim, 1996). The current study will only use the 8 items from this scale that focus on support from supervisor and support from coworkers. The 8 items in this modified scale have a reported coefficient α of .80 (Lim). Cronbach’s α coefficient for the current sample is .79.

Life orientation test–revised (LOT-R; Scheier, Carver, & Bridges, 1994)

This test was developed to measure individual differences in generalized optimism and pessimism (e.g., In uncertain times, I usually expect the best). The instrument consists of 10 items that are answered on a 5-point Likert-type scale ranging from (A) I agree a lot to (E) I disagree a lot. Four of the items (2, 5, 6, 8) are fillers and should not be scored. Evidence of convergent and discriminant validity as well as internal consistency and test–retest reliability have been demonstrated (Scheier & Carver, 1992; Scheier et al., 1994). Scheier et al. report a Cronbach’s α coefficient of .82. Cronbach’s α coefficient for the current sample is .78.

I-ADAPT (Ployhart & Bliese, 2006)

This scale is a measure of an individual’s flexibility and adaptability in regard to work. Of the eight subscales of this measure, two were selected as most appropriate for the context of the current study: work stress adaptability and uncertainty adaptability. Work stress adaptability refers to one’s ability to handle stressors at work (e.g., I am easily rattled when my schedule is too full). Uncertainty adaptability refers to comfort in dealing with unpredictable situations (e.g., I become frustrated when things are unpredictable). The work stress subscale consists of 5 items and the uncertainty subscale consists of 9 items that are each answered on a 5-point Likert-type scale ranging from (5) strongly agree to (1) strongly disagree. Ployhart and Bliese (2006) report evidence of the I-ADAPT’s convergent and discriminant validity. Wessel, Ryan, and Oswald (2008) reported a Cronbach’s α coefficient of .74 for the uncertainty subscale. Cronbach’s α coefficient of this subscale in the current sample is .69. Ployhart and Bliese reported a Cronbach’s α coefficient above .70 for the work stress subscale. Cronbach’s α coefficient of this subscale in the current sample is .79.

Career management self-efficacy (Kossek et al., 1998)

This is an 11-item measure of the degree to which a person believes he or she is capable of managing one’s own career (e.g., When I make plans for my career, I am confident I can make them work). All questions are answered on a 5-point Likert-type scale ranging from (1) strongly disagree to (5) strongly agree. Previous research supports the convergent and criterion validity of this measure (e.g., Kossek et al., 1998; McArdle, Waters, Briscoe, & Hall, 2007). Day and Allen (2004) report a Cronbach’s α coefficient of .81. Cronbach’s α coefficient in the current sample is .76.

Utrecht Work Engagement scale-Nine (UWES-9; Schaufeli et al., 2006)

This instrument measures work engagement, meaning a positive work-related state characterized by vigor, dedication, and absorption (e.g., My job inspires me). The UWES-9 consists of 9 items measuring three dimensions: vigor, dedication, and absorption. Items are scored on a scale ranging from (0) never to (6) always, with higher scores representing higher levels of work engagement. Evidence supports the factorial and divergent validity of this scale (Schaufeli et al., 2006). Schaufeli et al. reported that Cronbach’s αs for this scale exceeded .80 across a range of samples. The current sample has a Cronbach’s α coefficient of .91.

Maslach Burnout Inventory– general survey (MBI-GS; Schaufeli, Leiter, Maslach, & Jackson, 1996)

This instrument is intended to measure burnout across a range of occupations. It consists of 16 items and 3 subscales: exhaustion, cynicism, and professional efficacy. The exhaustion subscale consists of 5 items (e.g., I feel used up at the end of the work day), the cynicism scale consists of 5 items (e.g., I just want to do my job and not be bothered), and the professional efficacy subscale consists of 6 items (e.g., I have accomplished many worthwhile things in this job). All items are rated on a 7-point frequency scale ranging from (0) never to (6) daily. The construct validity of this instrument has been established (e.g., Taris, Schreurs, & Schaufeli, 1999). Leiter and Schaufeli (1996) report Cronbach’s α coefficients between .84 and .90 for exhaustion, .74 and .84 for cynicism, and .70 and .78 for professional efficacy. Cronbach’s α coefficients in the current sample are .91 for exhaustion, .84 for cynicism, and .77 for professional efficacy.

Results

Preliminary Data Examination

Prior to analyses, all missing continuous data were handled using the expectation maximization (EM) algorithm available through Statistical Package for the Social Sciences (SPSS) 19.0. Table 1 provides correlations between each of the independent and dependent variables. Possible differences between men and women on each of the study’s variables were examined by conducting an independent samples t-test of gender. Only job insecurity was found to differ significantly by gender, t(203) = 2.71, p < .01. Specifically, men (M = 54.58) indicated higher job insecurity than women (M = 44.18), although both levels were within the average range.

Table 1.

Intercorrelations Between Variables of Interest.

Variable	1	2	3	4	5	6	7	8	9	10	11
1 Job insecurity	1
2 Work overload	.24**	1
3 Social support	−.16*	−.28**	1
4 Optimism	−.07	−.29**	.36**	1
5 UA	−.32**	.01	.04	.03	1
6 WSA	−.49**	−.23**	.10	.12	.62**	1
7 CMSE	−.18*	−.18*	.24**	.40**	.38**	.32**	1
8 Engagement	.32**	−.18*	.26**	.46**	.02	−.13	.33**	1
9 Exhaustion burnout	.41**	.41**	−.17*	−.23**	−.32**	−.61**	−.24**	−.19**	1
10 Cynicism burnout	.32**	.34**	−.32**	−.36**	−.24**	−.40**	−.34**	−.43**	.64**	1
11 Professional efficacy	−.09	−.05	.23**	.25**	.29**	.18**	.37**	.49**	−.23**	−.34**	1

Note. CMSE = career management self-efficacy; UA = uncertainty adaptability; WSA = work stress adaptability.

*p < .05. **p < .01.

Multiple Regression Analyses

Hypothesis 1: It was hypothesized that the job demands of job insecurity and work overload would be predictive of burnout. Multiple regression analyses of the burnout subscales by the control variables of gender, education, job level, and tenure (Step 1), along with the demands of job insecurity and work overload (Step 2) were conducted to examine this hypothesis. The control variables were dummy coded prior to being entered into the analysis, with the number of variables equaling the number of levels minus one. In the case of job level, the highest levels of senior management and executive level were combined as only 1% of participants indicated being executive level.

Approximately 31% of the variance in exhaustion burnout can be explained by the control and job demand variables, R ² = .31, F(10, 192) = 8.46, p < .001. A nonsignificant 7% of the variance in exhaustion burnout was explained by the control variables; however, the addition of job insecurity and work overload accounted for a significant 24% of additional variance, R ² change =.24, F change(2, 192) = 32.87, p < .001. Both job insecurity, β = .32, t(202) = 5.04, p < .001, and work overload, β = .33, t(202) = 4.75, p < .001, played relatively equivalent roles in predicting burnout.

The variables accounted for slightly less variance in cynicism burnout. Approximately 22% of the variance in cynicism burnout can be explained by both the control and the job demand variables, R ² = .22, F(10, 192) = 5.52, p < .001. The control variables accounted for a significant 8% of variance, R ² change =.08, F change(2, 192) = 2.17, p = .03. However, the only significant control variable was highest level of education. Specifically, having a college degree was predictive of higher cynicism in comparison to individuals with a graduate degree, β = .19, t(202) = 2.20, p = .03. Again, job insecurity, β = .20, t(202) = 4.32, p < .001, and work overload, β = .29, t(202) = 2.72, p = .01, played relatively equivalent roles in predicting cynicism burnout, accounting for 14% of the variance, R ² change =.14, F change(2, 192) = 17.47, p < .001.

Finally, approximately 9% of the variance in professional efficacy can be explained by the control and job demand variables, R ² = .09, F(10, 192) = 1.92, p = .04. Work overload and job insecurity did not explain a significant amount of variance in professional efficacy when added in Step 2, R ² change <.01, F change(2, 192) = .16, p = .86. However, several of the control variables were significant. Having a college degree as one’s highest level of education was predictive of lower professional efficacy in comparison to individuals with a graduate degree, β = −.19, t(202) = −2.08, p = .04, and being in an entry-level position was predictive of less professional efficacy in comparison to individuals in senior or executive-level positions, β = −.22, t(202) = −2.37, p = .02.

Hypothesis 2: It was also hypothesized that the resources of social support, optimism, uncertainty adaptability, work stress adaptability, and career management self-efficacy would be predictive of engagement. A multiple regression analysis of engagement by the control variables of gender, education, job level, and tenure (Step 1), along with the resources of social support, optimism, work stress adaptability, uncertainty adaptability, and career management self-efficacy (Step 2) was conducted. Approximately 36% of the variance in engagement can be described by the variables examined, R ² = .36, F(13, 189) = 8.21, p < .001. The control variables accounted for a significant 11% of the variance, R ² = .11, F(8, 194) = 2.90, p = .01, although none of the β coefficients for the control variables was individually significant. The resources accounted for an additional 25% of the variance, R ²change = .25, F change(5, 189) = 15.03, p < .001. Each of the resources was a significant predictor of engagement, with the exception of uncertainty adaptability. Optimism played the largest role, β = .34, t(202) = 4.97, p < .001. Work stress adaptability played the second largest role, although surprisingly the relationship was negative, β = −.28, t(202) = −3.47, p = .001. Both social support, β = .14, t(202) = 2.13, p = .04, and career management self-efficacy, β = .18, t(202) = 2.44, p = .02, played smaller roles in the prediction of engagement.

Hypotheses 3: It was also hypothesized that the resources of social support, optimism, work stress adaptability, uncertainty adaptability, and career management self-efficacy would moderate the relationships between the job demands and the three burnout subscales. We used hierarchical multiple regression to examine possible moderator effects, as suggested by Frazier, Tix, and Barron (2004). The variables in each equation were centered in order to reduce problems associated with multicollinearity (Aiken & West, 1991). Product terms were created by multiplying the centered predictor and moderator variables. A single multiple regression analysis was conducted with the centered job demand variables entered in Step 1, the centered moderator variables entered in Step 2, and the product terms entered in Step 3. The significance of the moderation effect was tested by examining the significance of the R ² change between Steps 2 and 3. This was conducted for each of the three burnout subscales. The moderation effects were not found to be significant for exhaustion, R ² change = .02, F change(10, 186) = .63, p = .78, cynicism, R ² change = .04, F change(10, 186) = 1.00, p = .44, or professional efficacy, R ² change = .05, F change(10, 186) = 1.31, p = .23, indicating that the resources do not moderate the relationship between the job demands and burnout.

Hypotheses 4: The possible mediation effects of engagement were tested according to the recommendations of Preacher and Hayes (2004). A nonparametric bootstrapping approach was used to circumvent problems associated with nonnormality and the smaller sample size. Specifically, we used an SPSS macro (Preacher & Hayes, 2004) to conduct 5,000 bootstrap resamples testing the significance of the indirect effects of the resources, via the possible mediating effect of engagement, on burnout. According to Preacher and Hayes, if the 95% confidence interval for the bootstrapped results of the indirect effect does not contain 0, than the indirect effect is considered significant at the .05 level, indicating that the effect of the resources on burnout is (partially) mediated by engagement. Tables 2 –4 present the tests of mediation for the relationship between each of the resources and the three burnout subscales, with engagement as a possible mediator. Using 95% confidence intervals, engagement was found to mediate the relationship between social support and cynicism burnout [−.39, −.08], social support and professional efficacy [.06, .29], career management self-efficacy and cynicism burnout [−.59, −.16], career management self-efficacy and professional efficacy [.11, .40], optimism and cynicism burnout [−.46, −.14], and optimism and professional efficacy [.14, .35].

Table 2.

Results of Tests for the Mediating Effects of Engagement on the Relationship Between Each of the Resources and Exhaustion Burnout.

Independent variable		Normal theory tests				Bootstrapped results for indirect effects [95% CI]
	Path	Coefficient	SE	t	p	SE	Lower	Upper
Social support	b(YX)	−.37	.15	−2.4	.02	.05	[−.19, .00]
	b(MX)	.45	.11	3.92	<.01
	b(YM.X)	−.21	.10	−2.14	.03
	b(YX.M)	−.28	.16	−1.77	.08
CMSE	b(YX)	−.74	.21	−3.57	<.01	.08	[−.28, .04]
	b(MX)	.75	.15	5.03	<.01
	b(YM.X)	−.16	.10	−1.63	.10
	b(YX.M)	−.62	.22	−2.84	<.01
Optimism	b(YX)	−.42	.12	−3.35	<.01	.07	[−.22, .05]
	b(MX)	.63	.09	7.40	<.01
	b(YM.X)	−.14	.10	−1.32	.19
	b(YX.M)	−.34	.14	−2.36	.02
WSA	b(YX)	−.99	.09	−10.88	<.01	.04	[−.01, .16]
	b(MX)	−.16	.08	−1.87	.06
	b(YM.X)	−.37	.07	−5.09	<.01
	b(YX.M)	−1.05	.09	−12.10	<.01
UA	b(YX)	−.97	.20	−4.80	<.01	.04	[−.12, .12]
	b(MX)	.04	.16	0.24	.81
	b(YM.X)	−.25	.09	−2.76	.01
	b(YX.M)	−.96	.20	−4.84	<.01

Note. CMSE = career management self-efficacy; UA = uncertainty adaptability; WSA = work stress adaptability; b(YX) = total effect of the independent variable on the dependent variable; b(MX) = effect of the independent variable on the proposed mediator; b(YM.X) = effect of the proposed mediator on the dependent variable controlling for the independent variable; b(YX.M) = effect of the independent variable on the dependent variable controlling for the proposed mediator.

Table 3.

Results of Tests for the Mediating Effects of Engagement on the Relationship Between Each of the Resources and Cynicism Burnout.

Independent variable		Normal theory tests				Bootstrapped results for indirect effects [95% CI]
	Path	Coefficient	SE	t	p	SE	Lower	Upper
Social support	b(YX)	−.71	.15	−4.78	<.01	.08	[−.39, −.08]
	b(MX)	.45	.11	3.92	<.01
	b(YM.X)	−.51	.09	−5.80	<.01
	b(YX.M)	−.49	.14	−3.42	<.01
CMSE	b(YX)	−1.01	.20	−5.05	<.01	.11	[−.59, −.16]
	b(MX)	.75	.15	5.03	<.01
	b(YM.X)	−.49	.09	−5.46	<.01
	b(YX.M)	−.65	.20	−3.26	<.01
Optimism	b(YX)	−.66	.12	−5.43	<.01	.08	[−.46, −.14]
	b(MX)	.63	.09	7.39	<.01
	b(YM.X)	−.46	.10	−4.80	<.01
	b(YX.M)	−.37	.13	−2.85	<.01
WSA	b(YX)	−.66	.10	−6.27	<.01	.07	[−.02, .26]
	b(MX)	−.16	.08	−1.87	.06
	b(YM.X)	−.67	.07	−8.94	<.01
	b(YX.M)	−.76	.09	−8.51	<.01
UA	b(YX)	−.71	.21	−3.43	<.01	.13	[−.26, .24]
	b(MX)	.04	.16	0.24	.81
	b(YM.X)	−.58	.08	−6.93	<.01
	b(YX.M)	−.69	.19	−3.70	<.01

Table 4.

Results of Tests for the Mediating Effects of Engagement on the Relationship Between Each of the Resources and Professional Efficacy.

Independent variable		Normal theory tests				Bootstrapped results for indirect effects [95% CI]
	Path	Coefficient	SE	t	p	SE	Lower	Upper
Social support	b(YX)	.30	.09	3.30	<.01	.06	[.06, .29]
	b(MX)	.44	.11	3.92	<.01
	b(YM.X)	.37	.05	7.22	<.01
	b(YX.M)	.14	.08	1.63	.10
CMSE	b(YX)	.67	.12	5.68	<.01	.07	[.11, .40]
	b(MX)	.75	.15	5.03	<.01
	b(YM.X)	.33	.05	6.45	<.01
	b(YX.M)	.43	.11	3.71	<.01
Optimism	b(YX)	.26	.08	3.66	<.01	.05	[.14, .35]
	b(MX)	.63	.09	7.40	<.01
	b(YM.X)	.38	.06	6.79	<.01
	b(YX.M)	.03	.08	0.45	.65
WSA	b(YX)	.18	.07	2.64	.01	.04	[−.16, .02]
	b(MX)	−.16	.08	−1.87	.06
	b(YM.X)	.42	.05	8.71	<.01
	b(YX.M)	.24	.06	4.21	<.01
UA	b(YX)	.52	.12	4.22	<.01	.09	[−.15, .19]
	b(MX)	.04	.16	0.24	.81
	b(YM.X)	.39	.05	8.24	<.01
	b(YX.M)	.50	.11	4.74	<.01

Discussion

It appears increasingly important that vocational psychologists understand the factors that may be protective for individuals during organizational transitions, given the increased prevalence of layoffs over the past several years (U.S. Department of Labor, 2012) and their stressful effects on both layoff victims and survivors (Noer, 2009). The current study examined factors that may potentially be protective for individuals who remain working at downsizing organizations. The findings of this study are discussed below as well as the study’s limitations, implications, and recommendations for future research.

Job Demands and Burnout

As expected, both job insecurity and work overload were positively related to the exhaustion and cynicism forms of burnout. This finding is in accordance with the bulk of the research on the JD-R model (Bakker & Demerouti, 2007), which supports a positive relationship between job demands and burnout (e.g., Bakker et al., 2005). It appears that interventions specifically targeted at helping individuals cope with job insecurity and work overload may possibly improve outcomes for layoff survivors.

Resources and Engagement

The resources of social support, optimism, and career management self-efficacy each had a positive relationship with engagement, as would be expected based on prior theory and research (e.g., Aspinwall & Taylor, 1997; Lim, 1996; van den Heuvel, Demerouti, Schaufeli, & Bakker, 2010; Xanthopoulou et al., 2007). Contrary to hypotheses, career adaptability did not have a positive relationship with engagement. This is surprising, as previous research relates career adaptability to positive outcomes, including an increased sense of power and life satisfaction (Hirschi, 2009). However, Klehe, Zikic, van Vianen, and de Pater (2011) suggest that career transitions actually trigger career adaptability in the form of forward-looking career behaviors, such as career exploration. These behaviors may help individuals become more independent from their current position, therefore decreasing engagement as they explore other career options and contemplate exiting their current position. This is in agreement with past research by Ito and Brotheridge (2005), who found that career adaptability was related to higher turnover intentions, and who described career adaptability as a “two-edged sword” (p.14). Qualitative research also suggests that adaptability involves forward-looking behaviors and planning the details of the next career move, even when transition is not imminent (Ebberwein, Krieshok, Ulven, & Prosser, 2004), which may reduce work engagement. Further research is needed to examine this relationship.

Both uncertainty adaptability and work stress adaptability had small-to-moderate negative relationships with burnout. Savickas (1997) states that career adaptability encompasses the readiness to cope with unpredictable changes in work. Therefore, it appears that when individuals feel confident that they can cope with organizational transitions effectively, they are less likely to experience the emotional exhaustion, cynicism, and decreases in accomplishment associated with burnout (Fernet, Guay, & Senecal, 2004; Ito & Brotheridge, 2003).

Moderation Effects

The resources examined did not display the hypothesized moderating effects between the demands and burnout. Previous research has also reported conflicting results related to the buffering nature of resources (Bakker et al., 2004; Xanthopoulou et al., 2007). One possible explanation regarding why these particular resources failed to have interaction effects relates to the concept of optimal match between demands and resources (de Jonge & Dormann, 2003). Some scholars have suggested that resources be evaluated more carefully prior to being selected as salient for a given demand (Cooper, Dewe, & O’Driscoll, 2001; de Jonge & Dormann, 2003). For instance, social support or optimism may be beneficial, but they may not provide the specific ingredients needed to cope effectively with job insecurity.

Mediation Effects

Engagement played a mediating role between many of the resources and burnout. Engagement mediated the relationships between the resources of social support, optimism, and career management self-efficacy, and the cynicism and professional efficacy forms of burnout. In other words, an increase in these resources is related to an increase in engagement, which in turn reduces burnout. This is in agreement with prior research suggesting that resources may actually have an indirect relationship with important outcomes due to their facilitation of engagement, which in turn works as a mediator (e.g., Salanova & Schaufeli, 2008). This is also consistent with the broaden-and-build theory of positive emotions developed by Frederickson (2001), which posits that positive emotions (such as those experienced when one is engaged at work) may help individuals utilize improved coping strategies, possibly leading to more proactive work behavior and a therefore decrease in burnout. In addition, some research even suggests that increased engagement may lead to positive “gain spirals,” meaning that as engagement increases, the opportunity to accumulate more resources also increases, such that resources and engagement are reciprocally enhancing (Hakanen, Perhoniemi, & Toppinen-Tanner, 2008).

Implications for Practice

The mediating role engagement plays in the relationship between resources and burnout has important implications, suggesting that career counselors should help foster resources that may enhance engagement within their clients. Regarding personal resources, optimism and confidence in managing one’s career are two important characteristics that are linked to engagement and improved work outcomes. Career counselors can help foster these characteristics in clients through the use of active problem solving, encouragement and affirmations, and role modeling positive attitudes regarding clients’ career development (Scholl & Cascone, 2010). In terms of the job resource of social support, research suggests that management can play a key role in helping layoff survivors adjust postdownsizing, particularly if they receive training in basic helping skills and how to empower others (Mishra, Mishra, & Spreitzer, 2009). Psychologists who work with organizations should encourage employers to provide this training to those in frontline management positions.

Limitations

This study has several limitations that should be noted. The first limitation involves the sampling procedures. Participants for this study were recruited online, and some received a 5-$ monetary compensation for their participation. While it is impossible to accurately estimate the response rate because snowball sampling was used, it was most likely under 10%. Thus, self-selection bias played a role in the study’s results. In addition, recruitment from professional networking sites made it difficult to control for double entry, that is, participants could hypothetically come back and take the survey again if they provided a different e-mail address. Furthermore, because participants were not recruited from a single organization, it became more difficult to control for confounding variables, such as the magnitude of the layoffs. A second area of limitation relates to the internal consistency of the uncertainty adaptability subscale, which fell slightly below .70. It is questionable whether this scale measured the specific construct of interest, and a more precise measure may have provided more compelling results. A third limitation is the sample size, as larger samples may be needed to detect significant effects when dealing with smaller effect sizes (Frazier, Tix, & Barron, 2004). Perhaps, a larger sample would have been better able to detect significant interaction effects.

Recommendations for Future Research

One critical area for future research involves the development of effective interventions for working with layoff survivors. Despite a few exceptions (e.g., Foley & Smith, 1999; Noer, 2009), few scholars have examined this topic. While interventions such as focus groups, training programs, stress management workshops, and individual and group counseling have been recommended, little is known about the relative efficacy of these options for this population. Research is also needed to examine possible multicultural differences in layoff survivors’ reactions and coping processes. Despite some exceptions, the majority of layoff survivor samples have been predominantly White or have not listed the racial/ethnic breakdown of participants, thus limiting knowledge regarding the generalizability of their findings. Some studies suggest that factors such as gender or cultural values may affect survivors’ reactions (Armstrong-Stassen, 1994; Probst & Lawler, 2006; Westman, 2000) and continued research is needed to examine these and other dimensions of cultural identity as they relate to surviving a layoff.

Footnotes

Acknowledgments

The author wishes to express gratitude to Dr. Romila Singh for her support and guidance throughout this research study.

Authors’ Note

Portions of this article were adapted from the author’s dissertation written in partial fulfillment of the requirements for a doctoral degree at the University of Wisconsin–Milwaukee.

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.

References

Aiken

L. S.

West

S. G.

(1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.

Armstrong-Stassen

(1994). Coping with transition: A study of layoff survivors. Journal of Organizational Behavior, 15, 597–621.

Aspinwall

L. G.

Taylor

S. E.

(1997). A stitch in time: Self-regulation and proactive coping. Psychological Bulletin, 121, 417–436.

Bakker

Demerouti

(2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22, 309–328.

Bakker

A. B.

Demerouti

Euwema

(2005). Job resources buffer the impact of job demands on burnout. Journal of Occupational Health Psychology, 10, 170–180.

Bakker

A. B.

Demerouti

Verbeke

(2004). Using the job demands-resources model to predict burnout and performance. Human Resource Management, 43, 83–104.

Brockner

(1988). The effects of work layoffs on survivors: Research, theory and practice. In Cummings

B. M.

(Ed.), Research in organizational behavior (pp. 213–255). Greenwich, England: JAI Press.

Brockner

DeWitt

Grover

Reed

(1990). When it is especially important to explain why: Factors affecting the relationship between managers’ explanations of a layoff and survivors’ reactions to the layoff. Journal of Experimental Social Psychology, 26, 389–407.

Brockner

Grover

Reed

T. F.

Dewitt

(1992). Layoffs, job insecurity, and survivors’ work effort: Evidence of an inverted-U relationship. Academy of Management Journal, 35, 413–425.

10.

Burke

R. J.

Greenglass

E. R.

(2000). Effects of hospital restructuring on full time and part time nursing staff in Ontario. International Journal of Nursing Studies, 37, 163–171.

11.

Caplan

R. D.

Cobb

French

J. R. P.

Van Harrison

Pinneau

S. R.

(1980). Job demands and worker health. Ann Arbor: University of Michigan, Institute of Social Research.

12.

Carlson

Perrewe

(1999). The role of social support in the stressor-strain relationship: An examination of work-family conflict. Journal of Management, 25, 513.

13.

Cascio

W. F.

(1993). Downsizing: What do we know? What have we learned? Academy of Management Executive, 78, 95–104.

14.

Cooper

C. L.

Dewe

P. J.

O’Driscoll

M. P.

(2001). Organizational stress: A review and critique of theory, research, and applications. Thousand Oaks, CA: Sage.

15.

Day

Allen

T. D.

(2004). The relationship between career motivation and self-efficacy with protégé career success. Journal of Vocational Behavior, 64, 72–91.

16.

de Jonge

Dormann

(2003). The DISC model: Demand-induced strain compensation mechanisms in job stress. In Dollard

M. F.

Winefield

A. H.

Winefield

H. R.

(Eds.), Occupational stress in the service professions (pp. 43–74). New York, NY: Taylor & Francis.

17.

Demerouti

Bakker

A. B.

Nachreiner

Schaufeli

W. B.

(2001). The job demands-resources model. Journal of Applied Psychology, 86, 499–512.

18.

Ebberwein

C. A.

Kreishok

T. S.

Ulven

J. C.

Prosser

E. C.

(2004). Voices in transition: Lessons on career adaptability. Career Development Quarterly, 52, 292–308.

19.

Fernet

Guay

Senecal

(2004). Adjusting to job demands: The role of work self-determination and job control in predicting burnout. Journal of Vocational Behavior, 65, 39–56.

20.

Foley

P. F.

Smith

J. E.

(1999). A model psychoeducational group for survivors of organizational downsizing. Journal for Specialists in Group Work, 24, 354–368.

21.

Frazier

P. A.

Tix

A. P.

Barron

K. E.

(2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51, 115–134.

22.

Frederickson

B. L.

(2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56, 218–226.

23.

Hakanen

Bakker

A. B.

Shaufeli

(2006). Burnout and work engagement among teachers. Journal of School Psychology, 43, 495–513.

24.

Hakanen

J. J.

Perhoniemi

Toppinen-Tanner

(2008). Positive gain spirals at work: From job resources to work engagement, personal initiative and work-unit innovativeness. Journal of Vocational Behavior, 73, 78–91.

25.

Hirschi

(2009). Career adaptability development in adolescence: Multiple predictors and effect on sense of power and life satisfaction. Journal of Vocational Behavior, 74, 145–155.

26.

Ito

J. K.

Brotheridge

C. M.

(2003). Resources, coping strategies, and emotional exhaustion: A conservation of resources perspective. Journal of Vocational Behavior, 63, 490–509.

27.

Ito

J. K.

Brotheridge

C. M.

(2005). Does supporting employees’ career adaptability lead to commitment, turnover, or both? Human Resource Management, 44, 5–19.

28.

Kalimo

Taris

T. W.

Schaufeli

W. B.

(2003). The effects of past and anticipated future downsizing on survivor well-being: An equity perspective. Journal of Occupational Health Psychology, 8, 91–109.

29.

Kaufman

G. M.

Beehr

T. A.

(1989). Occupational stress, individual strains and social supports among police officers. Human Relations, 42, 185–197.

30.

Kivimäki

Vahtera

Griffiths

Cox

Thompson

(2000). Sickness absence and organizational downsizing. In Burke

R. J.

Cooper

C. L.

(Eds.), The organization in crisis (pp. 78–94). Oxford, England: Wiley-Blackwell.

31.

Klehe

Zikic

van Vianen

de Pater

(2011). Career adaptability, turnover and loyalty during organizational downsizing. Journal of Vocational Behavior, 79, 217–229.

32.

Kossek

Roberts

Fisher

DeMarr

(1998). Career self-management: A quasi-experimental assessment of the effects of a training intervention. Personnel Psychology, 51, 935–960.

33.

Kristensen

T. S.

Hannerz

Høgh

Borg

(2005). The Copenhagen psychosocial questionnaire (COPSOQ)—A tool for the assessment and improvement of the psychosocial work environment. Scandinavian Journal of Work, Environment, and Health, 3, 438–449.

34.

Leiter

M. P.

Schaufeli

W. B.

(1996). Consistency of the burnout construct across occupations. Anxiety, Stress, and Coping, 9, 229–243.

35.

Lim

V. K. G.

(1996). Job insecurity and its outcomes: Moderating effects of work-based and nonwork-based social support. Human Relations, 49, 171.

36.

Maslach

(2003). Job burnout: New directions in research and intervention. Current Directions in Psychological Science, 12, 189–192.

37.

Maslach

Jackson

S. E.

Leiter

M. P.

(1996). Maslach burnout inventory manual (3rd ed.). Palo Alto, CA: Consulting Psychologists Press.

38.

McArdle

Waters

Briscoe

J. P.

Hall

D. T.

(2007). Employability during unemployment: Adaptability, career identity and human and social capital. Journal of Vocational Behavior, 71, 247–264.

39.

Mishra

Spreitzer

(2009). How to downsize your company without downsizing morale. MIT Slone Management Review, Spring, 39–44.

40.

Moore

Grunberg

Greenberg

E. S.

(2004). “Repeated downsizing contact: The effects of similar and dissimilar layoff experiences on work and well-being outcomes. Journal of Occupational Health Psychology, 9, 247–257.

41.

Noer

D. M.

(2009). Healing the wounds: Overcoming the trauma of layoffs and revitalizing downsizing organizations. San Francisco, CA: Jossey-Bass.

42.

Nübling

Stößel

Hasselhorn

H. M.

Michaelis

Hofmann

(2006). Measuring psychological stress and strain at work—Evaluation of the COPSOQ Questionnaire in Germany. GMS Psycho-Social-Medicine, 3, Doc05.

43.

Parker

S. K.

Chmiel

Wall

T. D.

(1997). Work characteristics and employee well-being within a context of strategic downsizing. Journal of Occupational Health Psychology, 2, 289–303.

44.

Pejtersen

J. H.

Kristensen

T. S.

Borg

Bjorner

J. B.

(2010). The second version of the Copenhangen Psychosocial Questionnaire. Scandinavian Journal of Public Health, 38, 8–24.

45.

Ployhart

Bliese

(2006). Individual adaptability (I-ADAPT) theory: Conceptualizing the antecedents, consequences, and measurement of individual differences in adaptability. Advances in Human Performance and Cognitive Engineering Research, 6, 3–39.

46.

Preacher

K. J.

Hayes

A. F.

(2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, and Computers, 36, 717–731.

47.

Probst

Lawler

(2006). Cultural values as moderators of employee reactions to job insecurity: The role of individualism and collectivism. Applied Psychology: An International Review, 55, 234–254.

48.

Robbins

S. P.

(1999). Layoff survivor sickness: A missing topic in organizational behavior. Journal of Management Education, 23, 31–43.

49.

Saks

(2006). Antecedents and consequences of employee engagement. Journal of Managerial Psychology, 21, 600–619.

50.

Salanova

Schaufeli

W. B.

(2008). A cross-national study of work engagement as a moderator between job resources and proactive behavior. International Journal of Human Resource Management, 19, 116–131.

51.

Savickas

(1997). Career adaptability: An integrative construct for life-span, life-space theory. Career Development Quarterly, 45, 247–259.

52.

Schaufeli

Bakker

(2004). Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study. Journal of Organizational Behavior, 25, 293–315.

53.

Schaufeli

Bakker

Salanova

(2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66, 701–716.

54.

Schaufeli

Leiter

Maslach

Jackson

(1996). MBI-General survey. Maslach Burnout Inventory Manual, 3, 19–26.

55.

Scheier

M. F.

Carver

C. S.

(1992). Effects of optimism on psychological and physical well-being: Theoretical overview and empirical update. Cognitive Therapy and Research, 16, 201–228.

56.

Scheier

Carver

Bridges

(1994). Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): A reevaluation of the life orientation test. Journal of Personality and Social Psychology, 67, 1063–1063.

57.

Scholl

M. S.

Cascone

(2010). The Constructivist resume: Promoting the career adaptability of graduate students in counseling programs. Career Development Quarterly, 59, 180–189.

58.

Shah

P. P.

(2000). Network destruction :The structural implications of downsizing. Academy of Management Journal, 43, 101–112.

59.

Tabatchnik

B. G.

Fidell

L. S.

(2007). Using multivariate statistics (5th ed.). Boston, MA: Pearson/Allyn and Bacon.

60.

Taris

T. W.

Schreurs

P. J. G.

Schaufeli

W. B.

(1999). Construct validity of the Maslach burnout inventory-general survey: A two-sample examination of its factor structure and correlates. Work and Stress, 13, 223–237.

61.

U.S. Department of Labor, Bureau of Labor Statistics. (2009). Mass layoff statistics. Retrieved from http://www.bls.gov/schedule/archives/mslo_nr.htm#2009

62.

U.S. Department of Labor, Bureau of Labor Statistics. (2011). Mass layoffs summary. Retrieved from http://www.bls.gov/news.release/mslo.nr0.htm

63.

U.S. Department of Labor, Bureau of Labor Statistics (2012). Extended mass layoffs-first quarter 2012. Retrieved from http://www.bls.gov/news.release/pdf/mslo.pdf

64.

van den Heuvel

Demerouti

Schaufeli

W. B.

Bakker

A. B.

(2010). Personal resources and work engagement in the face of change. In Houdmont

Leke

(Eds.), Contemporary occupational health psychology: Global perspective on research and practice (Vol. 1, pp. 124–150). Malden, MA: John Wiley.

65.

Wessel

J. L.

Ryan

A. M.

Oswald

F. L.

(2008). The relationship between objective and perceived fit with academic major, adaptability, and major-related outcomes. Journal of Vocational Behavior, 72, 363–376.

66.

Westman

(2000). Gender and job insecurity. In Burke

Cooper

(Eds.), The organization in crisis (pp. 119–131). Hoboken, NJ: Wiley-Blackwell.

67.

Xanthopoulou

Bakker

A. B.

Demerouti

Schaufeli

W. B.

(2007). The role of personal resources in the job demands-resources model. International Journal of Stress Management, 14, 121–141.

68.

Xanthopoulou

Bakker

A. B.

Demerouti

Schaufeli

W. B.

(2009). Reciprocal relationships between job resources, personal resources, and work engagement. Journal of Vocational Behavior, 74, 235–244.