Journal of Occupational Health Psychology 2015, Vol. 20, No. 1, 62–71

© 2014 American Psychological Association 1076-8998/15/$12.00 http://dx.doi.org/10.1037/a0037675

Dynamics of a Wellness Program: A Conservation of Resources Perspective Sung Doo Kim and Elaine C. Hollensbe

Catherine E. Schwoerer

University of Cincinnati

University of Kansas

Jonathon R. B. Halbesleben This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

University of Alabama We leverage conservation of resources theory to explain possible dynamics through which a holistic wellness program results in positive longer-term outcomes. Specifically, we hypothesize that wellness self-efficacy at the end of a wellness program will create a positive resource gain spiral, increasing psychological availability (a sense of having cognitive, physical, and emotional resources to engage oneself) 6 months later, and career satisfaction, 1 year later. To test these hypotheses, using a time-lagged with control group design, we gathered questionnaire data from 160 Episcopal priests who participated in a 10-day off-site wellness program. We developed a scale measuring self-efficacy in the 4 wellness areas the program was designed to improve: physical, spiritual, financial, and vocational. Our findings provide evidence from a field setting of a relatively untested tenet of conservation of resources theory, resource gain spirals. The wellness program that we studied served as an opportunity for participants to gain new resources in the form of wellness self-efficacy, which in turn helped participants experience positive outcomes over time. We discuss theoretical and practical implications of the findings. Keywords: career satisfaction, conservation of resources theory, self-efficacy, wellness program

ness, more attention is needed to better understand how they work (Parks & Steelman, 2008). Little research has examined the dynamics through which wellness programs may result in positive employee-related outcomes. Such an understanding may help organizations design wellness programs that increase positive employee outcomes long term. To address this gap, we draw on conservation of resources theory (Hobfoll, 1989; Hobfoll & Shirom, 1993). According to this theory, individuals who hold greater resources are more capable of resource gain, and enrichment of resources in these individuals results in a cycle in which existing gains beget future gains generating “gain spirals” (Hobfoll, 1989; Hobfoll, 2001; Westman, Hobfoll, Chen, Davidson, & Laski, 2004). Resource gain spirals have received relatively little attention even though conservation of resources theory identifies them as playing a critical motivational role (Hakanen, Perhoniemi, & Toppinen-Tanner, 2008; Mäkikangas, Bakker, Aunola, & Demerouti, 2010). A key unknown in the area of gain spirals is how resource gains start in the first place (Halbesleben, Neveu, Paustian-Underdahl, & Westman, 2014). We argue that wellness programs may serve as a stimulus in triggering a resource gain cycle by increasing wellness selfefficacy, a resource we define as the belief in one’s ability to plan for and manage one’s wellness. This initial resource gain subsequently fuels psychological availability, the belief that one has the cognitive, physical, and emotional resources to engage in work (Kahn, 1990; May, Gilson, & Harter, 2004), and career satisfaction over time. To capture this hypothesized resource gain cycle over time, we used a time-lagged with control group design. We studied 160 Episcopal priests who participated in a wellness program

A growing number of organizations offer wellness programs to employees to improve their physical and psychological well-being (92% of employers with 200 or more employees [Mattke, Schnyer, & Van Busum, 2012]). Positive effects of wellness programs include reduced absenteeism (Daley & Parfitt, 1996; Watson & Gauthier, 2003) and turnover (Cox, Shephard, & Corey, 1981), and increased job satisfaction (Ho, 1997; Norvell & Belles, 1993) and productivity (Bernacki & Baun, 1984; Falkenberg, 1987; Goetzel et al., 2002). Yet, not all empirical evidence on their effectiveness has been conclusive. For example, Erfurt, Foote, and Heirich (1992) found that wellness programs employing fitness facilities were successful in some cases, but not others. Given the prevalence of wellness programs and mixed results on their effective-

This article was published Online First August 25, 2014. Sung Doo Kim and Elaine C. Hollensbe, Department of Management, Lindner College of Business, University of Cincinnati; Catherine E. Schwoerer, Department of Management, School of Business, University of Kansas; Jonathon R. B. Halbesleben, Management Department, Culverhouse College of Commerce and Business Administration, University of Alabama. We express our gratitude to Bill Craddock, Senior Vice President/ Managing Director for the Church Pension Group Education and Wellness, for allowing us access to study the CREDO wellness program, as well as for providing partial funding for our work. Correspondence concerning this article should be addressed to Sung Doo Kim, Department of Management, Lindner College of Business, University of Cincinnati, 538 Lindner Hall, Cincinnati, OH 45221-0165. E-mail: [email protected] 62

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DYNAMICS OF A WELLNESS PROGRAM

designed to improve wellness in four key areas (physical, spiritual, financial, and vocational). Our study contributes to the literature in the following ways. First, we contribute to the wellness literature by investigating the process through which wellness programs may lead to positive outcomes. Given the predominant focus of current studies on what outcomes wellness programs may produce (Parks & Steelman, 2008), we attempt to show how and why that might be the case. We also advance knowledge on conservation of resource theory by examining a largely untested tenet (Hobfoll, 2011), resource gain spirals. Through surveying wellness program participants over multiple time periods, we are also able to observe the long-term effects of the program. This also contributes to the careers literature through demonstrating the effects of wellness self-efficacy on psychological availability and career satisfaction over time.

Theory and Hypotheses Wellness and Wellness Programs Although researchers have conceptualized wellness in multiple ways, one common conceptualization is that wellness is a positive state of being in terms of physical and mental health (Roscoe, 2009), a view consistent with a key reason why organizations offer wellness programs—to improve employee health, thereby lowering absenteeism and increasing job satisfaction (Parks & Steelman, 2008). Wellness programs can also mitigate presenteeism, loss of performance attributable to health problems, including poor work quality and diminished job and life satisfaction (Lalic´ & Hromin, 2012). The scope of wellness programs ranges from simply handing out pamphlets to more comprehensive programs such as onsite fitness centers and training courses (Devries, 2010; Gebhardt & Crump, 1990). We focus on a comprehensive wellness program that includes a wide variety of activities. With such programs, training often takes place off site for an extended period of time and addresses multiple wellness issues.

Conservation of Resources Perspective Conservation of resources theory (Hobfoll, 1989; Hobfoll & Shirom, 1993) is often used as a framework for stress and burnout research (e.g., Brotheridge & Lee, 2002; Grandey & Cropanzano, 1999; Halbesleben, 2006; Neveu, 2007). According to the theory, individuals seek to obtain, retain, protect, and foster valued resources and minimize any threats of resource loss. Those valued resources can be classified as objects (e.g., money), conditions (e.g., supportive work environment), energy-related (e.g., knowledge), and personal (e.g., self-efficacy). Threats to resource loss occur when individuals are exposed to challenging work and life demands for an extended period of time with no opportunity to gain new resources, which can result in resource depletion and burnout (Hobfoll & Shirom, 1993; Wright & Cropanzano, 1998). Given these negative effects, organizations are increasingly seeking ways to avoid resource losses and provide employees with resources to improve well-being (Halbesleben & Buckley, 2004). Particularly relevant for wellness programs is the resource investment principle, which suggests that individuals are motivated to acquire additional resources by investing the resources they currently have (Hobfoll, 1989). Further, individuals who possess

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resources are more capable of resource gain and less vulnerable to resource loss (Hobfoll, 2001). Resource investment is likely to lead to further positive outcomes that accumulate over time, a phenomenon called gain spirals in which a virtuous cycle, set in motion by initial resource gain, leads to further positive outcomes (Halbesleben & Wheeler, 2012; Hobfoll, 2001). For example, individuals who make an effort to exercise (i.e., resource investment) are more likely to stay healthy (i.e., resource gain) and in turn are more likely to engage at work over time (Gebhardt & Crump, 1990). To advance our understanding of resource gain spirals, more empirical study is needed. Most studies on resource gain focus on condition resources, which are largely related to context, both the job (e.g., autonomy, performance feedback) and supervisor or coworker support (e.g., Hakanen, Peeters, & Perhoniemi, 2011; Halbesleben & Wheeler, 2012; Llorens, Schaufeli, Bakker, & Salanova, 2007; Mäkikangas et al., 2010; Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2009), or home (e.g., family or friend support) (e.g., Hakanen et al., 2011). Positive outcomes examined include work engagement (e.g., Hakanen et al., 2011; Llorens et al., 2007; Xanthopoulou et al., 2009), flow at work (e.g., Mäkikangas et al., 2010), financial returns (e.g., Xanthopoulou et al., 2009), and marital satisfaction (e.g., Hakanen et al., 2011). Although these prior studies have provided rare evidence on gain spirals, little is known about how people might initiate a positive gain cycle utilizing personal or individual-based resources. Our study attempts to fill this gap by investigating how individuals may create positive gain spirals—through successful experiences in wellness programs. Further, we seek to extend the repertoire of possible outcomes to include psychological availability and career satisfaction.

Wellness Self-Efficacy Self-efficacy refers to “people’s belief about their capabilities to produce designated levels of performance that exercise influence over events that affect their lives” (Bandura, 1994, p. 71). We focus on specific (wellness) self-efficacy rather than general selfefficacy because of its relatively greater malleability through training interventions (e.g., Mencl, Tay, Schwoerer, & Drasgow, 2012; Schwoerer, May, Hollensbe, & Mencl, 2005). Self-efficacy is derived from four sources of information: enactive mastery experience (experiencing success on similar tasks in the past), vicarious experience (observing a ‘similar other’ successfully perform a task), verbal persuasion (receiving encouragement and support from others), and physiological states (reducing fear or anxiety that can impede performance) (Bandura, 1997). Well-designed wellness programs expose participants to these self-efficacy sources. First, through creating opportunities to succeed at wellness-related tasks, they allow participants to experience enactive mastery. By exposure to others who have achieved a high-level of wellness, participants gain vicarious experience. In addition, coaches provide tools for achieving wellness. Finally, experiences and learning during the programs help participants recognize physiological and emotional cues that can create challenges in meeting wellness goals. Wellness programs in which these components are included increase participants’ specific wellness self-efficacy, the belief that they have the ability and resources needed to plan and manage their well-being. To test this

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baseline premise, we developed a wellness self-efficacy measure that included items to tap self-efficacy in areas the wellness training we studied was targeted to improve. Given that selfefficacy is among the resources that Hobfoll (1989) empirically identified, wellness-self-efficacy can be conceptualized as a resource gained by participating in the wellness programs. Hypothesis 1: Participants in the wellness program will experience an increase in wellness self-efficacy resources post-program.

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Psychological Availability We believe that participants who develop wellness self-efficacy are more likely over time to experience greater psychological availability, a belief that one has the physical, emotional, or cognitive resources to engage in work given other competing life activities (Kahn, 1990; May et al., 2004). Heightened wellness self-efficacy may lead participants to undertake activities in other aspects of their life with renewed energy and confidence. As noted earlier, gaining resources in one area (wellness) can lead to a spiral in which resources are gained in other areas. In fact, previous studies have linked self-efficacy, a resource, with work engagement, a positive work-related state of mind that is characterized by vigor, dedication, and absorption (Schaufeli & Bakker, 2004, p. 295). The limited studies done on resource gain spirals have consistently found that initial resource gains (e.g., from coaching) lead to greater work engagement (e.g., Hakanen et al., 2011; Xanthopoulou et al., 2009). So, we can see the impact of one resource, self-efficacy, in generating beliefs that one has the resources and energy to engage in work. Further, empirical evidence on self-efficacy suggests a link between self-efficacy and psychological availability. First, researchers have linked self-efficacy beliefs with positive affective experiences and physical health (Schwerdtfeger, Konermann, & Schönhofen, 2008). These results may be attributable, in part, to the renewed energy and resources that accompany self-efficacy, which create a sense that one has the physical, emotional, and cognitive resources to succeed. Similarly, self-efficacy has been found to be an important predictor of a number of health behaviors (e.g., smoking cessation, reducing alcohol consumption, exercise) (Ashford, Edmunds, & French, 2010). To engage in these healthrelated behaviors, individuals must believe they have sufficient resources. Thus, we predict that wellness self-efficacy, a resource gained through a wellness program, will result in an increase in other physical, emotional, or cognitive resources, or psychological availability. However, resource gains or building resources likely takes time. Thus, the resource gain spiral—the effects of selfefficacy on psychological availability—will be evident down the road, several months after the program, once participants have experienced some wellness successes driven by self-efficacy. Hypothesis 2: Wellness self-efficacy at the end of the wellness program will positively affect psychological availability six months after the program.

the longer term. Specifically, we propose career satisfaction, which refers to “the evaluation of an individual’s progress toward meeting different career-related goals and career-related success” (Spurk, Abele, & Volmer, 2011, p. 315), will be increased as a result of the wellness program. Career satisfaction has been shown to relate to a broad spectrum of both one’s work and life, including well-being (Ng, Eby, Sorensen, & Feldman, 2005; Powell & Mainiero, 1992). Unlike some previous research, which has focused on job satisfaction as a result of a wellness program (Parks & Steelman, 2008), given that our study participants (priests) view careers as a calling, we focus on career satisfaction as an outcome. The priests we studied have relatively limited career options; thus, career satisfaction may be particularly important for their wellbeing. From a conservation of resources perspective, gaining a critical personal resource such as wellness self-efficacy is more likely to lead to condition resource gain in work and life domains, resulting in greater career satisfaction. In addition, social learning theory (Bandura, 1997) posits that efficacy beliefs motivate people to persist in goal pursuit even when faced with challenges. Indeed, the training literature suggests that efficacious individuals tend to apply knowledge and skills from training to their jobs (Baldwin & Ford, 1988; Blume, Ford, Baldwin, & Huang, 2010), which can have a broader impact on their satisfaction with them. Bandura (2012) further suggests that self-efficacy can help people identify effective courses of action to change the environment in a way that boosts their emotional states (Bandura, 2012). Thus, increased wellness self-efficacy may help individuals persist in goals that they set and lead to greater career satisfaction over the longer haul. Since changes in careers take time to enact, we measure the effects of wellness self-efficacy on one’s career satisfaction one year post-program. Hypothesis 3: Wellness self-efficacy at the end of the wellness program will positively affect career satisfaction one year after the program.

Method Sample and Procedure The sample was randomly selected from a roster of all active Episcopal clergy in the United States (around 8000 at the time of the study) provided by the Pension Fund of the Episcopal Church. Priests selected were invited to participate in a 10-day wellness program, approximately 30 priests per program, targeted toward improving their wellness in four areas: physical, spiritual, financial, and vocational well-being. The wellness program was designed and facilitated by an organization affiliated with the Church.1 The on-site team facilitating the wellness program included eight members: a physical health expert (a physician or nurse), two financial experts (financial planners/advisors), two spiritual experts (clergy spiritual advisers), a vocational expert (deployment officer or career counselor in the Church), a leader, and an assistant. Held at Episcopal Church conference sites around the United States, the wellness program was designed to provide a

Career Satisfaction In addition to increasing psychological availability, we expect that wellness self-efficacy will lead to further positive outcomes in

1 Two of the authors were evaluation advisors to the organization (CREDO) that designed and administered the wellness program.

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DYNAMICS OF A WELLNESS PROGRAM

healthy and safe environment for participants, away from the demands of work, to plan and discern steps they could take to increase their well-being in the four component areas. The program team ensured that participants had healthy food for all meals; bottles of water to encourage healthy drinking; daily options for walks, meditation, and enriching spiritual practices; comfortable lodging; and so forth. The idea of the program was to provide time, space, resources, role models, encouragement, guidance, and support so that participants could focus on their wellness planning. During the program, plenary sessions were provided in each of the wellness areas, with experts on hand for individual consultation. For example, the financial expert presented information on retirement planning, and then met with participants individually to review net worth statements and other financial documents. The physical health expert presented a plenary on physical wellness then held individual meetings to review the results of a wellness profile completed by each participant in advance. The vocational expert presented a plenary on turning feedback into change and held individual meetings with participants to review the results of a vocational profile (360 assessment). The spiritual expert completed a plenary on spiritual practices and held meetings to provide spiritual support and guidance. Program participants were also assigned to small groups in which they completed reflections on each component area. The small groups served as a support network for participants, both during the program and afterward. An outcome of the program was the development of a wellness action plan, an in-depth list of goals and objectives in each of the four wellness areas covered in the program. Participants completed the survey instrument for the study three months preprogram (T1), immediately post-program (T2), six months post-program (T3), and one year after the program (T4) in a time-lagged design. All of the study variables including controls were measured at T1. We also measured wellness self-efficacy at T2 and T4 while measuring psychological availability at T3 and career satisfaction at T4. The timing of the surveys was chosen for both theoretical and practical reasons. First, given our interest in resource gain spirals, we wanted to capture the effects of wellness self-efficacy at multiple points. Although we measured selfefficacy effects immediately post program, we wanted to ensure that the wellness program’s effects on our outcome variables were not merely “spikes” often seen immediately posttraining with engaging program experiences. Further, because we were proposing a spiral effect in which resources were gained down the road, we measured psychological availability six months post-program. We believed this time period would allow for us to detect the effects of wellness self-efficacy in generating physical, emotional, and cognitive resources. Finally, because we proposed career satisfaction as an outcome that develops over the longer term, we measured this variable in the final survey, one year post-program. Although participants gained career-related resources during the wellness program, we expected that the effects of these resources would not be immediately felt. That is, unlike shorter term wellness-related changes, adjustments in one’s career that would potentially impact career satisfaction take time. A practical reason for us to collect the measures when we did was that it also provided the organization with program evaluation feedback at timed intervals. With the exception of the T2 survey, all surveys were mailed to participants who were assigned an identification number, which ensured confidentiality throughout

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the study but allowed matching of responses across time. The T2 survey was administered either by the second author, who attended some of the 10-day wellness programs, or by a program administrator trained in survey administration. The four surveys were matched by participant, which yielded a sample of 160 participants over the four time periods. The average age of participants was 50 years; 67% were males, and 5% held a supervisory position as a bishop, a leader in the Episcopal Church. In addition, a control group of 30 priests who did not attend the wellness program were randomly selected from the same roster of active Episcopal clergy from which study participants were drawn. These priests were paid $100 to complete our survey on two occasions, an initial survey (T1) and a final survey one year later (T4). Responses for the two surveys were matched by participant across time periods, which yielded a sample of 27 participants over the two time periods. There was no significant difference between study and control groups in terms of demographics. This step was taken to give us greater assurance that the effects we observed were related to the wellness program itself. Given the unequal sample size between the study (160) and control group (27), it is necessary to ascertain the comparability. Levene’s test of equality of variances between two groups was not significant for study variables (all p ⬎ .05). Though unequal sample sizes can be a concern using ANOVA, this homogeneity of variance between two groups suggests that the two groups are comparable despite the different sample size (Levene, 1960). For participants in the study group, we tested whether those who dropped out from the surveys differed significantly on any demographic or study variables. The numbers of dropouts from T1 to T2, from T2 to T3, and from T3 to T4 are zero, 100, and 56, respectively. Therefore, we calculated t tests and chi-square difference Tests (a) between participants who took both the T2 and T3 surveys and those who took only the T2 survey, and (b) between those who took all subsequent surveys (T2, T3, and T4) and those who took only the T2 and T3 surveys (Goodman & Blum, 1996). No differences were found in demographic and study variables (T1).

Measures All of the items in the measures below were assessed using a 7-point Likert scale anchored by 1 ⫽ Strongly disagree and 7 ⫽ Strongly agree. Wellness self-efficacy. We developed a measure of wellness self-efficacy consisting of 14 items to tap physical (4 items), spiritual (3 items), financial (3 items), and vocational self-efficacy (4 items). This was done to align the measure with the four wellness components that the program was designed to improve. Sample items for each of the components include I am confident that I can create a plan to improve my physical condition or fitness (physical self-efficacy), I am confident that I can improve my spiritual well-being if I think it is important (spiritual selfefficacy), I am confident that I can identify steps to improve my financial position (financial self-efficacy), and I am confident that I can pursue vocational goals that I think are important (vocational self-efficacy; see the Appendix for a full list of items). The alpha reliabilities were all well within an acceptable range: physical (T1 ␣ ⫽ .85, T2 ␣ ⫽ .83, and T4 ␣ ⫽ .85), spiritual (T1 ␣ ⫽ .81, T2 ␣ ⫽ .82, and T4 ␣ ⫽ .84), financial (T1 ␣ ⫽ .85, T2 ␣ ⫽

KIM, HOLLENSBE, SCHWOERER, AND HALBESLEBEN

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.72, and T4 ␣ ⫽ .80), and vocational (T1 ␣ ⫽ .83, T2 ␣ ⫽ .83, and T4 ␣ ⫽ .88). An exploratory factor analysis was conducted on these items, and each item loaded on its corresponding factor above the 0.63 level except for one item (0.57). Given that the goal of the program was to raise overall self-efficacy, however, we developed our hypotheses about wellness self-efficacy at the overall construct level and did not consider differential effects across its dimensions. Thus, the four subscales were combined to derive a global assessment of wellness-self-efficacy. The coefficient alpha for the global assessment of wellness self-efficacy was T1 ␣ ⫽ .86, and T2 ␣ ⫽ .89, and T4 ␣ ⫽ .88. Psychological availability. Psychological availability was assessed with nine items developed by May et al. (2004) comprising three dimensions: cognitive (3 items), physical (3 items), and emotional availability (3 items). Sample items for psychological availability were I am confident in my ability to handle competing demands at work (cognitive availability), I am confident that I can handle the physical demands at work (physical availability), and I am confident in my ability to display appropriate emotions at work (emotional availability). Cronbach’s alphas for each dimension were .80 (T1) and .81 (T3) for cognitive availability, .89 (T1) and .91 (T3) for physical availability, and .77 (T1) and .81 (T3) for emotional availability. For the same reason as cited with wellnessself-efficacy above, we averaged responses to produce a total score of psychological availability. Cronbach’s alphas for this scale were .85 (T1) and .86 (T3). Psychological availability (a belief that one has the resources and energy to engage in work in general) is conceptually distinct from wellness self-efficacy (a belief in one’s ability to plan for and manage one’s wellness in particular). In addition, the former variable measures perceived ability to handle various types of work-related demands (cognitive, physical, and emotional), whereas the latter measures confidence in planning for and managing one’s wellness. However, given that both involve confidence beliefs, it was necessary to establish that the two measures were distinct. Therefore, confirmatory factor analyses were conducted to evaluate the merits of the wellness self-efficacy-psychological availability distinction. According to the CFAs, the fit of a twofactor measurement model where the covariance between wellness self-efficacy and psychological availability was unconstrained was significantly better than the fit of a single-factor model in which

the covariance between the wellness self-efficacy and psychological availability variables was set equal to one (⌬␹2 ⫽ 81.46, ⌬df ⫽ 1, p ⬍ .001). Thus, in addition to the conceptual differences regarding the focus of the two constructs, the empirical distinction between the measures was supported. Career satisfaction. We used five items developed by Greenhaus, Parasuraman, and Wormley (1990) to measure career satisfaction. Sample items included I am satisfied with the progress I have made toward meeting my overall career goals and I am satisfied with the progress I have made toward meeting my goals for income. Cronbach’s alphas were .80 (T1) and .82 (T4). Control variables. We controlled for age because people view their careers differently depending on their life stage (Judge, Cable, Boudreau, & Bretz, 1995; Veiga, 1983); thus, age may be related to career satisfaction. We also controlled for gender, since gender may also influence career satisfaction in that men have been found to enjoy some advantages over women in some career aspects such as wage levels and workplace status (Rosenfeld, 1980). Lastly, we controlled for perceived financial security and supervisory position (i.e., bishop) because career satisfaction may relate to current hierarchical position and income (Korman, Mahler, & Omran, 1983). In the latter case, we wanted to control for potential shared variance given that supervisors in this occupation undergo an election process to become a bishop; thus, they could be expected to have both higher self-efficacy and career satisfaction as a result (Judge et al., 1995). Perceived financial security was assessed with one item (i.e., I have sufficient money to live comfortably).

Results Table 1 displays the means, standard deviations, and correlations of the variables included in our study. As expected, mean levels of post-program wellness self-efficacy increased compared with preprogram levels. Also, these results revealed a strong association between wellness self-efficacy at the end of the program, and psychological availability and career satisfaction, six months and one year later, respectively. To have greater confidence that hypothesized effects came from the wellness program itself, the preprogram levels of the three study variables should be not significantly different between the

Table 1 Means, Standard Deviations, and Correlations Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

Age Gender Supervisory position Perceived financial security Wellness self-efficacy (T1) Wellness self-efficacy (T2) Wellness self-efficacy (T4) Psychological availability (T1) Psychological availability (T3) Career satisfaction (T1) Career satisfaction (T4)

M

SD

50.09 0.64 0.05 5.36 5.51 6.11 5.77 5.69 5.83 5.11 5.46

6.40 0.48 0.22 1.53 0.71 0.51 0.52 0.64 0.60 0.94 0.70

1 ⫺.04 .27ⴱⴱ .14 .01 ⫺.07 ⫺.02 .00 .08 .10 .11

2

3

4

5

6

7

8

9

10

.15ⴱ ⫺.08 ⫺.05 ⫺.06 .02 .07 .01 ⫺.16ⴱ ⫺.02

.05 ⫺.03 ⫺.14 ⫺.02 ⫺.06 ⫺.05 .04 .09

.21ⴱⴱ .10 .15ⴱ .07 .04 .44ⴱⴱ .30ⴱⴱ

.54ⴱⴱ .55ⴱⴱ .41ⴱⴱ .38ⴱⴱ .34ⴱⴱ .21ⴱⴱ

.56ⴱⴱ .45ⴱⴱ .45ⴱⴱ .28ⴱⴱ .24ⴱⴱ

.44ⴱⴱ .48ⴱⴱ .24ⴱⴱ .37ⴱⴱ

.65ⴱⴱ .34ⴱⴱ .24ⴱⴱ

.21ⴱⴱ .26ⴱⴱ

.41ⴱⴱ

Note. n ⫽ 160. Gender: 0 ⫽ female, 1 ⫽ male. Supervisory position: 0 ⫽ no, 1 ⫽ yes (bishop). T1 ⫽ 3 months before program, T2 ⫽ at the end of program, T3 ⫽ 6 months after program, T4 ⫽ 1 year after program. ⴱ p ⬍ .05, two-tailed. ⴱⴱ p ⬍ .01, two-tailed.

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DYNAMICS OF A WELLNESS PROGRAM

study and control groups whereas 1-year post-program levels should be significantly different. Thus, we ran a one-way ANOVA comparing the study and control groups on wellness self-efficacy, psychological availability, and career satisfaction at T1, and on wellness self-efficacy and career satisfaction at T4 (see Table 2). As expected, preprogram levels (T1) were not significantly different for all three variables: wellness self-efficacy (M ⫽ 5.51, SD ⫽ .71 for the study group; M ⫽ 5.44, SD ⫽ .43 for the control group, p ⬎ .05); psychological availability (M ⫽ 5.69, SD ⫽ .64 for the study group; M ⫽ 5.55, SD ⫽ .59 for the control group, p ⬎ .05); and career satisfaction (M ⫽ 5.11, SD ⫽ .94 for the study group; M ⫽ 4.77, SD ⫽ 1.02 for the control group, p ⬎ .05). Next, consistent with our expectations, we found significant differences between the study and control groups on our study variables: wellness self-efficacy (T4) (M ⫽ 5.77, SD ⫽ .52 for the study group; M ⫽ 5.54, SD ⫽ .38 for the control group, p ⬍ .05) and career satisfaction (T4) (M ⫽ 5.46, SD ⫽ .70 for the study group; M ⫽ 5.02, SD ⫽ .63 for the control group, p ⬍ .01). Hypothesis 1 states that experiencing the wellness program will result in increased wellness self-efficacy. To examine this hypothesis, we conducted a paired t test of pre- and post-program measures of wellness self-efficacy. As shown in Table 2, relative to the preprogram measure (T1), there was a significant increase in wellness self-efficacy at the end of the program (T2) (t ⫽ ⫺12.53, df ⫽ 159, p ⬍ .01) and one year later (T4) (t ⫽ ⫺5.41, df ⫽ 159, p ⬍ .01). This increase was not observed in the control group as there was no significant difference in wellness self-efficacy between T1 and T4 (t ⫽ ⫺1.36, df ⫽ 26, p ⬎ .05). Thus, Hypothesis 1 was supported. Hypothesis 2 states that wellness self-efficacy at the end of the program (T2) will positively predict psychological availability six months after the program (T3). Hierarchical regression analyses were used to test this hypothesis. We entered the control variables (gender, supervisory position, and income) in Step 1. Next, to control for the preprogram level of the outcome variables, we entered preprogram psychological availability (T1) into the equation as Step 2. In Step 3, we included wellness self-efficacy at the end of program (T2) to test whether it explained significant variance in psychological availability beyond that of the control variables and the preprogram measures of the outcome variable. In this step, we also included preprogram wellness self-efficacy (T1) to ensure that wellness self-efficacy as a result of participating in the wellness program, not preprogram wellness self-efficacy, was responsible for the variance in the outcome variable. Table 3 shows that wellness self-efficacy at the end of program (T2) accounted for significant variance in psychological availability six months after the program (T3) (␤ ⫽ .17, p ⬍ .05) over and above that

Table 2 Results of Paired t Test for Wellness Program Effects on Wellness Self-Efficacy Condition

M

SD

Study

T1

5.51

.71

Control

T1

5.44

.43

T2 T4 T4

M

SD

Paired t test

6.11 5.77 5.54

.51 .52 .38

t(159) ⫽ ⫺12.53ⴱⴱ t(159) ⫽ ⫺5.41ⴱⴱ t(26) ⫽ ⫺1.36

Note. n ⫽ 160 for study and 27 for control group. p ⬍ .01.

ⴱⴱ

67

Table 3 Results of Hierarchical Regression Analyses for Psychological Availability and Career Satisfaction Psychological availability (T3) Variable

␤

Step 1: Control variables Age Gender Supervisory position Perceived financial security Step 2: Outcome variables (T1) Step 3: Wellness self-efficacy (T1) Wellness self-efficacy (T2) Total R2

.09 .00 ⫺.01 .00 .56ⴱⴱ .07 .17ⴱ

⌬R2

Career satisfaction (T4) ␤

.09ⴱⴱ

.02

.43ⴱⴱ .48ⴱⴱ

⌬R2

.06 .09 .05 .14 .34ⴱⴱ ⫺.04 .18ⴱ

.12ⴱⴱ .23ⴱⴱ

Note. n ⫽ 160. Beta weights refer to the full model. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

explained by the controls and preprogram levels. Thus, Hypothesis 2 was supported. Finally, to test our last hypothesis, we followed the same steps described above. Consistent with Hypothesis 3, wellness selfefficacy at the end of program (T2) positively predicted career satisfaction one year after the program (T4). As expected, wellness self-efficacy at the end of program (T2) accounted for significant variance in career satisfaction at T4 (␤ ⫽ .18, p ⬍ .05) over and above that explained by the controls and preprogram levels. Thus, Hypothesis 3 was supported.

Discussion Drawing on conservation of resources theory, we sought to examine the dynamics of wellness programs. Specifically, we employed a time-lagged with control group design to study a holistic wellness program. Our results demonstrated that participating in this program improved participants’ wellness selfefficacy, and subsequently, this initial resource gain led to increased psychological availability and career satisfaction over time. Consistent with our prediction, participants exhibited higher wellness self-efficacy at the end of the program, and six months and one year later. As a result of the program, they became more efficacious (i.e., resource gain) in their ability to improve aspects of their physical, spiritual, financial, and vocational well-being. Consistent with resource gain spirals, we found that people who were high on wellness self-efficacy at the end of program experienced greater psychological availability six months post-program and career satisfaction one year post-program. These results contrast with a demographically similar control group who did not attend the program in whom no significant increases were found, providing greater assurance that the observed effects resulted from the program itself.

Theoretical Contributions Our study contributes to the literature in several ways. First, we contribute to conservation of resources theory by providing evidence of gain spirals, which has been understudied relative to loss spirals (Hobfoll, 2001). In doing so, we also contribute to the

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KIM, HOLLENSBE, SCHWOERER, AND HALBESLEBEN

growing body of work emphasizing the importance of examining positive aspects of human behavior rather than focusing only on negative ones (Seligman & Csikszentmihalyi, 2000). Our study contributes to knowledge on gain spirals, which may deepen our understanding of the conservation of resources perspective. Further, this knowledge may be used by organizations as a starting point that could move their employees into a positive cycle of well-being (Halbesleben et al., 2014). Our study conceptualized wellness programs as resource investment opportunities, and demonstrated that the wellness program we studied indeed triggered a resource gain in the form of wellness self-efficacy, and that this initial gain fueled greater psychological availability and career satisfaction over time. While condition resources (e.g., job and home resources) have been previously examined as a trigger for gain spirals, this study extends the literature by recognizing the importance of personal resources. Individuals can play a proactive role in initiating their own positive gain spirals as a result of participating in a wellness program. Second, our study goes beyond previous research on wellness programs by providing a possible explanation for how and why such programs may work. Current research efforts have been devoted to understanding predominantly outcomes of wellness programs rather than the processes that underlie their effects (Parks & Steelman, 2008). Further, our findings offer insight into a process that might help explain inconsistent findings regarding the effectiveness of wellness programs. To ensure organizations offer their employees more effective wellness programs, knowledge about the dynamics of wellness programs is vital. In this study, we have illustrated the positive effects of a wellness program designed to boost levels of wellness self-efficacy in four specific wellness-related areas. Our findings are consistent with social learning theory (Bandura, 1977), which suggests that selfefficacy can be enhanced through observing and learning from behaviors of others. During the wellness program participants were exposed to four source of self-efficacy (i.e., enactive mastery experience, vicarious experience, verbal persuasion, physiological states) (Bandura, 1997). As Bandura suggested, the perceived expertise and relevance of role models (e.g., experts in different areas of wellness, noted figures, competent coaching staff) made a difference in increasing self-efficacy. Our study adds to the evidence suggesting that training techniques targeted at boosting employee resources increase psychological capital such as selfefficacy, optimism, and resiliency (Luthans, Avey, Avolio, Norman, & Combs, 2006).

Limitations and Future Research Though our time-lagged control group design allowed us to overcome some threats to validity, we acknowledge limitations of our study. First, we relied exclusively on self-report measures, and this may have inflated observed relationships. Accordingly, future wellness studies would benefit from additional data collection approaches such as physiological indices and ratings of participants’ levels of wellness and career satisfaction by individuals close to participants (Ng et al., 2005). Second, to test our model, we chose a relatively unique sample, priests. Although this may raise a question about generalizability of our study’s findings to other types of participants, priests engage in many activities that match those of other types of workers. For example, the priests and

bishops we studied engaged in many prototypical managerial activities, and many held previous jobs from a broader array of occupations increasing the likelihood that they experienced similar wellness challenges. However, it would be useful for future research to study other types of workers to assess the applicability of our findings. Additionally, our study focused on one type of wellness program, a comprehensive off-site program comprising intensive educational plenaries and a variety of activities covering a broad spectrum of wellness-related issues. Thus, future research might examine resource gains associated with other types of wellness programs such as on-site fitness centers and shorter workshops addressing specific wellness topics. However, given the more limited scope of these programs, we suspect that there may not be enough compelling information to challenge one’s wellness image and start a gain spiral. For example, a meta-analysis of 27 physical activity intervention studies found that changes in self-efficacy are highly associated with the type of intervention and the extent to which it engages sources of self-efficacy. Specifically, feedback on past performance and vicarious experience were highly associated with increases in self-efficacy, whereas verbal instructions or teaching how to identify barriers were not (Ashford et al., 2010). Also, Freedy and Hobfoll (1994) found that when nurses received training consisting of only enactive mastery experience, there was little beneficial effect on their ability to stave off burnout. When the program was composed of both enactive mastery experience and social support enhancement, however, they found a marked improvement in nurse’s resiliency in the face of stressful work demands. Accordingly, future research might assess resource gains and longer-term attitudes associated with different types of wellness programs. Another limitation concerns the limited scope of outcomes variables (i.e., psychological availability, career satisfaction) we chose to illustrate a resource gain spiral. To further demonstrate that increased wellness self-efficacy as a result of participation in the wellness program creates upward spiral effects on broad and various aspects of everyday lives, it may be helpful to examine additional wellness-related factors such as changes in diet, exercise, and financial management. Thus, future research might investigate resource gain spirals by assessing a broader spectrum of factors that may be affected by participation in wellness programs. Lastly, to more convincingly illustrate that sequential resource gain spirals take place over time, we may have benefited from additional data collection for the outcome variables. Career satisfaction, for example, was measured twice: preprogram (T1) and 1-year post-program (T4) because we expected that it would take at least a year for participants to enact career-related changes that impact career satisfaction. However, if we had measured it at additional time points (e.g., 4 and 8 months after the program), we might have been able to pinpoint more precisely when this resource started to increase and how it changed over time. Thus, further research may benefit from measuring outcomes variables multiple times after the intervention. From a practical point of view, our findings indicate that welldesigned, comprehensive wellness programs can have a positive impact on employees long after the program concludes. Organizations then might benefit not only from providing well-designed wellness programs but also from evaluating the effects of these programs over the longer term. By measuring wellness self-

DYNAMICS OF A WELLNESS PROGRAM

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efficacy and expected outcomes at multiple points, human resource professionals may be better able to more precisely assess the effectiveness of wellness programs. Our study showed that people who were high on wellness self-efficacy at the end of program were more likely to have greater cognitive, physical, and emotional resources to engage in tasks six months later, and feel more satisfied with their career one year later. In many cases, the effectiveness of wellness programs is assessed only immediately after completion of the program. Our study suggests the utility in conducting additional assessments and incorporating measures of resources, as well as attitudes, rather than merely reactions to the wellness program itself.

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Appendix

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Wellness-Self-Efficacy Scales Physical self-efficacy 1. I am confident that 2. I am confident that 3. I am confident that 4. I am confident that Spiritual self-efficacy 1. I am confident that 2. I am confident that 3. I am confident that Financial self-efficacy 1. I am confident that 2. I am confident that 3. I am confident that Vocational self-efficacy 1. I am confident that 2. I am confident that 3. I am confident that 4. I am confident that

I I I I

can evaluate my physical condition or fitness. can identify ways to improve my physical condition or fitness. can create a plan to improve my physical condition or fitness. am able to improve my physical health if I decide it is necessary.

I can evaluate my spiritual well-being. I have the resources necessary to improve my spiritual well-being. I can improve my spiritual well-being if I think it is important. I can evaluate my financial position. I can identify steps to improve my financial position. I can improve my financial position by implementing my plans. I I I I

can pursue vocational goals that I think are important. can assess the state of my vocation. have the skills necessary to improve my vocational wellness. can improve my vocational wellness.

Received January 19, 2014 Revision received May 12, 2014 Accepted June 6, 2014 䡲