Chapter 2: Literature Review

https://doi.org/10.1177/19394225241242893

New Horizons in Adult Education and Human Resource Development 2024, Vol. 36(2) 117 –126 © The Author(s) 2024 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/19394225241242893 journals.sagepub.com/home/nha

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Work and health are inextricably linked (Fairlie, 2017). Approximately 82% of all large organizations and 53% of small organizations within the United States offer some type of corporate wellness program designed to influence employee engagement and wellbeing—resulting in a bal- looning $8 billion industry (Song & Baicker, 2019). The prevailing logic follows that a physically and mentally healthy employee is also likely an engageable employee (see e.g., Schaufeli et al., 2008; Shuck & Reio, 2014; Shuck, Alagaraja, et al., 2017).

Research in the Human Resource Development (HRD) field, as well as related disciplines, have lauded and exten- sively reviewed the importance of both employee engage- ment (c.f., Shuck et al., 2011) and wellbeing (Kossek et al., 2012). Despite the available research on work and the working experience, organizationally focused health and wellness programs have been routinely absent from most models of work in HRD (for an exemplar, see Osam et al., 2020). Only recently, has HRD begun to answer the call for flexibility (Yawson, 2020) through its expansion into ave- nues for application such as in the field of healthcare

(McLean & Jiantreerangkoo, 2020). However, HRD is beginning to understand how work and the overall working experience could influence employee decision points around their own personal engagement with health and health related behaviors (i.e., health engagement). Health engagement was defined in this research as the mainte- nance, intensity, and direction of effort and energy a per- son devoted to their own personal health (CHOT, 2022). Drawing from traditional engagement theory (c.f., Shuck, Osam, et al., 2017), engagement is a function of how meaningful a person experiences a given context, how safe that context is to engage with, and whether someone has the resources to both compete and complete in the

1242893 NHAXXX10.1177/19394225241242893New Horizons in Adult Education and Human Resource DevelopmentDuffy et al. research-article2024

1Rockford University, IL, USA 2The University of Alabama at Birmingham, USA 3University of Louisville, KY, USA

Corresponding Author: Clayton Duffy, Rockford University, 5150 E. State Street, Rockford, IL 61108-2393, USA. Email: [email protected]

Employee Engagement With Corporate- Based Health and Wellness Programs: A Multiple Regression Analysis

Clayton Duffy1 , J’Aime Jennings2, Brad Shuck3, and Jason Immekus3

Abstract Organizations for decades have offered a myriad of health benefit options designed to engage employees in their own personal health. These programs have been aimed at supporting a healthier workforce in hopes that, a healthy workforce would also equate to a more productive and engaged workforce. As a result, organizations have developed a myriad of choices that employees can choose from to enhance their personal health (i.e., wellness programs, assistance counseling, health risk assessments, etc.). From a workplace perspective, research in the Human Resource Development (HRD) field, as well as related disciplines, have started to explore connections between work and health. Despite emerging research on work and the working experience, organizationally focused health and wellness offerings have been historically absent from most models of work in HRD. The purpose of this research was to examine how work and the working experience influenced employee decision points around personal levels of health engagement. Using two multiple regression models with data from 206 participants working at a Fortune 500 global logistics company, we explored the linkage between work, health, and employee agency in participating in corporate wellness programs. Through our work, we contribute to traditional engagement theory as well as an emerging framework in HRD—Work Determinants of Health (WDOH)—and provide practical suggestions for how leaders could prioritize employee wellness and health engagement within their organization.

Keywords human resource development, health engagement, employee engagement, wellness programs, regression

118 New Horizons in Adult Education and Human Resource Development 36(2)

context (Kahn, 1990; Shuck et al., 2011). The amount of effort and energy that a person gives to maintaining a healthy lifestyle is the behavioral output of health engage- ment. As such, the purpose of this work was to examine how work and the working experience influenced employee decision points around an employee’s personal levels of health engagement. In doing this, we hoped to empirically explore the linkage between work and health and to iden- tify specific workplace variables that might have even a small amount influence in individual decision making around proactive health-related behaviors. In what follows, we provide relevant background information and review related literature, detail our methods, analysis, and finally conclusions. We close by articulating the implications of this work for research and practice by expanding, foster- ing, and calling for an expansion of interest on the influ- ence of work-based experiences on employee wellbeing and individual health engagement.

Background and Review of Related Literature

Organizations have for decades offered a myriad of health benefit options designed to engage employees in their own personal health (i.e., health engagement). From gamified step challenges where participants compete in competitions to see how many footsteps a person can take a day (Alahäivälä & Oinas-Kukkonen, 2016; Cugelman, 2013; González-González Carina & Navarro-Adelantado, 2021; King et al., 2013) to weight loss (Peñalvo et al., 2021) and substance abuse/support programs (Spell & Blum, 2005), organizations have developed a multitude of choices that employees can choose from to enhance their personal health by way of the organization they work for. Such programs have been intentionally designed to empower employees with the agency they need to support their health and well- being, as well as influence performance related metrics such as employee engagement and employee wellbeing (Drennan et al., 2006; Gubler et al., 2018). So much effort has been invested in this area that the Centers for Disease Control recently launched a Total Worker Health Initiative (Tamers et al., 2019), aimed at supporting and developing workplace wellness programs that foster wellbeing and engagement through personal health choices as well as the identification of risk factors and barriers that hamper those efforts. Connected to this national public-service effort, local level workplace wellness programs are efforts pro- vided by an organization to employees that aim to “enhance awareness, change behavior, and create environments that support good health practices” (Aldana, 2001, p. 297). Scholars generally consider wellness programs to encom- pass three basic areas of health: (a) biometric screenings, where clinical measures of health are taken; (b) health risk

assessments that analyze lifestyle habits; and (c) wellness activities, where active and healthy lifestyle behaviors are taught and practiced (Jones et al., 2019).

Despite their popularity, workplace wellness programs have seen ambiguity in their support from both scholars and practitioners. On one hand, Baicker et al. (2010) found that medical costs lower significantly with participation in work- place wellness programs, where it was estimated that medi- cal costs fall by $3.27 for each dollar spent on wellness programs. Additionally, absenteeism cost was found to decline by $2.73 for every dollar spent on wellness program- ming. The support for workplace wellness programs was further supported by Cuellar et al. (2017), who found that wellness programs with financial incentives resulted in more preventative health visits and cholesterol testing. Despite these supportive findings, in other research, employee par- ticipation in wellness programs failed to produce a signifi- cant change in utilization or spending of healthcare resources (Fronstin & Roebuck, 2015). Moreover, despite the very recent focus on implementing wellness programs to lower healthcare costs and improve employee wellbeing (Song & Baicker, 2019), programs are typically only utilized by less than 20% of eligible employees (Mattke et al., 2013). Coupled with low participation rates, in other research, the evidence on wellness programs has shown almost no reli- able significant return on investment. For example, Song and Baicker (2019) pointed out that actual health outcome measures like cholesterol, hypertension, and obesity failed to differ between groups who participated in wellness pro- gramming and those who did not. More, in a 2-year longitu- dinal study, Song and Baicker (2021) highlighted that while wellness programs positively influenced self-reported health behaviors, the initiative had no measurable impact on objec- tive measures such as blood pressure, diabetes, or hyperlip- idemia. At present, the research is at best contradictory.

As a result of these studies, many scholars have recom- mend the wellness programs be discontinued altogether due to bloating cost, ineffective outcomes, and poor results (Jones et al., 2018; Knippen et al., 2018; Mattke et al., 2015). It seems that despite choice and, at times financial incentive to be involved, employees are not taking advan- tage of the offerings that organizations are providing for them, and those that are may not be actually benefitting. An employee’s level of health engagement—their individual programmatic participation in wellness programs—seems to be failing at the national level, but the reasons why appear not to be programmatic, but rather outside factors influenc- ing decision making around personal health.

Within HRD, it is believed that the overall phenomenon of engagement can be grounded in how a person experiences a particular context and whether that context is meaningful, safe to engage in, and whether a person has the resources they need to be engaged (see Shuck, Osam et al., 2017 for additional details). These three domains operate as

Duffy et al. 119

antecedental conditions that can explain the intensity and direction of effort and energy. Operationalizing the phenom- enon of health engagement within this study, meaningful- ness was about the level of value, significance, or purpose in a given health/wellness programmatic effort or organiza- tional effort. When health programs lack overall meaning (perceived or real), engagement in those contexts are likely to be lower than when meaning is high. Health meaningful- ness was defined as the assessment of and attribution towards the value and significance of overall health within a person’s life (CHOT, 2022).

More, safety has often been focused on as a physical vari- able, however, emotional and psychological safety have become areas of focus as the boundaries of the workplace shift and slide from traditionally tight margins. Here, well- being has emerged as a component of the growing conversa- tion in health and healthcare in recent years and HRD is well embedded in these conversations. Overall wellbeing could be an indicator of how safe someone feels, or how someone is experiencing life in the moment, which could influence their perceptions of safety. Grounded in traditional engage- ment theory, the degree that someone feels safe is likely to impact one’s willingness and ability to engage proactively in their own health. Because wellbeing plays an important role in shaping momentary perceptions, health safety was defined as the degree of overall wellbeing a person was experiencing in the moment regarding their overall health (CHOT, 2022).

Finally, the ability to complete and compete was concep- tualized as having the physical, emotional, and psychologi- cal resources necessary for the completion of a task within a given context (Kahn, 1990; Shuck, Osam, et al., 2017). Resources have been conceptualized as supplies, access, and the energy required to complete a task. When it comes to health resources, feeling supported has been shown to be a critical resource as well as knowledge about programs and programmatic access, which could include financial access or geographical access. As a result, health resources was defined as the degree of, and access to, routine resources that employees believe they have to invest in their personal health (CHOT, 2022).

Grounded in this literature and drawing from traditional engagement theory in HRD, we hypothesized the following:

H1: Health meaningfulness, health safety, and health resources would explain statistically significant portions of the variance in overall health engagement.

Because wellness-type programs are offered as a benefit of the working experience, the context for participation for health engagement is bounded within a working context. Shuck et al. (2023) offered a framework—Work Determinants of Health (WDOH)—for understanding the impact of work- based experience on the overall work-health connection.

Traditionally speaking, determinants of health have focused on exposure risks at work or the likelihood of slips and falls, however, rarely did research on determinants of health focus on the social and emotional aspects of work that could influ- ence health. As a result, WDOH was offered as a work expe- rience-based organizing framework, reflecting four key areas of integrated research and practice, including work- based stress, work capacity, the physical and social environ- ment, and meaningful work. The main proposition behind WDOH was that dysfunctional environments of work could enhance risk for chronic disease in ways traditional models cannot explain. In short, an employee may become sick or at risk for disease not because they are choosing to be or because they are too lazy or need to go to bed earlier. Instead, the WDOH framework explores how work-based experi- ences could be an underlying and contributing factor to choice and decisions pertaining to health, and that disease could be a function of how employees internalize experi- ences of work and physically manifest outcomes that lead to illness (see Shuck et al., 2022, 2023 for more complete details).

In the context of health engagement, organizational cul- ture could be identified as a wraparound construct for WDOH. How work is done, —on a human level—how it feels to work in a place, and how collaboration and support materialize are all components of the overall working expe- rience that could impact things like the capacity to engage, how meaningful health is conceptualized, or whether some- one believes they have the resources to engage in their health. These areas are directly connected to the physical and social environment aspects of WDOH as well as stress and meaningful work. As such, at work, engagement cannot happen in a vacuum, whether that is employee engagement or health engagement. Being engaged always requires a context (Lee et al., 2020) and, that context can be operation- alized in a work-based experience context such as culture. Historically, organizational culture has been shown to influ- ence the antecedents of engagement, especially within the work and employee engagement literature (c.f., Wollard & Shuck, 2011). Connected, scholars have even identified both individual and organizational factors that impact employee participation with wellness programs (Person et al., 2010; Spence, 2015). There is deep evidence that the bounded context matters and is likely to influence behavior. We wondered if it were possible for a work context to impact health engagement in any way, —even if only a small amount—and if so, we wondered what this relation- ship could look and feel like. Explaining any level of sig- nificance within health engagement connected to organizational culture would be a novel, and a first of its kind finding. Grounded within previous research in HRD, we used this reasoning to purpose a second hypothesis for exploration in our study:

120 New Horizons in Adult Education and Human Resource Development 36(2)

H2: Employee-level perceptions of organizational cul- ture and employee engagement will explain variance in health engagement.

Methods

Our research team partnered with a Fortune-100 multi- national transportation logistics company to assess employee perceptions of their work environment and overall health engagement. The partner organization was experiencing problems with overall health engagement in multiple bene- fits programs and had indicated that while employees had a menu of options for managing their health, participation across the board was extremely low. In concert with execu- tive leadership of the partner logistics organization, this study had two aims: (a) to support and inform evidenced- based practice around health engagement at the local level and (b) to extend the known literature on health engagement using the lens of employee engagement and its known ante- cedents through the WDOH framework (c.f., Shuck et al., 2021). The major contribution of this research provides new insight into the real-world practice of employees engaging in their health by building on an existing framework (c.f., Shuck et al., 2023) using an HRD-specific lens.

Data and Sample

This multisite, multivariate regression model project was conducted on location within a Fortune-100 multi-national transportation logistics company. The research was started at the request of the logistics company after experiencing declining levels of health and wellness program engage- ment—an offering provided by approximately 82% of large organizations (Song & Baicker, 2019). Participants were pulled from two worksites (Columbia, SC and Tempe, AZ). These two locations were chosen by executive leadership due to each location having similar job expectations, demands, and workloads yet offering the benefit of being geographi- cally unique. These two sites sourced a heavy volume of work and showed lower overall levels of participation with

health and wellness programming. Demographics, work experience, and job descriptions were not collected to main- tain anonymity at the request of organizational stakeholders. The research participant sample was recruited via email through a gatekeeper at each location and directed to a Qualtrics™ survey link. Participant (N = 206) response rates for each site were as follows: Tempe, AZ—16.3%, Columbia, SC—51.6%.

Measures

The following sections detail each survey index deployed in this project, including the available psychometrics and sam- ple items. The descriptive statistics of each measure are listed in Table 1. Because indexes around constructs such as health engagement and health meaningfulness did not previously exist, many of the items and scales deployed in this study were developed for use by the Center for Health and Organizational Transformation (CHOT) at the University of Louisville (Louisville, Kentucky). Until early 2023, CHOT was a National Science Foundation-funded research center focused on transforming the cost, quality, and access of healthcare services across the United States. Scale items were developed by (a) examining the known literature on each concept, (b) developing a series of test items that each researcher examined for content validity and construction, and (c) deciding on a final set of items. The scale items pre- sented below represent a first round of exploration for each measure used in the field. Table 1 reports exploratory internal and descriptive statistics for each scale including Cronbach’s alpha (Fraenkel & Wallen, 1996).

Health Engagement. The Health Engagement-CHOT-6 was developed for use in this project. The purpose of this six- item instrument was to operationalize the maintenance, intensity, and direction of effort and energy a person devoted to their own personal health. Participants who indicated a higher total score represented higher levels of engagement with their health. A sample item for the HE-CHOT-6 was: “being healthy has a great deal of personal meaning to me.”

Table 1. Descriptive Statistics.

N Range M SD Minimum Maximum Variance α No. of items

Health engagement 159 24 21.91 5.43 6 30 29.45 .94 6 Health meaning 159 20 21.30 3.49 5 25 12.15 .93 5 Health resources 157 20 19.15 3.45 5 25 11.93 .73 5 Health safety 156 34 33.31 8.43 11 45 71.01 .90 9 Organizational culture 155 33 43.17 7.87 22 55 61.98 .88 11 Employee engagement 153 21 25.21 4.38 9 30 19.19 .88 6 Valid N (listwise) 147

Duffy et al. 121

Health Meaning. The Health Meaningfulness-CHOT-5 was developed for use in this project. The purpose of this five- item instrument was to assess employee perceptions of how meaningful health was to them. Participants who indicated a higher total score represented higher levels of perceived meaningfulness with their health. A sample item for the HM-CHOT-5 was: “my overall health is important to me.”

Health Resources. The Health Resources-CHOT-5 was devel- oped for use in this project. The purpose of this five-item instrument was to assess employee perceptions of their level of access to health resources. Participants who indicated a higher total score represented higher levels of perceived resources to engage with their health. A sample item for the HR-CHOT-5 was: “I have the resources I need to be healthy.”

Health Safety. The Health Safety-CHOT-9 was developed for use in this project. The purpose of this five-item instru- ment was to assess employee perceptions of how safe they felt engaging with their health. Participants who indicated a higher total score represented higher levels of perceived safety to engage with their health. A sample item for the HS-CHOT-9 was: “I feel like I never have a day off.”

Organizational Culture. The Cognitive Work Appraisal-11© (CWAS-11; Shuck, Adelson, et al. 2017) was used to opera- tionalize culture in this project. Robust psychometric proper- ties for this scale were detailed in Shuck, Adelson et al. (2017) including discriminate, convergent, and incremental validity. Historically, Cronbach alphas for this scale range between .88 and .92. Participants who indicated a higher total score on the CWAS-11 represented more positive levels of overall organi- zational culture. A sample item for the CWAS-11 was: “I feel a sense of responsibility to complete my work.”

Employee Engagement. The six-item Employee Engage- ment Scale-6© (EES-6; Shuck, Adelson, et al. 2017) was used to operationalize employee engagement. Robust psy- chometric properties for this scale were detailed in Shuck, Adelson et al. (2017) including discriminate, convergent, and incremental validity. Historically, Cronbach alphas for this scale range between .91 and .93 (see e.g., Osam et al., 2020). Participants who indicated a higher total score on the EES-6 represented higher levels of overall employee engagement. A sample item for the EES-6 included the fol- lowing: “I am very focused when I am working at my job.”

Procedures and Data Analysis

An internet-based self-report survey battery was used as the data collection tool for this research. Dillman et al.’s (2009) four-stage method was used for preparation. All research related communication was forwarded through the gate- keeper at each location. For scheduling, Dillman et al.’s

(2009) interval-scheduling framework was used to adminis- ter the initial survey and send two follow-up reminders accompanying the survey to participants (thus, the survey battery was sent out three times over a three-week period [i.e., once each week]). The survey was placed in an online computer survey tool for administration. Participation was strictly voluntary, and participants were able to opt out of the study at any point. No significant issues were encoun- tered with the distribution method. Data was recorded in an electronic file accessible only to the research team and monitored weekly. The data file did not contain identifying information; thus, participant confidentiality was reason- ably assured. Data cleaning requirements were set at >50% response completion. A total of 47 responses were consid- ered invalid, and the final response amount cleared for sta- tistical analyses was 159. Upon data cleaning, descriptive statistics were identified (see Table 1). To explore potential differences in group scores across the two geographical sites, an independent samples t-test was conducted. There were no statistically significant differences across the two sites (p < .01) and results passed assumptions of normality across all indexes.

Results

For correlation analysis, Pearson’s Correlation test was con- ducted (see Table 2). The correlation model consisted of five independent variables (health meaning, health safety, health resources, organizational culture, and employee engage- ment) and one dependent variable (health engagement). Of these correlations, the strongest correlation was between health engagement and health meaning r(158) = .692, p < .01, resulting in a moderate positive correlation. The second strongest correlation was organizational culture and employee engagement r(151) = .640, p < .01. Additionally, health engagement and health resources r(156) = .515, p < .01 demonstrated a moderate positive correlation. Finally, all constructs demonstrated statistically significant correlations to health engagement at the .05 level.

Tables 3 and 4 show the model summary and coefficients result for H1, where the simultaneous regression model fea- tures health resources, health safety, and health meaning as independent variables and employee health engagement as the dependent variable. Within the model, two of the inde- pendent variables (health meaning and health resources) were statistically significant in their contribution to the dependent variable (p < .01). These three independent vari- ables explained 52.6% of the variance in health engagement (R2 = .526) and resulted in the following regression equation:

y - 381 917 Health Meaning

269 Health Resources

 = + ( ) +

0 0

0

. .

. (( ) − ( ) 72 Health Safety0 0.

122 New Horizons in Adult Education and Human Resource Development 36(2)

In exploring the model more fully, health meaning and health resources contributed significant amounts of vari- ance to the outcome, where health safety feel just short of

statistical significance. We, however, note the practical sig- nificance of the variable in driving experiences of engage- ment. We suspect that if employees were not secure in how

Table 2. Correlations.

Health engagement

Health meaning

Health resources

Financial wellbeing

Organizational culture

Employee engagement

Health safety

Health engagement Pearson correlation 1 .692** .515** .259** .223** .192* −.231** Sig. (2-tailed) .000 .000 .001 .005 .017 .004 N 159 159 157 155 155 153 156 Health meaning Pearson correlation .692** 1 .536** .277** .213** .267** −0.105 Sig. (2-tailed) .000 .000 .000 .008 .001 .192 N 159 159 157 155 155 153 156 Health resources Pearson correlation .515** .536** 1 .431** .536** .444** −.344** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 N 157 157 157 153 153 152 154 Organizational culture Pearson correlation .223** .213** .536** .323** 1 .640** −.456** Sig. (2-tailed) .005 .008 .000 .000 .000 .000 N 155 155 153 151 155 152 155 Employee engagement Pearson correlation .192* .267** .444** .167* .640** 1 −0.115 Sig. (2-tailed) .017 .001 .000 .042 .000 .156 N 153 153 152 149 152 153 153 Health safety Pearson correlation −.231** −0.105 −.344** −.283** −.456** −0.115 1 Sig. (2-tailed) .004 .192 .000 .000 .000 .156 N 156 156 154 152 155 153 156

*Correlation is significant at the .05 level (2-tailed). **Correlation is significant at the .01 level (2-tailed).

Table 3. Model Summary (Health Meaning, Resources, and Safety).

Model R R2 Adjusted

R2 Std. error

of the estimate

Change Statistics

R2 change F change df1 df2 Sig. F Change

1 .726a .526 .517 3.81172 .526 55.578 3 150 .000

aPredictors: (constant), health meaning, health resources, health safety.

Table 4. H1 Coefficients.

Modela

Unstandardized coefficients

Standardized coefficients

t Sig.

95.0% confidence interval for B

B Std. error β Lower bound Upper bound

1 (Constant) −0.381 2.754 −0.138 .890 −5.822 5.060 Health meaning 0.917 0.104 .591 8.807 .000 0.711 1.123 Health resources 0.269 0.112 .170 2.400 .018 0.048 0.491 Health safety −0.072 0.039 −.111 −1.851 .066 −0.150 0.005

aDependent variable: health engagement.

Duffy et al. 123

they viewed their health, this variable would have been a significant overall predictor; only future research would confirm the veracity of this claim.

With regards to H2, Tables 5 and 6 show a summary of the second regression model that featured employee engage- ment and organizational culture as independent variables, and health engagement as the dependent variable. Within this second model, neither independent variable was statis- tically significant in contribution to the outcome variable (p < .05). These two independent variables accounted for 5.2% of the variance in health engagement (R2 = .052) and resulted in the following regression equation:

y 14 177 11 Employee Engagement

114 Organizationa

 = + ( ) +

. .

.

0

0 ll Culture( )

Discussion of Findings

This multisite, multivariate regression model provided an empirical foundation for understanding why some employ- ees choose to engage with health and wellness programs that have an impact on their personal health, and, why some may not. Overall, data showed that health meaningfulness and health resources, exploratory variables proposed for this study, were critical to health engagement. In addition to showing the exploratory relationships, this study identified and operationalized four new variables for exploration in HRD-focused transdisciplinary projects. Those variables were: health engagement, health meaningfulness, health safety, and health resources. Additionally, these variables were used alongside established measures (e.g., the EES and CWAS-11; Shuck, Osam, et al., 2017).

Moreover, this work directly responds to the call by Wang (2019) who suggested that HRD must cross boundar- ies and by doing so, builds on the best of multiple fields and opens new eras of social science research. We were inspired by and agreed with Alagaraja and Githens (2016) who artic- ulated that the future of HRD goes beyond traditional boundaries of learning and development and is increasingly pushing into other contexts of life, such as workplace spiri- tuality (e.g., McClurg et al., (2023). Here, we connect that to what it could mean in the Future of Work and what impli- cations that could have for work life integration, work life boundaries, and how contexts of work and health are inter- twined. While we connect this work to Shuck et al.’s (2023) framework of Work Determinants of Health, we go further by showing how behavior is shaped around health and how culture and work impact those decision points. As previ- ously mentioned, we deeply connect this work to Yawson (2020) who has openly called for the need for flexibility in HRD, as well as with McLean and Jiantreerangkoo (2020) who suggested ways for HRD to assist with issues of health and healthcare. We hope to add to this work and amplify their call for additional work in this area as the field matures and sophisticates in this space.

Limitations

As with any study, this research has embedded limitations that could be addressed in future research. First, multiple new measures were introduced surrounding relatively under researched concepts (e.g., CHOT measures, health mean- ingfulness, safety, etc.). As these research strands grow and understanding of these concepts develops, these findings may shift. We would encourage further exploration of these

Table 5. Model Summary (Organizational Culture and Employee Engagement).

Modela R R2 Adjusted R2 Std. error of the estimate

Change statistics

R2 change F change df1 df2 Sig. F change

1 .228a .052 .039 5.36199 .052 4.090 2 149 0.019

aPredictors: (constant), organizational culture, employee engagement.

Table 6. H2 Coefficients.

Modela

Unstandardized coefficients

Standardized coefficients

t Sig.

95.0% confidence interval for B

B SE β Lower bound Upper bound

1 (Constant) 14.177 2.767 5.123 .000 8.709 19.644 Employee engagement

0.110 0.130 .088 0.852 .396 −0.146 0.366

Organizational culture

0.114 0.073 .161 1.552 .123 −0.031 0.259

aDependent variable: health engagement.

124 New Horizons in Adult Education and Human Resource Development 36(2)

indexes in varied work-based contexts as well as serious psychometric scrutiny with larger sample sizes. Second, because we employed self-reports, we must be cautious about generalizing the results as well as the possibility that common source method variance (CMV) might have pro- duced inflated or deflated correlations (Podsakoff et al., 2003). In our work, we took a procedural (i.e., we assured participants anonymity and there were no right or wrong answers) and statistical approach to reduce the likelihood of CMV bias. Harman’s one-factor diagnostic test revealed no evidence that CMV bias was an issue in this research. Future research might take additional steps to reduce pos- sible CMV bias, such as collecting the dependent variable at a different time than the independent variables, using bio- logical or usage data in combination with self-reports, and observing actual health behaviors when and where appro- priate. Third, this research features a sample of participants only working in the United States. As health and wellness perspectives can vary across cultures, this study features only the perspective of United States employees from two geographically diverse locations. Care should be taken when interpreting the results beyond their intended bound- aries. Finally, during the data collection process, no demo- graphic or identifying information was able to be collected. As a result, the statistics and analyses featured are for the general workforce, and it would be inappropriate to seg- ment the data by age, race, or position title.

Implications and Recommendations for Future Research

As we consider the practical implications of our work, scholar-practitioners looking to influence higher levels of health engagement might focus their efforts by influencing how health perceptions are shaped, how culture impacts health, and what resources can be provided. For example, practitioners may benefit in tailoring their messaging and organizational communications toward why personal health is important. Specifically, leaders in organizations might focus on and prioritize their marketing and communication efforts on the health of the individual and not just the employee, and what that could mean for life outside of the boundaries of work. Through this, organizations might be able to improve the level of meaning employees attribute to their health, and thus, improve employee willingness to engage with their programs.

Interestingly, in our models, emotional and social per- ceptions of culture were shown to explain a small level of variance in health engagement models. This finding sug- gested that work environments have the propensity to influ- ence health and wellness in ways not seen before within the HRD literature (McLean & Jiantreerangkoo, 2020). Exploring the intersection of work and health through this lens could be a new way for HRD scholars and practitioners

to lead a conversation between the intersection of work and health in deeply meaningful ways and is a direct refinement of the WDOH framework (Hart et al., 2024). Perhaps, for some, it is not that the right programs are in place or the right resources, but rather the demand from a dysfunctional culture that outweighs the capacity to engage in personal health. Grounded in our data, we would encourage leaders to work through and on the culture as a way to build an environment of overall health. In concert with this, the data models would suggest that organizations focus on quality of healthcare program deliverables, instead of only quantity. As most employees are aware of wellness programs within their organizations (Drennan et al., 2006; Gubler et al., 2018), the issue resides within their willingness to engage with them. By working through development plans that emphasize quality wellness programs, organizations are more equipped to provide their workforces with meaningful health interventions.

In terms of the implications of this work for research, this study provided only a quantitative overview of employee perceptions toward engagement, wellbeing, and wellness programs. Future research centered around qualitative com- ponents of the study may aid scholars in understanding the rationale behind these perceptions. In doing this, scholars could be better equipped with a qualitative understanding of the phenomena of engagement, wellbeing, and wellness pro- grams, but will also have specific workforce feedback to address why these phenomena or events occur. More nuanced data is a likely outcome. Moreover, future research may ben- efit from implementing replication studies across multiple organizations or business realms/specialties (i.e., sales, man- ufacturing, education, etc.). Through these efforts, this mul- tiple regression may be further supported, analyzed, or generalizable to the workforce as a whole. Finally, the use of moderator (e.g., organizational climate, personality traits) and mediator (e.g., intrinsic and extrinsic motivation) vari- ables could add depth to the understanding of this topic, as their use has proved meaningful in recent HRD research (Song & Lim, 2015).

Finally, this research only provided a foundational over- view of the factors that influence employee health engage- ment extending and refining what we know about engagement, as a phenomenon. Specifically, it identified the impact that these variables statistically had on employee health engagement using a historically grounded frame- work of engagement in HRD. As noted, for organizations to emphasize engagement in health meaningfulness and well- being (pivotal aspects of health engagement), leaders need to understand what also proceeds them. As this is the case, future research centered around regression models with health meaningfulness and wellbeing as dependent vari- ables may prove beneficial. This could support and help answer the call by scholars (c.f., Spence, 2015) for HRD practitioners to work toward mitigating low employee

Duffy et al. 125

engagement with corporate sponsored health programs, a significant and practical outcome of this work.

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.

ORCID iD

Clayton Duffy https://orcid.org/0000-0003-0450-6239

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Author Biographies

Clayton Duffy is a Professor of Business at Rockford University and a Ph.D. candidate in the Educational Leadership and Organizational Development program at the University of Louisville. Clayton teaches and researches a variety of topics across leadership, management, and HRD.

J’Aime Jennings, PhD, is an Associate Professor in the Department of Health Services Administration at the University of Alabama at Birmingham and Program Director for the Master of Science in Health Administration, residential format. Her research focuses on organizational strategy to improve quality and access to healthcare.

Dr. Brad Shuck is a professor in the Department of Educational Leadership, Evaluation, and Organizational Development at the University of Louisville, and Program Director of the Master of Science in Human Resources and Organizational Development. His research is focused on the application of employee engagement theory and the connections between biological health and work.

Jason Immekus, PhD, is professor and chair of the Department of Educational Leadership, Evaluation, and Organizational Development at the University of Louisville. His research addresses issues related to test score validity regarding the inter- pretation and uses of scores for designated purposes and diverse groups, which includes considerations for scale development.

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