The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States

To examine if mentorship can be utilized to alleviate workaholic tendencies and encourage heavy work investment, our paper explored the links between mentorship functions, mentorship quality, and employee outcomes. Hypotheses were tested among 271 full-time employees living in the United States from various organizations using path analysis. Our research's novelty is the analysis of how mentorship functions of career support, psychosocial support and role modeling have a direct effect on mentorship quality and an indirect effect on employee flourishing, job satisfaction, and job stress. The mentoring function of career support also directly affected the mentorship quality and indirectly affected job stress. A direct effect was found between career support and employee flourishing and job satisfaction. Practical implications, such as the easing of workaholic tendencies and encouragement of heavy work investment, along with limitations, and directions for future research, are analyzed.


Introduction
Even before the 2020 medical and economic global crisis, the realm of work was being transformed by technological, cultural, and economic factors. The crisis will probably further accentuate these tendencies, although much will depend on the policies and measures adopted by firms and governments. The shifting nature of work, along with a possible severe economic downturn and the continuous threat of outsourcing, will probably exert pressure on workers and accentuate workaholic tendencies. This aspect will invariably lead to loss of productivity, work-life disbalance, work conflicts, substandard work performance, poor work quality, and overall on-the-job and off-the-job negative behaviors. Governments and firms need to identify creative instruments to discourage damaging workaholism yet embolden heavy work investment. The future global work environment will need dedicated and vigorous workers to solve the various problems that will arise without sacrificing their well-being and social relationships. Our paper attempts to apply the theory of mentorship to the negative phenomenon of workaholism and motivate people towards heavy work investment.
In our research question, we examined if mentorship could alleviate workaholic tendencies and encourage heavy work investment. Although the literature on workaholism and heavy work investment is extensive, Maxwell and Bachkirova (2010) and Houck (2011) state that there is a gap in the applicability of mentorship principles and practices to alleviate workaholism and encourage heavy work investment. In our survey, we tested if there was a positive relationship between the mentoring functions of career support, psychosocial support, and role modeling, and the quality of the mentorship relation. We also explored whether a positive relationship existed between the quality of the mentoring relationship and positive employee outcomes such as job satisfaction and adverse outcomes such as job stress. We finally examined a mediating role of mentorship quality between the mentoring functions of career support, psychosocial support, and role modeling, and the employee outcome variables of employee flourishing, job satisfaction, and job stress.
We surveyed 271 full-time employees between ages 18 and 82 who worked at their current organizations between one month to 34 years. We conducted the survey online to examine the relationships between mentors and mentees and the level of satisfaction of the mentees. We measured the "mentoring functions" of career support, psychosocial support, and role modeling; the "mentorship quality", the "employee flourishing", "job satisfaction" and "job stress". We propose that mentorship is an unexplored instrument in this debate, and its inclusion should be considered for future studies in both theory and practice. Our study concentrates exclusively on US workers, but we propose that this approach be extended to other cultures. In the first section of our paper, we concentrate on the literature review beginning with a brief outline of the current state of work and the global forces shaping it; next, we succinctly outline the literature on workaholism, heavy work investment, and mentorship. We then move to describe our survey, the methods we employed, and the results of the study. We close with conclusions, implications, limitations, and further research suggestions.

The current state of work
The first global condition determining the current labor condition is demography. In the past four decades, the global population has almost doubled from approximately four billion in 1980 to almost eight billion in 2020 and is predicted to reach ten billion by 2050 (Plăiaş et al., 2011). Most demographic expansions occurred in developing nations, while AE The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States developed nations remained constant or declined (Palacios-Lopez et al., 2019). This aspect led to the second significant global condition of labor: the ecological burden on natural resources. Global warming, high levels of air pollution, and deforestation are but a few negative consequences of the traditional, fossil-based economic development model adopted by the growing, developing nations (Uniyal et al., 2020). Demographic and ecological pressures have led to the third global condition, namely a deficit in democracy and free-market capitalism. These conditions are either not being developed or have reversed and are replaced by autocratic governments and state-command economies (Krastev, 2019). The fourth and perhaps the most impactful global challenge is the technological revolution and the global integration it has made possible (Muscio and Ciffolilli, 2020).
The world is currently experiencing "The Fourth Industrial Revolution" (Schwab, 2017). The first one emerged in the late 18 th century with the advent of steam power, making humans more productive with machines replacing manual and animal labor. The second industrial revolution emerged in the late 19 th century and was built around petroleum and electricity, creating new organizational models and social classes (Mokyr, 1998). The third industrial revolution emerged in the late 1970s with the advent of personal computers, communication technology, and global finance, transforming the world and unleashing a wave of innovation and globalization. Many jobs and industries were outsourced to new locations, such as South East Asia, Eastern Europe, and South America (Mowery, 2009), because of low labor costs, new consumer markets, and relaxed environmental standards (Maskell et al., 2007). The fourth industrial revolution started in the early 2000s and is characterized by the production, organization, and commercialization of knowledge and data (Xu, David and Kim, 2018). New technologies may augment and possibly replace professional jobs in customer service, finance, education, healthcare, government, and others. (Fleming et al., 2019). Finally, since the mid-2010s, this phenomenon has been supercharged by the competition between the United States and China, leading some to refer to a new "digital cold war" (Ciuriak, 2019). The implications for labor and working conditions are significant, necessitating a paradigm shift from employees, educators, companies, and policymakers. The McKenzie Global Institute (Manyika et al., 2017) published a report estimating the impact technology will have on 54 nations or 78% of the global economy. They forecast that approximately 50% of agricultural jobs, 64% of manufacturing jobs, and 54% of the service jobs could also be automated in the next decades. This could affect close to 400 million jobs in China, 235 million jobs in India, and 60 million jobs in the United States. Over the past decade, orders for industrial robots have tripled, while investment in artificial intelligence and blockchain technologies doubles every year (OECD, 2019).
Thus far, in most OECD (Organization for Economic Co-operation and Development) nations, the overall rate of employment has increased, given the substantial upsurge of women in the labor force and the increase of the effective retirement age. New technologies and a global market offer greater freedom, mobility, and higher wages for the new techsavvy class, improving work-life balance. Routine and dangerous tasks can be automated, increasing safety and accuracy while boosting productivity. The global elites hail these transformations as incredible human achievements, which will continue the long march of progress into new areas such as biotechnology and space travel. Crucially, many of these innovations are driven by private companies and investment funds that lack public accountability and have budgets that dwarf the budgets of many governments and agencies (Dal Maso, Robertson and Rogers, 2017).
However, there are several adverse effects upon labor caused by the digital revolution, such as the plight of subcontractors, workers with outdated skills, and the uneducated or undereducated young people. Digitalization enabled experimentation with new business models, which, in some cases, prefer sub-contractors instead of standardized employees (Postelnicu, Dinu and Dabija, 2015;Zadik et al., 2019). Contract work, remote working, and other such practices have created new organizational structures where physical locations with large quantities of people working under the same roof are no longer required. Subcontractors may work more independently, but they lack job security, a sense of belonging, experience wage stagnation, frequent job changes, and risk skill obsolescence (Manu et al., 2015;Zadik et al., 2019). Second, workers with outdated skills in sectors such as labor-intensive manufacturing, hospitality, restaurants, and low-end retailing have also been negatively affected by technological transformations (Dinu, 2017;Janssen and Mohrenweiser, 2018). Innovative technologies were introduced to replace or augment their work, while a "Milton Freedman-like ideology" neutralized labor unions' traditional role. Thirdly, nations with rigid labor laws and traditions unintendedly discriminated against young employees, many of whom are either uneducated or undereducated (Dunsch, 2016;Dinu, 2016).
There are also grievances from employers and graduates that the current educational system does not teach the necessary skills for the digital economy (Fletcher Jr. and Tyson, 2017;Vătămănescu et al., 2020). There are even suggestions that "front-loaded" educational systems are inadequate for a continually changing economy and should be replaced by a "lifelong" learning process (Crisan, Dabija and Dinu, 2015). These difficulties were acerbated by the recent COVID-19 crisis where subcontractors, low-skilled workers, and the young were disproportionately affected by the lockdown of the economy and may not recover. The current state of labor is polarized, lending itself to workaholism abuses and necessitating effective work engagement practices. These tendencies will persist into the future, as indebted governments will be unable to invest in education and social safety, and the private sector will be unevenly divided between "tech-superstar" and "digital laggards" (Templeton et al., 2019).

Workaholism
Oats (1971) was the first to coin the phrase "workaholism" and implied that it is more profound than the quantity of time spent working. Machlowitz (1977) pointed out that workaholism was an internal attitude that people had regarding their jobs. Spence and Robbins (1992) gave the field a working definition affirming "workaholic feels driven or compelled to work, not because of external demands or pleasure in work, but because of inner pressures that make the person distressed or guilty about not working" (p.161). Their influential work introduced the "workaholic triad", and a framework utilized by subsequent researchers to investigate workaholism. The Workaholism Battery (WorkBat) is a three parts instrument that delineates workaholics by (a) their high work involvement, (b) high drive, and (c) low enjoyment of their work. Porter (1996) built on their work and discovered that workaholics tend to obsess about the work and neglect other aspects of their lives. This does not happen because of external demands, but mainly due to internal factors. Robinson (1998) suggested that work-addiction workaholics experience is similar to an obsessive-compulsive psychological disorder since individuals cannot control their approach to work regardless of the negative consequences. Even if externally workaholics may seem to be just overworking,

The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States
their behavior is not justified by organizational or financial demands (Douglas and Morris, 2006;del Líbano et al., 2012). The evidence suggests that workaholism comes from within and has long-term negative consequences upon the individual's personal and social life. Snir and Harpaz (2012) concluded that workaholism is an internal and most often uncontrollable disorder and that "every workaholic is a heavy work investor, but not every heavy work investor is a workaholic" (p. 232).
A complementary perspective on workaholism was presented by Schaufeli Taris and Bakker (2008), who proposed a two-dimensional assessment instrument making the distinction between working excessively (WE) and working compulsively (WC). According to them, excessive work is an external, observable, and measurable behavior, while working compulsory is an internal attitude determining people to do more and feeling guilty when not working. This addictive side of workaholism was perceived as the most negative aspect of the phenomenon (Schaufeli Taris and Bakker, 2008). These findings led to the introduction of the Dutch Work Addiction Scale (DWAS), which is probably the most utilized instrument for quantitative research on workaholism. Workaholics report lower levels of mental and physical health (Shimazu, Schaufeli and Taris, 2010;Andreassen, 2014) and complain of emotional and mental fatigue (Taris, Schaufeli and Verhoeven, 2005). They are more likely to have trouble sleeping, experience cardiovascular complications and physical pain, do not regularly exercise, and do not take regular vacations (Ng, Sorensen and Feldman, 2007;Andreassen et al., 2011). Invariably, workaholics pay a heavy toll in their family life and social lives, engaging in unnecessary conflicts, manipulating or abusing their family members, and having an overall lower quality of life (Bonebright, Clay and Ankenmann, 2000;Di Stefano and Gaudiino, 2018).
For the organization where the workaholic works, there can be short-term benefits (Friedman and Lobel, 2003;. There may be cultural expectations and financial incentives to encourage and reward workaholic behavior . However, in the long run, this may be detrimental for both the individual and the organization, leading to burnout, absenteeism, poor quality of goods and services and work conflict Rabenu, Shkoler and Tziner, 2016). Workaholics typically cannot control their emotional outbursts, are not good delegators, and have difficulties communicating, collaborating, and creating in teams (Porter, 1996;Schaufeli, Taris and Bakker, 2008). Instead, organizations and teams should encourage substantial work investment (HWI) for the short run to solve the immediate crisis or to capitalize on unexpected opportunities (Ng, Sorensen and Feldman, 2007;Chernyak-Hai and Tziner, 2014). Kahn (1990) was the first author to introduce the concept of engagement at work, and he viewed it as the process by which people invested their time, energy and efforts in their jobs. He further articulated the relationship between individual identity and work responsibilities where people derived (a) meaning, (b) safety, and (c) availability from their work. Building on Kahn's concepts, Rothbard (2001) described work engagement in a dual paradigm of "attention" and "absorption". To him, the attention entailed the mental energy and time spent engaged in work, and absorption was the intensity an individual displayed while doing their job. Defining a slightly different methodology, Schaufeli, Taris and Bakker (2008) described work engagement as a cognitive attitude towards work comprised of three positive behaviors. They identified vigor (VI), which is the high mental and physical energy required to undergo intense efforts and enabled individuals to bypass the difficulties and challenges of their jobs. Their second positive element was dedication (DE), the thoughts and feelings an individual possessed, which enabled them to be enthusiastic and proud of their work. The third element was absorption (AB), which is an intense and enjoyable focus on work, as people do not want to stop and felt time passing quicker. Eventually, this became the paramount model on work engagement and led to the development of the Utrecht Work Engagement Scale (UWES), probably the most utilized assessment tool (Bailey et al., 2017). They pursue the organizational goals with genuine engagement, require less guidance and supervision, are a constructive influence on the organizational stakeholders and are not negatively affected in their personal and social lives (Tziner et al., 2015;Tziner and Shkoler, 2019).

Heavy work engagement
Engaged workers are typically motivated and satisfied with their jobs and claim to have fun while working (Shimazu, Taris and Schaufeli, 2010;Taris Schaufeli and Verhoeven, 2005;Shkoler and Tziner, 2020). For them, work generates positive feelings and emotions; they feel appreciated and feel that they contribute to their field (Bakker and Oerlemans, 2011;van Wijhe et al., 2013). Their mental and physical health is a priority; they do not engage in harmful behavior, they administer their physical and mental well-being better and report and overall high satisfaction with their lives (Schaufeli, Taris and Bakker, 2008;Shimazu et al., 2012). There is evidence to suggest that they earn more money than their disengaged colleagues (Bakker and Demerouti, 2008) and have better job performance (Bakker, 2009) and produce higher returns for their organizations (Bakker and Schaufeli, 2008;. In particular, Bailey et al. (2017) point to the benefits of workers' engagement in team performance, client loyalty, quality of service, and extra-role performance.

Mentorship as a creator of positive workplace attitudes
One workplace relationship that seems to relate to workaholism (Ng, Sorensen and Feldman, 2007;Robak, 2012) and heavy work investment through engagement (Caesens, Stinglhamber and Luypaert, 2014) is mentorship. As a result of four decades of research on mentoring relationships in the workplace (Levinson, 1978;Kram and Isabella, 1985), mentorship is an essential part of an employee's work experience. Most of the Fortune 500 companies now implement formal mentorship programs to develop such vital relationships (Bridgeford, 2007). Mentorship in the workplace has been developed from a single idea to a threecomponent construct, with early definitions describing mentors as counselors, sponsors, or guides (Levinson, 1978) who help provide upward movement and career support for mentees (Ragins and Scandura, 1999). These relationships generally included some hierarchical power distance between the mentor and mentee and focused primarily on career advancement (Wanberg, Welsh and Hezlett, 2003). Later, Kram (1983) articulated the second type of mentorship, offering psychosocial support for mentees through friendship, counseling, and role modeling. Subsequent studies distinguished role modeling as a separate construct from psychosocial support (Scandura, 1992;Scandura and Viator, 1994). First, career support enables mentees to gain experience and expertise through coaching and being included in challenging work assignments. Career support may also include sponsorship, which exposes mentees to other departments and helps them develop a more global, systems view of the organization (Hu, 2008;Gill, Roulet and Kerridgeet, 2018). Other functions within career support include networking opportunities and protection within the institution. This type of support is beneficial as the mentor can help newer employees develop more robust social AE The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States networks and invite them to external social events. These interactions increase work engagement and allow natural interactions with colleagues from different departments or business units (Newman, Thanacoody and Hui, 2012).
Psychosocial support is a more personal and developmental form of mentorship and involves friendship, counseling, and affirmation (Kram, 1985). Psychosocial support engenders trust, encouragement, and support. This aspect allows for truthful, candid conversations, as mentees feel safe to discuss fears and anxieties, ask questions, take risks, and disagree with their mentors (Lankau and Scandura, 2002). Mentors who show psychosocial support are friendly, accepting, and serve as a counsel for mentees as they navigate the institution. While little is known on the effects of psychosocial support on workaholism, this type of caring support has been positively related to employee engagement (Claxton et al., 2012). The third and more passive form of mentoring (Hu, Pellegrini and Scandura, 2011) is role modeling. Mentees who identify with their mentors may imitate their actions, attitudes, values, and principles (Kram, 1983). In this case, the junior person admires the senior person's career path and tries to imitate and seek advice from that person. However, in some rare cases, as employees seek to imitate their mentors, this type of mentorship may increase workaholism (Robak, 2012). In addition to specific behaviors associated with mentorship, another important construct to note within the mentor/mentee relationship is mentorship quality. Mentorship quality refers to the overall character of the relationship and satisfaction with one's mentor.
Empirical research has shown that mentoring functions positively to mentee learning and job satisfaction, and negatively to turnover intentions, actual turnover behavior, and role ambiguity (Lankau and Scandura, 2002). Allen et al. (2004) also found high quality mentoring to lead to increased pay and promotion possibilities, a greater sense of selfcompetence, and increased self-esteem. Besides being positively related to essential employee outcomes, quality mentoring can also reduce negative behaviors such as workaholism and work-related conflict (Ng, Sorensen and Feldman, 2007;Caesens, Stinglhamber and Luypaert, 2014). Employees engaged in mentoring relationships reported lower levels of role stress, work-family conflict, and stress during institutional turmoil (Kram and Hall, 1989). Employee flourishing, job satisfaction, and job stress are measurable employee outcomes linked to important organizational variables, including workaholism and heavy work investment (Shimazu, Schaufeli and Taris, 2010;Caesens, Stinglhamber and Luypaert, 2014). Employee flourishing refers to employees' positive emotions, engagement, relationships, meaning, and accomplishment (Seligman, 2011). Employees who flourish experience higher job satisfaction and organizational commitment. Job satisfaction refers to negative or positive attitudes regarding a job (Russell et al., 2005), and it relates positively to performance, work quality, and productivity (Parker et al., 2003). Both employee flourishing and job satisfaction showed positive associations to work engagement (Diedericks and Rothmann, 2013). Job stress refers to work conditions that disrupt worker physiological or psychological characteristics. Employees with high levels of job stress have shown lower organizational commitment, job satisfaction (Rashid, Bajwa and Batool, 2016), and higher levels of burnout (He et al., 2020). Because quality mentoring relationships have shown to influence the workplace experience positively, we propose the following hypotheses: H1: There is a positive relationship between mentoring functions (career support, psychosocial support, and role modeling) and mentorship quality.

H2a: There is a positive relationship between mentorship quality and the employee outcomes of (a) employee flourishing and (b) job satisfaction.
H2a: There is a negative relationship between mentorship quality and the employee outcome of (c) job stress.
As mentorship programs are becoming more formal in organizations, studies have shown that the quality of interactions (e.g., depth of relationship and sharing of information) decreases (Johnson, Anderson and Franchetti, 2009). In other words, while formal mentorship programs are developed for noble purposes, mentorship quality, in addition to mentorship functions, may play a part in influencing the mentee experience. Therefore, we propose the following hypothesis: H3: Mentorship quality mediates the relationship between mentor functions (career support, psychosocial support, and role modeling) and employee outcome variables (employee flourishing, job satisfaction, and job stress).

Research design
The survey was conducted online to examine the relationships between mentors and mentees in a work-related setting, as well as the level of satisfaction on behalf of the mentees. To reduce the risk of response sets, we introduced an instructional manipulation check (Oppenheimer, Meyvis and Davidenko, 2009). Our study was comprised of the following measurements:

Mentor Functions. We measured mentor functions using Castro (2004) "Mentoring
Functions Questionnaire" (MFQ-9). This 9-item scale measures the three significant dimensions of mentoring, which are (a) career support, (b) psychosocial support, and (c) role modeling. Examples of items measuring career support include, "My mentor takes a personal interest in my career" and "My mentor helps me coordinate professional goals." Examples of items measuring psychosocial support include, "I consider my mentor to be a friend" and "I share personal problems with my mentor." Examples of items measuring role modeling include, "I try to model my behavior after my mentor" and "I respect my mentor's ability to teach others." Our study's internal reliability coefficients were as follows: for career support 0.86; for psychosocial support 0.83; and for role modeling 0.82. These internal reliability coefficients are strong, as in general, the accepted minimum alpha level for studies utilizing survey data is 0.70 (Nunnally, 1978).

Mentorship Quality.
We measured mentorship quality using Allen and Eby's (2003) 5-item Likert-type scale. Examples of items measuring mentorship quality include, "The mentoring relationship between my mentor and I was very effective", "I am very satisfied with the mentoring relationship my mentor and I developed", and "I was effective at utilizing my mentor." Our alpha coefficient for measuring mentorship quality was = 0.91. Employee Flourishing. We measured employee flourishing using the 15-item Likert-type "PERMA" instrument developed by Seligman (2011

The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States
Job Satisfaction and Job Stress. We measured job satisfaction and job stress using House and Rizzo's (1972) 7-item Likert-type instrument. Examples of items measuring job satisfaction include, "I feel a great sense of personal satisfaction from my line of work" and "All things considered (i.e., paid promotions, supervisors, coworkers, etc.), how satisfied are you with your present line of work?" Examples of items measuring job stress include, "At the end of the day, my job leaves me stressed out" and "Problems associated with work have kept me awake at night." The internal reliability for job satisfaction questions was 0.94 and 0.85 for job stress. Means and standard deviations for all measures appear in table no. 1. We mention that the scores on all scales had a theoretical range from 1 to 5 (mentorship variables), 1 to 10 (flourishing), and 1 to 7 (job satisfaction and job stress), such that higher scores indicated a greater level of the variable. The scores on all multipleitem scales represented the mean of the items comprising that scale. Some items were worded positively and others negatively to mitigate response sets. 3.59 1.49 ns 0.12 * ns ns -0.24 ** -0.16 ** -0.19 ** -0.28 ** -0.31 ** -0.39 ** 1 Note: 1-Mentee Gender; 2-Education; 3-Years at Organization; 4-Income; 5-Career Support; 6-Psychosocial Support; 7-Role Modeling; 8-Mentorship Quality; 9-Employee Flourishing; 10-Job Satisfaction; 11-ob Stress; * p < 0.05; ** p < .01; ns = not significant; SD = Standard Deviation.

Research methodology
In order to test the hypothesis mentioned above, we undertook a research study to explore the impact of the traditional mentoring functions of (1) career support; (2) psychological support and (3) role modeling on the employees (a) flourishing, (b) satisfaction and (c) jobrelated stress. We further wanted to assess the quality of the mentorship relationship and its possible implications on the overall quality of the work experience. This study utilized a cross-sectional dataset whereas participants who engaged in a mentoring relationship with a mentor completed a questionnaire indicating the types and quality of mentorship received, as well as key employee outcome variables. To test our hypotheses, we utilized a path analysis. The path analysis methodology is typical for measuring latent and mediator variables in management/business journals (Loehlin and Beaujean, 2017). The aim of this study is to contrast mentorship with HWI. For example, if workaholism is believed to be a negative phenomenon, we ask the question: what tools do we have to make it better? In the present study, we explored mentorship as one of those tools. Although mentorship has been generally viewed as a positive phenomenon within the workplace, it has seldom been applied to workaholism and heavy work investment. During the summer of 2018, we collected a sample of 271 (N=271) full-time employed adults through Amazon's Mechanical Turk website, which is recognized as a high-quality source of data collection for social science research (Buhrmester, Kwang and Gosling, 2011). The self-selection criteria were that they were already engaged in a work-related mentoring relationship and could provide us with valuable information and insight regarding their engagement and level of satisfaction. Although the group is not representative of the entire US working population, we feel it is sizeable enough to provide insight applicable to mentoring and work-related studies. The reason for choosing the sample from the US is the fact that the authors who collected the data live in the US. The sample group comprised 60% males and 40% females, all living in the US and ranging between 18 to 82 (M = 34.40 years, SD = 11.17). The ethnic background of the group was: 71.2% Caucasian, 7.4% Asian/Pacific Islander, 4.4% Hispanic, 8.9% Black/African American, 1.1% Native American, and 7.0% other. They indicated the length of employment with their current organization raging between one month to 34 years (M = 6.72 years, SD = 6.30). This data highlights the demographic breakdown of the sample in the study.

Results of the survey
To test our hypotheses, we used a path analysis in AMOS. We controlled for mentee gender, mentor gender, age, race, education, years at the organization, and income. Mentee gender, education, years at the organization, and income showed significant correlations with study variables (see table no. 1). Once included in the model, the control variables became nonsignificant, so we removed them for simplicity.

The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States
As illustrated in table number 2, the following showed a positive relationship with the mentorship quality: (1) career support (β = 0.51, p < 0.01); (2) psychosocial support (β = 0.14, p < 0.01); and (3) role modeling (β = 0.32, p < 0.01). These results support hypothesis nr. 1, where we stated that there is a positive relationship between mentor functions (career support, psychosocial support, and role modeling) and mentorship quality. Mentorship quality also showed significant relationships with employee flourishing (β = 0.27, p < 0.01) and job satisfaction (β = 0.27, p < 0.01) thus supporting hypothesis nr. 2a that there is a positive relationship between mentorship quality and the employee outcomes of (a) employee flourishing and (b) job satisfaction. Mentorship quality also showed a significant negative relationship with job stress (β = -0.28, p < 0.01), supporting hypothesis nr. 2b that there is a negative relationship between mentorship quality and the employee outcome of (c) job stress.
In hypothesis nr. 3, we stated that mentorship quality mediates the relationship between mentor functions (career support, psychosocial support, and role modeling) and employee outcome variables (employee flourishing, job satisfaction, and job stress). This hypothesis was supported except for two hypothesized indirect paths. Relationships between psychosocial support and employee flourishing (β = 0.04), job satisfaction (β = 0.04), and job stress (β = -0.04) were indirect and significant. Additionally, role modeling also showed significant, indirect relationships with employee flourishing (β = 0.09), job satisfaction (β = 0.09), and job stress (β = -0.09). Results indicated that direct affects were also present in the relationships between career support and employee flourishing (p < 0.05, β = 0.23) and between career support and job satisfaction (p < 0.01, β = 0.32). Seven out of nine relationships support hypothesis 3, and we illustrate the results of the path analysis in figure no. 1. Fit indices for the path analysis model suggest a good model fit. The model showed a non-significant χ 2, and the root mean square error of approximation (RMSEA) (0.047), the comparative fit index (CFI) (0.99), and the Tucker-Lewis index (TLI) (0.99), all met critical values for a good model fit. Figure no. 1 also represents the originality of our research as we trust it will be a modest contribution to mentorship studies in general and workaholic studies in particular. The results suggest that the activity of mentoring and the quality of mentoring can reduce workaholic tendencies if properly done. results/significant relationships between variables with their respective beta weights. While some of them are hyptotheses that we tested, others are significant results that were present in the data, but not hypothesized. Those represent the partial mediation.

Conclusions
The findings of the present study may help organizations reduce workaholism and increase heavy work investments through formal mentorship programs. However, without the appropriate mentor functions, the mentee will probably not perceive the relationship as one of high quality, even if the mentor authentically desires to be helpful for the mentee. Quality is a perception by nature, and it takes intentional behaviors demonstrated by the mentor and support by the organization that leads to the perceived quality of the mentoring relationship. Although the current global work situation favors an increase in workaholism tendencies, and some people have an internal predisposition towards workaholism (Schaufeli, Taris and Bakker, 2006), our study highlights that mentoring can diminish the adverse effects of this behavior, a fact also supported by the literature (Ng, Sorensen and Feldman, 2007). Furthermore, massive work investment (MWI), through which people have a positive attitude towards their workplace (Shimazu, Schaufeli and Taris, 2010), is strengthened by the process of mentoring at work (Caesens, Stinglhamber and Luypaert, 2014). The present research demonstrates that a qualitative mentoring activity supports employees' career development and psychosocial support, aspects found in previous research (Kram, 1985). The literature also indicates a positive relationship between the quality of mentoring and employee flourishing and job satisfaction (Lanku and Scandura, 2002), which was also highlighted by the results of this research. Another essential aspect underlined in the present research is that employees who benefit from mentoring relationships report a lower level of stress at work (Kram and Hall, 1989). These results indicate that the literature on mentorship is valid for the United States workforce. We trust that our findings may offer insight to organizations and individuals who aim to equip their employees for more effective mentoring engagement. Results indicate that if mentorship is well-executed, it can improve the overall employee experience, leading to a particular attitudinal profile of the mentee that may help alleviate workaholism and facilitate engagement.
Our research aimed to survey the connections between the mentorship functions of career support, psychosocial support, and role modeling on the consequences of employee flourishing, job satisfaction, and job stress by focusing on the mediating role of mentorship quality. The broad application of our study is to examine whether mentorship can have a separating impact upon mentees away from workaholism and towards heavy work investment. The literature on workaholism and heavy work investment covers various organizational topics relating to the workplace experience. The present study extends the literature by illustrating the importance of mentorship concerning the mentee's workplace experience to offer insights that may ultimately alleviate workaholism and encourage heavy work investment.
From a managerial point of view, our survey results seem to suggest three key findings. First, each of the mentorship functions of career support, psychosocial support, and role modeling showed direct and positive associations with mentorship quality. Thus, we can conclude that when mentors intentionally engage in these three behaviors, the mentees will report higher levels of satisfaction with the relationship and the mentor. Therefore, individuals and organizations that intend to create and engage in a formal mentorship program to alleviate workaholism and encourage heavy work investment, among other things, should train their mentors along these dimensions.

The Importance of Mentorship in Diminishing Workaholism and Increasing Heavy Work Investment: Evidence from the United States
Second, we examined how mentorship quality relates to employee outcomes. The data shows that the quality of the mentorship relationship was positively associated with employee flourishing and job satisfaction and negatively related to job stress. Thus, we can conclude that organizations and individuals who want to foster employee flourishing and job satisfaction, as well as reduce job stress in their employees, should not only focus on the existence of mentorship relationships in the organization but more so on their quality.
Third, a path analysis illustrated how the mentorship functions of career support, psychosocial support, and role modeling had direct effects on the quality of mentoring and indirect effects on employee flourishing, job satisfaction, and job stress. While the quality of mentoring relationships only partially mediated the relationships between career support and the outcomes of employee flourishing and job satisfaction, the model provided evidence supporting the seven remaining paths. It does seem to conclude that mentors who intentionally provide career support, psychosocial support, and role modeling, their mentees benefit from a higher level of mentorship quality. This aspect, in turn, increases employee flourishing, job satisfaction, and reduces job stress.
The first limitation of our research is that it only surveys employees of organizations and may not apply to entrepreneurs and subcontractors, which, as stated in the introduction, increasingly comprise a larger workforce. A subsequent study may include business owners and subcontractors. The second limitation of our study is that it only surveys US workers, missing a large portion of the global workforce. Inherently, it does not consider the impact of culture on issues such as mentorship, workaholism, and heavy work investment. Future studies could focus on geographic regions outside the US to enhance the representativeness of the research or specific industries to explore how mentoring relationships are enacted differently by industry. Thirdly, our study's scope was generally in the mentorship and the quality of the work experience and not explicitly focusing on workaholism and heavy work engagement.
Future studies should focus on this, perhaps with a longitudinal test design to survey if mentorship does have a sustainable impact on alleviating workaholism. Some literature argues that mentors and role models may contribute to workaholism. Future studies could explore the role of mentorship functions and quality with workaholism and heavy work investment included in the model.