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1. Article
An Integrated Model of
Work–Study Conflict and
Work–Study Facilitation
Mikaela S. Owen1
, Phillip S. Kavanagh1
, and Maureen F. Dollard1
Abstract
The rise in working university students is a global phenomenon with more than half of the student
population working while studying at university. Within this trend of dual participation, working
students face unique stressors such as work–study conflict and facilitation. Work–study conflict
drives students’ poor health, whereas work–study facilitation drives positive academic outcomes. In
this article, we review and critique several work–study interface models proposed to explain the
development and consequences of these stressors. The review uncovers important omissions and
limitations of the models, reducing their utility and generalizability. Therefore, we propose a new
work-to-study model, which addresses the omissions of the previous models. The work-to-study
model builds on the current literature and models and integrates psychosocial safety climate theory,
as it relates to the extended job demands–resources model to advance our understanding of the
development and consequences of work–study conflict and facilitation.
Keywords
work–study conflict, work–study facilitation, working students, psychosocial safety climate, job
demands–resources model
Currently in Australia and across the globe, most university students are working while studying. For
example, from 2007 to 2010, the rates of working students in Australia remained relatively stable yet
high in the Australasian Survey of Student Engagement, ranging between 65% and 69% for first-year
university students, and 71% to 76% for later year students (Coates, 2015). Additionally, high propor-
tions of working students are found in the United States (78%; American Council on Education,
2006) and United Kingdom (75%; National Union of Students, 2008). Participation in paid employment
while studying appears to be common practice for students. Research indicates that working while study-
ing can lead to detrimental outcomes such as low academic engagement, poor grades, high turnover
1
School of Psychology, Social Work and Social Policy, Asia Pacific Centre for Work Health and Safety, University of South
Australia, Adelaide, South Australia, Australia
Corresponding Author:
Mikaela S. Owen, School of Psychology, Social Work and Social Policy, Asia Pacific Centre for Work Health and Safety,
University of South Australia, GPO Box 2471, Adelaide, South Australia 5001, Australia.
Email: mikaela.owen@mymail.unisa.edu.au
Journal of Career Development
1-14
ª Curators of the University
of Missouri 2017
Reprints and permission:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/0894845317720071
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2. intentions from study (Baron & Corbin, 2012; Jackling & Natoli, 2011; Webber, Krylow, & Zhang,
2013), and poor psychological health (Mounsey, Vandehey, & Diekhoff, 2013). While employment can
also lead to several benefits (e.g., increased income, increased esteem, improved communication and
social, and technical and generic skills; Broadbridge & Swanson, 2006; Smith & Patton, 2013), the kinds
of jobs students acquire are often stressful (i.e., long working hours, high work pressure, insecure, and
on-call) and commonly clerical, sales, or service related (Polidano & Zakirova, 2011).
University students are our future workforce, and as such, their success and development during
university study drives the future success and development of the economy when they later enter the
labor market after completing their qualifications. Therefore, it is important to understand the factors
that drive negative and positive outcomes from combining work with study. Given the high proportion
of university students working while studying and the potential negative implications for health and
academic outcomes, it is important to understand whether and how conditions in students’ external
working environment influence their health and academic outcomes. Given these costs and benefits,
research needs to focus on the conditions that students face in the workplace so that policies and stra-
tegies are developed to protect students’ health and academic performance.
We propose a new framework, the work-to-study model, to understand how workplace conditions
affect students’ health and academic outcomes. The framework integrates previous research on work–
study conflict and facilitation, prior models of work–study conflict, and the work stress model: the psy-
chosocial safety climate (PSC; Dollard & Bakker, 2010) extended job demands–resources model
(JD-R; Bakker & Demerouti, 2007; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). In elaborating
our model, we focus on two main constructs work–study conflict and work–study facilitation. We
define work–study conflict as the experience when demands and responsibilities in a workplace inter-
fere with an ability to meet the demands and responsibilities in the study domain (see Markel & Frone,
1998). We define work–study facilitation as the improvement in students’ ability to engage in study
due to participation in work (see Butler, 2007). In the work-to-study model, there are two main pro-
positions. First, feelings of work–study conflict and work–study facilitation mediate the association
between students’ job demands and resources and their health and academic outcomes. Second, levels
of PSC in the students’ workplace trigger the work-to-study model by influencing their exposure to
various job demands and job resources.
PSC Extended JD-R Model
The PSC (Dollard & Bakker, 2010) extended JD-R (Bakker & Demerouti, 2007; Demerouti et al.,
2001) is a comprehensive model of work stress that incorporates task-level factors and climate factors.
The two task-level factors, job demands and job resources, explore the impact workplace environments
can have on workers’ health and well-being and their occupational outcomes. PSC explains how jobs
are designed and how workplace conditions, demands and resources, arise.
PSC refers to the enacted practices, policies, and procedures that promote workers’ psychological
health and well-being (Dollard & Bakker, 2010). The level of PSC within an organization is deter-
mined by workers’ perception of how their senior management performs in four important domains:
(1) involvement and commitment toward stress prevention, (2) priority given to psychological health
and safety over productivity goals, (3) communication across various levels of the organization about
health and safety, and (4) participation and consultation about occupational health and safety issue by
various members of an organization (Hall, Dollard, & Coward, 2010). Therefore, organizations with
high PSC will prioritize workers’ psychological health and safety by developing and communicating
policies and processes in consultation with various members of the organization to prevent stress and
promote positive well-being among their workers.
PSC triggers the two underlying pathways in the JD-R model, the health erosion pathway and moti-
vational pathway, through its influence on job demands and job resources (Dollard & Bakker, 2010;
2 Journal of Career Development XX(X)

3. Idris, Dollard, & Winefield, 2011). In high PSC organizations, senior management will help design
jobs that promote the psychological health and well-being of their workers, by ensuring workers have
manageable demands and adequate access to resources. Demands are the aspects of a job that are phys-
ical, social, or organizational in nature requiring sustained physical or mental effort, leading to poor
physiological and psychological outcomes (Bakker & Demerouti, 2007; Demerouti et al., 2001).
Resources are health-protecting aspects of a job that are physical, psychological, social, or organiza-
tional in nature and (a) assist in the achievement of work goals; (b) reduce job demands and their asso-
ciated physiological and psychological outcomes; and (c) promote personal growth, learning, and
development (Bakker & Demerouti, 2007; Demerouti et al., 2001).
In the health erosion pathway, job demands trigger a health eroding process. Demands require sus-
tained physical and/or psychological efforts potentially leading to physiological and/or psychological
costs affecting workers’ health and in turn outcomes in their organization, such as high absenteeism
(Bakker, Demerouti, de Boer, & Schaufeli, 2003). While the main component of the health erosion
pathway is job demands, resources can moderate the impact of demands on workers’ psychological
and emotional health. That is, under conditions of high job resources, the impact of demands on psy-
chological and emotional health outcomes is reduced (Bakker, Demerouti, & Euwena, 2005; Xantho-
poulou et al., 2007).
In the motivational pathway, access to resources triggers a motivation process, as resources assist in
achieving work goals and satisfy basic physiological needs such as autonomy, belongingness, and
competence, affecting workers’ organizational outcomes (Hakanen, Schaufeli, & Aloha, 2008; Schau-
feli & Bakker, 2004). Consistent with the health erosion pathway, there can be a moderation of job
demands on the association between workers’ resources and their engagement in the workplace. That
is, when workers have high levels of demands, the positive association between workers’ resources and
their engagement is enhanced (Bakker, Hakanen, Demerouti, & Xanthopoulou, 2007; Bakker, Van
Veldhoven, & Xanthopoulou, 2010).
Working Students
In the extant literature, the impact of combining work and study primarily focuses on students’ working
hours. Students who work over 22hr per week have lower grades and are more likely to dropout compared
to students who work 22 hr or less per week (Applegate & Daly, 2006). Students who do not work at all
have lower grades and report greater intentions to dropout when compared to students who engage in a
moderate amount (10–19 hr) of paid employment (Dundes & Marx, 2007). Therefore, some paid employ-
ment appears beneficial for students in addition to the financial benefits such as being able to afford text-
books. The threshold for experiencing benefits from paid work appears to be approximately 10 hr of work
per week with a Goldilocks zone (i.e., just the right amount) ranging between 10 and 22 hr.
Research on work–study conflict and work–study facilitation has started to explore the impact of
working conditions (i.e., job demands and job resources) on students’ health and academic outcomes,
beyond just working hours. Poor working conditions, high demands, and low levels of resources can
lead to high levels of work–study conflict and low levels of work–study facilitation (Adebayo, 2006;
Butler, 2007; Markel & Frone, 1998).
Work–Study Conflict
Most predictors currently identified leading to work–study conflict derive from students’ places of
work. Specifically, the predictors of work–study conflict are those that lead to feelings of exhaustion
and feelings of engagement among nonstudent workers, job demands and job resources, respectively
(Schaufeli & Bakker, 2004). Students employed in poorly designed workplaces with high demands and
low resources experience high levels of work–study conflict (Adebayo, Sunmola, & Udegbe, 2008).
Owen et al. 3

4. Work environments high in job demands drain vital finite resources that students need for their study,
such as time and energy (Butler, 2007), which in turn leads to feelings of work–study conflict. Specif-
ically, high levels of job demands, such as workload and working hours, are associated with high levels
of work–study conflict (Adebayo, 2006; Adebayo et al., 2008; Markel & Frone, 1998).
Students who report high levels of job resources, such as control and rewards in the workplace,
report lower levels of work–study conflict (Butler, 2007; Creed, French, & Hood, 2015). Social sup-
port, family support, university support, and work support are additional resources that influence
work–study conflict. High levels of supervisor social support and coworker social support are nega-
tively associated with work–study conflict (Adebayo et al., 2008). Further, when students’ cowor-
kers and/or supervisors take an interest in the students’ study domain (i.e., interpersonal support),
students experience lower levels of work–study conflict (Wyland, Lester, Ehrardt, & Standifer,
2016). Family support does not appear to have an influence on work–study conflict once students’
supervisor and coworker support are accounted for (Adebayo, 2006). Therefore, it seems that the
supports students receive from their workplace are more important in reducing work–study conflict
than family support.
High work–study conflict contributes to students’ poor health and well-being (Adebayo et al.,
2008; Brunel & Grima, 2010; Cinamon, 2016; Park & Sprung, 2013). For example, students with
high levels of work–study conflict report having poor sleep quality and fatigue (Park & Sprung,
2014) and a higher number of physical injuries (e.g., contusions/bruises) in the workplace (Ou &
Thygerson, 2012) compared to students with low work–study conflict. Additionally, high work–
study conflict is linked with depression (Cinamon, 2016) as well as poor psychological health (Park
& Sprung, 2013). While having high work–study conflict can lead to minor physical injuries in the
workplace, there seems to be little evidence to support an association between work–study conflict
and general physical health (i.e., Park & Sprung, 2013). Overall, students with poor work–study con-
flict experience poor health and well-being.
Work–Study Facilitation
Similar to work–study conflict, the work environment plays a role in the development of students’
work–study facilitation. Job resources in the workplace environment can provide students with
resources that can be utilized in their studies. When students have control in their workplace, they can
develop skills on how to manage their time and prioritize tasks, skills students could use in their stud-
ies. These job resources lead to positive feelings about combining work with study and as such feelings
of work–study facilitation. For example, university students experiencing high levels of resources,
such as social support and job–education congruence, report experiencing high levels of work–study
facilitation (Butler, 2007; Cinamon, 2016; Wyland et al., 2016). Students who have control over how
and when they perform their work tasks (i.e., job control) and who need to use the specific knowledge
and skills acquired from their studies in their workplace (i.e., job–education congruence) have high
levels of work–study facilitation (Butler, 2007; Wyland et al., 2016). Similarly, students in workplaces
that provide rewards in the form of enhancing status or providing privileges accessible for use in
another domain have high levels of work–study facilitation (Creed et al., 2015).
Research exploring the link between job demands and work–study facilitation is lacking. Currently,
only work hours and psychological demands are linked with work–study facilitation, with students who
spend more hours in the workplace experiencing low levels of work–study facilitation (Cinamon, 2016)
and that high psychological demands lead to high levels of work–study facilitation (Wyland et al., 2016).
Students with high levels of work–study facilitation have high dedication levels, academic perfor-
mance, satisfaction, and engage in high levels of academic planning (Butler, 2007; Cinamon, 2016;
Creed et al., 2015; McNall & Michel, 2011). There does not appear to be any significant associations
between work–study facilitation and turnover intentions/dropout intentions (Taylor, Lekes, Gagnon,
4 Journal of Career Development XX(X)

5. Kwan, & Koestner, 2012) or attendance (McNall & Michel, 2011). Overall, it appears that work–study
facilitation has an impact on students’ academic outcomes, but due to the limited research, the extent
of this influence is unclear. As work–study facilitation has received less attention in the work–study
interface literature, fewer outcomes have been identified, resulting in a limited understanding of the
outcomes of work–study facilitation, with the majority of identified outcomes in the academic domain.
Prior Work–Study Models
With large proportions of students combining paid employment with study across the globe, it is unsur-
prising that models based on the impact of this combination of study and paid employment among
working students have arisen. Specifically, several models of work–study conflict and work–study
facilitation were developed to bring more clarity to the wealth of antecedents and outcomes for
work–study conflict and work–study facilitation. Specifically, the work–study interface model (Lin-
gard, 2007), the model of work–study conflict (Markel & Frone, 1998), and the work–study conflict
and facilitation model (Butler, 2007) were proposed to address how conditions in the workplace influ-
enced students in their studies. The work–study interface and conflict models focus on the detrimental
side of combining work with study, whereas the work–study conflict and facilitation model considers
both the negative and the positives of combining work with study. Our proposed model, the work-to-
study model, considers the strengths and flaws in the aforementioned models and builds on these mod-
els and existing empirical literature.
Work–Study Interface Model
Lingard (2007) proposed the work–study interface model. This model proposes a pathway from time
spent working to study burnout and work satisfaction, via work–study conflict. The work–study inter-
face model also includes the pathway beginning with study, in that time spent studying time interferes
with students’ study satisfaction via study–work conflict.
The work–study interface model is based on propositions from the scarcity perspective/approach to
role theory (Marks, 1977) and work–family interface model (Frone, Russel, & Cooper, 1992; Frone,
Yardley, & Markel, 1997). Within the scarcity perspective, individuals have a prescribed finite amount
of resources, time, and energy. Therefore, resources used in one role, such as work, are consequently
unavailable for another role, such as study. When individuals are invested in both roles, they will expe-
rience a degree of role conflict, as committing to one role invariably reduces the ability to succeed in
another role. Lingard (2007) applied the scarcity perspective in terms of time commitments to the
development of work–study conflict. Time students spend at work reduces the time they have available
for their university studies, making it more difficult to successfully fulfill their study tasks, resulting in
feelings of work–study conflict.
The work–family interface model (Frone et al., 1992, 1997), from which the work–study interface
model was developed, draws from work stress and family stress research and integrates the two to form
one comprehensive model. The work–family interface model explores associations between psycho-
social factors in the workplace and outcomes in the family environment, via work–family conflict, and
the relation between psychosocial factors within the family environment and workplace outcomes, via
family–work conflict. Consistent with the work–family interface, the constructs of work–family con-
flict and family–work conflict are mediating variables that explain how stressors in one domain, work,
spill over and affect an individual in another domain—family (Frone et al., 1997). For example, indi-
viduals who have poor working environments, such as high workloads and little support, will experi-
ence a high level of work–family conflict, which promotes high levels of domain-specific distress, in
this case, family distress. In turn, individuals who have poor family environments will have high fam-
ily–work conflict and as such experience distress in their workplace. This work–family interface model
Owen et al. 5

6. provided the framework for the work–study interface model proposed by Lingard (2007), in that work–
study conflict acts as a mediator between the workplace conditions, time spent working, and the aca-
demic environment, study burnout. However, the rest of the model has the predictors and outcomes in
the same domain, from time spent studying to study satisfaction via study–work conflict, and from
time spent working to work satisfaction via work–study conflict.
Against expectations, Lingard (2007) found that time spent studying is not significantly associated
with students’ study–work conflict nor is time spent working with work–study conflict. Consistent
with the scarcity perspective, time spent studying and time spent working are negatively associated
(Lingard, 2007), in that time spent in one role inevitably limits the time available for another role
(Marks, 1977). It is possible that the lack of association found between time spent working/studying
and interrole conflict is because time is not a predictor of students’ interrole conflicts (i.e., work–study
and study–work conflict); however, there is support in the literature for the pathway between time
commitments and interrole conflict. Markel and Frone (1998) found that university and high school
students who spent a high number of hours in paid employment had high levels of work–study conflict.
Similarly, students working full time in Nigeria have higher levels of work–study conflict due to
greater time commitments, compared to students only working part time (Adebayo et al., 2008). Over-
all, research on work–study conflict indicates that time commitments are only important while consid-
ering the role of other workplace/study demands and resources in the development of interrole conflict.
Inconsistent with previous research identifying links between students’ work–study conflict and
their health and well-being (i.e., Adebayo, 2006; Park & Sprung, 2013), Lingard (2007) did not find
significant associations between work–study conflict and work satisfaction, emotional exhaustion, or
cynicism when testing the work–study interface model. However, these inconsistent findings may be
due to methodological issues with Lingard’s (2007) sample recruited during an in-person psychology
lecture using pen-and-paper surveys—students who experience high levels of work–study conflict are
less likely to attend their university lectures and/or tutorials (McNall & Michel, 2011); therefore, stu-
dents experiencing dangerous levels of work–study conflict were likely excluded from the study.
The Model of Work–School Conflict
The second model is the model of work–school conflict as proposed by Markel and Frone (1998). The
work–family conflict model (Frone et al., 1992, 1997) provides the framework for the model of work–
school conflict. Like the work–family conflict model, interrole conflict (e.g., work–study conflict) med-
iates the link between workplace conditions and the outcomes in the second primary role (e.g., study).
Research testing this model (i.e., Markel & Frone, 1998) found that students’ psychological demands, job
dissatisfaction, and hours worked negatively affect students’ study readiness, via work–study conflict
with study readiness positively influencing further study outcomes, such as academic performance.
Similar to Markel and Frone (1998), Butler (2007), Cinamon (2016), and Creed, French, and Hood
(2015) identified that time demands influenced students’ experience of work–study conflict, with more
hours worked driving high levels of work–study conflict. The link between psychological demands and
work–study conflict in the model of work–study conflict was also found among undergraduate and post-
graduate students in both Nigeria and the United States(Adebayo, 2006; Butler, 2007; Wylandet al., 2016).
The pathway from job dissatisfaction to work–study conflict has received less attention in the lit-
erature than from work–study conflict to study readiness. To date, there is lack of research that has
explored the pathway from job dissatisfaction to work–study conflict; however, there is evidence of
a link between work–study conflict and the various aspects of study readiness (attendance, effort, and
preparedness; Markel & Frone, 1998). Researchers have found a positive association between work–
study conflict and attendance (Butler, 2007; McNall & Michel, 2011) and between work–study con-
flict and study effort (Butler, 2007). Overall, there is support for most of the pathways in the model of
work–study conflict.
6 Journal of Career Development XX(X)

7. Work–Study Conflict and Facilitation Model
The third model, the work–study conflict and facilitation model (Butler, 2007)—informed by the scar-
city perspective and resource expansion approach (Marks, 1977)—is based on the proposition that the
working environment influences students’ academic outcomes via the two work–study interfaces,
work–study conflict and work–study facilitation. In the resource expansion approach, resources are
“abundant and expansible” (Marks, 1977, p. 926) with the expansionist approach acknowledging that
certain environments can increase individuals’ energy (in contrast to the scarcity perspective, where
roles drain an individual’s resources making them unavailable for another role). Environments that are
supportive not only prevent an individual from loss of energy but also create energy for the individual
either in the originating role or for use in another role (Marks, 1977). Within the work–study conflict
and facilitation model, low job resources (e.g., job control) and high job demands (e.g., psychological
demands and hours worked) correspond with high levels of work–study conflict, which in turn drives
students’ low study satisfaction and poor academic performance. This work–study conflict and facil-
itation model also considers the potential positive impact of working while studying by incorporating a
pathway including work–study facilitation. Students with high job resources (e.g., job-education con-
gruence and job control) experience both high study satisfaction and high academic performance, via
high levels of work–study facilitation.
According to the work–study conflict and facilitation model, job demands deplete working stu-
dents’ finite energy and time, resulting in increased work–study conflict, consistent with the scarcity
perspective. As such, time and energy spent in the work role to meet the demands of various workplace
tasks reduces the time and energy available to spend on various study demands. When students invest
too much time and energy in their work role via hours worked and job demands, feelings of work–
study conflict arise, as it becomes more difficult to successfully complete their study tasks due to
depleted time and energy resources. This pathway from job demands to work–study conflict is consis-
tent with the findings from the model of work–study conflict among high school and undergraduate
university students in the United States (Markel & Frone, 1998).
In the work–study and facilitation model, job resources, job control, and job–education congruence
are proposed to increase feelings of work–study facilitation. Consistent with the resource expansion
theory, job control and job–education congruence can provide students with resources for use in their
study role, enhancing feelings of work–study facilitation. For example, job–education congruence, in
which students are required to apply the skills and knowledge they learn in their studies, could enhance
their skills and understanding through application and practice. The enhanced study skills and knowl-
edge then increases feelings of work–study facilitation. As such, access to resources (e.g., job control
and job-education congruence) provides students with access to further resources (e.g., work–study
facilitation), in accordance with the resource expansion perspective. Further, there is consistent
research evidence for the pathway from job resources to work–study facilitation (see Butler, 2007;
Cinamon, 2016; Creed et al., 2015; Wyland et al., 2016).
Limitations With the Current Models
The work–study interface model attempts to provide an understanding of how combining paid employ-
ment with university study affects students’ health and well-being as well as satisfaction with their
study and work; however, the model does not adequately capture the environment (e.g., demands and
resources) students face when they are at work. While the work–study conflict model takes into
account the working environment, it only explains one side of the work–study interface, work–study
conflict. This same critique can be said of the work–study interface which only takes into consideration
the conflict pathway (Lingard, 2007). Only exploring one side of the work-study interface is proble-
matic because in order to best understand the factors that contribute toward students’ outcomes, both
Owen et al. 7

8. negative and positive sides of the work–study interface need to be considered (i.e., work–study conflict
and facilitation). As demonstrated by Butler (2007), a work environment high in control that has con-
gruence with students’ study increases work–study facilitation and results in high academic perfor-
mance and study satisfaction. Therefore, it is also important to consider the positive side of the
work–study interface.
Unlike the work–study interface model and the model of work–study conflict, the work–study con-
flict and facilitation model (Butler, 2007) acknowledges the potential positive impact the working
environment can have on working students through a positive enriching pathway via work–study facil-
itation; however, the model does not consider the influence demands in the workplace can have upon
students’ work–study facilitation (see, e.g., Wyland et al., 2016). Additionally, the model only consid-
ers the impact of the two work–study constructs have upon academic outcomes. Research on work–
study conflict has found a detrimental pathway from students’ work–study conflict to their health and
well-being outcomes (Adebayo et al., 2008; Park & Sprung, 2013, 2014). As such, our proposed work-
to-study model will build upon these limitations by incorporating both work–study conflict and
work–study facilitation (consistent with Butler, 2007) and students’ health as an outcome of work–
study conflict as well as incorporating the role of job demands on work–study facilitation and job
resources on work–study conflict.
Finally, while most work–study conflict and facilitation research is based on the work–family lit-
erature, we integrate the work stress literature. Our model will specifically integrate the PSC extended
JD-R model which highlights the importance of task roles. Work–study conflict and facilitation rep-
resents the interaction between two task roles, work and study. Work–family conflict and work–family
facilitation, on the other hand, represent the interaction between one task role—work and one social
role—family. Therefore, instead of developing the model from the work–family research, our model
is developed from work stress theory, PSC theory which extends the JD-R model and considers task
roles, in conjunction with prior models and research of work–study conflict and facilitation.
New Proposed Work-to-Study Model
The new model proposed in this article, the work-to-study model (refer to Figure 1), is based on the
proposition that working environments influence students’ health, well-being, and academic outcomes
via two mediating constructs, work–study conflict and work–study facilitation. It is through the two
work–study interface constructs that the workplace environment can have consequences in other
domains of a working students’ life such as their academic and health outcomes. PSC will affect both
job demands and job resources in the workplace which in turn influence students’ psychological and
emotional health and academic outcomes via work–study conflict and work–study facilitation.
Consistent with the PSC extended JD-R model, we expect that PSC will influence working stu-
dents’ job demands and job resources. To our knowledge, no research to-date has explored the asso-
ciations between PSC and job demands and job resources, among student workers. Working students
occupy the role of worker as well as student; hence, work stress theories developed for workers, such as
Figure 1. The proposed work-to-study model.
8 Journal of Career Development XX(X)

9. the PSC extended JD-R model, are also applicable to working students. Therefore, consistent with
existing literature on PSC and workplace conditions (refer to Dollard et al., 2012; Idris & Dollard,
2011), we expect that high PSC will lead to low job demands (Pathway 1a) and high job resources
(Pathway 1b) in our proposed work-to-study model.
Consistent with the scarcity perspective and resource expansion perspective of role theory (Marks,
1977), we propose that job demands will predict students’ work–study conflict, and job resources will
predict work–study facilitation. Job demands will predict work–study conflict, as meeting demands in
the workplace requires an investment of time and energy. The time and energy invested in the work-
place subsequently reduces the time and energy for students to spend on their studies. If students have
less time and energy to complete their university study, it may feel like their participation in their work
role is making it difficult to successfully fulfill their required study tasks, leading to feelings of work–
study conflict. In support of this proposition, job demands have consistently been linked with various
students’ work–study conflict (see, e.g., Adebayo, 2006; Butler, 2007; Markel & Frone, 1998; Wyland
et al., 2016). As such, we expect that high job demands in the work-to-study model will lead to high
work–study conflict (Pathway 2a).
The association between job resources and work–study facilitation can be understood from the
resource expansion perspective. One component of job resources is that they promote personal growth,
learning, and development, which could include learning new skills and the growth and development
of personal resources (Bakker & Demerouti, 2007; Demerouti et al., 2001). These skills and personal
resources developed in the work role then become available for use in another role, such as study. For
example, students who have control over how and when they perform their work tasks can learn or
grow and develop the valuable skill of time management, which can then be used in their studies. Bet-
ter time management skills can assist in the successful completion of more study tasks, as better time
management frees up more time to meet their required tasks. Therefore, students’ ability to perform
their study tasks is improved by their participation in work, leading to feelings of work–study
facilitation.
In the extant literature, access to high levels of job resources in the work environment corresponds
with high levels of work–study facilitation. For example, university students in the United States, who
reported high levels of job resources, such as job control, social support, and job–education congru-
ence, had high work–study facilitation (Butler, 2007; Wyland et al., 2016); and likewise for Australian
and Israeli undergraduate students, positive associations between job resources and work–study facil-
itation have been reported (Cinamon, 2016; Creed et al., 2015). Therefore, in the work-to-study model,
high job resources lead to high work–study facilitation (Pathway 2b), consistent with the existing lit-
erature and the resource expansion perspective.
The links between work–study conflict and students’ psychological and emotional health outcomes,
and work–study facilitation and students’ academic outcomes, may be understood via the PSC
extended JD-R model of work stress. Specifically, we use the health erosion pathway to explicate the
pathway from work–study conflict to students’ health outcomes—workers may sacrifice their health to
sustain high energy investment required to meet excessive levels of demands (Bakker & Demerouti,
2007). Work–study conflict is a stressor unique to working students that can be conceptualized as a
demand (Park & Sprung, 2013). Within the PSC extended JD-R model, demands are core components
of a health erosion pathway. As work–study conflict is conceptualized as a demand, it is proposed,
consistent with the health erosion pathway, that students will experience poor health from trying to
successfully balance the two roles of work and study, work–study conflict. That is, students who are
experiencing high levels of work–study conflict are required to invest high energy levels, resulting in
physical and/or physiological costs affecting their health.
There is a link between work–study conflict and students’ psychological health and well-being (i.e.,
the health erosion pathway). University students who experienced high levels of work–study conflict
reported high levels of depression (Cinamon, 2016), stress (Brunel & Grima, 2010), poorer subjective
Owen et al. 9

10. well-being (Adebayo et al., 2008), and psychological health (Park & Sprung, 2013). There is limited
evidence for a link between work–study conflict and physical health with Ou and Thygerson (2012)
reporting a link between work–study conflict and physical injuries in the workplace (i.e., contusions),
with no significant link between work–study conflict and general physical health reported by Park and
Sprung (2013). Overall, there is clear evidence of a pathway from work–study conflict to students’
psychological health outcomes (Pathway 4a).
We also propose a pathway from student psychological and emotional health to their academic out-
comes, which has not been explored in the work–study interface literature. We propose a mediation of
work–study conflict to academic outcomes, via students’ psychological and emotional health. There is
support for a mediational pathway between demands and domain-specific outcomes via health in the
JD-Rliterature,forexample,indirectassociationsbetweenworkers’demandsandtheir turnoverintentions
and organizational commitment via their feelings of burnout (Hu, Schaufeli, & Taris, 2011). To success-
fully meet their demands, workers keep expending more energy. The energy drain from high work
demands has been associated with physiological and physical costs (Bakker, Demerouti, & Verbeke,
2004), such as exhaustion, which has a direct impact on organizational outcomes. Therefore, we propose
thattheimpactofthedemandwork–studyconflictwillaffectstudents’academicoutcomesviatheirhealth.
The motivational pathway explains the role work–study facilitation plays in students’ academic out-
comes. In the motivational pathway, resources can provide extrinsic and intrinsic motivation for work-
ers enhancing their experience in the work role, such as improving their engagement, job performance,
and other organizational outcomes (Schaufeli & Bakker, 2004; Bakker et al., 2004). Resources are core
to the motivational pathway, as they trigger a motivation process. Work–study facilitation is an aca-
demic resource students can utilize to enhance their experience in their studies (Park & Sprung, 2013).
Much like a job resource, work–study facilitation demonstrates demand reducing properties with high
work–study facilitation reducing the impact work–study conflict had on students’ psychological health
(Park & Sprung, 2013). Therefore, consistent with the motivational pathway in the PSC extended JD-R
model, work–study facilitation will provide students with motivation in their study role allowing for
better academic outcomes.
Evidence of the association between work–study facilitation and academic outcomes has been
found among university students in Australia, Israel, and the United States. In the United States,
work–study facilitation was found to be linked with students’ study satisfaction and academic perfor-
mance, specifically, effort and attendance, along with grade point average (GPA) (Butler, 2007;
McNall & Michel, 2011). That is, students with high levels of work–study facilitation have greater
satisfaction with their studies and invest more effort, have higher attendance levels, and better grades,
compared to students with low work–study facilitation. The association between work–study facilita-
tion and academic grades was also found among students in Israel (Cinamon, 2016). Finally, in Aus-
tralia, university students who experience high work–study facilitation correspondingly experience
high academic engagement (Creed et al., 2015). Therefore, we propose in the work-to-study model that
high work–study facilitation will lead to better academic outcomes for students (Pathway 4b).
An aspect of the work-to-study model that has not been previously considered is the interaction
between demands and resources upon students’ work–study conflict and work–study facilitation. One
part of the resource expansion perspective is that certain aspects within an environment can prevent a
reduction in personal resources, time, and energy. Therefore, the drain of time and energy associated
with demands in the workplace can be moderated when students have access to resources to manage
their demands. This moderation of resources on demands is consistent with the JD-R model. Several
studies have reported that job resources moderate the impact of job demands upon workers’ feelings of
burnout (Bakker et al., 2005; Xanthopoulou et al., 2007). As such, we expect that students’ job
resources will moderate the association between job demands and work–study conflict (Pathway 3a).
Further, we propose that job demands will moderate the association between job resources and
work–study facilitation (Pathway 3b). Job resources facilitate the learning of new skills, and growing
10 Journal of Career Development XX(X)

11. and developing existing skills, in addition, assisting the achievement of work goals (Bakker et al.,
2010; Demerouti & Bakker, 2011). In accordance with the interaction proposal, exposure to job
demands, when students have high resources, can enhance their learning and development of skills for
use in their studies. The satisfaction of achieving challenging work goals, as determined by high job
demands, can also enhance the positive affect associated with goal achievement from the job
resources, which can influence students’ affect (i.e., feelings) in relation to their studies. The argument
is that when faced with high demands, workers can make the most use of their job resources, leading to
feelings of engagement (Bakker et al., 2007, 2010). Therefore, we propose that under demanding con-
ditions, students will be able to get the most out of their job resources, enhancing their work–study
facilitation.
In our model, instead of work–study conflict having a direct pathway to academic outcomes, we
expect that the association between work–study conflict and academic outcomes will be through stu-
dents’ psychological and emotional health (Pathway 5). Some academic outcomes are only predicted
by work–study conflict, when work–study facilitation is not incorporated into the analysis, such as
study satisfaction. For example, Olson (2014) reported a significant association between work–study
conflict and study satisfaction; however, Olson (2014) did not consider the role of work–study facil-
itation in the development of study satisfaction. When Butler (2007) and McNall and Michel (2011)
incorporated both work–study conflict and work–study facilitation, only work–study facilitation was
significantly linked with study satisfaction. Thus, it is likely that work–study facilitation provides the
main explanatory power of students’ academic outcomes. We have only considered the role of stu-
dents’ workplace demands and resources, due to the primary role these two task-level risk factors play
in the development of work–study conflict.
Future Directions
While our proposed work-to-study model has been developed from theoretical frameworks and empiri-
cal evidence on work–study conflict and work–study facilitation, the subsequent work–study models,
and the well-supported PSC extended JD-R model, it is important to test the newly proposed pathways,
as well as the entire model. Research on the PSC extended JD-R model among nonstudent workers has
reported that PSC negatively predicts workers’ job demands and positively predicts job resources.
However, these pathways are yet to be tested among a working student population.
Currently, the pathways from students’ work environment to the two types of work–study interface
constructs are established with evidence of a direct impact of students’ workplace demands and
resources on work–study conflict and work–study facilitation (Butler, 2007; Wyland et al., 2016);
however, the interaction between the two task-level risk factors (i.e., demands and resources) is yet
to be tested. The first step is to establish what combination of demands and resources influence stu-
dents’ work–study conflict and work–study facilitation. The second step is to determine if PSC func-
tions similarly in working students as it does in nonstudent workers and establish which combination of
demands and resources affect work–study conflict and work–study facilitation. The final stage will be
to test the whole work-to-study model. When testing the entire model, it will be important to consider
both the work–study conflict pathway and work–study facilitation pathway concurrently. By only
focusing on one pathway, important information is lost about the associations between work–study
conflict or work–study facilitation onto students’ health and academic outcomes.
Finally, the current proposed model is targeting students who are engaged in external paid employ-
ment to their studies. It is unclear on how the various types of work–study arrangements (e.g.,
university-sponsored assistantships, fellowships, and work–study programs), influence students’ expe-
rience of the work-to-study model. As such, it is important to explore the work-to-study model among
students who are participating in external paid employment as well as students in nonexternal paid
employment arrangements.
Owen et al. 11

12. Conclusion
University students combining paid employment with study is a global phenomenon that requires atten-
tion from policy makers to improve the benefits of combining work with study and reduce the negative
consequences. Prior recommendations have focused on hours worked instead of the quality of the stu-
dents’ working environments. While research on work–study conflict and work–study facilitation has
shifted the focus away from hours worked to the quality of the working environment, the models pro-
posed have several flaws and/or omissions. To address these issues, we propose a work-to-study model.
The work-to-study model explains how and why the working environment can be beneficial and/or detri-
mental for students’ health and academic outcomes concurrently, through work–study conflict and
work–study facilitation. Future research is required to test the work-to-study model before we can begin
to guide future policy surrounding the phenomenon of working university students.
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) disclosed receipt of the following financial support for the research, authorship, and/or
publication of this article: The authors would like to thank the Australian Government Research Train-
ing Program and Safework SA for their support of this research.
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Author Biographies
Mikaela S. Owen is a PhD student at the University of South Australia in work and organizational psychology,
with a specific focus on work–study conflict and facilitation, student sexual harassment, and student bullying. Her
research interests include psychosocial risk factors in the workplace/at university, organizational/educational cli-
mate, gender issues, and working students. In her spare time, she enjoys playing tennis, reading classic novels, and
listening to crime podcasts.
Phil S. Kavanagh is currently the Discipline Head: Psychology for the School of Psychology, Social Work and
Social Policy at the University of South Australia and the Program Director for the Master of Psychology (Clin-
ical) program. He lectures across both the undergraduate and the postgraduate psychology programs. His main
research interests lie at that intersection between personality, social, and clinical psychology from an evolutionary
perspective. In his spare time, he enjoys outdoor activities such as camping, hiking, and mountain biking.
Maureen F. Dollard is the Director and Head of the Asia Pacific Centre for Work Health and Safety at the Uni-
versity of South Australia. Her main research focus is on multilevel frameworks for worker health, psychosocial
safety climate for psychological health in organizations, and interventions for psychosocial risk. Her interests
include cycling, traveling, and spending time with her family.
14 Journal of Career Development XX(X)