The impact of employment-level characteristics on work–life interference in school-aged children

Abstract

Work–life interference is important for school-aged workers because it influences their educational outcomes/career aspirations. Although research highlights the role of work hours in determining work–life interference for these workers, work/job-level characteristics have received limited attention. Using survey data from Queensland school students who work part-time, we assess the influence of a range of employment-level variables on work–life interference. The results of multiple regression analysis indicate work–life interference is exacerbated by having low trust in managers and limited scope to refuse work hours and stability in work hours, emphasising the importance of organisational variables in integrating work and non-work spheres for school-aged workers.

Keywords

Employee control school-aged workers work hours work–life interference work pressure

Introduction

Changes to youth employment patterns over the last two decades are well documented in the literature. Of particular importance for these workers is the growth of casual jobs in retail and services brought about by increased consumerism, changes to government policies allowing deregulated trading hours, and a long period of relative economic prosperity driven by the resources boom (Campbell, 2000; Langer, 2005; Lloyd, 2008). Although research on work and employment conditions for adults has a long tradition, very little of this work focuses on young workers and even less examines school-aged workers (Price et al., 2011). This is despite the fact that young people in most Organisation for Economic Co-operation and Development (OECD) countries are participating in paid work at an increasing rate, beginning work as early as the age of 13, and comprise a significant segment of the casual labour force (Australian Bureau of Statistics (ABS), 2010; OECD, 2006; Usalcas and Bowlby, 2006). The limited research that has been carried out on young workers has focused mainly on objective measures of wage rates, institutional protections such as limits on the timing and length of work hours (Mourell and Allan, 2006) and the impact of total work hours on educational outcomes such as school achievement (e.g. Vickers, 2011). Relatively less work has addressed more nuanced dimensions of young people’s working arrangements, such as the stability and predictability of work hours, relational aspects such as orientations to management, or the more subjective but nonetheless significant issue of socio-emotional experience of simultaneously engaging in the workplace and school.

Another broad body of research points to close links between the conflict that arises in managing demands across boundaries of economic and non-economic spheres, and diminished physical and psychological health. Both individual and organisational factors, including the workplace environment and the nature of jobs themselves, have been recognised as key variables determining the ability of individuals to reconcile their work and non-work lives, with significant implications for employee well-being, job satisfaction, organisational citizenship behaviours and turnover intentions (Anand et al., 2010; Beauregard and Henry, 2009; Buzzanell and Liu, 2007; Hornung et al., 2008). This large body of literature has focused mainly on adult workers, and particularly on working mothers/parents (Chang et al., 2010), with very little scholarship targeting young people specifically, much less those still in high school.

This study utilises data from a survey of children in Queensland, Australia who combine full-time participation in high school and part-time work, to assess the influence of a range of employment-level variables on work–life interference. The study contributes to broader scholarship addressing work–life boundaries for this particular group as well as to scarce knowledge about the dimensions of paid employment for very young workers more generally.

Work–life interference and school-aged workers

Although specific definitions of work–life interference tend to vary, there is relative consensus that interference occurs when the emotional and behavioural demands of work and outside work responsibilities and interests are incompatible, such that participation in one sphere is made more difficult by virtue of participation in the other (Greenhaus and Beutell, 1985). The ‘spillover’ model (Loscocco and Roschelle, 1991) underpins the majority of current research on work–life interference whereby work and non-work roles are considered related to the extent that efforts expelled in one role spill over into the other.

A large body of research in fields such as organisational behaviour, sociology and employment relations conducted over several decades has addressed a range of structural, organisational and individual antecedents and outcomes of work–life interference in specific groups of workers, particularly women with dependent children, and those engaged in professional and/or long-hours knowledge-related work. Indeed, some argue that work–life interference is one of the most pressing social problems facing most developed economies (Beauregard, 2011; Zetlin and Whitehouse, 1998). Studies of work–life interference have directly linked the construct to fatigue, stress, burnout, psychological well-being, depressed mood and physical symptoms amongst adult workers (Duxbury, 2003; National Centre for Epidemiology and Population Health (NCEPH), 2003). Research also indicates that where adult workers report high work–life interference the negative effects extend to their children (Duxbury, 2003; NCEPH, 2003; Pocock, 2006). Organisations too have been shown to benefit significantly from policies designed to negate work–life interference, including improvements in retention rates (Squirchuk and Bourke, 1999), improved morale and productivity (McCampbell, 1996) and reduced absenteeism (Kossek and Nichol, 1992).

The well-established link between work and ill-health is a sufficient reason to make work–life interference an important area of investigation insofar as it affects young workers. More information is needed, however, about the extent of interference experienced by school-aged workers and its causes and consequences, particularly as youth make up a significant proportion of the part-time and casual labour force, especially in retail and services (ABS, 2010) where turnover rates are high. While research demonstrates that evening work and work hours in excess of 15 to 20 hours per week have negative implications for educational outcomes, injuries at work and career aspirations for young people (Loudoun, 2010; Vickers, 2011), there is little knowledge of how adolescents integrate paid work with their predominant non-work ‘life’ sphere, which is educational participation. Our study contrasts with the broader bodies of work outlined above in two ways.

First, research on work–life interference or conflict has generally examined particular groups of workers such as women with children, single parent families and those providing eldercare (Chang et al., 2010). This is not surprising given that there is considerable evidence indicating that interference is most acute for these workers (Loudoun and Bohle, 1997; Skinner and Pocock, 2008). However, it is important to know the causes of interference for workers of different ages and at different life-stages. Findings from studies focusing primarily on older workers cannot be directly generalised to school-aged workers, because substantial differences are likely to exist between the two populations in job tasks, frequency and intensity of work, developmental abilities and work-related experience. For example, the jobs that many young workers hold tend to be low skilled and are more physically demanding than jobs held by adults (Barling and Kelloway, 1999; Loughlin and Frone, 2004). Interference for school-aged workers may even differ from ‘older youth’, such as those simultaneously participating in paid work and tertiary or vocational education.

The second point of departure is that much of the research to date on work–life interference has focused on either the individual level using (implicitly or explicitly) job stress as the underpinning framework, or on the organisational/policy level. Although an emphasis on individual factors has led to progress in understanding responses and coping strategies to manage interference, it attributes the responsibility to reconcile work and non-work responsibilities to the individual worker. Indeed, some researchers conclude that the ability to balance the demands of work and study for school-aged children rests with their commitment to academic success (Vickers, 2011: 110, citing Marsh, 1992). Research shows that it is difficult and relatively ineffective for adult workers to use individual efforts to reconcile work–life interference (Menaghan and Mervis, 1984; Shinn et al., 1984); this can only be more difficult for young workers who may lack the employment security, work experience and maturity to effectively negotiate with employers when conflicting demands arise (Denniss, 2005). For example, research demonstrates that young workers rarely take advantage of the right to union representation (only 10% of Australian workers between 15 and 24 years are union members; ABS, 2010); lack awareness of some rights such as procedural fairness in dismissal (Allegretto and Chase, 2005); and sometimes do not exercise their rights, even if their knowledge of such rights is high, such as around health and safety (McDonald et al., 2012). Compounding this problem are significant shifts in labour security and the erosion of the terms of labour which threaten various aspects of employment safety, security and remuneration (Standing, 2002).

Meanwhile, research at the organisational/policy level has tended towards single-issue debates and narrow discussion about workplace strategies that may alleviate work–life interference, such as paid parental leave or part-time work (Dempster, 2003). Studies addressing young workers in particular have also emphasised structural interference, which arises from the competing demands for time in work and family roles (Voydanoff, 1988) and associated policies such as working time restrictions. This focus on individual or organisational/policy constructs has been at the expense of employment-level variables which may also contribute to work–life interference. For example, while it is often difficult for adult workers to simultaneously perform paid work and caring duties, this problem may be aggravated for (mostly casualised) young workers because they often have little control over either their working arrangements or their educational commitments. Adolescents may be advised of their working hours at short notice and have little choice about when they work or what tasks they perform, at the same time as having to navigate non-negotiable school hours, assignment deadlines and examinations. A number of structural responses have been imposed on employers, young people and their parents, in attempting to respond to what are recognised dual risks faced by young workers. These risks are first, their potential to experience exploitation or at least vulnerability in the labour market, and second, the negative effects of excessive working hours on educational outcomes. Structural interventions include the requirement for parental consent to work for children under certain ages, restrictions on night and term-time work hours, and other supervision and monitoring requirements (Mourell and Allan, 2006).

In summary, research has indicated that work–life interference for school-aged working children is characterised by risks to health, well-being and educational outcomes and career aspirations. Important progress has also been made in understanding the importance of structural policies designed to assist young workers to meet competing demands between their work and other spheres of life. Research has also established a range of individual coping strategies that may alleviate interference for adult workers, but which may not facilitate work–life boundaries for adolescents. Indeed, we have little knowledge of either the extent of work–life interference experienced by young workers, or the dimensions of work itself that impact this. Questions of whether work process variables influence young workers’ health, well-being, educational attainment or future earnings, and whether the labour market and workplace relations system more broadly allow or even encourage work practices that inhibit the ability of school-aged workers to balance their work, home, sporting and scholarly responsibilities, should concern both researchers and those involved in policy development (Baffoe-Bonnie and Golden, 2007). In an effort to gain a more critical picture of work–life interference for school-aged workers, the study examines the relationship between work-level variables and work–life interference for children who combine part-time work with full-time school.

The model of low-control high-demand jobs

In this article, we ask: What is the relationship between low-/high-demand jobs and work–life interference? There are many ways to measure job demand and many terms used in the literature to describe it, including job strain, high-performance jobs and high-commitment jobs (see e.g. Berg et al., 2003; D’Souza et al., 2003; Janssen and Nijhuis, 2004). Although it is worthwhile to be aware of these alternative and sometimes-conflicting interpretations, we argue that focusing on relationships between the variables, rather than the terms used to categorise job dimensions, will make more progress. In this study, we draw on Theorell and Karasek’s (2000) demand-control model to ask whether high-demand jobs result in compromised experiences in non-work spheres. For school-aged workers, this could be conceptualised as pressure to prioritise paid work over school, family and social commitments. Consistent with Theorell and Karasek’s (2000) model, we focus on three aspects of job demands: trust in management, knowledge of work rights and stability of work hours.

Working hours (timing and stability of work scheduling)

There is clear evidence that the amount of time that people spend at work has a strong influence on work–life balance (Allan et al., 2007). For young people, the detrimental effects of work–school interference extend to fatigue (Oginska and Pokorski, 2006), academic performance and time spent in educational activity (Baffoe-Bonnie and Golden, 2007; Butler, 2007). Workload hours encompass the amount of and control over work hours. This variable is important because if an individual spends more time engaged in paid work, and/or at a time when it impinges on non-work responsibilities, then they must either spend less time engaged in these activities or they must complete tasks at a faster pace. As we noted earlier, studies of young people have tended to confine their focus to the number of hours worked, with most concluding that the negative effects of working only apply to students who work long hours or over a certain threshold (Payne, 2003). In a similar way, studies that have examined work intensity have neglected to adequately define this construct or they equate it solely with the number of hours worked per week (see Schoenhals et al., 1998; Staff and Schulenberg, 2010; Vickers, 2011). For example, Lerman (2000) found that American high school students from low-income families who reported ‘high work intensity’ (more than 20 hours per work) exhibited improved school engagement and schoolwork performance compared to those who reported ‘moderate intensity’ (less than 20 hours per week). Although such studies provide valuable insights into the relationship between educational engagement and outcomes and the type of work performed, more focused studies using a wider cohort of ages and income levels is needed before generalisations can be made.

In this study, we examine not only weekly paid work hours performed by school-aged children, but also fairness of work scheduling. In particular, we focus on scope to refuse work hours and the stability of work scheduling, based on previous research indicating that job strain is higher amongst university-aged students who lack control over aspects of their jobs such as work hours (Golden and Gebreselassie, 2007). Whether this extends to school-aged children, however, is unknown.

Knowledge and experience of work

There is no doubt that young people have less experience in employment relationships and less capacity to bargain with employers, relative to their adult counterparts, based on endemic disparities in power (Denniss, 2005). Furthermore, young workers are generally unaware of their legal rights at work, such as procedural fairness in dismissal (Allegretto and Chase, 2005; McDonald et al., 2012). We extend this previous research by examining whether young workers' level of knowledge about their rights at work, and the years of experience they have of their job, diminish work–life interference. Accordingly, we asked questions about knowledge of penalty rates, holiday pay, superannuation and sick pay, parental consent to work, permitted work hours for children aged under 16 years, recording and reporting injuries at work, overtime, unpaid work, breakages at work and caring for employers' property, trade union membership and harassment at work.

Trust in management

There is considerable research examining the importance of management support and trust for older workers (e.g. Breaugh and Frye, 2008; Lapierre and Allen, 2006), but limited research that focuses directly on the impact of manager support on work–life interference for young workers. Peetz et al. (2003), for example, found that management support is particularly important for counteracting pressures to work longer hours. Their results show that workplace policies to prevent overwork and increased safety risks from extended working hours are ineffective if managers do not support and monitor the policy. Other work has demonstrated a strong association between manager support and reductions in emotional exhaustion, fatigue and psychosomatic symptoms such as anxiety and depression (Janssen and Nijhuis, 2004; Snow et al., 2003) Furthermore, research on flexibility policies shows that whether supervisors enthusiastically support the integration of paid work and other responsibilities, or conversely send negative signals that the use of flexible benefits is a problem for them and the organisation, affects the likelihood of employees utilising available work–life balance options (Bardoel, 2003; McCarthy et al., 2010; Rapoport and Bailyn, 1996). Finally, managers, due to their status and power as decision makers and supervisors, can act as gatekeepers and as change agents for informal supportive organisational cultures (Straub, 2012). Despite the consistent clarity in the literature about significant links between manager support and work–life interference (and its consequences), it remains unknown whether similar associations apply to young workers, particularly in industries that employ large numbers of young workers such as retail and fast food, where very long hours of operation and precarious work arrangements are the norm (Vickers, 2011).

Method

The data reported in this article were derived from a larger research project which investigated understanding and experiences of paid work for high school students in Queensland, Australia. Students from 19 schools from metropolitan Brisbane, provincial cities and rural locales provided interview and survey data.

While the sample was not intended to be fully representative of high school students in Queensland, it included students from both government (N = 16) and non-government Catholic (N = 3) schools; schools from urban, regional and rural areas, and geographic regions with varying industry predominance. The procedure for accessing schools involved initially contacting school principals and requesting participation. Where schools declined to participate, a process of substitution was utilised in order to fulfil the target mix of schools.

All data gathering for the broader project was conducted during a single site visit at each school in order to minimise impact on the participating schools. Consistent with University and Education Department-defined ethical requirements, only students with a signed parental consent form were allowed to participate in the research. Students participating in the survey phase were requested to attend a pre-designated quiet area of the school and were provided with information from the research team outlining the purpose of the study and what participation involved.

This procedure resulted in 892 survey responses; around half of which were completed by students who were not employed.¹ The sample utilised for this study constituted 438 surveys from students who had participated in weekly paid employment within the year prior to the survey. Students ranged in age from 13 years (32 students), which is the minimum age for employment in Queensland, to 17 years (145 students aged 14 years, 72 students aged 15 years, 176 students aged 16 years and nine students aged 17 years). Questions were worded in a way that suggested a formal employment relationship (e.g. reference was made to the type of employment contract the student was employed under and whether they received training when they started their employment), but students were not told specifically to exclude informal employment so the possibility that students were referring to informal rather than formal employment when answering the questionnaire cannot be excluded. Thirty-three per cent of students were females; 66% were males; four students failed to indicate their gender or age. The data are unweighted.

Measures

In addition to the questions about the demographic characteristics of respondents, the survey instrument also elicited respondents’ views about and experience of a range of workplace matters. Self-report measures were used for all variables in the study because this approach is less invasive than so-called objective indices of the variables of interest. Although it is important to recognise that data using self-report measures can be influenced by factors such as personality, researchers have found similar results using self-report and alternative measures (see Sparks et al., 1997 for a review of these studies).

Trust in management

We measured trust in management using Peetz’s (1998) scale of work beliefs. Respondents answered items on a five-point Likert scale ranging from ‘strongly agree’ to ‘strongly disagree’, with a higher scale score indicating greater perceived trust. Internal consistency was .85.

Work hours

Control and stability of work hours were measured using three separate items. The first item asked respondents: ‘Do you have your shifts cancelled after you turn up to work?’ The second question asked about stability of work hours: ‘Do your work hours vary a lot from week to week?’ The final question asked: ‘Does your employer cut your work hours if you refuse a shift?’ Each item was rated on a three-point Likert scale (3 = Yes always, 1 = No never).

Work–life interference

We measured work–life interference using a modified version of Netemeyer et al.’s (1996) work-conflict scale. All the items were modified to ensure that they were appropriate for a school-aged setting (e.g. ‘The demands of my work interfere with my home and family life’ was changed to ‘The demands of my job interfere with my school work’ and ‘The demands of my job interfere with my leisure time’). Each item was rated on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). Internal consistency was .83.

Knowledge of work rights

The knowledge measure comprised 20 questions derived mainly not only from provisions in the Child Employment Act 2006 (Qld), but also from prior research identifying common breaches of employment legislation and specific areas of vulnerability for young workers. The construction and validity of this scale are described in detail in McDonald et al. (2013). For the knowledge of work rights scale participants were presented with a series of statements about rights at work relevant to young workers and were requested to respond ‘true’, ‘false’ or ‘don’t know’. These responses were then recoded to provide a total number of correct responses. ‘Don’t know’ responses were coded as incorrect.

Control variables

To control for other characteristics, we included in the analysis dummy variables for age, sex and job tenure. We also included in the equation two numeric variables: hours worked per week and volunteer hours worked per week. One case was removed from the sample owing to an unrealistic response in terms of the number of hours worked each week (95 hours).

Results

Validity of measures

Because a reduced version of Peetz’s (1998) trust in management scale was used for the study and the Netemeyer et al. (1996) conflict scale had not been used previously with a sample of school-aged workers, the discriminant validity of the measures was tested using principal components analysis (PCA). Prior to PCA the suitability of the data for factor analysis was assessed. Inspection of the correlation matrix revealed the presence of many coefficients of .3 and above. The Kaiser–Meyer–Olkin measure of sampling adequacy was .8, exceeding the recommended value of .6 (Kaiser, 1974), and Bartlett’s test of sphericity (Bartlett, 1954) reached statistical significance, supporting the factorability of the correlation matrix.

PCA revealed the presence of two components with eigenvalues exceeding 1, explaining 40.59% and 17.45% of the variance, respectively. An initial examination of the screen plot suggested a two- or three-factor solution. The two-factor solution was chosen because of theoretical interpretability and because it had a more clearly defined, simple structure. We eliminated one item, ‘employers have more power than employees’ that loaded at below 0.5 to resolve cross loadings onto a third factor. The analysis included some 438 cases although the n was reduced due to missing values. As a cross-check, a separate factor analysis was run using means variable replacement substitution instead of excluding missing values. The same factor solution loading on identical variables was derived, indicating that the missing data, due to missing values, did not affect the outcome of the factor analysis.

The two-component solution explained a total of 58.04% of the variance. To aid in the interpretation of these three components, oblimin rotation was performed. The rotated solution revealed the presence of simple structure (Thurstone, 1947), with both components showing a strong number of loadings (Table 1). Therefore all items were retained, suggesting that the modified versions of both scales are appropriate for a school-aged context.

Table 1.

Factor analysis: Work–life interference and management trust, two-factor solution.

	Component
	Work–life interference	Management trust
The demands of my job interfere with my school work	.788
The amount of time my job takes interferes with my leisure time (including sport and time with friends)	.717
Things I want to do in relation to my education do not get done because of the demands my job puts on me	.827
My job does not interfere with my school work	.757
Due to work-related duties, I have to make changes to my plans for school activities	.549
The amount of time my job takes interferes with my family life	.699
Managers can be trusted to keep their word	.374	.840
Managers can be trusted to give you an honest answer to a question	.435	.800
Employers have more power than employees		.348

Regression analysis

Multiple regression was used to assess the ability of various workplace-level variables (trust in management, knowledge of work rights, control over and stability of work hours) to predict work–life interference. Preliminary analyses were conducted to ensure no violation of the assumptions of normality, linearity, multicollinearity and homoscedasticity. Volunteer work hours, paid work hours, job tenure, sex and age were entered in Step 1, explaining 33.2% of the variance in work–life interference. The results of the regression analysis are shown in Table 2.

Table 2.

Regression of work–life interference.

	Unstandardised coefficients	t-stat.	Sig.
(Constant)	−.133	−.205	.838
Paid work hours	.010	2.255	.025
Age	.196	4.588	.000
Gender	.284	3.123	.002
Volunteer hours	−.005	−.326	.744
Job tenure	−.058	−1.402	.162
Knowledge of work	.001	.060	.952
Shift cancelled short notice	−.193	−2.878	.004
Hours vary each week	−.148	−3.177	.002
Hours cut for refusing work	−.173	−3.143	.002
Management trust	−.125	−3.216	.001

Adjusted R²= 0.22; N = 437.

After entry of the knowledge of work rights scale, trust in management, work hours cut for refusing work, shifts cancelled at short notice, certainty in work hours, at step 2 the total variance explained by the model as a whole was 47.2%, F(10, 427) = 12.21, p < .001. These measures explained an additional 14% of variance in work–life interference.

The results of the regression analysis indicated that work–life interference was negatively correlated with trust in managers, having work cancelled at short notice, having hours cut for refusing work and having work hours vary considerably from week to week. The results also showed a statistically significant relationship between work–life interference and hours worked, age and gender.

Discussion

Overall, our findings indicate that while regulation and policy, which restrict children’s work hours, are important in mitigating risks associated with early workforce participation, work/job-level characteristics are also critical in facilitating the integration of work and non-work spheres for school-aged workers. The work/job-level variables examined in the study reflect the more experiential and relational dimensions of young people’s early engagement with the labour market. The impact of these facets of employment on work–life balance has been hitherto neglected in research addressing young workers, but is likely to have important policy and practice implications for regulators, parents, schools and employers.

We operationalised work/job-level characteristics as knowledge of workplace rights, job autonomy and management style. Building on literature, which suggests management practices are vital in facilitating positive work–life outcomes (Janssen and Nijhuis, 2004; Peetz et al., 2003), we tested whether management style, conceptualised in terms of high- or low-trust employee relations, predicted work–life interference. Within limits, it is managers who are responsible for allocating workloads, assigning job tasks and setting work hours. This is especially the case in the low control/high demand types of work environments such as retail, hospitality and fast food organisations where young people typically work. The scope of managerial prerogative therefore circumscribes young workers’ ability to exercise control over aspects of their working lives. The results here suggest that management style predicts interference, with supportive ‘high-commitment’ styles of management considerably more likely to minimise interference than low-trust management styles. Hence, the role of management is critical to the amelioration or attenuation of work–life interference, insofar as educational demands and opportunities for social development.

As expected, certainty of work hours was also a significant predictor of work–life interference. Students whose hours were more predictable from week to week, who did not generally have shifts cancelled after they arrived at work, and whose employers did not cut their hours if they refused shifts, experienced less interference than students with less certainty and control over their work hours. Unpredictability and uncertainty of work hours are dimensions of the employment relationship that have been established as critical in alleviating work–life interference for university-aged students (Golden and Gebreselassie, 2007). What the findings here suggest is that control is as important for adolescents as older youth, and therefore that it is the imperatives of non-work responsibilities per se, rather than their nature, that affect the overall control–interference relationship. Adults, for example, often require control over and stability of work hours to care for dependent children or elderly or disabled relatives, or for their own health needs. Although school students are not usually engaged in directly caring for dependents, they must contend with other non-economic responsibilities over which they have relatively little control, including fixed school hours, exams and assignment deadlines, sporting commitments and family obligations.

Although the benefits of certainty in employment scheduling may be clear, regardless of the age of the employee or the nature of their non-work responsibilities, the strategies to achieve this may differ substantially for different groups. It is likely to be a challenging prospect, for example, for employees as young as 13 to achieve consistent scheduling within the reality of an employment relationship characterised by significant power disparity. In addition to the realities of precarious employment arrangements which also affect an increasing number of adults, young workers articulate high levels of anxiety at the thought of individually negotiating with employers (Denniss, 2005) and often lack not only knowledge of where to seek basic information on employment-related matters, but also assistance and training around workplace negotiation and conflict resolution (Price et al., 2011). Conversely, some employers (of young people and school-aged workers in particular) may need to take greater account of the fixed nature of adolescents’ non-work commitments beyond adherence to specific regulatory guidelines around working hours. With very few exceptions, little research has documented or examined employer views and practices associated with school-aged workers, despite their critical role in creating and shaping the labour market in which children participate (Price et al., 2011). Rather, employers are only considered in research on young workers insofar as how their patterns of recruitment choices affect school–employment–unemployment transitions (Maguire and Maguire, 2007) or how the skills they require are facilitated through the education system (e.g. Smith and Patton, 2007).

Contrary to our expectations, young workers’ knowledge of workplace rights, in areas such as duties and entitlements, remuneration and health and safety, did not ameliorate work–life interference. This may be because even when young people are aware of their rights at work, they may either lack the procedural knowledge to accomplish a formal enactment of those rights should a problem arise, or, in an employment relationship characterised by unequal power relationships, they may have insufficient agency to assert their rights to managers or employers (Price et al., 2011). For example, while students demonstrated a high level of knowledge about occupational health and safety entitlements, in the context of the workplace they may not have been empowered to enact those rights when a workplace accident or injury occurred, such as through completion of an incident report, correcting the danger or accessing commensurate time off to recover. Similarly, time on the job, which captures tenure and experience in a particular work context, did not predict interference. Hence, knowledge of entitlements at work, and on-the-job experience, were less important than the control and relational dimensions of work in mitigating interference between these adolescents’ work and non-work spheres.

The extent of engagement in work, operationalised as number of weekly hours, was found to be a significant predictor of interference. This job characteristic, in addition to demographic factors including age, gender and time on the job, constituted the control variables in our regression analysis. The impact of total work hours has been examined mostly in terms of educational outcomes (e.g. Payne, 2003; Staff and Schulenberg, 2010). While methodological issues have sometimes resulted in inconsistent findings in terms of the precise number of threshold hours at which educational attainment starts to diminish (Vickers, 2011), generally speaking, ‘intensive employment’ results in negative academic consequences (Staff and Schulenberg, 2010). The findings here further suggest that limiting weekly hours is important not only for preserving educational attainment and facilitating educational retention, but also for reducing interference between adolescents’ economic and non-economic activities during their school years. This provides further support for the continuation and enforcement of child employment legislation which limits weekly hours and late night work for children during term time.

Older students experienced more interference than younger students. Further research would be needed to establish precisely why this is the case, but it is possible, for example, that a 16-year-old student in Year 11 would experience greater academic pressures, such as more frequent assignment deadlines and high-stakes exams, compared to a 14-year-old in Year 9, and hence more interference, irrespective of weekly work hours. Although older students worked more hours on average, the fact that time on the job did not predict interference suggests that it is the heightened non-work responsibilities experienced by older students that lead to interference, rather than tenure or work hours per se. Girls also experienced more interference than boys. Again, our study could not ascertain why this is the case, but previous research has demonstrated that adult women experience worse work–life outcomes than men (when work hours are taken into consideration; Skinner et al., 2012) and it is possible that this trend begins in adolescence.

Conclusion

Overall, the study contributes to the relatively neglected research area of young workers by revealing insights into how adolescents in this phase of youth formatively navigate, understand and experience the labour market and their place within it, relative to other life spheres. This is in contrast to an emphasis on the structural conditions of young people’s work and their vulnerability from a static standpoint seen in the employment relations literature, and issues around education-to-work pathways in research addressing the sociology of youth. Our focus on interference between paid employment and non-work spheres – which includes not only school education, but also leisure, peer friendships and intimate relationships – has also received little attention. The experience of work–life interference has consistently been shown in the adult employment literature to be directly linked to physical symptoms such as fatigue, stress, burnout and depressed mood (Duxbury, 2003; NCEPH, 2003), and it is possible that interference may have similar effects in adolescent samples. There is substantial opportunity for future research to consider the dimensions of employment experiences and the context of the workplaces in which young people engage, not in isolation from communities, social spaces and private spheres, but as integral to them (Wajcman, 2000: 196).

Our sample was constrained in several ways. Students were located (and employed) in one Australian state and attended mainly government schools. Further, consistent with ethical requirements, only students with a signed parental consent form were allowed to participate in the research, resulting in an under-representation of students from indigenous and culturally and linguistically diverse backgrounds. A factor offsetting these limitations, however, and suggesting applicability to the broader literature, is that while young workers are heterogenous in terms of geographical location, gender and ethnicity, and access to financial and social capital resources (Shu and Marini, 2008), unlike adults they are a relatively homogenous group in terms of the types of jobs they participate in, their propensity to be employed under casual contracts, the regulations they are subject to in terms of work hours restrictions during term-time, and the remuneration they receive under Australia’s youth wages legislation. Furthermore, while the findings of earlier studies often varied according to whether student samples were located in early versus later high school years, in the sense that older high school students were more likely to have intentions of graduating from high school and continuing onto tertiary study (Vickers, 2011), the relatively recent ‘earn or learn’ imperative and consequent increased retention rates of students in Years 11 and 12 (Lamas, 2012) have diluted these cohort differences. Hence, we would expect that our key findings about the importance of management style, work intensity and control over working hours in alleviating work–life interference for these particular school-aged workers will have broad resonance.

Footnotes

Funding

This research was supported by an Australian Research Council (ARC) Grant (FT120100635).

Note

Biographical notes

Rebecca Loudoun is a Senior Lecturer at Griffith University and a member of the Research Centre for Work, Organisation and Well-Being. Her research focuses on the influence of organisational, social and economic issues on health and safety performance. She has a particular interest in the nexus between workplace bargaining and occupational health and safety, including the role of unions in influencing health and safety outcomes.

Paula McDonald is a Professor and ARC Future Research Fellow in the QUT Business School. Her research addresses work in its social context, in particular gendered forms of workplace discrimination and harassment, work–life boundaries and young people’s early employment experiences.

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