Sage Journals: Discover world-class research

Abstract

Flexible work is often heralded as a key solution to the work–family ‘juggle’, yet evidence of its effectiveness is mixed, and few studies consider how parents combine flexible work options to balance work and care. This study aimed to examine the interplay between formal (employer-provided) and informal (self-directed) flexible work arrangements and identify usage patterns that support parents’ management of the work–family interface. We examined data from 3669 coupled Australian parents collected in 2016–2017. Using latent class analysis, we identified three distinct patterns of total flexibility use (low, moderate and high). Parents who were low users had the poorest work–family experiences, reporting higher work-to-family conflict, lower work–family enrichment and less balance than moderate or high users. However, high users experienced higher family-to-work conflict, and greater flexibility uptake did not ease perceptions of time pressure. Overall, findings demonstrate that formal and informal flexibility is a beneficial resource for mothers and fathers.

Keywords

Work and family flexibility gender parents latent class analysis

Balancing the dual demands of paid work and raising children is a common challenge of contemporary parenthood (Pocock et al., 2013). One approach to help employed parents balance work and non-work responsibilities is flexible working arrangements – workplace practices that permit employees to have some control over work hours, pattern or location, such as flexitime and flexiplace (Fair Work Ombudsman, 2021). Flexible work practices and policies have become widespread as organisations recognise the benefits of supporting work–life balance, for both employees and employers (Workplace Gender Equality Agency, 2019). Several governments have introduced legislation that entitles all employees (e.g. Germany, UK) or employees with caring responsibilities (e.g. Australia) the right to request flexible work arrangements. More recently, government and organisational responses to the COVID-19 pandemic have thrown flexible work into the spotlight, with stay-at-home measures enforcing many employees to work remotely from home. Despite this emphasis on workplace flexibility, evidence to support its use for parents is mixed (Allen et al., 2013). Some work–family outcomes (i.e. work–family enrichment, time pressure) have received little empirical attention (French and Shockley, 2020), and few studies consider how parents use flexible work arrangements (provided by employers) in conjunction with informal work accommodations (self-directed strategies). Our prior research using data from a national sample of Australian parents found that informal work accommodations were widespread and regularly used by mothers and fathers, despite most parents also accessing formal flexible work provisions (Hokke et al., 2021). The present study sought to extend previous evidence and provide a more nuanced understanding of how parents use flexible work arrangements, guided by the following research questions: (i) How do parents use formal and informal flexible work options in combination?; (ii) Which patterns of use help or hinder mothers’ and fathers’ experience of the work–family interface?; and (iii) Which parents are at risk of poorer work–family experiences?

The current study

We focus our study on employed parents who comprise around two-fifths of the Australian labour force, and on parents who reside in couple households, the most common household type in Australia (Australian Bureau of Statistics, 2021), to address the following three objectives. First, we investigate how parents combine formal and informal flexibility to manage work and family demands. Our prior research (Hokke et al., 2021) examined parents’ use of these work arrangements separately, which then led us to query how parents use various flexible work options in combination. To address this aim, we sought a robust data-driven statistical approach and apply latent class analysis to identify distinct profiles of use of formal and informal work arrangements in a national sample of employed Australian parents. Latent class analysis is a probabilistic-based mixture modelling method used to detect latent (or unobserved) heterogeneity in samples and group individuals into homogeneous classes based on underlying patterns in the data (see Weller et al. (2020) for an overview). Compared to other ‘person-centred’ approaches such as cluster analysis, latent class analysis estimates class membership probabilities and provides several rigorous statistical tests to assess model fit (Porcu and Giambona, 2017).

Second, we ascertain which of the identified patterns or classes are most optimal for managing the work–family interface, evaluating between-class differences in parents’ experiences of work-to-family conflict, family-to-work conflict, work–family enrichment, work–family balance and time pressure. Third, we examine the demographic and employment characteristics that predict class membership, with variable selection informed by prior work–family research, to identify which mothers and fathers are at risk of poorer work–family experiences.

Literature review

Flexible work and the work–family interface

To date, most research considers flexibility in terms of ‘formal’ organisational policies provided by Human Resources or workplace practices implemented by unit managers (i.e. flexitime or flexiplace, also known as telework or remote work) (French and Shockley, 2020; Hokke et al., 2021). Such formal flexible arrangements are typically provided by employers to manage general, persistent work–family strain, and their use often requires employees to submit a written request for ongoing changes in work structure or demands (Hokke et al., 2021). We consider five key indicators of parents’ experience of the work–family interface that are commonly used to describe the ways people combine work and family domains (French and Shockley, 2020; Rose et al., 2013): work-to-family conflict, family-to-work conflict, work–family enrichment, work–family balance and time pressure.

Work–family conflict is a form of inter-role conflict where the demands of one domain interfere or compete with demands of the other domain, resulting in overload and strain (Greenhaus and Beutell, 1985; Marshall and Barnett, 1993). Work–family conflict is reported by one in three Australian parents (Lass, 2019; Strazdins et al., 2013) and is associated with poorer health consequences for mothers and fathers, and negative impacts for families and organisations (Amstad et al., 2011; Cooklin et al., 2016; Dinh et al., 2017). Work–family conflict is bidirectional and comprises family-to-work conflict, where family interferes with work, and work-to-family conflict, where work interferes with family (Allen et al., 2013). The relationship between flexibility and work–family conflict is inconsistent and complex. Some studies find employees with more flexibility (measured as schedule flexibility, flexitime or flexiplace) report less work-to-family conflict (Carlson et al., 2010; Hayman, 2010) including in meta-analyses (Allen et al., 2013; Byron, 2005), while others report no association (Clark et al., 2017) or an adverse association (Higgins et al., 2014; Kim et al., 2020). Research examining the relationship between flexibility and family-to-work conflict is also mixed (Allen et al., 2013; Byron, 2005; Hayman, 2010; Higgins et al., 2014). Notionally, flexible work arrangements provide employees with greater control over their work schedule and/or location. For example, flexitime can help ease time-based conflicts by scheduling work hours around childcare or school hours. Flexibility can serve as a boundary-spanning resource (Voydanoff, 2005a), enabling parents to allocate time, attention and energy in more autonomous and efficient ways. However, workplace flexibility may sometimes act as a boundary-spanning demand and increase work–family conflict (Allen et al., 2013; Kossek et al., 2006; Lapierre and Allen, 2006; Voydanoff, 2005a). For example, flexiplace removes the geographic separation between work and family and may facilitate boundary permeability across domains, potentially contributing to role blurring and strain.

Increasingly, researchers are recognising the positive effects of combining work and family roles. Work–family enrichment occurs when an accumulation of multiple roles enhances opportunities, rewards and resources transferable across or between roles, delivering benefits to individuals and their families (Greenhaus and Powell, 2006; Marshall and Barnett, 1993). For example, employment can provide social and financial resources which positively impact mental health and family functioning (McNall et al., 2010; Zhang et al., 2018). Or, social support from family members can increase job satisfaction and engagement (Chan et al., 2020). Work–family conflict and enrichment are distinct concepts that can co-occur, as employees may experience work–family gains and strains simultaneously (Greenhaus and Powell, 2006; Lapierre et al., 2018). Overall, literature supports a positive relationship between family–friendly organisational policies (including flexible work) and work–family enrichment (Carlson et al., 2010; Chen et al., 2018; Lapierre et al., 2018; McNall et al., 2010). Flexibility may increase work–family enrichment by enabling parents to devote more time to family responsibilities, participate more fully in family life, and enhance their performance in the parenting role (Greenhaus and Powell, 2006; Voydanoff, 2005a). A flexible work environment may also signal organisational family-friendly support, help individuals be more efficient and satisfied at work, and increase positive affect (French and Shockley, 2020; Lapierre et al., 2018).

Work–family balance is ubiquitous in mass media, yet has been conceptualised, defined and measured in various ways (Casper et al., 2018). Here, we consider work–family balance as the perception that work resources are sufficient to effectively manage work and family roles simultaneously (Voydanoff, 2005b). Balance is a global construct that captures an individual's overall evaluation of the interplay between work and family (Carlson et al., 2009; Casper et al., 2018). Work–family balance is positively related to well-being and job and family satisfaction, and adversely related to depression and anxiety (see Landolfi et al., 2020). Employees with schedule flexibility or perceived flexibility generally report greater work–family balance (Buchanan et al., 2020; Goni-Legaz and Ollo-Lopez, 2016), although working from home has been shown to negatively impact work–family balance satisfaction (Buchanan et al., 2020).

Time pressure (feeling rush or pressed for time) is a persistent concern for many parents and is central to the challenge of managing work and family commitments (Craig and Brown, 2017; Szollos, 2009). Excessive or competing demands of care and paid work can constrain people's time, while advances in technology and socio-cultural expectations to rush or simultaneously perform tasks can intensify experiences of time pressure (Strazdins et al., 2016). Living a time-balanced life promotes health and well-being, while time pressure can have negative effects on health, well-being and relationships (Ruppanner et al., 2019; Strazdins et al., 2016). Parents often use flexible work arrangements to improve time efficiency or time management, although few studies examine how flexibility relates to parents’ experience of time pressure. Flexible work options have been associated with lower time pressure for men and women (Darouei and Pluut, 2021; Rose and Hewitt, 2019), while others report no association between parents’ use of schedule flexibility and time pressure (Dunatchik et al., 2019). Other research suggests that attempts to merge work and home boundaries or multitask may increase time intensity and perceptions of time pressure (Rose, 2017; Thulin et al., 2019).

Examining formal and informal flexible work arrangements and the work–family interface

Less evidenced in the literature, yet also salient to parents’ management of work and family, are informal work accommodations to family (IWAF) (Behson, 2002; Hokke et al., 2021). These are the temporary, self-directed, ‘ad hoc’ adjustments employees make to usual work patterns to accommodate family responsibilities, such as performing family-related tasks at work (e.g. phone calls, paying bills) or working through breaks to leave work on time. While some IWAFs may require discretionary approval by a supervisor, their use is generally unofficial or ‘invisible’ (Behson, 2002) in comparison to more formal arrangements described above. Literature about IWAFs is sparse, yet our prior research showed that most (64%) Australian parents regularly use a range of informal work accommodations to respond to family demands (Hokke et al., 2021). Greater IWAF use was associated with higher work–family conflict, for both mothers and fathers. Badawy and Schieman (2020) investigated the consequences of family-related contact at work and found more frequent contact over time was associated with greater family-to-work conflict, particularly for women and workers with greater caring responsibilities. As noted for formal flexibility, informal flexibility may increase multitasking, role boundary blurring and disruptions, and represent a stressor for parents (Hokke et al., 2021; Paulin et al., 2017). We are not aware of any studies that examine the use of informal work accommodations and parents’ experience of work–family enrichment, balance or time pressure. Further evidence is warranted to understand the interplay between formal organisational provisions and informal self-directed strategies, and identify which patterns of flexible work are most effective at improving parents’ work–family management.

Gendered and social patterning of flexible work and the work–family interface

Work and family arrangements, including flexible work, are gendered. Employed mothers report more family-to-work conflict than fathers are among the most time-pressured groups and are the least satisfied with work–family balance; largely due to the disproportionate amount of time women spend relative to men on housework and childcare (Buchanan et al., 2020; Craig and Brown, 2017; Pocock et al., 2013; Strazdins et al., 2016). Australian mothers are expected, by themselves and society, to tailor work around caring responsibilities (Baxter, 2014; Radcliffe and Cassell, 2015). It follows that more mothers use formal flexible work arrangements than fathers in Australia (Australian Bureau of Statistics, 2018a; Skinner et al., 2016) due to persistent gendered expectations in how families negotiate work and care, and because fathers anticipate or face more stigma in accessing flexibility (Coltrane et al., 2013).

The role of gender on the relationship between flexibility and the work–family interface is mixed, and few studies consider parenting status. Some report no difference by gender (Allen et al., 2013), whereas others find flexibility is associated with higher family-to-work conflict for mothers compared to fathers (Badawy and Schieman, 2020; Hammer et al., 2005). This could reflect employees with more flexible jobs bearing more of the responsibility for caregiving and housework, and thus reporting greater conflicts (Hilbrecht et al., 2008). Other research suggests women benefit more from flexible work schedules than men (Byron, 2005; Carlson et al., 2010), whereas flexible work location may be more useful for men (Clark et al., 2017; Kim et al., 2020). No gender effects have been found regarding flexibility and work–family enrichment (Carlson et al., 2010; Chen et al., 2018; Lapierre et al., 2018).

Social inequalities may also impact parents’ uptake of flexibility. International evidence suggests poorly remunerated jobs have the most ‘inflexible’ conditions (Perry-Jenkins et al., 2017; Williams et al., 2013). Higher-status workers (i.e. employees with higher educational attainment, supervisory roles) are more likely to work flexibly (Chung, 2019; Williams et al., 2013). Both informal and formal arrangements are used more frequently by workers with job autonomy and schedule control (Behson, 2002; Kossek et al., 2006; Thompson and Prottas, 2006); job characteristics that tend to cluster in skilled or professional occupations. Access to flexibility also differs by contract type, with flexible work typically entitled to those in more secure employment (i.e. permanent/ongoing or long fixed-term contracts) than temporary or casual workers (Fair Work Ombudsman, 2021). This suggests that socio-economic position, job status and skill may be important determinants of use. Inequalities in workplace flexibility may widen social, income and health inequalities and may place parents ‘at risk’ of poorer work–family experiences, yet this is poorly described in Australia.

Method

Study design and sample

Data were drawn from the ‘Families at Work’ study, an online nation-wide survey on the employment conditions and workplace supports used by employed Australian parents to manage work and family demands. The study was approved by (La Trobe University Human Research Ethics Committee, reference number S16-112). Study design and recruitment procedures are described elsewhere (Hokke et al., 2021). In brief, parents were recruited between August and November 2016 via Facebook. Facebook advertisements invited working parents to complete a 15-min online survey about ‘balancing work and family’. Parents were eligible if they were at least 18 years of age, residing in Australia, in paid employment and a parent of one or more children aged 18 years or younger. In total, n = 5197 parents consented to participate. The overall sample was compared with a national, population-based cohort and found to be broadly representative of working Australian parents, although parents with lower educational attainment and parents born outside Australia were under-represented (Hokke et al., 2021).

Participants were included in the current analyses if they were organisationally employed and coupled (married or de facto relationship). Self-employed (n = 472) and single parents (n = 694) were excluded, as were parents who did not identify as either a man or woman (n = 11). Participants with missing data on variables of interest were also excluded from main analyses (n = 351). The final sample therefore comprised 3669 organisationally-employed coupled parents with a dependent child.

Measures

Work arrangements

Flexible work arrangements were assessed using a six-item measure of common work–life balance strategies (e.g. ‘Flexible work hours / flexitime’, ‘Working from home / offsite / remote or telecommuting regularly’, ‘Job share’) (De Cieri et al., 2005; Hokk et al., 2021). Parents reported which arrangements they had used in the past 12 months to manage work and family demands. Counts were derived (range 0–6).

Informal work accommodations to family (IWAF) were assessed using an adapted 12-item scale developed by Behson (2002) and as previously reported (Hokke et al., 2021). Parents indicated how often they had done each of the 12 IWAF items on a 4-point scale. Examples of IWAFs include ‘Doing household-related tasks while at work (e.g. paying bills or arranging plans by phone)’ and ‘Working through breaks to leave work on time’. Responses were summed (range 12–48), with higher scores indicating greater frequency of IWAF behaviours (Cronbach's α=.77).

Work–family interface

Work-to-family conflict and family-to-work conflict were assessed using four items adapted from Marshall and Barnett (1993). Two items assessed work-to-family conflict (e.g. ‘Because of my work responsibilities, my family time is less enjoyable and more pressured’; r = .51, p < .001) and two items measured family-to-work conflict (e.g. ‘Because of my family responsibilities, my work time is less enjoyable and more pressured’; r = .50, p < .001). Parents rated their agreement from one ‘Strongly disagree’ to five ‘Strongly agree’. Responses were averaged (range 1–5), with higher scores indicating more conflict. The correlation between work-to-family conflict and family-to-work conflict was small to moderate (r = .32, p < .0001), suggesting these two composite measures are related but distinct, and supporting work–family conflict as a bidirectional phenomenon for parents.

Work–family enrichment was measured using six-items adapted from Marshall and Barnett (1993) assessing the benefits of combining parenting and employment (e.g. ‘Having both work and family responsibilities makes me a more well-rounded person’; α=.82). Items were scored on a 5-point Likert scale from one ‘Strongly disagree’ to five ‘Strongly agree’ and averaged, with higher scores indicating greater enrichment.

Work–family balance was assessed with a single study-specific item (‘Overall, my current job allows me to balance my work and family demands’). Parents rated their agreement from one ‘Strongly disagree’ to five ‘Strongly agree’.

Time pressure was measured using a single item (‘How often do you feel rushed or pressed for time’) on a 5-point Likert scale (Australian Bureau of Statistics, 2018b). A binary variable was derived to compare parents who ‘always’ or ‘often’ feed rushed or pressed for time, with parents who ‘sometimes’, ‘seldom’ or ‘never’ do.

Demographic and employment characteristics

The demographic, family and employment characteristics selected for inclusion were informed by prior literature (e.g. Byron (2005), Page et al. (2018), and as described above). Demographic and family characteristics included: gender (male, female), parent age (in years), household income type (dual income, single income), country of birth (born in Australia, born outside Australia), educational attainment (Year 12 or below, post-school qualification, tertiary qualification), number of children in the household and age of youngest child (infant, preschool, school). Socio-economic position was determined using the Index of Relative Socio-economic Disadvantage, a relative measure of socio-economic disadvantage by geographic area (Australian Bureau of Statistics, 2011). Scores were ranked and divided into quintiles.

Employment characteristics included weekly individual income before tax, occupation (manager or professional, trades or labourer, clerical or service worker, other), weekly work hours, employment contract (permanent ongoing, fixed-term, casual), shift work, partner's job flexibility (able to change start/finish times; yes, no) and partner's weekly work hours.

Analytic strategy

Analyses were performed in three steps. To investigate how parents combine formal and informal flexibility to manage work and family demands (Aim 1), latent class analysis was performed using MPlus version 8 (Muthén and Muthén, 1998–2012) and guided by recommendations in the literature (Weller et al., 2020), to identify groups (classes) of parents with similar patterns of use (using the six flexible work items and 12 IWAF items). This involved identifying the smallest number of classes starting with a parsimonious 1-class model and fitting successive models with increasing numbers of classes. Based on maximum likelihood estimation, model solutions were evaluated using Likelihood ratio statistic (L²), Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) to determine the optimal number of classes. Better fitting models have lower L², BIC and AIC values. We also examined entropy values and Vuong-Lo-Mendall-Rubin Likelihood Ratio Test (VLMR-LRT) across the successive models. Entropy is an index for assessing the precision of assigning latent class membership, with higher values indicating greater precisions of classification. Posterior probabilities were obtained for each case, indicating the probability of belonging to each class. The VLMR-LRT was used to test for significant differences between the models. In addition to the above model fit indices, model selection was guided by the interpretability, utility and parsimony of identified classes. Class membership was assigned to all participants and used in subsequent analyses.

Next, to determine whether there were differences in work-to-family conflict, family-to-work conflict, work–family enrichment and work–family balance between the identified classes representing the distinct patterns of work arrangements (Aim 2), a series of one-way ANCOVAs (SPSS version 25) controlling for relevant demographic and employment characteristics were conducted. Analyses were stratified by gender to enable meaningful interpretation of results, given the different work–family characteristics of Australian mothers and fathers. Examination of correlation coefficients confirmed the absence of multicollinearity between covariates. Post hoc analysis was performed with a Bonferroni adjustment. Differences in time pressure (binary variable) between classes were assessed using multivariable logistic regression.

To examine the demographic and employment characteristics that predict the probability of parents’ class membership (Aim 3), we tested multinomial logistic regression models separated by gender. Bivariate logistic regressions were performed to model the relationship between class membership and various characteristics separately, with significant predictors (p < .1) subsequently included in a multivariable model.

Sample characteristics of parents excluded from analyses due to missing data were compared to complete cases using univariate analyses. To handle missing data and as an additional sensitivity analysis, analyses for Aim 2 were repeated using multiple imputation by chained equations (Royston and White, 2011). The imputation model included all model variables, and the results of the analyses using multiple imputation were pooled across 20 parallel imputed datasets.

Results

Sample characteristics

Sample characteristics are presented in Table 1. Around two-thirds were mothers (67%, n = 2474). Most parents were born in Australia (81%), tertiary educated (68%) and in a dual-earner household (86%), with an average of two children per household. Half had a youngest child of school age (5–18 years), 41% had a youngest child of pre-school age (1–4 years) and 10% had an infant. The majority of parents worked in a managerial or professional occupation (72%) and in a permanent ongoing role (81%). Mothers worked on average (SD) 33.0 (11.9) hours per week, and fathers worked on average 45.3 (11.9) hours per week. Mothers were more likely than fathers to be in a dual-income household, tertiary educated and in a managerial or professional occupation, and fewer mothers worked shifts. Mothers reported higher family-to-work conflict than fathers, and a greater proportion of mothers felt rushed or pressed for time; yet mothers also reported higher work–family enrichment and balance than fathers.

Table 1.
Sample characteristics.

Total sample n = 3669 Mothers n = 2474 Fathers n = 1195

Age, m (SD) 39.8 (6.4) 39.5 (5.9) 40.5 (7.4)

Dual-income household 3164 (86.2) 2329 (94.1) 835 (69.9)

Born in Australia 2966 (80.8) 2000 (80.8) 966 (80.8)

Education

Year 12 or below 316 (8.6) 142 (5.7) 174 (14.6)

Post-school qualification 846 (23.1) 429 (17.3) 417 (34.9)

Tertiary qualification 2507 (68.3) 1903 (76.9) 604 (50.5)

Number of children, m (SD) 2.0 (0.9) 2.0 (0.8) 2.1 (1.0)

Age of youngest child

Infant (<1 year) 360 (9.8) 208 (8.4) 152 (12.7)

Preschool (1–4 years) 1486 (40.5) 1013 (40.9) 473 (39.6)

School (5–18 years) 1823 (49.7) 1253 (50.6) 570 (47.7)

Socio-economic position

Most disadvantaged quintile 314 (8.6) 197 (8.0) 117 (9.8)

Middle quintiles 2083 (56.8) 1392 (56.3) 691 (57.8)

Least disadvantaged quintile 1252 (34.1) 872 (35.2) 380 (31.8)

Weekly individual income before tax (AUD)

<$800 611 (16.7) 544 (22.0) 67 (5.6)

$800–$1249 723 (19.7) 556 (22.5) 167 (14.0)

$1250–$1999 1155 (31.5) 713 (28.8) 442 (37.0)

>$2000 1041 (28.4) 565 (22.8) 476 (39.8)

Occupation

Manager or professional 2633 (71.8) 1878 (75.9) 755 (63.2)

Trades or labourer 193 (5.3) 17 (0.7) 176 (14.7)

Clerical or service 474 (12.9) 396 (16.0) 78 (6.5)

Other 369 (10.1) 183 (7.4) 186 (15.6)

Weekly work hours, m (SD) 37.0 (13.2) 33.0 (11.9) 45.3 (11.9)

Weekly work hours

<20 319 (8.7) 301 (12.2) 18 (1.5)

20 to <40 1598 (43.6) 1328 (53.7) 270 (22.6)

≥40 to <50 1126 (30.7) 595 (24.1) 531 (44.4)

≥50 626 (17.1) 250 (10.1) 376 (31.5)

Employment contract

Permanent ongoing 2966 (80.8) 1908 (77.1) 1058 (88.5)

Fixed term 454 (12.4) 377 (15.2) 77 (6.4)

Casual 224 (6.1) 170 (6.9) 54 (4.5)

Usually works shifts 732 (20.0) 393 (15.9) 339 (28.4)

Partner has job flexibility^a 2240 (70.6) 1657 (70.1) 583 (69.6)

Partner's weekly work hours, m (SD)^a 40.0 (12.8) 43.3 (11.2) 30.7 (12.5)

Partner's weekly work hours

0 (unemployed) 494 (13.5) 137 (5.5) 357 (29.9)

<40 1221 (33.3) 625 (25.3) 596 (49.9)

≥40 to <50 1210 (33.0) 1042 (42.1) 168 (14.1)

≥50 741 (20.2) 668 (27.0) 73 (6.1)

Work-to-family conflict, m (SD) 3.62 (0.94) 3.60 (0.94) 3.65 (0.93)

Family-to-work conflict, m (SD) 3.11 (0.97) 3.22 (0.96) 2.87 (0.95)

Work–family balance, m (SD) 3.49 (1.08) 3.55 (1.05) 3.38 (1.13)

Work–family enrichment, m (SD) 3.68 (0.64) 3.74 (0.62) 3.55 (0.67)

Often/always pressed for time 2533 (69.0) 1840 (74.4) 693 (58.0)

Values are n (%) unless specified.

a
Partner unemployed, n = 494.

Compared to those included in analyses (n = 3669), parents who were eligible but excluded due to missing data (n = 351) had less educational attainment and lower occupational status, and were more likely to be male and in a single-earner household (p < .001). No other differences in demographic or employment characteristics were found between parents with and without missing data.

Identifying classes of formal and informal flexible work use (Aim 1)

To understand how parents use formal and informal flexible work arrangements in combination, latent class models specifying one to five classes were estimated using work arrangement measures as indicators (Table 2). Although the model fit indices (L², BIC, AIC) continued to decrease as class size increased, the 3-class model was selected as the final model after examining all tests of model fit and parsimony. Entropy values were highest for the 3- and 5-class models, and both models had significant VLMR-LRT values. However, the number of fathers in the smallest class in the 5-class model was below 5% of the sample (n = 54). In the 3-class model, the number of individuals in each class was adequate for analysis (smallest class size, 12%) and the average latent class posterior probabilities were high (Class 1 = .95; Class 2 = .91; Class 3 = .96), suggesting acceptable precision in assigning individual cases to their appropriate class. Therefore, the more interpretable 3-class model was chosen.

Table 2.
Model fit indices for latent class model.

Model L² BIC AIC Entropy VLMR-LRT p Smallest class size (n, %)

1-class −17,835.16 35,703.16 35,678.32 3669 (100)

2-class −17,444.99 34,947.44 34,903.97 .68 <.001 1512 (41)

3-class −17,272.70 34,627.51 34,565.41 .84 <.001 561 (15)

4-class −17,235.05 34,576.82 34,496.10 .79 <.001 348 (9)

5-class −16,718.16 33,567.67 33,468.32 .97 <.001 234 (7)

L²: Likelihood-ratio statistic; BIC: Bayesian Information Criterion; AIC: Akaike Information Criterion; VLMR-LRT: Vuong-Lo-Mendell-Rubin likelihood ratio test.

Selected latent class solution shown in bold.

The estimated means of work arrangements for each class, based on this optimal solution, are presented in Table 3. The first and largest class (n = 1,707, 46.5%) consisted of parents with the lowest usage of both work arrangement types. This group had on average used ‘half’ a formal flexible work arrangement in the previous 12 months and were labelled Low Use. The second class (n = 1,401, 38.2%) consisted of parents who reported using on average two flexible work arrangements and were moderate users of IWAFs; they were labelled Moderate Use. The third and smallest class (n = 561, 15.3%) consisted of parents who reported the highest use of both flexibility types. On average, they used four formal work arrangements in the previous 12 months, and were the most frequent IWAF users; this group were labelled High Use. Class size and estimated mean work arrangements were also determined for mothers and fathers, with the latent class analysis solution stratified by gender (Table 3). Fathers were more likely to report patterns of Low Use than mothers (χ²(2) = 33.23, p < .001).

Table 3.
Class size and mean work arrangements for the 3-class model solution, stratified by gender.

Class 1 Class 2 Class 3

Low use Moderate use High use

Total sample, n = 3669 n = 1707 (46.5%) n = 1401 (38.2%) n = 561 (15.3%)

FWAs, m (SD) 0.47 (0.50) 2.42 (0.49) 4.46 (0.59)

IWAFs, m (SD) 19.94 (4.75) 22.65 (5.02) 25.15 (5.12)

Mothers, n = 2474 n = 1076 (43.5%) n = 977 (39.5%) n = 421 (17.0%)

FWAs, m (SD) 0.51 (0.50) 2.44 (0.50) 4.48 (0.60)

IWAFs, m (SD) 20.09 (4.75) 22.37 (5.02) 24.98 (5.12)

Fathers, n = 1195 n = 631 (52.8%) n = 424 (35.5%) n = 140 (11.7%)

FWAs, m (SD) 0.40 (0.49) 2.39 (0.49) 4.40 (0.52)

IWAFs, m (SD) 19.68 (4.74) 23.29 (4.95) 25.69 (5.11)

FWAs: flexible work arrangements; IWAFs: informal work accommodations to family.

Class membership and parents’ experience of the work–family interface (Aim 2)

Separate one-way ANCOVAs were conducted to determine if parents’ work-to-family conflict, family-to-work conflict, work–family enrichment and work–family balance differed by class membership, controlling for demographic and employment characteristics (Table 4). Overall, we observed a gradient effect whereby parents with High Use or Moderate Use of work arrangements reported better work–family outcomes than Low Use parents. For example, mothers with Low Use had higher work-to-family conflict, lower work–family enrichment and less work–family balance than mothers who had either Moderate Use or High Use. Similar patterns were observed for fathers: fathers with Low Use had greater work-to-family conflict and less work–family balance than Moderate Use or High Use fathers, and lower enrichment than fathers with High Use. However, mothers and fathers with High Use of work arrangements reported greater family-to-work conflict than those with Low Use or Moderate Use. Multivariable logistic regression was performed to assess parents’ time pressure by class membership, with no difference found for either gender (Table 4). For all ANCOVA models, the patterning of results from the multiple imputation sample did not differ from the main study sample (data available upon request), suggesting minimal risk of bias introduced by missing data.

Table 4.
Class membership and parents’ experience of the work–family interface.

Low use Moderate use High use F/χ² p_class

Mothers

Work-to-family conflict 3.71 (0.91) 3.53 (0.96) 3.47 (0.95) 7.97 <.001^ab

Family-to-work conflict 3.13 (0.96) 3.24 (0.97) 3.41 (0.93) 8.80 <.001^bc

Work–family enrichment 3.37 (0.63) 3.77 (0.62) 3.83 (0.59) 6.75 .001^ab

Work–family balance 3.23 (1.08) 3.72 (0.95) 3.95 (0.93) 78.62 <.001^abc

Often/always pressed for time, n (%) 797 (74.6) 725 (74.4) 318 (76.1) 0.95 ns

Fathers

Work-to-family conflict 3.81 (0.90) 3.51 (0.90) 3.34 (0.96) 12.37 <.001^ab

Family-to-work conflict 2.80 (0.95) 2.91 (0.94) 3.05 (0.96) 3.38 .04^b

Work–family enrichment 3.49 (0.67) 3.59 (0.64) 3.72 (0.71) 6.67 .001^b

Work–family balance 3.04 (1.11) 3.70 (0.99) 3.94 (1.09) 37.03 <.001^ab

Often/always pressed for time, n (%) 365 (58.4) 254 (60.6) 74 (53.2) 2.41 ns

Values are m (SD) unless indicated. All models adjusted for: parent age, country of birth, educational attainment, socio-economic position, number of children, age of youngest child, individual income, occupation, weekly work hours, employment contract, shift work, partner's job flexibility and partner's weekly work hours.

Pairwise comparisons (Bonferroni): ^ap < .01 Low Use vs. Moderate Use. ^bp < .01 Low Use vs. High Use. ^cp < .01 Moderate Use vs. High Use.

Demographic and employment characteristics that predict class membership (Aim 3)

Multinomial logistic regression analysis was undertaken to model the relationship between parents’ class membership and demographic and employment characteristics, using High Use class as the reference group to identify parents at risk of poorer work–family experiences. Parameter estimates for mothers are presented in Table 5. Compared to mothers in the High Use class, mothers with Low Use were more likely to report lower individual income, live in more disadvantaged areas, have a youngest child of school age, work 50 or more hours per week and usually work shifts. Mothers in the Moderate Use class also differed to mothers in the High Use class, being more likely to report low individual income, live in more disadvantaged areas and usually work shifts. For example, mothers who earned less than AUD$2000 per week had 1.59–3.31 higher odds of being in the Low Use class than high income earners; and mothers who worked shifts had a 4.24 increase in odds of being a Low User and a 2.01 increase in odds of being a Moderate User than non-shift workers.

Table 5.
Predicting mothers’ class membership: parameter estimates of multinomial regression model.

Mothers Low use Moderate use

aOR 95% CI SE aOR 95% CI SE

Weekly individual income^a

<$800 3.31*** 2.15, 5.09 0.22 1.66* 1.09, 2.54 0.22

$800–$1249 2.32* 1.59, 3.36 0.19 1.37 0.95, 1.97 0.19

$1250–$1999 1.59 1.15, 2.20 0.17 1.15 0.84, 1.57 0.16

Born outside Australia^b 0.74 0.55, 1.00 0.15 0.80 0.60, 1.07 0.15

Socio-economic position^c

Most disadvantaged quintile 2.13 1.27, 3.57 0.26 1.68 1.00, 2.80 0.26

Middle quintiles 1.59* 1.24, 2.06 0.13 1.30* 1.02, 1.68 0.13

Age of youngest child^d

Infant (<1 year) 0.63* 0.40, 0.99 0.23 0.93 0.61, 1.43 0.22

Preschool (1–4 years) 0.77* 0.59, 0.99 0.13 0.92 0.72, 1.19 0.13

Weekly work hours^e

20 to <40 0.82 0.53, 1.28 0.23 0.77 0.50, 1.20 0.22

≥40 to <50 1.69 0.99, 2.84 0.27 0.94 0.56, 1.58 0.27

≥50 2.72 1.46, 5.07 0.32 1.02 0.54, 1.90 0.32

Usually works shifts^f 4.24* 2.74, 6.58 0.22 2.01** 1.28, 3.16 0.23

Partner does not have job flexibility^g 1.04 0.79, 1.37 0.14 1.07 0.81, 1.40 0.14

Partner's weekly work hours^h

<40 0.92 0.66, 1.29 0.17 1.18 0.84, 1.64 0.17

≥40 to <50 0.93 0.69, 1.25 0.15 1.03 0.77, 1.39 0.15

High Use is the reference group. aOR: adjusted odds ratio.

Comparison groups for categorical variables: ^aIncome >$2000 per week. ^bBorn in Australia. ^cLeast disadvantaged quintile. ^dSchool age (5–18 years). ^e<20 h. ^fNo shift work. ^gPartner has job flexibility. ^h≥50 h.

p < .05, p < .01, p < .001.

Parameter estimates of the demographic and employment characteristics predicting fathers’ class membership are presented in Table 6. Compared to fathers with High Use, fathers in the Low Use class were more likely to report lower individual income, work as a tradesperson or labourer, work 40 to 50 h per week compared to <40 h and usually work shifts. Fathers in the Low Use class were also more likely to have a partner who did not have flexibility in their start/finish times. For example, fathers in trades or labourer roles had a 3.63 increase in odds of being a Low User than fathers in professional roles; and fathers who worked shifts had 3.04 times the odds of being a Low User than non-shift workers. There were no differences in sample characteristics between fathers in the Moderate Use and High Use classes.

Table 6.
Predicting fathers’ class membership: parameter estimates of multinomial regression model.

Fathers Low use Moderate use

aOR 95% CI SE aOR 95% CI SE

Weekly individual income^a

<$800 1.68 0.69, 4.04 0.45 0.67 0.26, 1.72 0.48

$800–$1249 2.80 1.30, 6.03 0.39 1.37 0.62, 3.04 0.41

$1250–$1999 2.04 1.30, 3.21 0.23 1.23 0.78, 1.94 0.23

Education^b

Year 12 or below 0.66 0.41, 1.07 0.25 0.75 0.46, 1.22 0.29

Post-school qualification 0.94 0.48, 1.84 0.35 1.03 0.51, 2.07 0.36

Socio-economic position^c

Most disadvantaged quintile 1.36 0.62, 2.95 0.40 1.18 0.53, 2.61 0.41

Middle quintiles 1.03 0.66, 1.58 0.22 0.86 0.56, 1.33 0.22

Occupation^d

Trades or labourer 3.63** 1.57, 8.35 0.43 1.37 0.56, 3.34 0.46

Clerical or service 1.29 0.57, 3.59 0.47 1.10 0.42, 2.86 0.49

Other 1.31 0.69, 2.35 0.31 0.97 0.51, 1.84 0.33

Weekly work hours^e

≥40 to <50 1.84* 1.11, 3.04 0.26 1.31 0.80, 2.15 0.25

≥50 1.66 0.97, 2.83 0.27 0.74 0.43, 1.28 0.28

Usually works shifts^f 3.04*** 1.78, 5.19 0.27 1.11 0.62, 1.96 0.29

Partner does not have job flexibility^g 1.72* 1.04, 2.83 0.26 0.98 0.58, 1.66 0.27

High Use is the reference group. aOR: adjusted odds ratio.

Comparison groups for categorical variables: ^aIncome >$2000 per week. ^bTertiary qualification. ^cLeast disadvantaged quintile. ^dProfessional. ^e<40 h. ^fNo shift work. ^gPartner has job flexibility.

p < .05, p < .01, p < .001.

Discussion

This study addresses gaps in knowledge regarding how parents use formal and informal flexible work arrangements and how these support parents’ work–family management. We applied a data-driven approach with a large, diverse national sample of employed Australian parents. We identified three distinct classes of total flexibility, with proportionate increases in frequency of use – low, moderate and high; as well as a social gradient in parents’ access to flexible work. Findings demonstrate that flexibility is a beneficial resource for parents overall: both mothers and fathers with moderate to high use reported more positive work–family experiences than mothers and fathers with low use, despite some detrimental effects for family-to-work conflict. Our findings highlight the interplay between employer-provided flexible work arrangements and self-directed informal work accommodations, and indicate that having multiple flexible work options supports parents to manage the work–family interface more effectively.

Aim 1 was to identify how parents use formal and informal flexibility in combination to balance work and care. Almost half of our sample were low flexibility users. This large group comprised parents who had used either none or one formal flexible work arrangement in the previous 12 months, and they used IWAFs the least frequently. In contrast, the smallest proportion of parents (15%) were high users. These parents used between four and six formal flexible work options and were the heaviest users of IWAFs. Moderate users comprised around a third of the sample, with flexible work mean scores between low and high users. Findings indicate that formal and informal flexibility use is concomitant. Parents whose employer supports, or permits, flexible work (such as flexitime and flexiplace) also have the autonomy and ability to make small, often invisible, adjustments in their day-to-day work to accommodate family (Behson, 2002; Hokke et al., 2021).

Aim 2 was to understand whether flexibility serves as a resource, or a demand, for parents’ management of work and family. Not surprisingly, parents with the lowest uptake of flexible work had the poorest experiences at the work–family interface. For both mothers and fathers, low users had higher work-to-family conflict, less work–family enrichment and worse work–family balance than parents who were moderate or high users, with mean scores for all three measures improving as flexibility use increased. Our findings support existing research where employees with a flexible work arrangement (often flexitime or flexiplace) report less work-to-family conflict, greater enrichment and more balance satisfaction than employees without flexibility (Allen et al., 2013; Goni-Legaz and Ollo-Lopez, 2016; Lapierre et al., 2018). We build on this literature and show that accessing multiple and varied flexible work options is beneficial for parents overall. Being able to draw from a suite of formal and informal flexible arrangements provides parents with control and autonomy to manage ongoing caring responsibilities and respond to specific daily caring demands (Allen et al., 2013). A flexible work environment is a boundary-spanning resource in this regard (Voydanoff, 2005a): greater flexibility at work enables parents to resolve conflicting family demands in various ways (temporal, spatial and/or behavioural) that optimise work and family role performance and satisfaction (Allen et al., 2014; Badawy and Schieman, 2020; Carlson et al., 2010). These benefits may also reflect a more inclusive, family-friendly organisational climate where family demands need not be invisible and parents feel genuinely supported by their supervisors to reconcile work and caring commitments (Dikkers et al., 2007).

While flexibility improved mothers’ and fathers’ work-to-family conflict, enrichment and balance, the opposite effect was found for family-to-work conflict. High flexibility users reported greater family-to-work conflict than low and moderate users, suggesting that utilising more formal and informal work arrangements contributes to parents’ perceptions of family interfering with work. Some flexible work arrangements may act as a stressor for parents through increased role-blurring and work disruption, as noted for telework (Lapierre and Allen, 2006; Schieman and Young, 2010; Tsen et al., 2021). Literature regarding informal flexibility is sparse, although greater IWAF use has been associated with higher family-to-work conflict (Behson, 2002) and work–family conflict (Hokke et al., 2021) in cross-sectional studies. Some informal arrangements may be particularly disruptive, especially when parents must abruptly respond to family demands. For example, family-related contact at work, a concept analogous to some IWAF behaviours, has been linked to higher family-to-work conflict over time (Badawy and Schieman, 2020). While taking care of family matters during the workday may be seen as desirable or necessary, sharing work and home demands across time, location and attention can increase parents’ work–family boundary permeability, role ‘contamination’ and multitasking (Badawy and Schieman, 2020; Paulin et al., 2017). It follows that parents who use more formal and informal flexible work options experience greater family-to-work conflict. Responding to family demands and ‘zigzagging’ between domains likely diminishes parents’ ability to fully engage in work, making work less enjoyable and more pressured (Harris and Haar, 2021).

Given our cross-sectional study, we acknowledge possible reverse or reciprocal relationships between flexibility and family-to-work conflict. Parents with greater family responsibilities may use more flexible work options as a coping strategy, although caring demands (i.e. youngest child age, number of children) seldom predicted flexibility use. Alternatively, greater organisational support for and access to flexibility may increase the amount of family responsibilities a coupled parent shoulders and intensify family-to-work conflict (Hammer et al., 2005).

This study is one of few to investigate the link between parents’ use of flexible work and time pressure. We found no difference in time pressure across the three flexibility classes. Our measure of time pressure may partly account for this. Compared to other work–family outcome measures under investigation, time pressure is a more general concept and is not often asked or framed in the context of work and/or family, including in this study. Nonetheless, time pressure is related to work–family balance and is an important indicator of time-based strains and pressures inherent in conflicts between work and family, ultimately linked to health (Rose et al., 2013). Our findings may indicate that using more flexible work options does not ease mothers’ or fathers’ perceptions of feeling rushed or pressed for time (Dunatchik et al., 2019). As noted for family-to-work conflict, juggling work and home tasks simultaneously or merging temporal boundaries may create additional forms of labour, increasing time intensity and reducing the quality of time experienced (Rose, 2017). While our flexibility measures included a range of formal and informal strategies and behaviours to increase time efficiency and management, we posit that these (unintended) negative consequences may counterbalance any intended gains.

Aim 3 was to identify which coupled parents are low flexibility users and therefore at risk of poorer work–family experiences. Our findings are consistent with extant research showing social inequalities in parents’ access to flexibility (Perry-Jenkins et al., 2017; Williams et al., 2013). Mothers and fathers with lower incomes were more likely to be low users than high users, as were mothers living in disadvantaged areas. Shift work and male-dominated trade and labourer occupations also predicted low use, indicating that white-collar jobs generally have more flexible work conditions (Chung, 2019; McNamara et al., 2012). Interestingly, fathers with low use were likely to have a partner without schedule flexibility, suggesting that inflexible jobs are a shared experience in some couple households. Flexibility use was higher among mothers with younger children as expected. This pattern was not reported among fathers, and fathers were more likely to be low users than mothers overall. Fathers working long hours were also unable to access family-friendly supports, further entrenching gender divisions in work and care (Maume, 2006; Radcliffe and Cassell, 2015).

We applied a gender lens to investigate similarities and differences in mothers’ and fathers’ experiences. Looking at the overall sample, mothers reported greater family-to-work conflict and time inadequacy than fathers and were more likely to be moderate or high flexibility users; consistent with the gendered patterning of work and care common among Australian coupled families (Baxter, 2014). Work-to-family conflict was similarly high between mothers and fathers, providing further evidence that fathers are vulnerable to work–family strains (Cooklin et al., 2016). Interestingly, mothers reported more work–family balance and greater enrichment than fathers, suggesting that mothers experience more gains, and more strains, in managing multiple roles. Despite these variations, we found little evidence of a gendered effect of flexibility at the work–family interface. Consistently, mothers and fathers showed comparable improvements in work-to-family conflict, balance and enrichment (and worsening in family-to-work conflict) as flexibility use increased across the three classes. We show that flexibility has benefits for both mothers and fathers and highlights the value of promoting and supporting men's uptake of flexible work.

Limitations

We acknowledge some limitations with our approach and sample. We used a cross-sectional study design, and causal directions and the long-term impact of flexibility cannot be established. While we contribute evidence from a large heterogenous sample of mothers and fathers from different organisations, occupations, industries and parenting stages, we used a convenience sample. Our recruitment advertisements may have attracted parents who were concerned about work–family strains, as indicated by relatively high levels of work–family conflict and greater socio-economic advantage than the general parent population (Hokke et al., 2021). This may limit the generalisability of study findings to more diverse parents than sampled here. Work–family interface indicators selected in this study represent defining features of parents’ work–family experiences within Australia and globally (French and Shockley, 2020). However, some measures were brief and may be less sensitive to variations in parents’ experiences of the work–family interface. While it was beyond scope to examine other indicators (e.g. work–family spillover and crossover, work–family fit, boundary integration and segmentation (Allen, 2013)), their relationship to workplace flexibility is also salient.

Future directions and considerations

We encourage further investigation of informal flexibility and the work and family contexts, and inequities, that influence its use to inform future policy and practice in Australia. Our findings suggest that high use of informal flexibility is an indicator of family-friendly workplace support. Limited access to informal flexibility may have significant implications for working parents, particularly considering the restructuring of family units, absence of extended family support and recent prominence of work location. Conversely, given the greater family-to-work conflict reported among high users, is there a threshold where too much informal flexibility is detrimental to employee engagement and productivity? Is one parent in a couple (likely mothers) performing more ‘zigzagging’ and shouldering more family disruption throughout the workday? Additional research is needed to further understand how informal arrangements impact parents’ well-being and productivity, how coupled parents share informal flexibility between them, and how workplaces can best support equitable and effective use.

As these data were collected in 2016, we consider our findings in the context of the COVID-19 pandemic. Emerging evidence indicates that government and organisational responses to the pandemic substantially heightened parents’ work–family conflict, role imbalance, stress and role boundary blurring, including while working from home, with a disproportionate burden of unpaid work falling on women (Bernhardt et al., 2022; Craig and Churchill, 2021; Graham et al., 2021; Yerkes et al., 2020). Prior to the pandemic, flexible work (including remote work) was typically a voluntary choice and agreed to by the employee and employer. While our data show that greater flexibility largely benefits the work–family interface, these gains are likely diminished and family-to-work strains are likely exacerbated in crisis situations such as COVID-19, where parenting responsibilities are heightened and choices in work location are removed. We expect that responses to the pandemic increased parents’ (particularly mothers’) use of IWAF behaviours and ‘zigzag’ working (Harris and Haar, 2021), contributing to tenuous demarcations between work and family domains. Nonetheless, it is likely that parents with more flexible jobs and ‘family-friendly’ organisational support would report better work–family experiences than parents who were unable to accommodate family demands, even if working from home.

The pandemic has raised important questions about the future of flexible work and ‘family-friendly’ workplaces in this new era of remote working and ‘visible’ caring (Allen and Orifici, 2021; Williamson and Pearce, 2022). Future research must investigate how the pandemic has shaped parents’ (in)ability to work flexibly, including the persistence of gender and social inequalities, and the long-term impacts on the work–family interface, employee and family well-being, and ultimately, productivity. Burgeoning research questions include: What was the impact of the pandemic on parents’ work–family conflict – were strains eased, sustained, increased – and who is vulnerable, or protected, over time? What does ‘family-friendly’ mean for working parents now? How can employers and workplace policy support flexible work in its various forms, given the new labour force stratification regarding hybrid and remote work (compared to front-line or service work)? The pandemic has provided opportunity to re-shape work–care regimes for working parents, and robust longitudinal evidence is needed on the job conditions and workplace factors that support work participation alongside parent and family well-being post-pandemic.

Conclusion

Overall, we show that workplace flexibility is a valuable resource in parents’ lives. Accessing multiple formal and informal flexible work options can improve mothers and fathers work–life experiences, particularly work-to-family conflict, enrichment and balance. Despite these protective effects, flexibility did not reduce parents’ perception of time pressure and may have intensified, or permitted, family demands to encroach on work. While accommodating family within the workday is likely beneficial to children and family members, our findings indicate that there is a cost for parents to work flexibly. Flexibility is not a universally effective workplace solution and flexible work practices should be utilised in conjunction with other family–friendly organisational resources and supports that sustain and promote employees to manage work–family demands.

Nonetheless, our findings highlight the salience of formal and informal flexible work strategies for parents and organisations. Similar positive effects were observed for mothers and fathers and we encourage uptake of flexible work arrangements for all parents, particularly fathers and socio-economically disadvantaged parents who are at risk of limited access and poorer work–family experiences. Findings provide impetus for workplaces to provide a range of flexible work options and supports that meet the varied needs of working parents, a significant cohort of the labour market. Ensuring employees feel supported to manage work and family responsibilities and have control over when, where and/or how they work will be critical as work evolves following the COVID-19 pandemic.

	Total sample n = 3669	Mothers n = 2474	Fathers n = 1195
Age, m (SD)	39.8 (6.4)	39.5 (5.9)	40.5 (7.4)
Dual-income household	3164 (86.2)	2329 (94.1)	835 (69.9)
Born in Australia	2966 (80.8)	2000 (80.8)	966 (80.8)
Education
Year 12 or below	316 (8.6)	142 (5.7)	174 (14.6)
Post-school qualification	846 (23.1)	429 (17.3)	417 (34.9)
Tertiary qualification	2507 (68.3)	1903 (76.9)	604 (50.5)
Number of children, m (SD)	2.0 (0.9)	2.0 (0.8)	2.1 (1.0)
Age of youngest child
Infant (<1 year)	360 (9.8)	208 (8.4)	152 (12.7)
Preschool (1–4 years)	1486 (40.5)	1013 (40.9)	473 (39.6)
School (5–18 years)	1823 (49.7)	1253 (50.6)	570 (47.7)
Socio-economic position
Most disadvantaged quintile	314 (8.6)	197 (8.0)	117 (9.8)
Middle quintiles	2083 (56.8)	1392 (56.3)	691 (57.8)
Least disadvantaged quintile	1252 (34.1)	872 (35.2)	380 (31.8)
Weekly individual income before tax (AUD)
<$800	611 (16.7)	544 (22.0)	67 (5.6)
$800–$1249	723 (19.7)	556 (22.5)	167 (14.0)
$1250–$1999	1155 (31.5)	713 (28.8)	442 (37.0)
>$2000	1041 (28.4)	565 (22.8)	476 (39.8)
Occupation
Manager or professional	2633 (71.8)	1878 (75.9)	755 (63.2)
Trades or labourer	193 (5.3)	17 (0.7)	176 (14.7)
Clerical or service	474 (12.9)	396 (16.0)	78 (6.5)
Other	369 (10.1)	183 (7.4)	186 (15.6)
Weekly work hours, m (SD)	37.0 (13.2)	33.0 (11.9)	45.3 (11.9)
Weekly work hours
<20	319 (8.7)	301 (12.2)	18 (1.5)
20 to <40	1598 (43.6)	1328 (53.7)	270 (22.6)
≥40 to <50	1126 (30.7)	595 (24.1)	531 (44.4)
≥50	626 (17.1)	250 (10.1)	376 (31.5)
Employment contract
Permanent ongoing	2966 (80.8)	1908 (77.1)	1058 (88.5)
Fixed term	454 (12.4)	377 (15.2)	77 (6.4)
Casual	224 (6.1)	170 (6.9)	54 (4.5)
Usually works shifts	732 (20.0)	393 (15.9)	339 (28.4)
Partner has job flexibility^a	2240 (70.6)	1657 (70.1)	583 (69.6)
Partner's weekly work hours, m (SD)^a	40.0 (12.8)	43.3 (11.2)	30.7 (12.5)
Partner's weekly work hours
0 (unemployed)	494 (13.5)	137 (5.5)	357 (29.9)
<40	1221 (33.3)	625 (25.3)	596 (49.9)
≥40 to <50	1210 (33.0)	1042 (42.1)	168 (14.1)
≥50	741 (20.2)	668 (27.0)	73 (6.1)
Work-to-family conflict, m (SD)	3.62 (0.94)	3.60 (0.94)	3.65 (0.93)
Family-to-work conflict, m (SD)	3.11 (0.97)	3.22 (0.96)	2.87 (0.95)
Work–family balance, m (SD)	3.49 (1.08)	3.55 (1.05)	3.38 (1.13)
Work–family enrichment, m (SD)	3.68 (0.64)	3.74 (0.62)	3.55 (0.67)
Often/always pressed for time	2533 (69.0)	1840 (74.4)	693 (58.0)

Model	L²	BIC	AIC	Entropy	VLMR-LRT p	Smallest class size (n, %)
1-class	−17,835.16	35,703.16	35,678.32			3669 (100)
2-class	−17,444.99	34,947.44	34,903.97	.68	<.001	1512 (41)
3-class	−17,272.70	34,627.51	34,565.41	.84	<.001	561 (15)
4-class	−17,235.05	34,576.82	34,496.10	.79	<.001	348 (9)
5-class	−16,718.16	33,567.67	33,468.32	.97	<.001	234 (7)

	Class 1	Class 2	Class 3
Total sample, n = 3669	n = 1707 (46.5%)	n = 1401 (38.2%)	n = 561 (15.3%)
FWAs, m (SD)	0.47 (0.50)	2.42 (0.49)	4.46 (0.59)
IWAFs, m (SD)	19.94 (4.75)	22.65 (5.02)	25.15 (5.12)
Mothers, n = 2474	n = 1076 (43.5%)	n = 977 (39.5%)	n = 421 (17.0%)
FWAs, m (SD)	0.51 (0.50)	2.44 (0.50)	4.48 (0.60)
IWAFs, m (SD)	20.09 (4.75)	22.37 (5.02)	24.98 (5.12)
Fathers, n = 1195	n = 631 (52.8%)	n = 424 (35.5%)	n = 140 (11.7%)
FWAs, m (SD)	0.40 (0.49)	2.39 (0.49)	4.40 (0.52)
IWAFs, m (SD)	19.68 (4.74)	23.29 (4.95)	25.69 (5.11)

	Low use	Moderate use	High use	F/χ²	p_class
Mothers
Work-to-family conflict	3.71 (0.91)	3.53 (0.96)	3.47 (0.95)	7.97	<.001^ab
Family-to-work conflict	3.13 (0.96)	3.24 (0.97)	3.41 (0.93)	8.80	<.001^bc
Work–family enrichment	3.37 (0.63)	3.77 (0.62)	3.83 (0.59)	6.75	.001^ab
Work–family balance	3.23 (1.08)	3.72 (0.95)	3.95 (0.93)	78.62	<.001^abc
Often/always pressed for time, n (%)	797 (74.6)	725 (74.4)	318 (76.1)	0.95	ns
Fathers
Work-to-family conflict	3.81 (0.90)	3.51 (0.90)	3.34 (0.96)	12.37	<.001^ab
Family-to-work conflict	2.80 (0.95)	2.91 (0.94)	3.05 (0.96)	3.38	.04^b
Work–family enrichment	3.49 (0.67)	3.59 (0.64)	3.72 (0.71)	6.67	.001^b
Work–family balance	3.04 (1.11)	3.70 (0.99)	3.94 (1.09)	37.03	<.001^ab
Often/always pressed for time, n (%)	365 (58.4)	254 (60.6)	74 (53.2)	2.41	ns

Mothers	Low use	Moderate use
Weekly individual income^a
<$800	3.31***	2.15, 5.09	0.22	1.66*	1.09, 2.54	0.22
$800–$1249	2.32***	1.59, 3.36	0.19	1.37	0.95, 1.97	0.19
$1250–$1999	1.59**	1.15, 2.20	0.17	1.15	0.84, 1.57	0.16
Born outside Australia^b	0.74	0.55, 1.00	0.15	0.80	0.60, 1.07	0.15
Socio-economic position^c
Most disadvantaged quintile	2.13**	1.27, 3.57	0.26	1.68	1.00, 2.80	0.26
Middle quintiles	1.59***	1.24, 2.06	0.13	1.30*	1.02, 1.68	0.13
Age of youngest child^d
Infant (<1 year)	0.63*	0.40, 0.99	0.23	0.93	0.61, 1.43	0.22
Preschool (1–4 years)	0.77*	0.59, 0.99	0.13	0.92	0.72, 1.19	0.13
Weekly work hours^e
20 to <40	0.82	0.53, 1.28	0.23	0.77	0.50, 1.20	0.22
≥40 to <50	1.69	0.99, 2.84	0.27	0.94	0.56, 1.58	0.27
≥50	2.72**	1.46, 5.07	0.32	1.02	0.54, 1.90	0.32
Usually works shifts^f	4.24***	2.74, 6.58	0.22	2.01**	1.28, 3.16	0.23
Partner does not have job flexibility^g	1.04	0.79, 1.37	0.14	1.07	0.81, 1.40	0.14
Partner's weekly work hours^h
<40	0.92	0.66, 1.29	0.17	1.18	0.84, 1.64	0.17
≥40 to <50	0.93	0.69, 1.25	0.15	1.03	0.77, 1.39	0.15

Fathers	Low use	Moderate use
Weekly individual income^a
<$800	1.68	0.69, 4.04	0.45	0.67	0.26, 1.72	0.48
$800–$1249	2.80**	1.30, 6.03	0.39	1.37	0.62, 3.04	0.41
$1250–$1999	2.04**	1.30, 3.21	0.23	1.23	0.78, 1.94	0.23
Education^b
Year 12 or below	0.66	0.41, 1.07	0.25	0.75	0.46, 1.22	0.29
Post-school qualification	0.94	0.48, 1.84	0.35	1.03	0.51, 2.07	0.36
Socio-economic position^c
Most disadvantaged quintile	1.36	0.62, 2.95	0.40	1.18	0.53, 2.61	0.41
Middle quintiles	1.03	0.66, 1.58	0.22	0.86	0.56, 1.33	0.22
Occupation^d
Trades or labourer	3.63**	1.57, 8.35	0.43	1.37	0.56, 3.34	0.46
Clerical or service	1.29	0.57, 3.59	0.47	1.10	0.42, 2.86	0.49
Other	1.31	0.69, 2.35	0.31	0.97	0.51, 1.84	0.33
Weekly work hours^e
≥40 to <50	1.84*	1.11, 3.04	0.26	1.31	0.80, 2.15	0.25
≥50	1.66	0.97, 2.83	0.27	0.74	0.43, 1.28	0.28
Usually works shifts^f	3.04***	1.78, 5.19	0.27	1.11	0.62, 1.96	0.29
Partner does not have job flexibility^g	1.72*	1.04, 2.83	0.26	0.98	0.58, 1.66	0.27

Footnotes

Acknowledgements

The authors would like to thank Jasmine Love for her help in preparing the manuscript, including editing and proofreading.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This work was supported by Transforming Human Societies Research Focus Area, La Trobe University and the Roberta Holmes Donation to La Trobe University. Dr Amanda Cooklin was supported by a Tracey Banivanua Mar Fellowship, La Trobe University and an Australian Research Council Future Fellowship (FT 200100209 2021–2025).

ORCID iD

Stacey Hokke

Biographical notes

Stacey Hokke is a Research Fellow at the Judith Lumley Centre, La Trobe University, a research centre that addresses issues of major public health importance for women, children and families. Stacey's research aims to examine key challenges facing parents in contemporary society and identify ways to support the health and well-being of mothers and fathers in their parenting role. She works across a number of projects, including investigating the role of parents’ jobs and the work–family interface on parent mental health and well-being, and the influence of social media during the transition to parenthood.

Simon Mason is an early career statistician and Research Assistant in the Work and Family Research Program at the Judith Lumley Centre, La Trobe University. Following completion of a Master of Applied Statistics, Simon's research has focused on examining the relationships between parents’ employment, job quality and work–family balance on parent mental health and well-being.

Rebecca Giallo leads a life course epidemiological and clinical intervention research program at Deakin University. Her research is focused on optimising the mental health of children and families affected by social adversity and intergenerational trauma. She is particularly passionate about men's health in early fatherhood, and family-based interventions in the early years of children's lives to prevent and disrupt intergenerational cycles of poor health within families. This work has been enabled by partnerships with community health services supporting children and their families. Her research is informed by 10 years’ experience as a psychologist working with children and families.

Shannon Bennetts is a Research Fellow at the Judith Lumley Centre, La Trobe University. She is a social scientist with a focus on supporting and understanding the needs of parents, children, and families. Her research interests include children's language, socio-emotional, and behavioural development, parenting during social adversity, parent and child mental health, the role of pets for child development, work–family conflict and enrichment, and the role of social media in parenthood and for use in research. She is Project Coordinator for the EHLS at School Study, a longitudinal study evaluating children's school-age outcomes following an early childhood parenting program.

Sharinne Crawford is a Research Fellow in the Judith Lumley Centre for women, children and family health research at La Trobe University. Sharinne works in the Transition to Contemporary Parenthood Program and collaborates across a range of programs within the Centre. Her research broadly focuses on contemporary parenthood, child and family health and well-being, and includes parents’ use of social media in the transition to parenthood and the ethical use of social media in research with parents, children and families. She is a mixed methods public health researcher, with expertise in qualitative research.

Amanda Cooklin is a social scientist and ARC Future Fellow at the Judith Lumley Centre at La Trobe University, leading the Work and Family Research Program. She has established expertise in the epidemiology of parents’ mental health, the social determinants of parenting, and the work–family interface. Her research comprises epidemiological cohort studies and intervention trials, with a focus on establishing the longitudinal relationships between parents’ mental health (anxiety, depression, fatigue), parenting and children's outcomes and the role of parents’ employment, job quality and work–family balance on parent mental health and parenting.

References

Allen

Orifici

(2021) Home truths: what did COVID-19 reveal about workplace flexibility? Australian Journal of Labour Law 34(1/2): 77–94.

Allen

(2013) The work-family role interface: a synthesis of the research from industrial and organizational psychology. In: Handbook of Psychology: Industrial and Organizational Psychology, 2nd ed. Hoboken, NJ: John Wiley & Sons, 698–718.

Allen

Cho

Meier

(2014) Work–family boundary dynamics. Annual Review of Organizational Psychology and Organizational Behavior 1(1): 99–121.

Allen

Johnson

Kiburz

, et al. (2013) Work–family conflict and flexible work arrangements: deconstructing flexibility. Personnel Psychology 66(2): 345–376.

Amstad

Meier

Fasel

, et al. (2011) A meta-analysis of work-family conflict and various outcomes with a special emphasis on cross-domain versus matching-domain relations. Journal of Occupational Health Psychology 16(2): 151–169.

Australian Bureau of Statistics (2011) Census of population and housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2011. Report, Australian Bureau of Statistics, Canberra.

Australian Bureau of Statistics (2021) Labour force status of families, June 2021. Report, Australian Bureau of Statistics, Canberra.

Australian Bureau of Statistics (2018a) Childhood education and care, Australia, June 2017. Report, Australian Bureau of Statistics, Canberra.

Australian Bureau of Statistics (2018b) Gender indicators, Australia, January 2013. Report, Australian Bureau of Statistics, Canberra.

10.

Badawy

Schieman

(2020) When family calls: how gender, money, and care shape the relationship between family contact and family-to-work conflict. Journal of Family Issues 41(8): 1188–1213.

11.

Baxter

(2014) Gender role attitudes within couples, and parents’ time in paid work, child care and housework. Report, Australian Institute of Family Studies, Melbourne, Australia.

12.

Behson

(2002) Coping with family-to-work conflict: the role of informal work accommodations to family. Journal of Occupational Health Psychology 7(4): 324–341.

13.

Bernhardt

Recksiedler

Linberg

(2022) Work from home and parenting: examining the role of work-family conflict and gender during the COVID-19 pandemic. Journal of Social Issues 79(3): 935–970.

14.

Buchanan

Das

McFarlane

(2020) Gender differences in within-couple influences on work–family balance satisfaction: when benefits become threats. Journal of Family Studies 26(1): 106–125.

15.

Byron

(2005) A meta-analytic review of work-family conflict and its antecedents. Journal of Vocational Behavior 67: 169–198.

16.

Carlson

Grzywacz

Michele Kacmar

(2010) The relationship of schedule flexibility and outcomes via the work-family interface. Journal of Managerial Psychology 25(4): 330–355.

17.

Carlson

Grzywacz

Zivnuska

(2009) Is work—family balance more than conflict and enrichment? Human Relations 62(10): 1459–1486.

18.

Casper

Vaziri

Wayne

, et al. (2018) The jingle-jangle of work–nonwork balance: a comprehensive and meta-analytic review of its meaning and measurement. Journal of Applied Psychology 103(2): 182–214.

19.

Chan

Kalliath

Chan

, et al. (2020) How does family support facilitate job satisfaction? Investigating the chain mediating effects of work–family enrichment and job-related well-being. Stress and Health 36(1): 97–104.

20.

Chen

Zhang

Sanders

, et al. (2018) Family-friendly work practices and their outcomes in China: the mediating role of work-to-family enrichment and the moderating role of gender. The International Journal of Human Resource Management 29(7): 1307–1329.

21.

Chung

(2019) ‘Women’s work penalty’ in access to flexible working arrangements across Europe. European Journal of Industrial Relations 25(1): 23–40.

22.

Clark

Rudolph

Zhdanova

, et al. (2017) Organizational support factors and work–family outcomes: Exploring gender differences. Journal of Family Issues 38(11): 1520–1545.

23.

Coltrane

Miller

DeHaan

, et al. (2013) Fathers and the flexibility stigma. Journal of Social Issues 69(2): 279–302.

24.

Cooklin

Dinh

Strazdins

, et al. (2016) Change and stability in work-family conflict and mothers’ and fathers’ mental health: longitudinal evidence from an Australian cohort. Social Science & Medicine 155: 24–34.

25.

Craig

Brown

(2017) Feeling rushed: gendered time quality, work hours, nonstandard work schedules, and spousal crossover. Journal of Marriage and Family 79(1): 225–242.

26.

Craig

Churchill

(2021) Dual-earner parent couples’ work and care during COVID-19. Gender, Work & Organization 28(S1): 514–527.

27.

Darouei

Pluut

(2021) Work from home today for a better tomorrow! How working from home influences work-family conflict and employees’ start of the next workday. Stress and Health 37(5): 986–999.

28.

De Cieri

Holmes

Abbott

, et al. (2005) Achievements and challenges for work/life balance strategies in Australian organizations. The International Journal of Human Resource Management 16(1): 90–103.

29.

Dikkers

JSE

Geurts

SAE

Dulk

, et al. (2007) Dimensions of work–home culture and their relations with the use of work–home arrangements and work–home interaction. Work & Stress 21(2): 155–172.

30.

Dinh

Cooklin

Leach

, et al. (2017) Parents’ transitions into and out of work-family conflict and children's mental health: longitudinal influence via family functioning. Social Science & Medicine 194: 42–50.

31.

Dunatchik

Mayer

Speight

(2019) Parents and time pressure: evidence from time use diaries. Report, National Centre for Social Research.

32.

Fair Work Ombudsman (2021) Flexible working arrangements. Best practice guide . Available at: https://www.fairwork.gov.au/tools-and-resources/best-practice-guides/flexible-working-arrangements.

33.

French

Shockley

(2020) Formal and informal supports for managing work and family. Current Directions in Psychological Science 29(2): 207–216.

34.

Goni-Legaz

Ollo-Lopez

(2016) The impact of family-friendly practices on work-family balance in Spain. Applied Research in Quality of Life 11(3): 983–1007.

35.

Graham

Weale

Lambert

, et al. (2021) Working at home: the impacts of COVID 19 on health, family-work-life conflict, gender, and parental responsibilities. Journal of Occupational and Environmental Medicine. DOI: https://doi.org/10.1097/jom.0000000000002337.

36.

Greenhaus

Beutell

(1985) Sources of conflict between work and family roles. The Academy of Management Review 10(1): 76–88.

37.

Greenhaus

Powell

(2006) When work and family are allies: a theory of work-family enrichment. Academy of Management Review 31(1): 72–92.

38.

Hammer

Neal

Newsom

, et al. (2005) A longitudinal study of the effects of dual-earner couples’ utilization of family-friendly workplace supports on work and family outcomes. Journal of Applied Psychology 90(4): 799–810.

39.

Harris

Haar

(2021) In a lockdown, where does work end and parenting begin? Welcome to the brave new world of ‘zigzag working’ . Available at: https://theconversation.com/in-a-lockdown-where-does-work-end-and-parenting-begin-welcome-to-the-brave-new-world-of-zigzag-working-169088.

40.

Hayman

(2010) Flexible work schedules and employee well-being. New Zealand Journal of Employment Relations (Online) 35(2): 76–87.

41.

Higgins

Duxbury

Julien

(2014) The relationship between work arrangements and work-family conflict. Work 48(1): 69–81.

42.

Hilbrecht

Shaw

Johnson

, et al. (2008) ‘I'm home for the kids’: contradictory implications for work-life balance of teleworking mothers. Gender, Work & Organization 15(5): 454–476.

43.

Hokke

Bennetts

Crawford

, et al. (2021) Does flexible work ‘work’ in Australia? A survey of employed mothers’ and fathers’ work, family and health. Community, Work and Family 24: 488–506.

44.

Kim

Henly

Golden

, et al. (2020) Workplace flexibility and worker well-being by gender. Journal of Marriage and Family 82(3): 892–910.

45.

Kossek

Lautsch

Eaton

(2006) Telecommuting, control, and boundary management: correlates of policy use and practice, job control, and work–family effectiveness. Journal of Vocational Behavior 68(2): 347–367.

46.

Landolfi

Barattucci

Lo Presti

(2020) A time-lagged examination of the Greenhaus and Allen work-family balance model. Behavioral Sciences 10(9): 140.

47.

Lapierre

Allen

(2006) Work-supportive family, family-supportive supervision, use of organizational benefits, and problem-focused coping: implications for work-family conflict and employee well-being. Journal of Occupational Health Psychology 11(2): 169–181.

48.

Lapierre

Kwan

, et al. (2018) A meta-analysis of the antecedents of work–family enrichment. Journal of Organizational Behavior 39(4): 385–401.

49.

Lass

(2019) Work or family? Available at: https://pursuit.unimelb.edu.au/articles/work-or-family.

50.

Marshall

Barnett

(1993) Work-family strains and gains among two-earner couples. Journal of Community Psychology 21(1): 64–78.

51.

Maume

(2006) Gender differences in restricting work efforts because of family responsibilities. Journal of Marriage and Family 68(4): 859–869.

52.

McNall

Nicklin

Masuda

(2010) A meta-analytic review of the consequences associated with work-family enrichment. Journal of Business and Psychology 25(3): 381–396.

53.

McNamara

Pitt-Catsouphes

Brown

, et al. (2012) Access to and utilization of flexible work options. Industrial Relations: A Journal of Economy and Society 51(4): 936–965.

54.

Muthén

(1998–2012) Mplus User’s Guide: Statistical Analysis with Latent Variables. Los Angeles: Muthén & Muthén.

55.

Page

Deuling

Mazzola

, et al. (2018) A fresh look at socio-demographics in work-family conflict: a cluster analysis approach. Occupational Health Science 2(2): 181–201.

56.

Paulin

Lachance-grzela

McGee

(2017) Bringing work home or bringing family to work: personal and relational consequences for working parents. Journal of Family and Economic Issues 38(4): 463–476.

57.

Perry-Jenkins

Smith

Wadsworth

, et al. (2017) Workplace policies and mental health among working-class, new parents. Community, Work & Family 20(2): 226–249.

58.

Pocock

Charlesworth

Chapman

(2013) Work-family and work-life pressures in Australia: advancing gender equality in “good times”? International Journal of Sociology and Social Policy 33(9/10): 594–612.

59.

Porcu

Giambona

(2017) Introduction to latent class analysis with applications. The Journal of Early Adolescence 37(1): 129–158.

60.

Radcliffe

Cassell

(2015) Flexible working, work–family conflict, and maternal gatekeeping: the daily experiences of dual-earner couples. Journal of Occupational and Organizational Psychology 88(4): 835–855.

61.

Rose

(2017) Never enough hours in the day: employed mothers’ perceptions of time pressure. Australian Journal of Social Issues 52(2): 116–130.

62.

Rose

Hewitt

(2019) Does part-time employment status really reduce time pressure? Journal of Sociology 55(2): 366–388.

63.

Rose

Hewitt

Baxter

(2013) Women and part-time employment: easing or squeezing time pressure? Journal of Sociology 49(1): 41–59.

64.

Royston

White

(2011) Multiple imputation by chained equations (MICE): implementation in Stata. Journal of Statistical Software 45(4): 1–20.

65.

Ruppanner

Perales

Baxter

(2019) Harried and unhealthy? Parenthood, time pressure, and mental health. Journal of Marriage and Family 81(2): 308–326.

66.

Schieman

Young

(2010) Is there a downside to schedule control for the work-family interface? Journal of Family Issues 31(10): 1391–1414.

67.

Skinner

Cathcart

Pocock

(2016) To ask or not to ask? Investigating workers’ flexibility requests and the phenomenon of discontented non-requesters. Labour & Industry: A Journal of the Social and Economic Relations of Work 26(2): 103–119.

68.

Strazdins

O'Brien

Lucas

, et al. (2013) Combining work and family: rewards or risks for children's mental health? Social Science & Medicine 87: 99–107.

69.

Strazdins

Welsh

Korda

, et al. (2016) Not all hours are equal: could time be a social determinant of health? Sociology of Health & Illness 38(1): 21–42.

70.

Szollos

(2009) Toward a psychology of chronic time pressure. Time & Society 18(2-3): 332–350.

71.

Thompson

Prottas

(2006) Relationships among organizational family support, job autonomy, perceived control, and employee well-being. Journal of Occupational Health Psychology 11(1): 100–118.

72.

Thulin

Vilhelmson

Johansson

(2019) New telework, time pressure, and time use control in everyday life. Sustainability 11(11): 3067.

73.

Tsen

Tan

, et al. (2021) Does flexible work arrangements decrease or increase turnover intention? A comparison between the social exchange theory and border theory. International Journal of Sociology and Social Policy 42(11-12): 962–983. Online ahead of print.

74.

Voydanoff

(2005a) Toward a conceptualization of perceived work-family fit and balance: a demands and resources approach. Journal of Marriage and Family 67(4): 822–836.

75.

Voydanoff

(2005b) Work demands and work-to-family conflict: direct and indirect relationships. Journal of Family Issues 26(6): 707–726.

76.

Weller

Bowen

Faubert

(2020) Latent class analysis: a guide to best practice. Journal of Black Psychology 46(4): 287–311.

77.

Williams

Blair-Loy

Berdahl

(2013) Cultural schemas, social class, and the flexibility stigma. Journal of Social Issues 69(2): 209–234.

78.

Williamson

Pearce

(2022) COVID-normal workplaces: should working from home be a ‘collective flexibility’? Journal of Industrial Relations 64(3): 461–473.

79.

Workplace Gender Equality Agency (2019) Flexible working is good for business. The Business Case. Report, Workplace Gender Equality Agency, Sydney, Australia.

80.

Yerkes

André

SCH

Besamusca

, et al. (2020) ‘Intelligent’ lockdown, intelligent effects? Results from a survey on gender (in)equality in paid work, the division of childcare and household work, and quality of life among parents in The Netherlands during the COVID-19 lockdown. PLoS One 15(11): e0242249.

81.

Zhang

Jin

, et al. (2018) The within and cross domain effects of work-family enrichment: a meta-analysis. Journal of Vocational Behavior 104: 210–227.

Mothers	Low use			Moderate use
Mothers	aOR	95% CI	SE	aOR	95% CI	SE
Weekly individual income^a
<$800	3.31***	2.15, 5.09	0.22	1.66*	1.09, 2.54	0.22
$800–$1249	2.32***	1.59, 3.36	0.19	1.37	0.95, 1.97	0.19
$1250–$1999	1.59**	1.15, 2.20	0.17	1.15	0.84, 1.57	0.16
Born outside Australia^b	0.74	0.55, 1.00	0.15	0.80	0.60, 1.07	0.15
Socio-economic position^c
Most disadvantaged quintile	2.13**	1.27, 3.57	0.26	1.68	1.00, 2.80	0.26
Middle quintiles	1.59***	1.24, 2.06	0.13	1.30*	1.02, 1.68	0.13
Age of youngest child^d
Infant (<1 year)	0.63*	0.40, 0.99	0.23	0.93	0.61, 1.43	0.22
Preschool (1–4 years)	0.77*	0.59, 0.99	0.13	0.92	0.72, 1.19	0.13
Weekly work hours^e
20 to <40	0.82	0.53, 1.28	0.23	0.77	0.50, 1.20	0.22
≥40 to <50	1.69	0.99, 2.84	0.27	0.94	0.56, 1.58	0.27
≥50	2.72**	1.46, 5.07	0.32	1.02	0.54, 1.90	0.32
Usually works shifts^f	4.24***	2.74, 6.58	0.22	2.01**	1.28, 3.16	0.23
Partner does not have job flexibility^g	1.04	0.79, 1.37	0.14	1.07	0.81, 1.40	0.14
Partner's weekly work hours^h
<40	0.92	0.66, 1.29	0.17	1.18	0.84, 1.64	0.17
≥40 to <50	0.93	0.69, 1.25	0.15	1.03	0.77, 1.39	0.15

Flexible work patterns and experiences of the work-family interface among Australian parents

Abstract

Keywords

The current study

Literature review

Flexible work and the work–family interface

Examining formal and informal flexible work arrangements and the work–family interface

Gendered and social patterning of flexible work and the work–family interface

Method

Study design and sample

Measures

Work arrangements

Work–family interface

Demographic and employment characteristics

Analytic strategy

Results

Sample characteristics

Identifying classes of formal and informal flexible work use (Aim 1)

Class membership and parents’ experience of the work–family interface (Aim 2)

Demographic and employment characteristics that predict class membership (Aim 3)

Discussion

Limitations

Future directions and considerations

Conclusion

Footnotes

Acknowledgements

Declaration of conflicting interests

Funding

ORCID iD

Biographical notes

References