Flexible working and its relations with work-life conflict and well-being among crowdworkers in Germany

Abstract

BACKGROUND:

New forms of digital work such as crowdwork promise to increase potentials for flexible working. As crowdworkers can work highly autonomous and from anywhere at any time via the internet, they may be able to make work and private demands more compatible and avoid role conflicts between the life spheres, and in turn, experience enhanced well-being.

OBJECTIVE:

This research asked whether crowdworkers benefit from flexible working potentials. It investigated the association of the use of different dimensions of flexible working (flex-time, flex-place, and task autonomy) in crowdwork with work-life conflict and well-being. Moreover, it explored whether the relationship between flexible working and well-being was mediated by work-life conflict.

METHODS:

The study drew upon a sample of 470 crowdworkers from a cross-sectional self-assessment survey on four different German crowdwork platforms. Structural equation modeling was conducted to estimate the effects of flexible working on work-life conflict, somatic health symptoms, and life satisfaction. Indirect effects were estimated to test the mediation hypothesis.

RESULTS:

The findings suggest that if crowdworkers use temporal and task flexibility, they experience fewer work-life conflict, fewer somatic health symptoms, and greater life satisfaction. This does not apply to flex-place. The relationship between flexible working and well-being is partly mediated by work-life conflict experiences.

CONCLUSION:

This study supports that crowdwork offers a high potential for working highly autonomous and flexibly in time and place. It is associated with lower levels of work-life conflict and enhanced well-being, but the benefits of this flexibility are not universally included in crowdwork.

Keywords

Crowdwork digital labor flex-place flex-time workplace flexibility

1 Introduction

In the course of the rise of the gig economy [1], new forms of digital work such as crowdwork (CW) promise to fundamentally increase flexible working by enabling individuals to decide when, where, and for how long to engage in gainful work [2, 3]. In line with a long tradition of work-life interface research, flexible working can be a key to making work and private obligations compatible and to facilitating work-life balance [4]. However, flexibility facilitated by digital technology, such as remote work, may come at the expense of high expectations of overwork and engagement as well as of work intensification and permanent accessibility, blurring the boundaries between life spheres, and making switching off from work more difficult (see, e.g., [5 –7]). The empirical knowledge on the mechanisms of work-life implications of CW and its involved flexibility potentials is still scarce. Are crowdworkers able to benefit from the use of flexible working or will the great flexibility promise remain an empty shell when it comes to work-life balance and individual well-being? We aim to fill this gap by investigating the blurring of boundaries between work and personal life obligations, mirrored by so-called work-life conflict (WLC) [8, 9], among crowdworkers in Germany, as well as possible implications for individual health and well-being.

Inspired by previous definitions [10, 11], we consider CW to be a task-based paid work that is assigned by a customer (= crowdsourcer) via a digital online platform (= CW platform) to crowdworkers from a crowd of potential workers registered on the platform. Online surveys found that between 4.7 percent [12] and 6 percent [13] of the German survey population to do CW regularly. Though there is no representative data on the prevalence of CW among the working population, scholars forecast a high potential for changing how value creation is carried out [14] and CW is suggested to become an increasingly attractive alternative of earning money, recently pushed by the worldwide COVID-19 pandemic [15]. CW platforms offer a large variety of work tasks regarding skill requirements, extent, and complexity as well as gratifications; they can mostly be carried out completely digitally (i.e., by text writing or website testing) and only require internet access through computers or smartphones [16, 17].

In sum, CW promises to be a unique possibility for individuals to have control of the timing and place of work, of what tasks are done, and of how much money is made by altering the amount of effort put into platform-based work [18]. We suggest that crowdworkers may use the flexibility benefits in CW to facilitate the integration of work and private life demands. To disentangle whether flexible working in CW is an advantage for crowdworkers’ work-life integration, or whether it comes at the expense of an increased blurring of boundaries after all, the present study examines whether WLC is correlated to the use of different dimensions of flexible working: flex-time, flex-place, and task autonomy. Moreover, we shed further light on the well-being of crowdworkers by exploring somatic health symptoms and life satisfaction as indicators of well-being. Finally, we examine the mediation of the relationship between flexible working and well-being by WLC. The latter has been tested for flexible working in different forms of employment [19 –21], but not for CW.

We add to several research streams: First, we expand the knowledge on flexible working by analyzing flexibility involved in CW. Second, we contribute to work-life interface research as well as to research on health and well-being by investigating CW as a new type of digital work, and its relationship with WLC and well-being. Third, we complement the research on the digitalization of work in Germany by adding empirical knowledge on the consequences of new forms of work enabled by digital technologies. We draw on a cross-sectional interdisciplinary study including a sample of 470 crowdworkers from four CW platforms (marketplace, microtask, mobile CW, and testing) in Germany [22].

2 Background

2.1 Flexible working and work-life conflict

The research on the work-life interface addresses the interrelatedness of performing multiple roles in work and personal life, such as being a paid worker and a parent [23, 24]. We address the difficulties in making work and personal life responsibilities compatible by referring to the well-established concept of work-family conflict [8]. This form of inter-role conflict [9] occurs when role demands from work interfere with demands from the family life. Considering that personal life is not limited to family roles only, we refer to role strains as the result of competing demands between both life spheres as work-life conflict (WLC). WLC is a typical issue of workers in all modern societies and documented for standard as well as non-standard forms of employment, no less in the German workforce [25 –27].

In this context, flexible working may be referred to as a job resource that allows for more individual scheduling of work obligations, and thus facilitates the integration of work and private life [4, 28]. Flexible working can be defined as “the ability of workers to make choices influencing when, where, and for how long they engage in work-related tasks” [29] (p. 152). It is differentiated between flexibility in the timing of work (flex-time), flexibility in the location of work (flex-place) [30], and flexibility in the amount of work, or workload [31]. This understanding of flexible working is complemented by flexibility in deciding what work to do and how to do it, also known as (job) autonomy [32, 33]. Accordingly, a lot of studies indicate flexible working in time and place as being associated with less WLC [26 , 35], and autonomy in particular may also be associated with lower levels of conflicts [36 –38].

However, research suggests that flexible working can also result in dissolving physical and/or temporal boundaries and that permanent switching between roles may lead to increased blurring of boundaries between the life spheres [39, 40]. This is especially discussed in research on telework and working from home in general. It is the most common form of technology-enabled flex-place because employees can transfer their work tasks, be it completely or partly, to their home and operate them remotely instead of working on-site at the workplace (see, e.g., 41). In the case of telework, work life and private life share the same environment, and as there are no physical barriers between the life domains, work directly interferes with the private life and the other way round [42]. Furthermore, the permanent presence and availability of technological tools that are used for digital work (e.g., smartphones, e-mails) further increase this limited ability to separate work and family life as workers who work in their home environment tend to set fewer boundaries and rather check for work-related updates permanently (43; 44). In line with the blurring of boundaries argument, some studies find no relationship of flexible working with WLC [45 –47], or even increased levels of those conflicts [7, 48].

Nevertheless, according to work-family border theory [49] and boundary management theory [50], it is not temporal or location flexibility alone that is resourceful, but having control over one’s location and timing of work obligations that allows for flexible coordination with private obligations. Empirical research points to control over one’s flexible working opportunities being the key to lower WLC experiences instead of flexible work schedules alone [51].

2.2 Flexible working in crowdwork

Whereas the opportunities to work flexibly are unequally distributed among the workforce, with being available especially in large organizations, in the public sector as well as for higher status positions [52, 53], CW promises to be accessible for almost everyone by offering low barriers for flexible working. It involves a high potential of flexible working along all previously discussed dimensions of flexibility. Crowdworkers have easy access to job tasks via platforms, and they can perform the job tasks at the location of their preference because tasks can be done completely digitally using internet-ready devices such as computers and smartphones [16]. For example, CW can be done at home but also at a caf $\overset{´}{e}$ or during commuting to another job and thus has a high degree of flexibility in place. CW can be carried out at any day of the week and at any time of the day [18]. Work schedules and the length of individual tasks can actively vary depending on the crowdworkers’ selection of work tasks [54]. Consequently, CW is characterized by a high degree of flexibility in time as well: the timing of the beginning and ending of work, the scheduling of breaks and days off, and the distribution of work over the day/week can easily be adjusted to obligations from other jobs or from private life. Finally, autonomy in CW is related to controlling what tasks are chosen from the available tasks on platforms, which is why we refer to it as task autonomy. For example, crowdworkers may decide to do more or less complex or time-consuming tasks, tasks that are more interesting than others, tasks that are more appropriate for individual skills and knowledge, or tasks that have a better anticipated cost-benefit ratio than others [17].

In sum, CW has the potential to involve a high degree of flexibility enabled by digital technologies, even in comparison with more widespread forms of flexible working, such as flex-time, part-time work, or telework [55, 56]. Thus, the theoretical considerations and the state-of-the-art suggest that flex-time, flex-place, and task autonomy in CW allow for very flexible adjustments of obligations in the different life spheres and should be connected to lower levels of WLC. Moreover, a unique feature of CW is that crowdworkers have a high degree of control over using or not using flexibility potentials. As previous research suggests that it is the control over one’s flexible working that is the key to lower WLC experiences [51], flexible working in CW should be all the more beneficial.

Hypothesis 1a-c: Crowdworkers who work flexibly have lower levels of WLC as compared to crowdworkers who do not work flexibly. This is the case for a) flex-time, b) flex-place, and c) task autonomy.

2.3 Flexible working, work-life conflict, and well-being

Possible risks of CW received at least as much scientific and public attention as its benefits [11]. Although CW has been discussed as a chance for workers with health issues [57], little is known on the possible consequences of CW for health and well-being. CW involves precarious working conditions such as employment and income insecurity [16], and lack of labor protection [18]. Those conditions have been associated with impaired health in other forms of employment [58, 59], and in entrepreneurship [60], and though there is little knowledge on CW in particular, these similarities may indicate comparable health risks of CW. Research on other forms of technology-enabled work suggests possible risks for health and well-being as well; examples are isolation and lack of support when working from home [61 –64], technology-driven work intensification [65], or poor ergonomics in mobile work environments [66]. As CW is completely internet-based and carried out on computers or smartphones, the risks of digitalized work and working at home are relevant for CW as well. Moreover, irregular and unsocial working hours, which seem to be very common in CW [67], are associated with impaired health and well-being as well [68].

Flexible working, however, has also been suggested to be a job-related resource for higher individual well-being, and better mental and physical health [47 , 69–72]. Scholars still try to disentangle the relationship between flexible working and indicators of well-being, referring to important mechanisms being its benefits for increased control and its potential as a buffer of job demands [72]. Another possible explanation is that WLC mediates the relationship between flexible working and well-being [72]. In other words, whether flexible working can serve as a resource for well-being may also depend on whether WLC is perceived when using flexible working. Based on the assumptions posed in stress theories [73, 74], WLC may be experienced as a stressor that threatens a person’s well-being [75, 76], and in line with the assumptions on chronic strain, WLC can be understood as relatively enduring strain that individuals face in their daily lives [77]. Manifold empirical studies confirm the negative effects of WLC on various outcomes of health and well-being (for overviews, see [78 –80]). Thus, if flexible working in CW is associated with blurring of boundaries and consequently, the experience of WLC, then the experienced strain should be related to impaired well-being. In contrast, whenever flex-time, flex-place, and task autonomy in CW are associated with lower WLC, crowdworkers should experience better well-being. That mediation assumption has been tested for flexible working in other regular or irregular forms of employment [19 –21], but not for CW. In sum, it can be assumed that flexible working is not only directly relevant for well-being but that the relationship is partly mediated by WLC perceptions.

Hypothesis 3: Crowdworkers who work flexibly experience higher well-being as compared to crowdworkers who do not work flexibly.

Hypothesis 4: The relationship between flexible working in crowdwork and well-being is partly mediated by WLC.

3 Data and methods

3.1 Data collection

This study is based on cross-sectional data from an interdisciplinary CW survey, collected on four German CW platforms within the collaborative research program “Digital Future”, funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia. This report follows the STROBE guidelines for cross-sectional studies provided by the EQUATOR Network. The study was reviewed and approved by the Ethics Committee of Bielefeld University (ubi24-08-2018). The research was conducted in full compliance with the ethical principles of research involving human beings. Participants were informed about the purpose of the study and the use of the data (anonymity and voluntariness of participation) in accordance with the national legislation and the institutional requirements. Informed consent was obtained for all participants.

In the first step, 58 German-speaking CW platforms were identified and systematized based on an existing cluster analysis of the German CW market [81]. In a second step, platforms were filtered (selection criteria: head office in Germany, registered crowdworkers from Germany, activity), resulting in a selection of 17 platforms. The most established platform was selected for each of the four platform types: marketplace, microtask, mobile CW, and testing based on the categorization by Leimeister et al. [81]. Using an online survey tool (Unipark), the request for participation in the survey was offered as a regular task on the platform from November to December 2018 (marketplace, microtask, and mobile CW) and May to June 2019 (testing). A total of 812 completed questionnaires were collected. Of these, 9 persons were excluded from the dataset due to a control question (for further documentation of methods and contents of the survey, see pages 22 and 82). Since we focus on the labor aspect of CW [11], those who are mainly unemployed or mainly in education were excluded from the sample. After reduction due to missing values, the analyses are based on a final sample of 470 crowdworkers (marketplace: 128; mobile CW: 126; microtask: 118; testing: 98). The sample consists of 188 female and 282 male crowdworkers aged 18 to 70 years (mean age: 39 years). A total of 355 crowdworkers had upper secondary education, 104 had lower secondary education, and 11 had primary education.

3.2 Variables

WLC: We measure WLC based on the validated work-family conflict scale developed by Carlson, Kacmar, and Williams [83]. We used six items to measure two subscales of work-life conflict, slightly adapting the wording to address that private life does not solely consist of family obligations (time-based WLC: e.g., ‘My work keeps me from my private activities more than I would like’; strain-based WLC: e.g., ‘I am often so emotionally drained when I get home from work that it prevents me from contributing to my private life’), ranging from 1 (never) to 5 (very often). To assess the overall WLC measure, all six items were totaled and averaged. The internal consistency of the WLC scale was very good; the Cronbach’s alpha of 0.89 values exceeded the conventional level of acceptance.

Well-being: Two indicators for individual well-being were used: somatic health symptoms and life satisfaction. Somatic health symptoms were measured using the Somatic Symptoms Scale (SSS-8), an abbreviated 8-item version of the PHQ-15 questionnaire [84], which is a widely used self-report measure for somatic symptom burden. Different aspects of somatic health (e.g., back pain, trouble sleeping, headaches) were each assessed on a 5-point Likert scale ranging from (1) not at all, to (5) very strong. All items were added to a sum index and divided by the number of items (Cronbach’s alpha = 0.806), with higher values indicating greater somatic health symptoms. Life satisfaction was measured using the 5-item German version of the Satisfaction with Life Scale (SWLS; [85]). All items were assessed on a 5-point Likert scale ranging from (1) does not apply, to (5) applies completely. Items were added to a sum index divided by the number of items (Cronbach’s alpha = 0.872), with higher values indicating higher life satisfaction.

Flexible working in CW: Flex-time was measured as working flexibly at different times in contrast to fixed times of the day and/or week (1 = yes; 0 = no). Flex-place was measured as working predominantly from different places, including working from home, as compared to working only at a fixed workplace (1 = yes; 0 = no). Thus, flex-time and flex-place were measured using single-item measures comparable to previous studies on flexible working (e.g., [4, 30]; see also meta-analytic overview, [69, 86]). Task autonomy was measured asking whether respondents can completely decide which tasks are done; assessed on a 5-point scale ranging from ‘does not apply at all’ to ‘applies completely’ and then dichotomized to ‘high task autonomy’ (= 1, only the highest scale value) and ‘no/low task autonomy’ (= 0, all other values).

Control variables: To account for differences in working conditions in CW, we controlled for demands in CW based on a 3-item measure of work intensity and workload (Cronbach’s Alpha = 0.733). We included working hours in CW as well as working hours in other jobs. Moreover, we considered the use of only one platform vs. multiple platforms (0 = use of only one platform; 1 = multi-user) and CW experience (in years). Crowdworkers are heterogeneous in their motivations, intentions, and characteristics (87; 17; 3). Thus, we controlled for gender (1 = female, 0 = male), age in years, age of the youngest child in years, being in a partnership (1 = yes, 0 = no), and educational level (0 = primary education/lower secondary education; 1 = upper secondary education [Abitur; entrance qualification for a university of applied sciences].

3.3 Analysis strategy

In addition to simple descriptive analyses (means, standard deviations, min, max) for all study variables (see Table 1), we calculated pairwise correlations of sociodemographic and CW variables with the use of flex-time, flex-place, and task autonomy to assess differences in the use of flexible working (see Table 2). To test the hypotheses, structural equation models with maximum likelihood estimations and robust standard errors were applied. In addition, direct, indirect, and total effects were estimated to test the mediation assumptions (88). We analyzed whether the use of flexible working in CW is associated with lower levels of WLC and higher well-being by estimating the direct effects of flex-time, flex-place, and task autonomy on WLC, somatic health symptoms, and life satisfaction including all control variables (Hypothesis 1 and Hypothesis 2). Moreover, the WLC mediation hypothesis (Hypothesis 3) was tested by estimating the indirect effects of flexible working in CW on somatic health symptoms and life satisfaction.

Table 1
Means, standard deviations and range of analysis variables

Mean SD Min Max

Work-life conflict 2.53 0.94 1 5

Somatic health 1.71 0.61 1 4.9

Life satisfaction 3.54 0.72 1.2 5

Flexible working

Flex-time (vs. no flex-time) 0.52 0.50 0 1

Flex-place (vs. no flex-place) 0.27 0.45 0 1

Task autonomy high (vs. no/low autonomy) 0.74 0.44 0 1

Working hours in crowdwork 9.47 11.2 1 60

Working hours in other jobs 37.2 12.6 1 80

Demands in crowdwork 2.04 0.86 1 5

Crowdwork experience (in years) 3.34 2.91 0 18.2

Multiple platforms user (vs. one platform) 0.76 0.43 0 1

Female (vs. male) 0.40 0.49 0 1

Age (years) 38.9 10.8 18 70

Age of the youngest child (years) 4.63 8.65 0 40

Being in a partnership (vs. no partnership) 0.61 0.48 0 1

Upper secondary education (vs. primary/ 0.76 0.43 0 1

lower secondary education)

	Mean	SD	Min	Max
Work-life conflict	2.53	0.94	1	5
Somatic health	1.71	0.61	1	4.9
Life satisfaction	3.54	0.72	1.2	5
Flexible working
Flex-time (vs. no flex-time)	0.52	0.50	0	1
Flex-place (vs. no flex-place)	0.27	0.45	0	1
Task autonomy high (vs. no/low autonomy)	0.74	0.44	0	1
Working hours in crowdwork	9.47	11.2	1	60
Working hours in other jobs	37.2	12.6	1	80
Demands in crowdwork	2.04	0.86	1	5
Crowdwork experience (in years)	3.34	2.91	0	18.2
Multiple platforms user (vs. one platform)	0.76	0.43	0	1
Female (vs. male)	0.40	0.49	0	1
Age (years)	38.9	10.8	18	70
Age of the youngest child (years)	4.63	8.65	0	40
Being in a partnership (vs. no partnership)	0.61	0.48	0	1
Upper secondary education (vs. primary/	0.76	0.43	0	1
lower secondary education)

Note: N = 470.

Table 2

Correlations of flexible working with analysis variables

	Flex-time	Flex-place	Task autonomy
Work-life conflict	–0.107*	0.070*	–0.153*
Somatic health	–0.057*	–0.007	–0.198*
Life satisfaction	0.010	0.071*	0.115*
Working hours in crowdwork	0.013	–0.220*	0.128*
Working hours in other jobs	–0.080*	0.061*	0.046*
Demands in crowdwork	–0.022	–0.033*	0.062*
Crowdwork experience (in years)	0.031	–0.144*	–0.020
Multiple platforms user (vs. one platform)	–0.075*	0.148*	–0.035*
Female (vs. male)	0.029	–0.102*	0.044*
Age (years)	–0.002	–0.180*	0.162*
Age of youngest child (years)	0.033*	–0.089*	0.084*
Being in a partnership (vs. no partnership)	–0.094*	–0.008	–0.091*
Upper secondary education (vs. primary/	–0.010	–0.071*	–0.015
lower secondary education)

Note: Pearson correlation coefficients; * p < 0.05; N = 470.

All analysis steps were additionally estimated for the time-based and strain-based WLC subscales, but not presented in detail as they are very similar for the subscales (available on request).

The robustness of the results and possible confounding factors were tested in further analyses; however, the following variables did not affect WLC or well-being significantly and did not change the conclusions, and thus, we decided to exclude them from the final analyses to reduce the complexity of the models. Platform type; occupation of the crowdworkers; additional variables that might be relevant for the flexibility involved in CW, such as the time of the day (morning, evening, or night) and the number of tasks per hour; gross earnings from CW and proportion of CW earnings of overall labor earnings to consider the relevance of CW in relation to other paid work. We further tested our results for group differences regarding gender, parenthood, age, qualification groups, and platform types by estimating interaction models, but found no significant differences.

4 Results

The descriptive distributions (see Table 1) reveal that German crowdworkers experience similar levels of WLC as do employees who have access to flexible workplace arrangements (e.g., 5). Looking at the prevalence of flexible working in CW, flex-time is used by 52 percent and flex-place by 27 percent of the surveyed crowdworkers. Task autonomy is high for 74 percent of the participants. The correlations (see Table 2) additionally indicate that flex-time is used more often by crowdworkers without a partner and children, but there is no correlation with gender, age, or educational level. Flex-place is used by men, younger crowdworkers, and parents. In comparison, task autonomy is higher for women, older crowdworkers, and those without a partner.

As hypothesized, WLC is negatively correlated to flex-time and task autonomy, and this is also the case for somatic health symptoms. Surprisingly, the correlations suggest a positive association between WLC and flex-place. Moreover, life satisfaction is positively correlated to flex-place and task autonomy.

Table 3 shows the results of the structural equation model and displays the effects of flex-time, flex-place, and task autonomy on WLC, somatic health symptoms, and life satisfaction. Supporting hypotheses 1a and 1c, the model predicts statistically significant negative effects of flex-time and task autonomy on WLC. Thus, crowdworkers who work flexibly in time experience lower levels of WLC as compared to those crowdworkers who do not use flex-time, and so do crowdworkers with high task autonomy as compared to those with low or no task autonomy. Working flexibly in place, however, is not significantly associated with WLC, contradicting hypothesis 1b. Regarding well-being, only the coefficient for high task autonomy is statistically significant. High task autonomy in CW is related to fewer somatic health symptoms and greater life satisfaction, only partly supporting hypothesis 2. Moreover, WLC is significantly associated with more somatic health symptoms, and lower life satisfaction.

Table 3
Structural equations models for work-life conflict, somatic health symptoms, and life satisfaction

Work-life conflict Somatic health Life satisfaction

symptoms

Flexible working

Flex-time (vs. no flex-time) –0.155⁺ (0.080) –0.042 (0.051) 0.020 (0.061)

Flex-place (vs. no flex-place) 0.048 (0.093) 0.018 (0.062) 0.064 (0.073)

Task autonomy high (vs. no/low autonomy) –0.214^* (0.087) –0.193^ (0.068) 0.132⁺ (0.073)

Work-life conflict / / 0.199^* (0.035) –0.185^*** (0.039)

Other crowdwork characteristics and controls

Working hours in crowdwork –0.013^ (0.005) 0.008^ (0.003) –0.010^ (0.003)

Working hours in other jobs 0.015^* (0.003) –0.006^* (0.002) 0.012^* (0.003)

Demands in crowdwork 0.312^* (0.050) 0.054 (0.041) –0.015 (0.042)

Crowdwork experience (in years) –0.007 (0.015) –0.001 (0.009) 0.013 (0.012)

Multiple platforms user (vs. one platform) –0.010 (0.102) –0.031 (0.060) 0.097 (0.076)

Female (vs. male) 0.194^* (0.085) 0.161^ (0.057) –0.056 (0.067)

Age (years) –0.007 (0.005) –0.003 (0.003) –0.005 (0.004)

Having children (vs. no children) –0.001 (0.084) –0.017 (0.053) 0.181^ (0.063)

Being in a partnership (vs. no partnership) –0.001 (0.006) –0.001 (0.003) 0.013^ (0.004)

Upper secondary education (vs. primary/lower secondary education) 0.056 (0.090) –0.082 (0.056) 0.103 (0.068)

Constant 2.513^* (0.234) 1.664^* (0.176) 3.383^* (0.203)

	Work-life conflict	Somatic health	Life satisfaction
Flexible working
Flex-time (vs. no flex-time)	–0.155⁺	(0.080)	–0.042	(0.051)	0.020	(0.061)
Flex-place (vs. no flex-place)	0.048	(0.093)	0.018	(0.062)	0.064	(0.073)
Task autonomy high (vs. no/low autonomy)	–0.214^*	(0.087)	–0.193^**	(0.068)	0.132⁺	(0.073)
Work-life conflict	/	/	0.199^***	(0.035)	–0.185^***	(0.039)
Other crowdwork characteristics and controls
Working hours in crowdwork	–0.013^**	(0.005)	0.008^**	(0.003)	–0.010^**	(0.003)
Working hours in other jobs	0.015^***	(0.003)	–0.006^*	(0.002)	0.012^***	(0.003)
Demands in crowdwork	0.312^***	(0.050)	0.054	(0.041)	–0.015	(0.042)
Crowdwork experience (in years)	–0.007	(0.015)	–0.001	(0.009)	0.013	(0.012)
Multiple platforms user (vs. one platform)	–0.010	(0.102)	–0.031	(0.060)	0.097	(0.076)
Female (vs. male)	0.194^*	(0.085)	0.161^**	(0.057)	–0.056	(0.067)
Age (years)	–0.007	(0.005)	–0.003	(0.003)	–0.005	(0.004)
Having children (vs. no children)	–0.001	(0.084)	–0.017	(0.053)	0.181^**	(0.063)
Being in a partnership (vs. no partnership)	–0.001	(0.006)	–0.001	(0.003)	0.013^**	(0.004)
Upper secondary education (vs. primary/lower secondary education)	0.056	(0.090)	–0.082	(0.056)	0.103	(0.068)
Constant	2.513^***	(0.234)	1.664^***	(0.176)	3.383^***	(0.203)

Notes: + < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001, Standard error in parentheses, N = 470; Fit statistics: SRMR 0.017, Coefficient of determination 0.354.

To test whether and to what degree the relationships between flexible working in CW and indicators of well-being are mediated by WLC (hypothesis 4), direct, indirect, and total effects are decomposed from the estimations. Table 4 shows that in addition to its direct effect on the two indicators for well-being, task autonomy has a statistically significant indirect effect on somatic health symptoms and life satisfaction. Thus, the relations between high task autonomy and more somatic health symptoms and higher life satisfaction are partly explained by the perception of lower WLC. Moreover, the effect of decomposition reveals that flex-time has an indirect effect on both somatic health symptoms and life satisfaction via the experience of lower WLC. The latter, however, is only significant on the 10% significance level. In sum, we find partial support for the mediation hypothesis 4.

Table 4

Direct, indirect, and total effects of flexible working on work-life conflict, somatic health symptoms, and life satisfaction

	Work-life conflict		Somatic health		Life satisfaction
			symptoms
Direct effects
Flex-time	–0.155^*	(0.080)	–0.042	(0.055)	0.020	(0.061)
Flex-place	0.048	(0.093)	0.018	(0.065)	0.064	(0.073)
Autonomy	–0.214^*	(0.087)	–0.193^**	(0.068)	0.132⁺	(0.073)
Work-life conflict	/	/	0.199***	(0.045)	–0.185***	(0.039)
Indirect effects
Flex-time	/	/	–0.031+	(0.017)	0.029+	(0.016)
Flex-place	/	/	0.010	(0.019)	–0.009	(0.017)
Autonomy	/	/	0.043*	(0.018)	0.040*	(0.018)
Total effects
Flextime	–0.155*	(0.080)	–0.073	(0.035)	0.049	(0.064)
Flexplace	0.048	(0.093)	0.027	(0.064)	0.055	(0.074)
Autonomy	–0.214*	(0.087)	–0.235**	(0.070)	0.172*	(0.073)
Work-life conflict	/	/	0.199***	(0.035)	–0.185	(0.039)
Controls included	yes		yes		yes

Notes: + < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001, Standard error in parentheses, N = 470.

5 Discussion

CW is suggested to provide great flexibility by allowing crowdworkers to work from anywhere at any time while having high autonomy in coordinating work tasks (e.g., [2; 55]). It promises to be an easily accessible possibility of earning money without being tied to fixed schedules and highly restricted work environments of standard employment relations. By making the flexible adjustment of work activities to individual preferences and demands easier, it may help to meet the challenge of balancing work and private life. To provide insights into the question of whether crowdworkers are truly able to benefit from these flexibility options, this research investigated WLC experiences when using flexible working in CW, as well as implications for the well-being of crowdworkers.

The empirical results showed that every other crowdworker works flexibly in time, but only one in four crowdworkers works flexibly in place. Task autonomy, however, is high for about three-quarters of the crowdworkers. Those crowdworkers who use flex-time and task autonomy indeed have fewer WLC as compared to those who do not, but that is not the case for using flex-place. Having high task autonomy is also related to less somatic health symptoms, and higher life satisfaction, but temporal and location flexibility in CW show no direct relationship with well-being. In addition to its direct effects, task autonomy is also indirectly related to less somatic health symptoms and higher life satisfaction partly mediated by lower levels of WLC. Moreover, though flex-time is not directly correlated with the indicators for well-being, it does have an indirect mediated effect.

The results of this study support previous assumptions on flexible working in the form of flex-time, flex-place, and high task autonomy being a typical part of CW. The use of these flexibility options, however, is not as widespread among crowdworkers as much as CW is suggested to offer as a universal part of its nature [18]. Though flexible working in CW is technically available for everyone, future research should aim to investigate more critically the reasons for crowdworkers not making use of flexibility options. Possible explanations include being tied to other work or private obligations that restrict CW to being done at fixed places or within limited time frames after all, which makes the further use of flexibility options more difficult.

The empirical findings need to be discussed with regard to several other scientific and social debates. First, insights into flexible working in general are provided by showing that different forms of flexible working also play a role in CW as a form of digital labor. Moreover, the findings support the assumption that the relationship between flexible working and health and well-being is partly mediated by WLC [19 –21] by showing that this mechanism seems to apply to CW as a new form of digital labor as well. To disentangle the risks and benefits of technology-enabled work, further research is needed to directly compare flexible working in CW, or other forms of digital labor, to flexible working in more traditional forms of employment. The worldwide COVID-19 crisis has recently drawn attention to a need for rethinking traditional ways of working at fixed locations and in fixed time schedules. Against this background, the evolution of new forms of digitally enabled work has gained momentum even more than it already had in the last decade [14, 15].

Second, the findings add knowledge to research on the work-life interface by showing that CW can be used as a way of earning money outside the boundaries of regular employment relations and without being tied to fixed schedules and highly restricted work environments. This may be especially beneficial for those groups on the labor market that have particularly high flexibility needs, such as parents and especially mothers [89]. Whereas we indeed found small but visible differences in the use of flex-time and flex-place in CW, we did not find significant differences between women and men or parents and non-parents in the association of flexible working with work-life conflict. Thus, we did not find evidence that those who have higher flexibility needs also benefit more strongly from flexible working in CW than other crowdworkers do. On one side, this can be interpreted as a positive finding because all crowdworkers seem to profit similarly from working flexibly. On the other side, this also means that CW is not the answer to the work-life issues of those groups with special flexibility needs after all. Not having to go to a specific place at a specific time to earn money makes paid work accessible for other disadvantaged labor market groups, such as disabled persons [57]. This cannot be investigated within this study but should be addressed in future research to shed more light on the question for whom and under which conditions flexible working in CW is beneficial for balancing work and private life, and individual well-being.

Besides the discussed unanswered questions, there are some limitations to the data that need to be addressed in future research. The most important drawback of the current research is related to the use of cross-sectional data and self-assessments. Therefore, we demonstrate the association of flexible work in CW with WLC and well-being, but we cannot clarify whether there are mechanisms of self-selection of individuals with difficulties with work-life balance or with lower well-being in doing CW. For example, finding no significant relation of flex-place with WLC might be because there is simply no relationship, but it may also be explained by the non-use being a consequence of a prior experience that working flexibly in place does not help avoiding work-life conflict. Thus, longitudinal data is needed to clarify causal uncertainties in future research. Moreover, since there is no overall registration of crowdworkers in Germany, it is not possible to make reliable statements about the representativeness of the sample regarding the CW population in Germany. Although we did not find important differences between the analyzed platforms, opportunities for and consequences of flexible working may still vary significantly on other platforms. Finally, as we focused on CW on external online CW platforms, we encourage future research to investigate CW on internal platforms that are used within companies. Internal CW may be very similar in the way work is organized and distributed; however, opportunities and risks for work-life conflict and well-being may be different because those platforms are embedded in a specific organizational context regarding structures, policies, or cultures in the work organization.

6 Conclusion

In conclusion, this study supports that CW is a new form of platform-based online labor that offers a high potential for working highly autonomous and flexibly in time and place. In turn, flexible working makes integrating the responsibilities from paid work and private life easier. The use of flex-time and high autonomy in particular are associated with lower levels of work-life conflict and enhanced well-being. Certainly, it must be called attention to that the benefits of this flexibility are not universally included in CW. Against the background of ongoing digitalization processes in the world of work and an increasing demand for flexibility just as much on the part of companies as of workers, CW remains a promising research object to understand how digital work has to be shaped to facilitate work-life balance.

Footnotes

Acknowledgments

The authors have no acknowledgments.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

This research was funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia within the research programme “Digital Future.”

References

Kenney

, Zysman

. The rise of the platform economy. Issues in Science and Technology. 2016;32(3):61–9.

Lehdonvirta

. Flexibility in the gig economy: managing time on three online piecework platforms. New Technology, Work and Employment. 2018;33(1):13–29.

Watson

, Kistler

, Graham

, Sinclair

. Looking at the Gig Picture: Defining Gig Work and Explaining Profile Differences in Gig Workers’ Job Demands and Resources. Group & Organization Management. 2021:105960112199654.

Hill

, Erickson

, Holmes

, Ferris

. Workplace flexibility, work hours, and work-life conflict: finding an extra day or two. J Fam Psychol. 2010;24(3):349–58.

Abendroth

A-K

, Reimann

. Telework and Work–Family Conflictacross Workplaces: Investigating the Implications ofWork–Family-Supportive and High-Demand Workplace Cultures. In: Lee Blair S, Obradović J, editors. The Work-FamilyInterface: Spillover, Complications, and Challenges. Bingley: Emerald Publishing Limited; 2018. p. 323–48 (ContemporaryPerspectives in Family Research; vol. 13).

Bal

, Izak

. Paradigms of Flexibility: A Systematic Review of Research on Workplace Flexibility. European Management Review 2020.

Felstead

, Henseke

. Assessing the growth of remote working and its consequences for effort, well-being and work-life balance. New Tech Work Empl. 2017;32(3):195–212.

Greenhaus

, Beutell

. Sources of Conflict Between Work and Family Roles. Acad Manage Rev. 1985;10(1):76–88.

Kahn

, Wolfe

, Quinn

, Snoek

. Organizational stress: Studies in role conflict and ambiguity. New York: Wiley; 1964.

10.

Estellés-Arolas

, González-Ladrón-de-Guevara

. Towards an integrated crowdsourcing definition. J Inf Sci. 2012;38(2):189–200.

11.

Schulte

, Schlicher

, Maier

. Working everywhere and every time?—Chances and risks in crowdworking and crowdsourcing work design. Gr Interakt Org. 2020;51(1):59–69.

12.

Serfling

. Crowdworking Monitor No. 2. Hochschule Rhein-Waal; 2019.

13.

Huws

, Spencer

, Syrdal

. Online, on call: The spread of digitally organised just-in-time working and its implications for standard employment models. New Technology, Work and Employment. 2018;33(2):113–29.

14.

Durward

, Blohm

, Leimeister

. Crowd Work. Bus Inf Syst Eng. 2016;58(4):281–6.

15.

Spurk

, Straub

. Flexible employment relationships and careers in times of the COVID-19 pandemic. J Vocat Behav. 2020;119, 103435.

16.

Berg

. Income security in the on-demand economy: Findings and policy lessons from survey of crowdworkers. Comparative Labor Law & Policy Journal. 2016;37(3):543–76.

17.

Howcroft

, Bergvall-Kåreborn

. A Typology of Crowdwork Platforms. Work Employ Soc. 2019;33(1):21–38.

18.

De Stefano

. The rise of the just-in-time workforce: On-demand work, crowdwork, and labor protection in the gig-economy. Comp Labor Law J. 2016;37(3):471–504.

19.

Geurts

, Rutte

, Peeters

. Antecedents and consequences of work–home interference among medical residents. Soc Sci Med. 1999;48(9):1135–48.

20.

Wirtz

, Nachreiner

. The effects of extended working hours on health and social well-being–a comparative analysis of four independent samples. Chronobiol Int. 2010;27(5):1124–34.

21.

Casey

, Grzywacz

. Employee health and well-being: The role offlexibility and work-family balance. The Psychologist-Manager Journal. 2008;11(1):31–47.

22.

Giard

, Hemsen

, Hesse

, Löken

, Nouri

, Reddehase

, et al. Technical Report. Interdisziplinäre Befragung von Crowdworkern. Bielefeld: Forschungsschwerpunkt Digitale Zukunft (Universität Bielefeld / Universität Paderborn): Universität Bielefeld/Universität Paderborn (Forschungsschwerpunkt Digitale Zukunft); 2019.

23.

Frone

, Yardley

, Markel

. Developing and Testing an Integrative Model of the Work–Family Interface. J Vocat Behav. 1997;50(2):145–67.

24.

Voydanoff

. Linkages Between the Work-family Interface and Work, Family, and Individual Outcomes. J Fam Issues. 2002;23(1):138–64.

25.

Beham

, Drobnič

. Satisfaction with work-family balance among German office workers. J Manage Psychol. 2010;25(6):669–89.

26.

Gallie

, Russell

. Work-Family Conflict and Working Conditions in Western Europe. Soc Indic Res. 2009;93(3):445–67.

27.

Reimann

, Diewald

, Pausch

. Work-family conflict in Germany: Psychological contracts as part of employment relationships in work-family research. Psychosociological Issues in Human Resource Management. 2017;5(2):127–53.

28.

Schieman

, Glavin

. Trouble at the Border?: Gender, Flexibility at Work, and the Work-Home Interface. Social Problems. 2008;55(4):590–611.

29.

Hill

, Grzywacz

, Allen

, Blanchard

, Matz-Costa

, Shulkin

, et al. Defining and conceptualizing workplace flexibility. Community, Work & Family. 2008;11(2):149–63.

30.

Shockley

, Allen

. When flexibility helps: Another look at the availability of flexible work arrangements and work–family conflict. J Vocat Behav. 2007;71(3):479–93.

31.

Kossek

, Michel

. Flexible work schedules. In: Zedeck S, editor. APA handbook of industrial and organizational psychology, Vol. 1: Building and developing the organization. Washington: American Psychological Association; 2011. p. 535–72.

32.

Baillien

, Cuyper

N de

, Witte

H De

. Job autonomy and workload as antecedents of workplace bullying: A two-wave test of Karasek’s Job Demand Control Model for targets and perpetrators. J Occup Organ Psych. 2011;84(1):191–208.

33.

Liu

, Spector

, Jex

. The relation of job control with job strains: A comparison of multiple data sources. J Occup Organ Psych. 2005;78(3):325–36.

34.

Byron

. A meta-analytic review of work–family conflict and its antecedents. J Vocat Behav. 2005;67(2):169–98.

35.

Nijp

, Beckers

DGJ

, Geurts

SAE

, Tucker

, Kompier

MAJ

. Systematic review on the association between employee worktime control and work-non-work balance, health and well-being, and job-related outcomes. Scand J Work Env Hea. 2012;38(4):299–313.

36.

Golden

, Veiga

, Simsek

. Telecommuting’s differential impact on work-family conflict: is there no place like home? J Appl Psychol. 2006;91(6):1340–50.

37.

Michel

, Kotrba

, Mitchelson

, Clark

, Baltes

. Antecedents of work-family conflict: A meta-analytic review. J Organ Behav. 2011;32(5):689–725.

38.

Schieman

, Young

. Are communications about work outside regular working hours associated with work-to-family conflict, psychological distress and sleep problems? Work Stress. 2013;27(3):244–61.

39.

Kossek

, Lautsch

, Eaton

. Telecommuting, control, and boundary management: Correlates of policy use and practice, job control, and work–family effectiveness. J Vocat Behav. 2006;68(2):347–67.

40.

Ashforth

, Kreiner

, Fugate

. All in a Day’S Work: Boundaries and Micro Role Transitions. Acad Manage Rev. 2000;25(3):472–91.

41.

Allen

, Golden

, Shockley

. How Effective Is Telecommuting? Assessing the Status of Our Scientific Findings. Psychol Sci Publ Int. 2015;16(2):40–68.

42.

Jostell

, Hemlin

. After hours teleworking and boundary management: Effects on work-family conflict. Work. 2018;60(3):475–83.

43.

Boswell

, Olson-Buchanan

. The Use of Communication Technologies After Hours: The Role of Work Attitudes and Work-Life Conflict. J Manage. 2007;33(4):592–610.

44.

Olson-Buchanan

, Boswell

. Blurring boundaries: Correlates of integration and segmentation between work and nonwork. J Vocat Behav. 2006;68(3):432–45.

45.

Anderson

, Coffey

, Byerly

. Formal Organizational Initiatives and Informal Workplace Practices: Links to Work-Family Conflict and Job-Related Outcomes. J Manage. 2002;28(6):787–810.

46.

Mesmer-Magnus

, Viswesvaran

. How family-friendly work environments affect work/family conflict: A meta-analytic examination. J Labor Res. 2006;27(4):555–74.

47.

Thomas

, Ganster

. Impact of family-supportive work variables on work-family conflict and strain: A control perspective. J Appl Psychol. 1995;80(1):6–15.

48.

Higgins

, Duxbury

, Julien

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

49.

Clark

. Work/Family Border Theory: A New Theory of Work/Family Balance. Hum Relat. 2000;53(6):747–70.

50.

Kossek

. Managing work-life boundaries in the digital age. Organ Dyn. 2016;45(3):258–70.

51.

Beutell

. Work schedule, work schedule control and satisfaction in relation to work-family conflict, work-family synergy, and domain satisfaction. Career Dev Int. 2010;15(5):501–18.

52.

Felstead

, Jewson

, Phizacklea

, Walters

. The option to work at home: another privilege for the favoured few? New Tech Work Empl. 2002;17(3):204–23.

53.

Lott

, Abendroth

A-K

. The non-use of telework in an ideal worker culture: why women perceive more cultural barriers. Community, Work & Family. 2020;54(1):1–19.

54.

Pesole

, Urzí

Brancati MC

, Fernández-Macías

, Biagi

, González Vázquez

, editors. Platform Workers in Europe [EUR 29275 EN]. Luxembourg: Publications Office of the European Union; 2018.

55.

Wood

, Graham

, Lehdonvirta

, Hjorth

. Good Gig, Bad Gig:Autonomy and Algorithmic Control in the Global Gig Economy. Work Employ Soc. 2019;33(1):56–75.

56.

Lehdonvirta

. Algorithms that divide and unite: delocalisation, identity and collective action in ‘Microwork’. In: Flecker J, editor. Space, place and global digital work. London: Palgrave Macmillan; 2016. p. 53–80.

57.

Zyskowski

, Morris

, Bigham

, Gray

, Kane

Accessible Crowdwork?

In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing – CSCW ’15. New York, New York, USA: ACM Press; 2015. p. 1682–93.

58.

Quinlan

, Mayhew

, Bohle

. The global expansion of precarious employment, work disorganization, and consequences for occupational health: a review of recent research. Int J Health Serv. 2001;31(2):335–414.

59.

Sverke

, Hellgren

. The nature of job insecurity: Understanding employment uncertainty on the brink of a new millennium. Applied Psychology: An International Review. 2002;51(1):23–42.

60.

Lek

, Vendrig

, Schaafsma

. What are psychosocial risk factors for entrepreneurs to become unfit for work? A qualitative exploration. Work. 2020;67(2):499–506.

61.

Collins

, Hislop

, Cartwright

. Social support in the workplace between teleworkers, office-based colleagues and supervisors. New Tech Work Empl. 2016;31(2):161–75.

62.

Cooper

, Kurland

. Telecommuting, professional isolation, and employee development in public and private organizations. J Organ Behav. 2002;23(4):511–32.

63.

Tavares

. Telework and health effects review. IJH. 2017;3(2):30.

64.

McNaughton

, Rackensperger

, Dorn

, Wilson

. “Home is at work and work is at home”: telework and individuals who use augmentative and alternative communication. Work. 2014;48(1):117–26.

65.

Meyer

S-C

, Tisch

, Hünefeld

. Arbeitsintensivierung und Handlungsspielraum in digitalisierten Arbeitswelten – Herausforderung für das Wohlbefinden von Beschäftigten? IndBez. 2019;26(2-2019):207–31.

66.

Long

, Richter

. The pitfalls of the traditional office ergonomics model in the current mobile work environment: Is visual ergonomics health literacy the remedy? Work. 2019;63(3):447–56.

67.

Berg

, Furrer

, Harmon

, Rani

, Silberman

. Digital labour platforms and the future of work. Towards Decent Work in the Online World. Geneva; 2018. Report. International Labour Office.

68.

Costa

, Sartori

, Akerstedt

. Influence of flexibility and variability of working hours on health and well-being. Chronobiol Int. 2006;23(6):1125–37.

69.

Shifrin

, Michel

. Flexible work arrangements and employee health: A meta-analytic review. Work Stress. 2021:1–26.

70.

Grzywacz

, Carlson

, Shulkin

. Schedule flexibility and stress: Linking formal flexible arrangements and perceived flexibility to employee health. Community, Work & Family. 2008;11(2):199–214.

71.

Jacob

, Bond

, Galinsky

, Hill

. Six critical ingredients in creating an effective workplace. The Psychologist-Manager Journal. 2008;11(1):141–61.

72.

Butler

, Grzywacz

, Ettner

, Liu

. Workplace flexibility, self-reported health, and health care utilization. Work Stress. 2009;23(1):45–59.

73.

Lazarus

, Launier

. Stress-Related Transactions between Person and Environment. In: Pervin LA, Lewis M, editors. Perspectives in Interactional Psychology. Boston, MA: Springer US; 1978. p. 287–327.

74.

Thoits

. Stress, Coping and Social Support Processes: Where Are We? What Next? J Health Soc Behav. 1995;31(Extra issue):53–79. Available from: URL: https://www-jstor-org.web.bisu.edu.cn/stable/2626957?seq=1#page_scan_tab_contents

75.

Greenhaus

, Allen

, Spector

. Health Consequences of Work–Family Conflict: The Dark Side of the Work–Family Interface. In: Perrewe PL, editor. Employee health, coping and methodologies. Bingley: Emerald Group Publishing Limited; 2009. p. 61–98 (Research in occupational stress and wellbeing; v. 5).

76.

Mauno

, Kinnunen

, Ruokolainen

. Exploring work- and organization-based resources as moderators between work–family conflict, well-being, and job attitudes. Work Stress. 2006;20(3):210–33.

77.

Pearlin

. The Sociological Study of Stress. J Health Soc Behav. 1989;30(3):241.

78.

Allen

, Martin

. The work-family interface: A retrospective look at 20 years of research in JOHP. J Occup Health Psych. 2017;22(3):259–72.

79.

Allen

, Herst

, Bruck

, Sutton

. Consequences associated with work-to-family conflict: A review and agenda for future research. J Occup Health Psych. 2000;5(2):278–308.

80.

Nohe

, Meier

, Sonntag

, Michel

. The chicken or the egg? A meta-analysis of panel studies of the relationship between work-family conflict and strain. J Appl Psychol. 2015;100(2):522–36.

81.

Leimeister

, Zogaj

, Durward

, Blohm

. Systematisierung und Analyse von Crowd-Sourcing-Anbietern und Crowd-Work-Projekten; 2016. Study der Hans-Böckler-Stiftung 324. Available from: URL. http://hdl.handle.net/10419/142715

82.

Giard

, Brunsmeier

, Hemsen

, Hesse

, Löken

, Nouri

, et al.. Research Report. Erkenntnisse zurArbeitsrealität deutscher Crowdworker. Bielefeld: Universität Bielefeld / Universität Paderborn(Forschungsschwerpunkt Digitale Zukunft); 2021. Available from: URL: https://pub.uni-bielefeld.de/record/2953491

83.

Carlson

, Kacmar

, Williams

. Construction and Initial Validation of a Multidimensional Measure of Work–Family Conflict. J Vocat Behav. 2000;56(2):249–76.

84.

Gierk

, Kohlmann

, Kroenke

, Spangenberg

, Zenger

, Brähler

, et al.. The somatic symptom scale-8 (SSS-8): a brief measure of somatic symptom burden. JAMA Intern Med. 2014;174(3):399–407.

85.

Glaesmer

, Grande

, Braehler

, Roth

. The German Version of the Satisfaction With Life Scale (SWLS). European Journal of Psychological Assessment. 2011;27(2):127–32.

86.

Allen

, Johnson

, Kiburz

, Shockley

. Work-Family Conflict and Flexible Work Arrangements: Deconstructing Flexibility. Pers Psychol. 2013;66(2):345–76.

87.

Dunn

. Making gigs work: digital platforms, job quality and worker motivations. New Tech Work Empl. 2020;35(2):232–49.

88.

Iacobucci

, Saldanha

, Deng

. A Meditation on Mediation: Evidence That Structural Equations Models Perform Better Than Regressions. J Consum Psychol. 2007;17(2):139–53.

89.

Young

, Schieman

. Scaling Back and Finding Flexibility: Gender Differences in Parents’ Strategies to Manage Work-Family Conflict. J Marriage Fam. 2018;80(1):99–118.