Working from home during lockdown: the association between rest breaks and well-being

Abstract

One of the challenges with working from home (WFH) is the question of its effect on health and well-being. The impact of home working on health has so far not been studied extensively. We address this gap by investigating the association between internal recovery, operationalised as rest break frequency (low, medium, and high) during the working day, on self-reported musculoskeletal pain, and post-work recovery symptoms in WFH knowledge workers (n = 382). The analysis showed that failing to take frequent breaks was associated with a dose-response increased risk of reporting headaches. For post-work recovery symptoms, failing to take rest breaks throughout the day was associated with an increased risk of reporting psychological fatigue, physical fatigue, and sleep problems, and a decreased risk of psychologically detaching from work and experiencing adequate rest. Our findings emphasise the importance of remote workers taking recovery breaks from work demands in the maintenance of health and well-being.

Practitioner Summary: For the foreseeable future, many knowledge workers will be obliged to work from home for at least, some days of the week. It is therefore important for workers to learn to regulate their behaviour, and workers need to be educated about the value of taking regular rest breaks throughout the working day.

Abbreviations: ICT: Information and communications technology; MSDs: musculoskeletal disorders; MSPs: Musculoskeletal pain symptoms; OR: Odds ratio; WFH: Working from home; WRRQ: Work-Related Rumination Questionnaire Questionnaire.

Keywords:

• Remote working
• recovery from work
• rest breaks
• musculoskeletal pain
• well-being

Introduction

Remote work, and particularly working from home (WFH), creates challenges. One of them is the question of its effect on health and well-being, where especially the impact of internal recovery, in terms of rest break behaviour while WFH, has so far not been extensively researched. This study addresses this gap by investigating the association between rest breaks and self-reported physical and mental health of workers WFH.

Remote working can be defined as the practice of WFH or working from other locations that are not part of an organisation's place of business (Hardill and Green 2003). Traditionally, home working used to be the domain of the cottage-industry worker, or the self-employed—although many academics have worked from home at least some of the time—but during the worldwide COVID-19 pandemic many employees were furloughed or forced to work from home, rendering WFH a new and enduring context for many, including knowledge workers (Wang et al. 2021).

There are many benefits of WFH for both employers and employees. It allows a degree of flexibility, as workers can ideally choose when to take a break, employees can wear more casual clothes, and household or domestic chores can be incorporated into the working day. There may also be less distractions from colleagues (van der Lippe and Lippényi 2020; Wöhrmann and Ebner 2021). WFH has been associated with increased productivity (Vega, Anderson, and Kaplan 2015) although this is not a consistent finding (van der Lippe and Lippényi 2020). Nonetheless, research suggests that people report they are happier having the flexibility to be able to work from home as they experience a better work/life balance (Mann and Holdsworth 2003; Wöhrmann and Ebner 2021). In terms of cost, WFH also reduces employee overheads, the need for office space, equipment, etc. (Mann and Holdsworth 2003).

Compelling people to WFH—as was the case during Covid-19—also raises some challenging issues, that, overtime, can be stress-inducing. Moreover, workers may not have a dedicated office space and are forced to work on the kitchen table, lounge, or bedroom. They may be forced to share a working space with a partner or children (with children receiving some lessons from home as schools have been regularly closed during the pandemic) while being physically isolated from colleagues (albeit virtually connected through ICT devices). Some workers may be (or may have been) forced to learn new technologies to manage remote working, which may induce stress. And there is also a shift in responsibility from employer to employee as in theory workers have more control of their working day. With this shift of control, employees have to learn to regulate their working behaviour, e.g. decide when they take rest breaks. WFH as a long-term practice raises some additional health concerns, although there is a general lack of research examining the effects of WFH on mental and physical health, as the percentage of the working population who worked from home before Covid-19 was relatively low. WFH has been associated with work overload (Allen, Golden, and Shockley 2015; Wang et al. 2021), and limiting the boundaries between work and private life, making it difficult to clearly separate these two worlds, which may impede psychological detachment and recovery from work.

Detaching from work is extremely important and has been emphasised in several theoretical models (Hobfoll 1989; Meijman and Mulder 1998, Ohash; Zijlstra, Cropley, and Rydstedt 2014). For example, in their Effort-Recovery model, Meijman and Mulder (1998) argue that energy expended during demanding work depletes essential psychological and physical resources that can only be replenished by taking adequate rest. Hobfoll (1989) argues that individuals have an innate drive that motivates them to create, foster, and preserve personal resources, such as those needed to maintain survival, and boost self-esteem and well-being. Within the occupational context, a resource could be deteriorated when an employee works hard to meet a tight deadline, works under pressure, or works long hours. However, even under normal circumstances, resources are unavoidably depleted by the general demands associated with work which are typically replenished during one’s leisure. Thus, the recovery process exists to replenish resources when demands/stressors are no longer present (Hobfoll 1989). Zijlstra, Cropley, and Rydstedt (2014) emphasise recovery as a dynamic and continuous process and a state that can never be fully achieved as there is no actual point to identify when someone is recovered. Here, recovery from work is understood as an ongoing regulation of one’s psychophysiological state. Although there are clear differences between the various theoretical models, they all share an underlying principle of the importance of workers taking rest and recovery from work demands in the maintenance of health and well-being (Steed et al. 2021).

Opportunities for recovery can be subsumed under two broad categories in terms of external and internal. External recovery takes place outside of work and occurs during leisure time, and arguably the most important external recovery activity is good quality sleep (Querstret and Cropley 2012). Internal recovery involves short periods of rest within scheduled or unscheduled breaks during the working day, or by shifting attention to an unrelated task (Van Veldhoven and Sluiter 2009) and is a statutory requirement and a fundamental right across the European Union (Cabrita and Cerf 2019). Studies have highlighted the role of autonomy over work breaks, suggesting that choice over when to take breaks strengthens the link between the break and recovery (Hunter and Wu 2016; Trougakos et al. 2014). Taking breaks from the demands of work during the working day has been associated with greater motivation (Demerouti et al. 2012; cf., Wendsche et al. 2017), positive affect (Kim, Park, and Headrick 2018), better health and well-being (Hopkins 2015; Wendsche et al. 2017), and less fatigue and sleep problems (Bennett, Bakker, and Field 2018; Cropley, Rydstedt, and Andersen 2020). In short, taking regular rest breaks throughout the day helps to maintain performance (Tucker 2003), but even more importantly, research has also shown that regular internal recovery, i.e. taking regular breaks during the working day, can also reduce the risks of developing musculoskeletal disorders.

In work and employment settings, lack of internal recovery is commonly associated with health disturbances, e.g. musculoskeletal pain, and headaches. Musculoskeletal disorders are ‘impairments of bodily structures’, such as muscles, joints, and bones that are thought to affect up to 40 million workers in Europe (Roquelaure 2018). Research suggests an association between internal workload and the development of musculoskeletal disorders. For example, musculoskeletal complaints are associated with prolonged sitting or leading a sedentary lifestyle (Crawford et al. 2020). Although taking breaks has been shown to reduce muscular discomfort during computer tasks or deskbound work (De Vera Barredo and Mahon 2007; Ding et al. 2020; Waongenngarm, Areerak, and Janwantanakul 2018), workers do not appear to take sufficient rest breaks during the working day (Griffiths, Mackey, and Adamson 2007; Tremblay et al. 2017), and many sit for long periods of time (Tavares 2017), particularly if their work involves computer use (Lamb and Kwok 2016). Unsurprisingly, a high internal workload and a lack of recovery breaks have been associated with musculoskeletal pain (Devereux, Rydstedt, and Cropley 2011).

Epidemiological studies have identified job demands/stress, sustained awkward postures of the wrists, elbows, or shoulders, and insufficient recovery time to be some of the main work-related factors associated with musculoskeletal pain (MDP) (Janwantanakul et al. 2010; Roquelaure 2018). Studies have also found gender differences with women tending to report more arm, neck, and shoulder complaints compared to men (Hooftman et al. 2004). Due to the static nature of the job, office workers are at an increased risk of developing musculoskeletal impairments (Janwantanakul et al. 2008), and in particular neck pain (Jun et al. 2017); however, these effects may be magnified when workers perform their normal office activities, reading, and typing, at home without sufficient breaks from work.

Although not always explicitly investigated, the impact of a high internal workload extends to other health complaints in knowledge workers, such as fatigue (Cropley, Rydstedt, and Andersen 2020), headaches or migraines (Li et al. 2020; Sato et al. 2012), or insomnia (Cropley, Rydstedt, and Andersen 2020; Sonnentag, Venz, and Casper 2017), and contributes to the inability to mentally unwind and switch off at the end of the working day (Cropley, Rydstedt, and Andersen 2020). By contrast, taking regular breaks during the day has been associated with reduced fatigue (Trougakos et al. 2014), and increased work engagement, motivation, and energy (Demerouti et al. 2012; Fritz, Lam, and Spreitzer 2011; Kühnel et al. 2017).

From a business and management perspective, it is important for workers to take recovery breaks during the day to reduce the risk of burnout and other mental health conditions, as these can lead to, or be associated with, lower productivity, increased absenteeism, and staff turnover (Adler et al. 2006; Dewa, Loong, and Bonato 2014; Scanlan and Still 2019). Both personally and commercially, it is, therefore, crucial to understand how workers regulate their time when working from home settings, and whether break frequency is associated with negative health indices.

To summarise, previous research has clearly demonstrated that high workload and insufficient recovery from work are detrimental to health and well-being. Most research has focussed on the role of external recovery (von Dreden and Binnewies 2017; Wendsche and Lohmann-Haislah 2016), however, employees are likely to spend more time working from home in the future and will have more control over when to take a rest break, understanding the role of internal recovery becomes even more important.

The aim of the present study was, thus, to investigate the effects of WFH (i.e. internal recovery) on health in knowledge workers, i.e. employees working in the knowledge-based economy. We examined the association between internal recovery—operationalised as the number of rest breaks taken during the working day—on self-reported musculoskeletal pain (elbow, hands/wrist, lower back, headaches, hip/leg, and neck), and recovery parameters post-work (psychological detachment, fatigue, insomnia, and rest) in knowledge workers WFH.

Methodology

Participants and design

Four hundred and ninety-four adult employees completed an online, cross-sectional survey between November 2020 and February 2021. The survey targeted knowledge workers, working in the UK, during a period of the Covid-19 pandemic when many workers were enforced to WFH. One hundred and twelve participants were excluded because they did not meet the inclusion criteria of being a knowledge worker, working 25 or more hours per week, or reporting they were still based at their workplace. The final sample consisted of 382 workers aged between 20 and 65 years who worked from home. They reported working between 25 and 90 h per week (mean 41.33 h). The majority of participants were educated to a degree level (54.2%) and did not report having dependent children under the age of 18 (52.1%). This project was approved by the University of (name anonymised), Faculty of Health and Medical Sciences Ethics Committee, and was pre-registered on AsPredicted ID 52795.

Procedure

Participants were recruited using professional industry contacts, snowballing and the survey link was also posted on social media platforms ‘Facebook’ and ‘LinkedIn’. Participants gave informed consent before starting the survey and were aware that they could withdraw their consent and/or participation at any time.

Measures

Frequency of breaks per day

A single item was used to assess the typical number of breaks taken by participants in a working day. This was rated on a 5-point scale: 1 = ‘I never take any breaks’, 2 = ‘I only take breaks for eating lunch’, 3 = ‘I take breaks two or three times a day’, 4 = ‘I take breaks at least four times a day’, and 5 = ‘I take breaks five or more times a day’. Ratings were recoded into dummy variables: values 1 through 2 were coded as low (less frequent breaks), 3 as medium, and values 4 through 5 were coded as high (more frequent breaks).

Recovery parameters post-work

Sleep problems were assessed using single items rated on a 4-point scale as to how bothered/troubled people were over the previous month (1 = ‘very troubled’, 2 = ‘quite bothered’, 3 = ‘slightly bothered’, 4 = ‘not bothered’). Mental and physical fatigue was assessed using the following two items: ‘How often do you feel physically exhausted when you are done with your work for the day?’, and ‘How often do you feel mentally exhausted when you are done with your work for the day?’. Rest was assessed with one item: ‘How often do you think that you are getting adequate rest and relaxation between workdays?’. All three items were rated over the previous month with 1 = ‘daily’, 2 = ‘sometimes per-week’, 3 = ‘once a week’, 4 = ‘sometime per-month’, and 5 = ‘never/almost never’. These items have been used in previous studies (Cropley, Rydstedt, and Andersen 2020; Revold and Bye 2017). Psychological detachment from work was assessed with 5-items of the Work-Related Rumination Questionnaire (WRRQ) (Cropley et al. 2012), e.g. as ‘I am able to stop thinking about work-related issues in my free-time’. Items are scored on a 5-point Likert scale from 1 (‘very seldom/never’) to 5 (‘very often/always’). Other studies have also demonstrated that the WRRQ has good reliability and validity (Cropley and Collis 2020; Syrek et al. 2017). The Cronbach’s alpha for detachment in the present study was 0.81. Ratings were recoded into dummy variables for each subscale; values 1–2.5 were coded as high detachment and values 3.5–5 were coded as low detachment.

Musculoskeletal pain symptoms were measured using single items. Participants were asked whether they had been bothered with the following in the past month, pain in the elbow, hands/wrist, lower back, hip/leg, head, and neck/shoulder. Items were rated on a 4-point scale from 1 (‘very troubled’) to 4 (‘not bothered’). Items were adapted from Cropley et al., (2020). Ratings were recoded into dummy variables; values 1–2 were coded as low, and 3–4 were high for each symptom.

Additional variables used as covariates

Job autonomy. Perceived control over work was assessed using three items, measured using a 4-point [1 (‘often’) to 4 (‘never/almost never’)], adapted from the Job Content Questionnaire (Karasek et al. 1998), (1) ‘To what extent can you decide how you work?’, (2) ‘To what extent can you decide your work pace?’, and (3) ‘Do you have a choice in what you do at work?’. Responses to the three questions were averaged to create a mean score, with $\alpha$ = .80.

Hours worked per week. Hours worked per week were measured as estimated hours worked per week.

Work-related stress. Levels of work-related stress were measured using a single item: ‘How stressful do you find this way of working?’ (Smith 2000). This was rated on a 5-point scale: 1 = ‘not at all stressful’, 2 = ‘mildly stressful’, 3 = ‘moderately stressful’, 4 = ‘very stressful’, 5 = ‘extremely stressful’. Ratings were recoded into dummy variables; values 1–3 were coded as low work stress, and values 4–5 were coded as high work stress.

Results

The results are reported in three sections. The first section reports the demographic characteristics and the means and standard deviations of the study variables. Section two reports the analysis of rest break frequency on musculoskeletal pain, and section three reports the analysis of rest break frequency on recovery from work symptoms. The frequency of work breaks per day was categorised into three groups (low, medium, and high). For each set of analysis, high break frequency was used as the comparison against the medium and low-frequency break groups. For each musculoskeletal pain item, and the recovery outcome variable, Odds Ratios (ORs) and 95% Confidence Intervals (CIs) were initially calculated using logistic regression analysis, and then the analysis was adjusted for age (years) gender (female, male), hours work per week, work stress, and job control. These variables were treated as possible confounders consistent with previous studies on occupational health and are known to be associated with rest behaviour (Blasche et al. 2017; Cropley, Rydstedt, and Andersen 2020; Wendsche et al. 2017).

Table 1 reports the demographic characteristics and the means and standard deviations of the study variables.

Table 1. Demographic characteristics and the means and standard deviations of the study variables.

	n = 382
	Mean	SD or (%)
Age (in years)	37.22	12.91
Gender
Female	226	(59.0%)
Male	156	(40.7%)
Musculoskeletal pain symptoms
Lower back	2.44	1.02
Elbow/forearms	2.45	1.26
Hand/wrist	2.42	1.26
Hips//legs/feet	2.44	1.18
Headache	2.41	1.08
Neck/shoulder	2.52	1.06
Post-work recovery symptoms
Mental fatigue	2.49	1.19
Physical fatigue	2.89	1.35
Psychological detachment	2.98	.85
Rest (adequate)	2.66	1.17
Poor sleep	2.44	1.08
Covariates
Hours worked per week	41.33	8.17
Job autonomy	2.98	.88
Job stress	2.35	.98

Musculoskeletal pain symptoms

Table 2 summarises the crude and adjusted odds ratios for the reporting of musculoskeletal pain symptoms. As can be seen in Table 2, medium break frequency was only associated with an increased risk of reporting headaches (crude estimate: OR = 1.89) and adjusted for age, gender, hours worked per week, job autonomy, and stress (OR = 1.91) relative to those reporting a high break frequency. A similar pattern was found for low break frequency but there was an increased risk of reporting headaches (crude estimate: OR = 1.91), and adjusted ORs (OR = 2.33) relative to those reporting high break frequency.

Table 2. Crude estimate and adjusted odds ratios (95% confidence intervals) of work break frequency (low, medium, and high) on musculoskeletal pain symptoms.

	Lower back	Elbow/forearms	Hand/wrist	Hips/legs/feet	Headache	Neck/shoulder
Crude OR (95% CI)
High	1	1	1	1	1	1
Medium	1.11 (.60–2.06)	1.25 (.75–2.10)	1.30 (.78–2.19)	1.29 (.76–2.21)	1.89 (1.06–3.35)	1.28 (.71–2.28)
Low	1.07 (.51–2.22)	1.48 (.81–2.72)	1.61 (.88–2.95)	1.22 (.63–2.38)	2.14 (1.09–4.22)	.94 (.45–1.98)
Adjusted OR (95% CI)
High	1	1	1	1	1	1
Medium	1.20 (.62–2.30)	1.15 (.67–1.99)	1.41 (.82–2.45)	1.23 (.70–2.17)	1.91 (1.04–3.53)	1.38 (.75–2.54)
Low	1.26 (.58–2.71)	1.31 (.68–2.53)	1.89 (.98–3.67)	1.15 (.57–2.33)	2.33 (1.09–4.98)	1.05 (.48–2.31)

Adjusted for age, gender, hours worked per week, job autonomy, and stress.

Table 2 reports the crude/adjusted ORs with 95% confidence intervals of work break frequency on musculoskeletal pain symptoms.

Post-work recovery symptoms

Table 3 summarises the crude and adjusted odds ratios for the recovery from work variables. As can be seen in Table 3, medium break frequency was associated with an increased risk of reporting poor psychological detachment (crude estimate: OR = 2.01), inadequate rest (crude estimate: OR = 2.89), and mental fatigue (crude estimate: OR = 2.90), relative to those reporting high break frequency. After adjustment for age, gender, hours worked per week, job autonomy, and job stress, inadequate rest (OR = 2.54) was the only variable with an increased odds ratio.

Table 3. Crude estimate and adjusted odds ratios (95% confidence intervals) of work break frequency (low, medium, and high) on recovery from work symptoms.

	Mental fatigue	Physical fatigue	Psychological detachment	Rest (adequate)	Poor sleep
Crude OR (95% CI)
High	1	1	1	1	1
Medium	2.90 (1.48–5.68)	1.80 (.90–3.61)	2.01 (1.16–3.47)	2.89 (1.66–5.03)	1.76 (.98–3.17)
Low	6.17 (2.47–15.4)	2.80 (1.13–6.88)	2.46 (1.28–4.71)	3.34 (1.68–6.64)	2.35 (1.20–4.58)
Adjusted OR (95% CI)
High	1	1	1	1	1
Medium	2.20 (.94–5.17)	.65 (.25–1.67)	1.31 (.69–2.48)	2.54 (1.41–4.54)	1.66 (.88–3.13)
Low	5.62 (1.70–18.6)	.74 (.20–2.72)	1.82 (.88–3.74)	3.22 (1.54–6.70)	3.22 (1.52–6.80)

Adjusted for age, gender, hours worked per week, job autonomy and stress.

Table 3 reports the crude/adjusted ORs with 95% confidence intervals of work break frequency on recovery from work symptoms.

For low break frequency there was an increased risk of reporting mental fatigue (crude estimate: OR = 6.17), physical fatigue (crude estimate: OR = 2.80), poor psychological detachment (crude estimate: OR = 2.46), inadequate rest (crude estimate: OR = 3.34), and poor sleep (crude estimate: OR = 2.35), relative to those reporting high break frequency. After adjustment for age, gender, hours worked per week, job autonomy and job stress, mental fatigue (OR = 5.62), inadequate rest (OR = 3.22), and poor sleep (OR = 3.22) were associated with increased risk.

Discussion

The present study aimed to explore the association between internal recovery—operationalised as rest break frequency—on self-reported musculoskeletal pain, and post-work recovery symptoms in knowledge workers who worked from home during the COVID-19 pandemic. Our analysis revealed that failing to take frequent breaks throughout the working day was associated with a dose-response increasing risk of reporting headaches, with individuals who reported they seldom take breaks throughout the day showing the greatest risk of developing headaches, compared to the medium and high frequent break group. Specifically, individuals who reported low break frequency were found to be twice as likely to report headaches, relative to those who reported taking frequent breaks throughout the day. The association between break frequency and headaches remained even after adjustment for covariates including job autonomy and occupational status. No other musculoskeletal pain symptom was found to be significant.

For post-work recovery symptoms, failing to take rest breaks throughout the day was associated with an increased risk of reporting psychological fatigue, physical fatigue, and sleep problems, and a decreased risk of psychologically detaching from work and experiencing inadequate rest. Individuals who reported low break frequency were approximately six times more likely to report mental fatigue relative to those who take frequent breaks, but interestingly low break frequency was associated with a 2-fold or above increased risk in all the post-work recovery indicators. After adjustment for known factors associated with poor recovery, mental fatigue, inadequate rest, and poor sleep were the only variables to remain significant. Notwithstanding, lack of recovery breaks throughout the day is clearly associated with poorer mental well-being.

Although the aim of this study was not to explicitly test a theoretical model of recovery, our results are nevertheless fully in accord with recovery models (i.e. the Effort-Recovery model, the Conservation of Resources Model, and the Regulation Model of Recovery). Uniquely, the Regulation Model of Recovery states that there is no actual point at which it is possible to verify that someone is ‘recovered’ and that recovery should be considered in terms of the regulation (Zijlstra, Cropley, and Rydstedt 2014). Our findings suggest that those who regulate their work behaviour by punctuating work activities with periods of rest are less likely to experience fatigue and more likely to report adequate rest between workdays; underlining the importance of workers taking rest breaks to recover from work demands in the maintenance of health and well-being.

Before the pandemic, WFH was relatively uncommon, and most knowledge workers worked at designated places of work, such as offices. In the office/work setting, the notion of taking rest breaks during the working day had been ingrained into the fabric of work. In addition to usual lunch or coffee breaks, shorter and spontaneous breaks, e.g. chitchat by the watercooler, the photocopier, or in the kitchen, was part of established everyday routines at work, with workers possibly being unaware of the importance and benefits of these micro-breaks. However, it is clear from this study, in the absence of office workplace settings, that a high percentage of home workers fail to take adequate rest breaks during the day. Concerning the reasons for this behaviour, we can only speculate. On the one hand, it is possible that the sudden shift to remote work has caused bosses to become more controlling because of a lack of trust, forcing employees to work more, harder, and constantly (Neeley 2021; Stoker, Garretsen, and Lammers 2021), however, we controlled for stress and perceived control in the analysis. In addition, situations of enforced self-isolation on employees during the pandemic might have caused mental challenges that intermingle with the perceived disadvantages of WFH routines as such. On the other hand, working alone from home does not provide employees with situations where short and spontaneous micro-breaks could develop naturally. In an interesting diary study, Zacher, Brailsford, and Parker (2014) found that taking spontaneous micro-breaks was associated with reduced fatigue and greater vigour. It is, therefore, important for workers to learn to regulate their behaviour when working from home, and more needs to be done to educate workers and their organisations about the value of rest breaks. One way to do this could be to ask workers to form intentions, as rest break intention has been associated with actual rest break behaviour and subsequent well-being (Blasche et al. 2017), but this will also depend on the degree of job autonomy the worker has (Blasche et al. 2021).

It was surprising that for musculoskeletal pain, increased risk of headaches was the only symptom associated with lack of internal recovery, which remained significant even after the findings were adjusted for age, gender, hours worked per week, job autonomy, and stress. It is not clear why only headaches showed an increased risk, as sedentary work—work that involves people sitting for long hours—has been associated in some studies with an increased risk of musculoskeletal pain (Janwantanakul et al. 2008), and intuitively it makes sense that sitting for long periods should be associated with musculoskeletal pain. The evidence, however, that breaks to reduce the risk of musculoskeletal disorders, is limited and mixed (Luger et al. 2019; Kennedy et al. 2010), and perhaps this relates to the quality of work (Brewer et al. 2006).

Conceivably it was perhaps too soon in lockdown, meaning there was insufficient time for musculoskeletal pain symptoms to develop, and future research needs to monitor musculoskeletal pain data over time in home workers to identify, if, when, and for whom pain symptoms develop. Intriguingly, workplace interventions that encourage sedentary workers to stand and walk more at work have surprisingly failed to demonstrate reduced musculoskeletal pain symptoms in the short or long-term (Parry et al. 2019) suggesting that perhaps prevention is the most prudent strategy to avoid musculoskeletal pain symptoms developing in the first place (Buckle 2005). Finally, it is important to keep in mind that the findings may not apply to situations when employee populations choose WFH practices voluntarily as a new routine in the post-pandemic world.

This study clearly demonstrates that failure to take regular rest breaks during the working day is associated with a range of psychological health symptoms. We controlled for factors that are thought to influence how often people take breaks and recovery symptoms, such as job autonomy, work hours, and job stress, but break frequency may be governed by a range of factors not assessed in this study, including individual, social as well as work demands. For example, a person may resist taking breaks if they need to fulfill child-care duties, or a perfectionist may spend more hours sedentary than is typical, trying to make a piece of work appear ‘flawless’. Such factors could be investigated in future studies. We also did not assess the length of the breaks taken, and this would be of interest in future research because frequent short rest breaks have been associated with greater performance and reduced strain (Wendsche, Lohmann-Haislah, and Wegge 2016). Finally, it may be of interest in future research to examine in more detail what people do during their rest breaks, and how activities during breaks influence health and well-being.

Conclusions

WFH brings many potential benefits to both employers and employees and based on the experiences during the COVID-19 pandemic, it may become increasingly normalised (Richter 2020). WFH has also environmental benefits in terms of reduced traffic congestion and pollution, it provides social benefits, as remote workers may provide a greater contribution to local communities (Soroui 2021) due to less commuting and less detachment from places of living, and it reduces the stress of commuting for individual workers (Kylili et al. 2020). Hence, WFH—as a new practice—can contribute to more sustainable remote working lifestyles.

In light of these considerations, this study contributes important knowledge on the effect of remote working from private home environments on knowledge workers' health and well-being. In particular, we address the research gap regarding the internal recovery of knowledge workers, i.e. white-collar remote workers, using the frequency of rest breaks. Demonstrating the importance of frequently taking (micro) breaks throughout the working day to maintain health and wellness—even during enforced WFH that cannot be controlled—has implications for remote leadership as well as for workplace policies: Despite the increased distance, and thus possibly a perceived loss of control from the side of employers, bosses, and leaders, our results show the necessity for an empowering, trusting leadership style (Kniffin et al. 2021; Stoker, Garretsen, and Lammers 2021), where leaders to delegate work to remote working employees and trust in their conscientiousness, competence, and willingness to perform well from their home offices (Cortellazzo, Bruni, and Zampieri 2019). Granting their employees this kind of autonomy communicates that the employee is trusted with knowing (best) how and when to perform work tasks (Neeley 2021; Weidenstedt 2020), and when and for how long to take breaks.

In terms of workplace policies, our results raise important questions: First, while a shift from the traditional co-located, face-to-face supervised workplace organisation (Soroui 2021) to remote work as WFH (or from anywhere) can be observed, a parallel shift in responsibility for the workplace environment is taking place from employers to employees. Hence, the question is to which extent employers and employees are aware of possible health issues induced by working remotely—and how they can be prevented. Considering this study's results, a shift in responsibilities for the work environment should not simply be taken for granted but questioned, researched, and discussed to provide insights on how to handle these questions in the future. As an example, the provision of ergonomic home office equipment could be one key solution in this matter. Second, the increased dependence of remote working employees on ICT and digital technologies may become a source of stress and other health concerns, and the missing social, real-life interaction may add to this so-called ‘technostress’ (Molino et al. 2020).

Acknowledgements

The authors would like to thank Sophia Bell, Aikaterini Douka, and Irem Yazici for their help in the data collection for this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).