Modern Times and Rest: Sleep Quality Among Office Workers 

Luzmy C. Paredes – luzmycamila.paredes@gmail.com

August 4th, 2025

Edited by the YNPS Publications Team.

—Abstract 

While not all office jobs uniformly influence sleep, a combination of environmental, behavioral, and occupational elements may affect sleep patterns. Poor workplace lighting, prolonged screen exposure, overtime work, elevated stress levels, and irregular daily routines are identified as possible contributors to diminished sleep quality. Although limiting screen use before bed is commonly recommended, it may not significantly improve sleep. Instead, exposure to circadian-effective lighting and increased physical activity shows greater potential for enhancing sleep. Dynamic office lighting may help reduce sleep onset latency, though results vary, requiring further research. Sleep hygiene factors are also correlated with longer sleep latency and shorter sleep duration, such as lack of light exposure in the morning, elevated caffeine consumption, irregular meal times, nightcap, poor diet, weight gain, and insufficient physical activity. While physical activity helps manage stress, which supports better sleep, its direct effect on sleep quality is less clear. Sleep quality also varies among office workers. Individual chronotypes influence how screen exposure affects sleep, suggesting a need for individually tailored workplace strategies. Future investigations should prioritize longitudinal and experimental methodologies to establish causality and to more thoroughly understand the long-term effects of office work on sleep, while also incorporating diverse demographic and cultural contexts. Current understanding is constrained by the predominance of cross-sectional, self-reported data and limited sample sizes in existing research, highlighting the imperative for more extensive studies to guide the development of effective workplace policies aimed at fostering improved sleep health among office professionals. 

Keywords: sleep patterns, office jobs, workplace lighting, screen exposure, stress levels, physical activity, sleep hygiene, chronotypes.

—Introduction 

In today’s society, securing employment is not only a personal achievement but also a social expectation. It is seen as a way to contribute to oneself, loved ones, and society (Cholbi, 2023). Among various forms of employment, office jobs are ubiquitous, commonly perceived as stable and desirable roles for both men and women across the globe (Silverstone, 1976; Norhayati Omar & Rossilah Jamil, 2025). However, as office-based work becomes more prevalent, concerns have emerged regarding its impact on employee well-being, particularly concerning sleep quality. 

Sleep disorders are widespread in the general population, yet often trivialized and perceived as minor issues (Farney & Walker, 1995). The modern work environment, particularly the prevalence of office-based employment, has raised concerns about its impact on employee well-being, with sleep quality emerging as a significant area of interest. Sleep quality encompasses more than just the number of hours slept: It includes how quickly one falls asleep, also called sleep latency, how long it takes to fall asleep, how often you wake during the night and the ratio of time you spend in bed versus the time you spend asleep (National Sleep Foundation [NSF], 2024). Good sleep quality is essential for not only physical and mental health, but also for mood regulation, productivity, and cognitive functioning in our daily lives. 

Modern office work environments are frequently characterized by high psychological demands and elevated stress levels, all of which may interfere with healthy sleep patterns (Åkerstedt, 2006). Despite increasing interest in workplace health, the complex relationship between office work and sleep quality remains insufficiently understood. 

By examining the interaction between occupational demands, environmental conditions, and individual differences, this meta-synthesis aims to bring together current research findings on sleep quality in office workers, analyzing the range of contributing factors and identifying

common themes and limitations across studies. It seeks to examine whether office jobs affect sleep quality, what factors may moderate this relationship, and whether certain subgroups of office workers experience sleep differently, all with the intention of providing a more complete view of the problem and understanding how the demands and characteristics of the modern office environment influence sleep.

—Literature Review 

The existing literature suggests a complex relationship between office work and sleep quality, often related to common consequences of work like stress affecting sleep quality, and others put more focus on lighting within these environments and overtime work in specific populations. Figueiro et al. (2017) titled The impact of daytime light exposure on sleep and mood in office workers, with a sample size of 109 participants, 81 participating in both winter and summer, found a relationship between indoor lighting in office environments and both sleep quality and mood in both seasons. The study was done in both winter and summer, and the measurements were self-reports for both mood and sleep, and data obtained from circadian effective lighting or dynamic lighting (DL), and activity rhythms. Daytime light exposure for circadian health was associated with reduced sleep onset latency and increased sleep quality, as well as reduced depression and better mood. Ru et al. (2023), with a sample of 21 participants in Temporal tuning of illuminance and spectrum: Effect of a full-day dynamic lighting pattern on well-being, performance and sleep in simulated office environment also compared the effects of DL and static lighting (SL) in a simulated office environment through an experimental approach, utilizing both self-reports and questionnaires. While DL setup offered benefits over SL depending on the time of the day, with improvements on vitality, alertness, self-control, mood, sustained attention, and perceived sleep quality, these effects were not consistent across all time-points and measurement categories. Kompier et al. (2022) also, through an experimental approach, compared SL with two types of DL differing in timing but providing the same total light exposure with a slightly larger sample of 30 employees in Contrasting dynamic light scenarios in an operational office: Effects on visual experience, alertness, cognitive performance, and sleep. Visual comfort was slightly lower in both DL scenarios, and while the DL scenario with brighter light around midday was associated with the lowest levels of

sleepiness, task performance, and sleep outcomes showed no significant differences. In this, individual light exposure did not predict sleepiness or performance, but variations in exposure and its timing within DL types were positively linked to earlier sleep onset latency and longer sleep duration. 

Others tried to look at sleep hygiene factors instead. Shimura et al. (2020) titled Which sleep hygiene factors are important? A comprehensive assessment of lifestyle habits and job environment on sleep among office workers, found through a cross-sectional survey with a sample size of 5640 participants, found that multiple sleep hygiene factors were associated with sleep quality in office workers, each with different effect sizes. The most significant factors found were lack of light exposure in the morning, electronic use in bed, high caffeine intake, waking up before dawn, lack of proper diet, irregular meal times, weight gain, and nightcap were associated with sleep quality in office workers. Larsen et al. (2021) through A multi-component intervention to affect physical activity, sleep length and stress levels in office workers, longitudinal study with a sample size of 63 office workers in three different workplaces, correlated physical activity, stress levels and sleep quality in office workers with an experimental design and 4 questionnaires: NEO Five Factor Inventory questionnaire (NEO-FFI-3), Nordic Physical Activity Questionnaire-short, Perceived Stress Scale (PSS) and the Insomnia Severity Index. In this study, restricting electronic use in the bedroom didn’t have a significant effect on sleep length, but physical activity had more health benefits, allowing for reduced physiological stress. Objective data didn’t support any changes in sleep quality, but participants felt their sleep improved. Similarly, Biswas et al. (2025) in Effects of extended digital screen exposure on sleep patterns and cognitive functioning of chronotypes in professional office environments, with a sample size of 200 male office workers and through three different questionnaires applied, Munich Chronotype Questionnaire Scale (MCTQ), Reduced Morningness Eveningness Questionnaire (rMEQ), and Epworth Sleepiness

Scale (ESS), found that electronic use was related to sleep quality, with increased sleep latency, daytime sleepiness, decreased sleep duration, and extended sleep inertia. Other studies have also found significant relationships between sleep quality and overtime work in office workers. Through a sample of 26144 office workers interviewed with a computer-assisted medical interview in Sekizuka & Miyake (2024), titled Overtime work is related to nonrestorative sleep independently of short sleep time among a Japanese occupational population, it was found that nonrestorative sleep, a symptom of insomnia related to sleep quality, had a more significant relationship with overtime work than sleep duration and overtime work. 

—Methodology 

Opted for an interpretative meta-synthetic review of a total of 7 studies published between 2015-2025 in multiple databases (PubMed, Sleep Health Journal, ScholarGoogle). To ensure the relevance and rigor of the selected literature, specific inclusion criteria were applied: Studies were incorporated if they featured keywords such as “office job”, “office worker”, “office”, “workplace”, or “sleep.” Additionally, a prerequisite for inclusion was a minimum sample size of 20 participants. The studies were also required to be published in either English or Spanish, and critically, they needed to focus on or be related to the topic of sleep within office environments or pertaining to office workers.

—Results 

Office jobs may be associated with changes in sleep quality of office workers, though the specific nature depends on environmental, behavioral, and occupational factors. Some studies have reported that office environments can negatively affect sleep, especially when certain conditions such as poor lighting or long working hours are present (Figueiro et al., 2017; Kompier et al., 2022). Two studies found that circadian-effective lighting during the day was associated with improved sleep quality, shorter sleep onset latency, and better mood, suggesting that office environments may negatively affect office workers’ sleep quality. The findings were consistent across multiple seasons in one of the studies. Ru et al. (2023) found that while DL seemed to improve sleep quality in comparison to SL, it showed inconsistent effects on it, indicating that further research is needed to assess how lighting interventions perform in real-world office settings. 

Sleep hygiene factors were significantly associated with sleep quality. Extended electronic use before bed and lack of exposure to morning light were among the most consistently significant, leading to increased sleep latency, decreased sleep duration, and heightened daytime sleepiness (Shimura et al., 2020; Biswaas et. al, 2025), but other factors included high caffeine intake, weight gain, irregular meal times, nightcaps, poor diet and waking up before dawn. Larsen et al. (2021) reported that physical activity was associated with lower stress levels, but their findings did not support any significant relationship between screen restriction and sleep length, and changes in sleep quality afterwards were mostly subjective and non-significant. 

Variability in sleep quality across different subgroups existed as well. Chronotype differences, as observed by Biswas et al. (2025), appeared to moderate the effect of screen exposure, with some individuals more vulnerable to late-night digital use than others. Differences in stress levels (Larsen et al., 2021; Sekizuka & Miyake, 2024) also played a

role, suggesting that both job type and individual coping habits might affect sleep outcomes. While most studies did not differentiate strongly between types of office jobs, work schedules, overtime work, and stress levels emerged as relevant variables in the variation of sleep quality in office worker populations.

—Discussion 

Office jobs may affect sleep quality, but not uniformly. Each study varied significantly in methodology to study sleep habits, duration, and its quality or efficiency. When it comes to environmental lighting, several studies found that office lighting can support or disrupt circadian rhythms depending on its quality, timing, exposure, and duration. While one study found inconsistent effects of DL systems in a simulated environment, it also presented a smaller sample size (Ru et al., 2023) in comparison to the sample sizes of two studies on Circadian-effective lighting, in which it was linked to better sleep quality (Figueiro et al., 2020), better sleep onset latency, and sleep duration (Kompier et al., 2022), although the data extracted from these were mostly obtained through self-reports and small samples. 

The relationship between sleep quality and office jobs is shaped by a combination of modifiable environmental and behavioural factors, as well as individual traits. The most relevant factors associated with sleep quality in office workers, when it comes to behavioral factors, do appear to be consistent across studies: electronic device use, poor exposure to morning light, irregular schedules, lack of physical activity, and high caffeine intake. Shimura et al. (2020) identified all of these as key components of poor sleep hygiene. Physical activity, on the other hand, was associated with reduced stress (Larsen et al., 2021), reinforcing the role of lifestyle habits, but didn’t seem to significantly affect sleep quality. Differences in sleep quality between groups of office workers were also noted, though not always explicitly analyzed. Biswas et al. (2025) found that chronotype influenced vulnerability to screen-related sleep disruption, with evening types more negatively affected by extended digital exposure. While job types and work schedules were not directly compared in most studies, the evidence suggests that office workers who face high stress,

long hours, overtime work, or inconsistent routines may be at greater risk for sleep disturbances. 

Most available studies are cross-sectional or based on self-reported data, making it difficult to draw causal conclusions. More research is needed to optimize lighting schedules and ensure that comfort and performance are balanced, as well as studies that analyze these factors concerning sleep quality in longitudinal designs. Longitudinal and experimental research will be essential to better understand how workplace design and policy can be optimized to support healthier sleep patterns among office workers. 

The findings highlight the importance of paying attention to an individual’s natural sleep-wake patterns when trying to improve health at work. Since people may be affected differently depending on their chronotype, it’s important to use personalized strategies for screen use and digital well-being to help employees stay healthy and perform well in today’s screen-heavy workplaces.

—Limitations 

This article is subject to limitations that must be taken into account while interpreting its findings. First, since it’s a meta-synthesis, it inherently absorbs the limitations and biases of each primary study included and its study design limitations. Many vary in methodological quality, sample size, and rigor. Even in those that featured larger sample sizes, not many have been reproduced more than once or twice, and there’s a noticeable lack of research focus in the optimization of office jobs for the development of healthier sleep patterns in office workers in general. Most rely on cross-sectional designs, limiting the ability to infer causality between office jobs and sleep quality, restricting our understanding of how sleep quality evolves in response to work-related variables. Second, this analysis was also limited to studies published between 2015-2025, to allow for an analysis of 5 years before and after the COVID-19 pandemic, which might have influenced some job changes. While this decade reflects contemporary workplace dynamics, it may exclude relevant earlier studies or emerging research. Third, there is a notable lack of primary research data in the area, and studies with null results are less likely to be published. All of these significantly reduce the amount of data available for this meta-synthesis and potentially skew the conclusions reached. Fourth, the generalizability of the findings may be limited due to the sample focus. Most studies are limited to specific office environments, populations, or cultural contexts, which may not represent the full diversity of work conditions globally. These limitations highlight the need for more primary data, primarily longitudinal, to understand how office work environments influence sleep quality and what moderates the relationship.

—Conclusion 

While office jobs do not uniformly affect sleep, certain workplace conditions such as poor lighting, extended screen exposure, overtime work, high stress levels, and irregular routines may be consistently associated with negative sleep outcomes. Evidence suggests that both circadian-effective lighting and healthy behavioral habits, and increased physical activity, may improve sleep quality. Reduced electronic use before bed may not have a significant effect. Individual differences, particularly chronotype, also moderate these effects, indicating a need for more personalized approaches to workplace health and digital well-being. Despite the growing awareness of sleep as a critical component of occupational health, the current research on sleep quality and office workers is largely based on cross-sectional, self-report data or small samples, limiting causal interpretation. The field remains underdeveloped, especially in evaluating long-term impacts and diverse work settings. To better inform workplace design and policy, future research should adopt longitudinal and experimental approaches and consider broader demographic and cultural variability.

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