Health of teleworkers: a scoping review on the assessment of the work-from-home environment

Abstract

Objectives

Inappropriate telework environments, including work-from-home (WFH) settings, have been linked to physical and mental health problems. However, no systematic assessment has been conducted regarding the WFH environment (WFH-E). The aim of this study was to clarify the current methods used to assess the WFH-E and its association with health- and work-related outcomes through a scoping review.

Methods

We searched PubMed, Web of Science, and Ichushi for literature published since 2010 on WFH-E assessment. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, assessment methods were summarized using 18 items categorized into 9 domains. Additionally, associations between the WFH-E and health- and work-related outcomes were reviewed.

Results

Of 1669 articles collected, 37 studies published from 2020 were ultimately included in this review. Thirty-four articles involved subjective assessments, and 9 involved objective assessments. The most frequently assessed item was artificial lighting, followed by thermal conditions and noise. Items such as color, greenery, building materials, and odor were rarely assessed. Most studies showed significant associations between the WFH-E and health- and work-related outcomes.

Conclusions

Studies on the WFH-E increased following the COVID-19 pandemic, showing significant associations between the WFH-E and health- and work-related outcomes. However, most assessments were subjective, with objective assessments remaining rare. Additionally, the assessment items were limited and biased, indicating that interior design elements were insufficiently assessed. Developing additional objective and comprehensive methods for assessing the WFH-E is needed.

Key points 

What is already known on this topic 

The transition to working from home (WFH) during the COVID-19 pandemic has raised concerns regarding its effects on workers’ physical and mental health. However, standardized methods for evaluating the WFH environment (WFH-E) remain underdeveloped.

What this study adds 

This scoping review identified existing assessment methods for the WFH-E, demonstrating that most involved subjective assessments. Few approaches incorporate interior design elements, such as color and materials. Significant associations were observed between the WFH-E and health- and work-related outcomes.

How this study might affect research, practice, or policy 

These findings underscore the need for additional objective and comprehensive assessment tools for the WFH-E. These insights may inform future research, support the development of practical interventions, and guide strategies aimed at promoting healthier remote working conditions.

1. Introduction

With the advancement of information and communication technology (ICT), “remote work,” which refers to working outside the traditional workplace, has expanded. Remote work is the broadest concept, encompassing work performed regardless of location; within this category, work styles that use ICT are referred to as “telework.”¹ Among various forms of telework, performing job tasks at home is classified as “work from home” (WFH).^2,3

Since the COVID-19 pandemic, WFH has rapidly become widespread in Western countries and is now regarded as the most common form of telework. In Japan, the Ministry of Health, Labour and Welfare defines telework as a flexible work style enabled by ICT, positioning home-based work as one of its primary forms.⁴ Given this context, WFH has become an important research focus for examining changes in work styles and their impacts on health, productivity, and well-being.

The rapid expansion of telecommuting, particularly WFH, has been associated with negative health effects. During the COVID-19 pandemic, individuals who initiated telecommuting reported more physical symptoms, such as shoulder stiffness, eye strain, and low back pain, compared with non-telecommuters.⁵ Previous studies have indicated that teleworkers are more vulnerable to work functioning impairment owing to an inappropriate work-from-home environment (WFH-E),⁶ and that such environments can exacerbate both physical and mental health problems.⁷

With the expansion of WFH, concerns have been raised regarding the impact of WFH-E on workers’ health and work performance. Vacchiano et al.⁸ conducted an exploratory review of 132 studies, revealing a wide range of reported physical, psychological, and social issues associated with WFH-E. In particular, environmental characteristics such as sufficient space, access to natural light, and the quality of digital infrastructure were identified as key factors related to worker well-being and productivity. Furthermore, domestic interruptions, social isolation, long working hours, and blurred work-life boundaries were frequently associated with increased stress and reduced job satisfaction.⁸ It has also been noted that an improper workstation environment leads to poor posture, resulting in a high incidence of musculoskeletal symptoms such as shoulder stiffness, low back pain, and neck pain.⁹

The transition from office-based to home-based work, accompanied by suboptimal home interior spaces, has contributed to the increase in physical ailments among telecommuters.¹⁰ Maintaining the health of telecommuters requires WFH-E assessment and the establishment of appropriate working conditions based on these assessments. This is a critical public and occupational health issue. The World Health Organization and the International Labor Organization have emphasized the importance of developing effective educational systems to evaluate and enhance telework environments from an ergonomic standpoint.¹¹

Evaluating and improving the WFH-E presents considerable challenges. Because most telecommuting occurs at home,¹² the home interior space, comprising diverse interior design elements such as lighting, furniture, building materials, and color, is inherently individualized. Moreover, the private nature of the home makes it difficult for employers or professionals to manage or monitor the work environment, unlike in office settings. Consequently, workers are often responsible for environmental management and maintenance. A Japanese study revealed that most companies implementing telework did not assess the WFH-E at the time of introduction.¹³ This highlights the necessity for assessment methods that can be conducted by both external professionals and teleworkers, along with corresponding improvement strategies.

The pandemic transformed the home environment into a concurrent work environment. Although a trend toward returning to office-based work now exists, a substantial number of workers continue to prefer home-based or hybrid work arrangements. Therefore, ensuring that the home environment is appropriately designed as a healthy work setting remains an important issue for health promotion.

Therefore, the aim of this scoping review was to identify current methods and items used to assess the WFH-E and to examine its association with health- and work-related outcomes, contributing to the maintenance of telecommuters’ health.

2. Methods

2.1. Study design

An exploratory literature review was conducted between June and July 2024 to investigate environmental assessment methods in telecommuting settings, using PubMed, Web of Science, and Ichushi. This scoping review was conducted to clarify the assessment methods and items used for the WFH-E and to explore their associations with health- and work-related outcomes, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.¹⁴

2.2. Literature search

Both English and Japanese search strategies were used in this study, and the literature search was conducted on August 2, 2024. An additional search was conducted on October 14, 2025, during the process of the revision in response to the reviewers’ comments.

The English search terms included (“work from home” or “teleworking” or “remote work”) and (“environment” or “condition”) and (“assessment” or “evaluation” or “checklist”), whereas searches in Japanese databases (eg, Ichushi-Web) used equivalent Japanese keywords to identify potentially relevant literature not indexed in international databases. The search strategy is shown in Appendix 1.

2.3. Selection of studies

The inclusion criteria were as follows: (1) studies in which home telecommuting environments were evaluated; (2) articles written in English or Japanese; and (3) articles published between 2010 and 2024. The exclusion criteria were as follows: (1) studies in which outdoor environments were evaluated; and (2) studies of older adults (aged 65 and over) or animals.

Screening was conducted using Rayyan to enhance efficiency.¹⁵ During primary screening, 2 independent reviewers (M.O. and Y.Y.) screened titles and abstracts based on the eligibility criteria. During secondary screening, the full texts of selected articles were reviewed in detail to determine their inclusion. Discrepancies between reviewers were resolved through discussion. Three supervisors (T.Y., S.A., and Y.F.) provided guidance and supervision during the selection process.

2.4. Data extraction

Data extraction was conducted in accordance with the PRISMA-ScR guidelines. The extracted information included the following: author, study design (cross-sectional or longitudinal), year of publication, year of survey, study region, study purpose, target population/sample size, type of assessment (subjective or objective), assessment method, assessment scale, assessment tools, specific assessment items, and associations with health- and work-related outcomes. Subjective assessment was defined as self-assessment by participants based on factors such as satisfaction, comfort, or perceived adequacy. Objective assessment refers to evaluations conducted by third parties using tools such as measurement instruments, images, or video data.

Based on previous studies linking interior design elements to physical and mental health disorders,^16–21 18 assessment items across 9 domains were identified: lighting, layout, furniture, building material, greenery, color, thermal condition, odor, and sound. The first 6 were classified as direct interior design elements, and the remaining 3 as indirect elements. Three items were evaluated in the lighting domain: artificial lighting, natural lighting, and glare; 2 in the layout domain: floor plan (including room type) and space size; 7 in the furniture domain: chair, desk, other furniture, desk space, monitor, mouse/keyboard, and type of personal computer; and the remaining 6 domains—building material, greenery, color, thermal condition, odor, and sound—each comprised a single item.

Additionally, information regarding the quality of the extracted papers was evaluated using a proprietary assessment criterion. The following 6 items were used to evaluate quality, based on the criteria for systematic reviews^22–24: (1) it is a longitudinal study; (2) the participants are a representative group (workers who regularly telework); (3) the sample size is adequate (evaluation criterion: sample size ≥100); (4) the response rate is adequate (evaluation criterion: response rate ≥50%); (5) outcomes (health- and work-related indicators) are measured using established methods; and (6) confounding factors are statistically adjusted (potential confounding factors are measured and considered in the analysis).

Data extraction was conducted by 2 reviewers (M.O. and Y.Y.), with final confirmation provided by the supervisors (T.Y., S.A., and Y.F.).

3. Results

3.1. Study selection and summary of accepted literature

A flowchart illustrating the literature selection process is presented in Figure 1. A total of 1585 articles were identified from PubMed, 45 from Web of Science, 30 from Ichushi, and 41 from manual searches (32 was duplicated). We excluded 1606 articles based on title and abstract screening. Following full-text review, an additional 26 articles were excluded, resulting in the final inclusion of 37 studies.

Figure 1.

PRISMA flow diagram of the literature search and selection process.

3.2. Characteristics of the included studies

Table 1 presents a summary of the 37 studies included in this review. The United States had the highest number of publications (n = 8), followed by Japan (n = 7) and Spain (n = 4), with additional studies conducted in other Asian and European countries. Participants in the included studies were desk workers who engaged in telecommuting at least once a week. Sample sizes ranged from 30 to 12 774.^25,26 Several studies involved the same participant population, despite being reported in different articles.^27–30

Table 1.

Summary of included studies on work-from-home environment (WFH-E) assessments.

Ref. no.	Authors	Study country	Study year	Research design	Subjects	WFH frequency/working hours	Subjective assessment	Objective assessment	Objective evaluation tool	Assessment of health/productivity
33	El Kadri, et al	Brazil	2020	Cross-sectional	55 employees of a labor forum	Weekly working hours 25-48 h (mean 38.1 h)		✓	ROSA-Br (ergonomic risk, assessed via video)	Job stress and musculosketetal symptoms
40	Gerding, et al	USA	2020	Cross-sectional	843 university employees	>1 h continuous work without break	✓		—	Stress/tiredness and discomfort
31	Cuerdo-Vilches, et al	Spain	2020	Cross-sectional	1271 anonymous teleworkers	—	✓	✓	Photovoice (photos, tags, contextual questions)	—
10	Radulović, et al	Croatia	2020	Cross-sectional	232 telecommunications company workers	WFH for 8 mo; >52% worked longer than in-office	✓		—	Pain
34	Kawakubo, et al	Japan	2021	Cross-sectional	198 employees of an equipment manufacturer	>80% worked from home ≥4 d/wk for ~10 mo	✓	✓	Temperature and humidity logger (KT-255 U)	Productivity
26	Matsugaki, et al	Japan	2020	Cross-sectional	12 774 anonymous desk workers	WFH frequency: ≥4 d (14.6%), 2-3 d (7.5%), <1 d (6.8%), almost none (71.1%)	✓		—	Low back pain and mental health
41	Galindo-Romero, et al	Spain	2021	Cross-sectional	198 presbyopic computer workers	59.1% used PC ≥6 h/d; 36.9% were WFH	✓		—	Computer vision syndrome–related symptoms
42	Chim and Chen	Hong Kong	2022	Cross-sectional	232 homeworkers	WFH frequency: ≥5 d/wk was the largest group (39.4%)	✓		—	Musculoskeletal discomfort
36	Cousins, et al	Canada	2021	Longitudinal	297 homeworkers	—	✓		—	Musculoskeletal discomfort
43	Matsugaki, et al	Japan	2020	Cross-sectional	3663 telecommuting workers	≥4 d/wk during COVID-19 third wave	✓		—	Low back pain
44	Garcia, et al	Ecuador	2020	Cross-sectional	201 staff of an academic institution	54.9% of office workers WFH ≥8 h/d; 47.1% ≥5 d/wk	✓		—	Physical discomfort
45	Sato, et al	Japan	2020	Cross-sectional	2537 telecommuting workers	≥4 d/wk	✓		—	Shoulder pain
37	Young, et al	USA	2020 to 2021	Longitudinal	206 office workers	≥4 d/wk	✓	✓	Awair Omni unit (CO2, PM2.5, temperature, RH, heat index); custom smartphone application cognitive tests	Cognitive function
6	Okawara, et al	Japan	2020 to 2021	Longitudinal	2530 anonymous homeworkers	≥1 d/mo	✓		—	Work functioning impairment
46	Sasaki, et al	Japan	2020	Cross-sectional	1086 homeworkers among a panel survey	Several days/month (exact number varies)	✓		—	Psychological distress and symptoms
39	Ferreira and Barros	Portugal	2020 to 2021	Cross-sectional	70 teleworkers of an education institution	Full-time WFH during lockdown		✓	DELTA OHM HD32.1, TSI Q-Trak Plus, PPM Formaldemeter htV, Lighthouse Particle Counters	Chronic illness or respiratory/allergic symptoms
35	McAllister, et al	USA	2021	Longitudinal	131 employees of a university	—	✓		—	Discomfort
47	Park, et al	South Korea	2022	Cross-sectional	1093 anonymous homeworkers	—	✓		—	Performance and satisfaction
25	Clèries Tardío, et al	Spain	2021/2022	Cross-sectional	30 workers (26 households)	—		✓	Dataloggers (T, RH, CO2); daily/final surveys	—
27	Awada, et al	USA	2020	Cross-sectional	988 anonymous homeworkers	Full-time WFH; hours not specified	✓		—	Productivity
28	Awada, et al.	USA	2020	Cross-sectional	988 anonymous homeworkers	Full-time WFH; hours not specified	✓		—	Physical and mental well-being
48	Muñoz-González, et al	Spain	2020	Cross-sectional	838 historic house owners	—	✓	✓	Daysim 4.0 calculation engine (simulation); online questionnaire	Disorders
38	Okawara, et al	Japan	2020	Cross-sectional	5760 homeworkers in a cohort study	≥1 d/mo	✓		—	Work functioning impairment
49	Salamone, et al	Italy	2020	Cross-sectional	330 civil servants and private employees	71% spent 6-9 h/d at workspace	✓		—	Productivity
32	Jaimes Torres, et al	Mexico	2020	Cross-sectional	956 anonymous samples	WFH/remote study hours evaluated; exact hours not detailed	✓	✓	Photo	Performance
50	Xiao, et al	USA	2020	Cross-sectional	988 anonymous homeworkers	Hours not specified	✓		—	Physical and mental well-being
51	Yang, et al	USA	2020	Cross-sectional	648 anonymous homeworkers	Comparison of WFH before vs during COVID; hours not detailed	✓		—	Productivity, satisfaction, and work-life balance
52	Bergefurt, et al	Netherlands	2020	Cross-sectional	1219 office workers	Contract hours 36 h/wk; WFH hours last 2 wk = 38 h	✓		—	Satisfaction and mental health
30	Ekpanyaskul, et al	Thailand	2020	Cross-sectional	869 anonymous homeworkers	Newly began WFH; hours not specified	✓		—	Physical and psychosocial health
57	Guo and Chen	USA	2020	Cross-sectional	204 workers in offices and at home	≥4 d/wk for WFH group	✓		—	—
54	Ortiz and Bluyssen	Netherlands	2020	Cross-sectional	502 office workers	78% reported home as main workplace; hours not detailed	✓		—	Medical history
29	Ekpanyaskul and Padungtod	Thailand	2020	Cross-sectional	869 anonymous homeworkers	Newly WFH; hours not detailed	✓		—	Stress, productivity and well-being
56	Seva, et al	Philippines	2020	Cross-sectional	352 homeworker using computers	—	✓		—	Stress and productivity

Table 1.

Summary of included studies on work-from-home environment (WFH-E) assessments (Including students).

Ref. no.	Authors	Study country	Study year	Research design	Subjects	WFH frequency/working hours	Subjective assessment	Objective assessment	Objective evaluation tool	Assessment of health/productivity
53	Guo, et al	China	2020	Cross-sectional	189 professionals and students	—	✓		—	Productivity
58	Hiyasat, et al	UAE	2021	Cross-sectional	113 students and employees in a university	≥4 d/wk	✓		—	—
61	Vasquez, et al	Brazil	2020/2021	Cross-sectional	694 professionals and students	Mixed; many involved in remote study/work; hours not detailed	✓	✓	Photographs (for view analysis)	—
55	Mura, et al	Italy	2021	Cross-sectional	521 students and 463 workers	WFH strongly recommended; hours not detailed	✓		—	Engagement, stress, and satisfaction

Abbreviations: PC, personal computer; PM2.5, particulate matter 2.5 μm in diameter; RH, relative humidity; T, temperature; WFH, working from home.

Four studies employed a longitudinal research design. The remaining studies were cross-sectional. Two cross-sectional studies were conducted using mixed methods, combining quantitative and qualitative data.^31,32

3.3. Assessment methods

Of the 37 studies reviewed, 34 involved subjective assessments, 9 involved objective assessments, and 6 incorporated both. Subjective assessments were conducted primarily via online questionnaires. Objective assessments included the measurement of air quality and illumination using instruments, as well as analysis of image and video data of telecommuting environments.

Four studies employed standardized scales: the Rapid Office Strain Assessment,³³ which provides objective assessments of furniture and equipment such as chairs, monitors, phones, keyboards, mice, seat height, and arm support based on images; the Telework Space Adaptation Index,³¹ which assesses telework space adequacy by coding image-based indicators, including presence of roommates, a dedicated workspace, room size, temperature, daylight, artificial lighting, furniture, and views; the CASBEE (Comprehensive Assessment System for Built Environment Efficiency) Health Checklist Short Version,³⁴ which evaluates the health aspects of built environments through 22 items covering thermal condition, lighting, sound, and air quality; and the Workstation Score,³⁵ a newly developed tool for rating workstation quality, focusing on office chairs, monitors, keyboards, and mice.

3.4. Associations with health and work-related outcomes

Table 1 also shows that associations between the WFH-E and health- and work-related outcomes were examined in 32 studies, among which 31 revealed statistically significant relationships.^{6,10,26–30,32–38,40–56} Conversely, 5 studies did not examine associations with the same specific outcomes.^{25,31,57,58,61} Health-related outcomes varied, with musculoskeletal discomfort and stress being the most frequently reported. Work-related outcomes included productivity, satisfaction, comfort/discomfort, and work-life balance. Eleven studies revealed associations with stress, psychosomatic illness, and other mental disorders.^{26,28–30,40,46,50,52,54–56} Eight studies revealed associations with both physical and mental health outcomes.^{26,28–30,40,50,54,56} Four studies revealed associations with both health indicators and work-related outcomes.^29,30,52,56 Significant associations with work-related outcomes were reported in all of these studies.^{6,27,29,30,32,34,37,38,47,49,51–53,56} Two studies employed the Work Functioning Impairment Scale as a measure of work-related outcomes.^6,38

3.5. Targets of the telework environment assessment

Table 2 summarizes the assessment items for telecommuting environments in the reviewed studies. Lighting was the most frequently assessed item, followed by thermal condition and noise. The category with the largest number of sub-items was furniture, including computer-related components, followed by lighting items. Conversely, color, building material, and greenery were the least frequently evaluated. Items that could be objectively assessed using instruments were evaluated more frequently compared with elements that were difficult to measure objectively. Overall, a notable imbalance was observed in the distribution of environmental assessment items across studies.

Table 2.

Assessment items for telecommuting environments: 18 items across 9 domains.

Ref. no.	Lighting	Natural light	Glare a	Concentration space b	Foot space	Chair	Desk	Monitor/display	PC type	Keyboard/mouse/input devices	Furniture c	Desktop space	Ventilation	Noise	Odor d	Material e	Green f	Color
33						✓		✓		✓
40			✓			✓	✓	✓	✓	✓	✓
31	✓	✓		✓	✓	✓	✓	✓	✓	✓	✓		✓	✓		✓	✓
10				✓		✓	✓	✓	✓	✓				✓	✓
34	✓					✓	✓						✓	✓	✓
26	✓				✓							✓	✓
41	✓				✓			✓	✓			✓
42				✓		✓	✓	✓	✓	✓
36						✓	✓	✓	✓	✓
43	✓			✓	✓	✓	✓					✓	✓
44	✓		✓			✓	✓	✓	✓	✓	✓	✓		✓
45	✓			✓	✓	✓	✓				✓	✓	✓
37													✓
6	✓			✓	✓	✓	✓				✓	✓	✓	✓
46	✓			✓									✓	✓	✓
39													✓
35	✓			✓		✓	✓	✓	✓	✓	✓
47														✓
25	✓												✓	✓
27	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓		✓	✓
28	✓	✓	✓										✓	✓
48	✓	✓
38	✓			✓	✓	✓	✓				✓	✓	✓	✓
49	✓		✓	✓		✓	✓						✓	✓	✓
32		✓		✓	✓		✓						✓	✓
50	✓	✓	✓	✓	✓								✓	✓
51				✓		✓	✓							✓
52	✓	✓		✓	✓								✓	✓			✓
30	✓			✓		✓	✓
57	✓	✓		✓									✓	✓		✓		✓
53	✓	✓	✓	✓									✓	✓
58		✓		✓							✓		✓	✓				✓
54	✓	✓		✓		✓	✓	✓					✓	✓	✓		✓
61	✓	✓	✓													✓
55	✓	✓									✓			✓
29				✓		✓	✓		✓				✓	✓
56						✓	✓	✓	✓	✓
Total	24	13	8	21	11	20	20	12	11	10	10	7	22	22	5	3	3	2

^aGlare refers to visual discomfort caused by bright light or reflections on surfaces like glass or screens.

^bConcentration spaces refer to quiet areas with partitions or private rooms for focused work.

^cFurniture refers to items supporting space and activities, such as storage, sofas, and kotatsu tables, excluding desks and chairs.

^dOdor refers to unpleasant smells or polluted air from the living environment.

^eMaterial refers to substances used in interiors and furniture that affect comfort through texture, warmth, sound, and light.

^fGreen refers to live or artificial plants placed in or visible from a room, including potted and tabletop greenery.

3.6. Evaluation of study quality

The results of the study quality evaluation based on the 6 criteria are shown in Appendix 2. Only 4 longitudinal studies were identified. Twelve studies had representative participants, whereas many studies lacked clear information on telework hours. The majority of studies had a sample size of ≥100. Only 2 studies clearly stated their response rate. Fifteen studies measured health- and work-related outcome indicators using established methods, representing less than half of the total. Confounding factors were considered in 22 studies. No study met all 6 criteria.

4. Discussion

Remote work represents the broadest category of work performed regardless of location, within which ICT-mediated work is defined as telework.¹ A principal subtype of telework is WFH, in which job tasks are carried out in the home environment.^2,3

In this scoping review, we examined 37 studies on telecommuting environments. All included studies were conducted after 2020, indicating that research interest in the WFH-E rapidly increased following the COVID-19 pandemic. More than 90% of the reviewed studies involved subjective assessments, whereas objective assessments were relatively uncommon. The most frequently evaluated items were artificial lighting, thermal conditions, and noise. Conversely, items such as color, greenery, building material, and odor were rarely assessed, highlighting a potential bias in the selection of assessment items. Many studies have shown significant associations between the WFH-E and health- and work-related outcomes, particularly physical discomfort in areas such as the low back and shoulders, which are related to ergonomic factors such as furniture and computer use.

Although this review searched studies published since 2010, all the reviewed studies were based on data collected in 2020 or later. This reflects the rapid increase in the prevalence of WFH arrangements owing to the COVID-19 pandemic, which has brought significant attention to issues associated with home-based work. In Japan, the telecommuting adoption rate rose sharply from 20.2% in 2019 (pre-COVID-19) to 51.9% in 2021 (post-COVID-19). Subsequently, telecommuting, including hybrid styles, has become a normalized work style.¹² The demand for telework remains high among workers,⁵⁹ and the importance of evaluating the WFH-E from the perspective of health protection will remain relevant in the future.

The study sites were primarily located in the Americas, Asia, and Europe. When evaluating the WFH-E, it is essential to consider regional characteristics and differences in housing cultures. Considerable variations exist across countries and regions in terms of housing size, ceiling height, building structure, and lighting conditions.⁶⁰ Among these, lighting conditions are particularly important, both as a critical component of the work environment and as an element that differs substantially by cultural context. In Japan, for instance, it is common to use artificial lighting even during daylight hours, with a general preference for artificial over natural light sources.⁶¹ In densely populated urban areas such as those in Japan, the close proximity of buildings often limits access to natural light, resulting in greater reliance on artificial lighting. Moreover, compared with Western countries, the Japanese tend to prefer bright white light, which may not always be beneficial for health.^62–64 These cultural and structural differences underscore the need for environmental assessment frameworks that incorporate criteria that reflect the characteristics of local living environments.

Most of the reviewed studies involved subjective assessments for 2 main reasons: First, the WFH-E is inherently a private space, making it difficult for external evaluators to intervene. Consequently, workers must rely on their own perceptions to assess their environment. Second, home interior spaces, which are highly personalized and influenced by individual preferences, play a critical role in determining the work environment. Satisfaction and comfort were also affected by these personal factors. Consequently, home interior spaces have traditionally been assessed subjectively.^65,66 However, the COVID-19 pandemic transformed home environments into formal workspaces, and continued reliance on subjective assessments alone may hinder accurate identification of exposure factors. Therefore, establishing objective assessment methods that are less susceptible to personal bias is essential to ensure a minimum quality standard for the WFH-E.

Nine of the reviewed studies involved objective assessments using quantitative methods, such as measurement instruments or visual data (eg, images). Common indicators for objective environmental assessment included illumination, air quality, temperature, humidity, sound, and odor, all of which are measurable using specialized equipment. However, the implementation of such tools in home settings presents logistical challenges, including cost, maintenance, and installation. Recent advancements in ICT and digital tools may offer accessible alternatives, such as smartphone-based assessments or app-driven measurements.

A summary of the 18 assessment items across the 9 domains revealed variability in item selection and combinations across studies. The most frequently assessed items were lighting, spatial layout, furniture, thermal condition, and noise. Traditionally, these elements have been evaluated in office settings as components of the work environment and have been shown to be closely associated with physical discomfort.^67,68 In particular, ergonomic items, such as furniture and computer-related equipment, have been extensively studied in relation to health issues that contribute to physical discomfort among workers.^69–71 Conversely, building material, greenery, color, and odor were among the least frequently assessed items. These elements are more characteristic of home interior spaces than of conventional office settings. Building material, greenery, and color, which are key components of interior design, have been shown to affect visual perception and exert psychological influences as well.⁷² For instance, glass or mirror-finished surfaces may reflect light, potentially contributing to glare. Greenery, in particular, is an important factor not only for preventing negative health effects but also for enhancing positive health outcomes, as it has been shown to influence worker productivity, creativity, and well-being.⁷³ Future assessments of telecommuting environments should go beyond office-based assessment frameworks and establish comprehensive assessment items that incorporate elements of interior design specific to home interior spaces.

Telecommuting environments have been found to influence both physical and mental health. Many studies have been conducted to assess ergonomic conditions and demonstrate associations with physical discomfort. Although the number of studies on the relationship between lighting conditions and health was limited, the association was reported to be significant.^41,45 These findings suggest that, in addition to ergonomic factors, evaluating and improving lighting conditions may contribute to the prevention of physical impairments.

The association between the WFH-E and work-related outcomes was examined in 14 studies, all showing statistical significance. Key exposure factors included lighting, ergonomic design, air quality, odor, and noise. Two studies used the Work Functioning Impairment Scale to measure productivity, indicating that physical discomfort may reduce work performance. These findings highlight the multifaceted interaction between health conditions (both physical and mental) and work-related outcomes. When identifying environmental exposure factors in home interior spaces, it is critical to consider not only health outcomes but also their effects on occupational performance.

This review had a few limitations. First, the literature search was limited to PubMed, Web of Science, and Ichushi and may not have fully captured relevant studies from architectural or engineering disciplines. However, the inclusion of engineering-related studies published in 2024 has partially addressed this limitation. Second, the classification of assessment items was determined independently by the authors, as the included studies did not provide a standardized framework for categorizing the items of the WFH-E assessment. Therefore, the item categorization proposed in this review can be regarded as both provisional and exploratory. Third, many of the reviewed articles did not sufficiently satisfy the criteria for study quality evaluation. This situation stems from telework rapidly becoming widespread under the unique circumstances of the COVID-19 pandemic, which led to research being conducted intensively within a short timeframe. As telework becomes increasingly normalized, higher-quality research is expected to accumulate going forward.

In conclusion, this scoping review included 37 studies on WFH-E published since the onset of COVID-19. Most of these studies were conducted to evaluate environmental factors such as lighting, thermal conditions, noise, and ergonomics, using subjective methods. These factors were significantly associated with both health- and work-related outcomes. However, only a few studies have been conducted to comprehensively assess interior design elements such as color, greenery, and building material, which can promote positive health outcomes. To protect the health and enhance the productivity of telecommuters, it is essential to develop additional objective and comprehensive assessment methods, particularly those that incorporate a broader range of environmental and design-related factors and can inform practical strategies for improving the WFH-E.

This study clarified the importance of environmental assessments for maintaining teleworkers’ health and identified areas for improvement. In subsequent work, we aim to develop a telework environment assessment tool and verify its effectiveness based on the findings obtained, thereby contributing to the effort to address these challenges.

Author contributions

We confirm contributions to the article as follows: Megumi Oda, Takuya Yamada, and Yoshiharu Fukuda: study conception and design; Megumi Oda and Yuu Yoshimori: primary review; Takuya Yamada, Shiho Amagasa, and Yoshiharu Fukuda: supervision of the review; Megumi Oda: draft manuscript preparation; and Yuu Yoshimori, Takuya Yamada, Shiho Amagasa, and Yoshiharu Fukuda: manuscript revision. All authors approved the final version.

Funding

None declared.

Conflicts of interest

No conflicts of interest to declare.

Data availability

This review is based entirely on data extracted from previously published peer-reviewed articles, which are accessible through academic databases such as PubMed, Web of Science, and Ichushi-Web. All relevant references have been included in the bibliography to ensure transparency and reproducibility.