Abstract
Objective
This study aimed to determine whether telecommuting's impact on psychological distress differed depending on the status of workers' cohabiting family members during the COVID‐19 pandemic.
Methods
We collected data from 33 302 workers in Japan through an Internet survey, and included 27 036 valid responses in the analysis. The survey included items on family cohabitation and telecommuting status during the COVID‐19 pandemic. We assessed workers' psychological distress using the Kessler 6.
Results
The psychological distress odds ratios (ORs) were higher for participants who lived with family members requiring care (OR = 1.38, P < .001), and lower for participants living with preschool children (OR = 0.77, P < .001) or a spouse (OR = 0.80, P < .001). Furthermore, odds ratios were higher for participants who worked from home and lived with family members requiring care or preschool children (OR = 1.52, P = .002; OR = 1.28, P = .028). Stratified by the presence or absence of family members living with them, psychological distress was higher for telecommuters with family members requiring care, preschool children, or elementary school children.
Conclusion
The association between telecommuting and psychological distress varies, depending on workers' living situation with family members.
Keywords: caregiving, cohabiting family, COVID‐19 pandemic, psychological distress, telecommuting
1. INTRODUCTION
The COVID‐19 pandemic has progressed globally since the first case was reported in December 2019; as of July 2022, approximately 550 million cases have been confirmed, with more than 6 million deaths worldwide. 1 Japan's first COVID‐19 infection was detected in January 2020; the number of infected people subsequently increased, especially in urban areas, and the infection rapidly spread to rural areas. The Japanese government declared a state of emergency in April 2020, asking people to stay home and close their workplaces. The broad movement restrictions implemented to suppress the pandemic reduced economic activity, which worsened working environments and corporate performance. This was followed by a period of infection spread, known as the second and third waves. 2 This study was conducted during the third wave, when the number of infected people reached record daily highs.
Workplaces and commuting provide high‐risk opportunities for infection spread. 3 Telecommuting was expected to decrease the risk of contracting COVID‐19 4 ; therefore, telecommuting policies were promoted to control the pandemic through social distancing. 5 Telecommuting implementation in Japan increased from 26.7% in March 2020 to 52.7% in May 2020. 6 The pandemic increased telecommuting worldwide, and it continues to be widespread globally. 7 , 8
Telecommuting has differing impacts on workers' personal and professional lives. Positive effects include improved work–life balance, increased autonomy, more sleep time, increased productivity, and improved morale and job satisfaction 9 , 10 resulting from reduced commuting time and increased flexibility regarding where and when work is performed. Furthermore, studies have reported a positive relationship between telecommuting and organizational outcomes, including increased productivity, higher retention rates, stronger organizational commitment, and improved organizational performance. 11
In contrast, telecommuting also has concerning effects, such as negative impacts on physical health, mental stress, and productivity. Telecommuting can involve overwork, tight deadlines, long work hours, and lack of rest periods, all of which are associated with fatigue, impaired mental and physical health, and reduced productivity. 10 Moreover, long hours of continuous computer work at home can lead to musculoskeletal problems in the neck, shoulders, wrists, hands, and lower back owing to repetitive motion and unnatural posture. 10 In addition, reduced supervisor and coworker support resulting from fewer opportunities for direct communication can lead to loneliness, isolation, anxiety, irritability, and depressed mood. 10 , 12 Telecommuting has also been associated with decreased sleep quality and mood disorders. 10 Other telecommuting factors that affect productivity include the availability of suitable equipment and workspace, a stable Internet connection and power supply, support from leaders, roles and responsibilities in the company, and clarity of collaborators regarding the work. 13
Cohabiting with family members may also affect telecommuting workers' health, stress, and productivity. Telecommuting blurs the boundary between work and home, which could lead to work–family conflicts, such as work interruptions to manage family demands and family life disruptions stemming from after‐hours work issues 14 ; the difficulty of separating work and personal life when telecommuting may be a significant factor in psychological distress. 15 For example, working women with children experience decreased happiness and work performance when caring for their children while working from home. 16 It is important to support telecommuters and not force them to do double work (caring and working), because caring for dependents while working is difficult. 17
Moreover, many workers who telecommuted during the COVID‐19 pandemic had to work from home without modifying their family environment, because situational demands, rather than personal choice, forced them to telecommute. The COVID‐19 pandemic closed or restricted the use of schools, daycare centers, and nursing homes; consequently, children and other family members requiring care were at home, and many workers needed to attend to these family members. Therefore, we hypothesized that workers living with children or family members who require care would experience increased psychological distress related to telecommuting. This study aimed to determine the impact of telecommuting on workers' psychological distress while living with family members needing care, preschool or elementary school children, or a spouse during the COVID‐19 pandemic.
2. METHODS
2.1. Study design and participants
We conducted an online survey for the Collaborative Online Research on the Novel‐Coronavirus and Work (CORoNaWork) project from December 22 to 26, 2020. The protocol for this cross‐sectional study was published previously in a peer‐reviewed journal. 18 Participants included workers with full‐time jobs at the time of the study. The survey was conducted by Cross Marketing Inc., which has 4.7 million registered monitors. Invitations were sent via email to 605 381 individuals; 55 045 responded to the initial screening questions, and 33 302 met inclusion criteria (related to worker status, region, sex, and age) and completed the survey. However, 6051 respondents were excluded because of invalid responses or response errors. Exclusion criteria were designed to identify invalid responses, including extremely short response times (6 min), extremely low reported weight (<30 kg) and height (<140 cm), inconsistent responses to similar questions throughout the survey (e.g., marital status or region of residence), and incorrect responses to validity questions (e.g., “Please choose the third largest number from the following five numbers”). As reported in the published study protocol, some excluded group characteristics differed from those of the included group. 18 In total, 27 036 valid responses were eligible for analysis. Participants were not compensated for participating in the survey.
This study was approved by the Ethics Committee of the University of Occupational and Environmental Health, Japan (reference No. R2‐079 and R3‐006). All participants provided informed consent after completing a form on the survey website. Data are not available owing to ethical restrictions and the need to preserve participants' anonymity.
2.2. Assessments
2.2.1. Family cohabiting situation
We surveyed whether workers had preschool or elementary school children, family members requiring care, or a spouse living with them (e.g., “Do you have a preschooler living with you?”).
2.2.2. Psychological distress
We used a validated Japanese version of the Kessler 6 (K6) scale to assess psychological distress, 19 , 20 and assigned a K6 score of 5 or higher as the psychological distress cut point. 20
2.2.3. Covariates
Covariates included age, sex, marital status, job type, annual equivalent household income, education, current smoking status, alcohol consumption, family cohabiting situation, telecommuting, and telecommuting preference.
2.3. Statistical analysis
We used a multilevel logistic model to estimate odds ratios (ORs) for psychological distress related to working from home while living with family members requiring care, preschool children, elementary school children, or a spouse, and to assess differences in participants' psychological distress based on the family cohabiting situation. We further estimated psychological distress ORs related to telecommuting, stratified by living with family members requiring care, preschool children, elementary school children, or a spouse.
The multivariate models were adjusted for age, sex, marital status, job type, annual equivalent household income, education, current smoking status, alcohol consumption, and telecommuting preference. All analyses were performed using Stata Statistical Software Release 17 (StataCorp LLC).
3. RESULTS
Table 1 presents participant characteristics. Of 27 036 participants, 2802 lived with their preschool children; of these, 512 (18.3%) worked from home and 1156 (41.3%) reported experiencing psychological distress. Furthermore, 1223 participants lived with family members requiring care; of these, 377 (30.8%) worked at home and 616 (50.4%) experienced psychological distress.
TABLE 1.
Characteristics of participants who live with preschool children or family members requiring care.
| Factors | Without preschool children | With preschool children | Without family members requiring care | With family members requiring care |
|---|---|---|---|---|
| N | 24 234 | 2802 | 25 813 | 1223 |
| Age, median (interquartile range) | 49.0 (42.0, 56.0) | 37.0 (32.0, 43.0) | 48.0 (39.0, 55.0) | 52.0 (43.0, 58.0) |
| N (%) | N (%) | N (%) | N (%) | |
|---|---|---|---|---|
| Sex, male | 12 722 (52.5%) | 1092 (39.0%) | 13 154 (51.0%) | 660 (54.0%) |
| Marital status, married | 12 429 (51.3%) | 2600 (92.8%) | 14 451 (56.0%) | 578 (47.3%) |
| Job type | ||||
| Mainly desk work | 12 190 (50.3%) | 1278 (45.6%) | 12 854 (49.8%) | 614 (50.2%) |
| Jobs mainly involving interpersonal communication | 6074 (25.1%) | 853 (30.4%) | 6611 (25.6%) | 316 (25.8%) |
| Mainly labor | 5970 (24.6%) | 671 (23.9%) | 6348 (24.6%) | 293 (24.0%) |
| Annual equivalent household income | ||||
| 0.5–2.49 million yen | 5137 (21.2%) | 573 (20.4%) | 5324 (20.6%) | 386 (31.6%) |
| 2.5–3.74 million yen | 6624 (27.3%) | 926 (33.0%) | 7233 (28.0%) | 317 (25.9%) |
| 3.75–4.89 million yen | 5763 (23.8%) | 862 (30.8%) | 6289 (24.4%) | 336 (27.5%) |
| More than 4.90 million yen | 6710 (27.7%) | 441 (15.7%) | 6967 (27.0%) | 184 (15.0%) |
| Education | ||||
| Junior high school | 338 (1.4%) | 30 (1.1%) | 352 (1.4%) | 16 (1.3%) |
| High school | 6391 (26.4%) | 562 (20.1%) | 6640 (25.7%) | 313 (25.6%) |
| Vocational school/ College/University/ Graduate school | 17 505 (72.2%) | 2210 (78.9%) | 18 821 (72.9%) | 894 (73.1%) |
| Current smoking status | 6464 (26.7%) | 540 (19.3%) | 6615 (25.6%) | 389 (31.8%) |
| Alcohol consumption | ||||
| 6–7 days per week | 5236 (21.6%) | 438 (15.6%) | 5386 (20.9%) | 288 (23.5%) |
| 4–5 days per week | 1882 (7.8%) | 195 (7.0%) | 1946 (7.5%) | 131 (10.7%) |
| 2–3 days per week | 2976 (12.3%) | 290 (10.3%) | 3102 (12.0%) | 164 (13.4%) |
| Less than 1 day per week | 4092 (16.9%) | 455 (16.2%) | 4367 (16.9%) | 180 (14.7%) |
| Almost none | 10 048 (41.5%) | 1424 (50.8%) | 11 012 (42.7%) | 460 (37.6%) |
| Family cohabiting situation | ||||
| With family members requiring care | 1097 (4.5%) | 126 (4.5%) | 0 (0.0%) | 1223 (100.0%) |
| With preschool children | 0 (0.0%) | 2802 (100.0%) | 2676 (10.4%) | 126 (10.3%) |
| With elementary school children | 1888 (7.8%) | 820 (29.3%) | 2569 (10.0%) | 139 (11.4%) |
| With spouse | 11 901 (49.1%) | 2553 (91.1%) | 13 904 (53.9%) | 550 (45.0%) |
| Telecommuting | 5248 (21.7%) | 512 (18.3%) | 5383 (20.9%) | 377 (30.8%) |
| Telecommuting preference | 7470 (30.8%) | 1128 (40.3%) | 8153 (31.6%) | 445 (36.4%) |
| Psychological distress (K6 ≥ 5) | 9661 (39.9%) | 1156 (41.3%) | 10 201 (39.5%) | 616 (50.4%) |
Table 2 shows psychological distress ORs related to participants' family cohabiting situation and telecommuting status, as estimated by the logistic model. Psychological distress ORs of workers who lived with family members requiring care were significantly higher than those who did not (OR = 1.45, 95% confidence interval [CI] 1.26–1.68, P < .001). A similar result was obtained in the multivariate analysis (OR = 1.38, 95% CI 1.19–1.59, P < .001). In contrast, the psychological distress ORs for workers who lived with preschool children or a spouse were significantly lower than those of workers who did not (OR = 0.81, 95% CI 0.73–0.89, P < .001 and OR = 0.74, 95% CI 0.70–0.79, P < .001, respectively). The same was true in the multivariate analysis (OR = 0.77, 95% CI 0.69–0.85, P < .001 and OR = 0.80, 95% CI 0.75–0.86, P < .001, respectively). In the multivariate analysis, psychological distress ORs were higher for workers who telecommuted than for those who did not (OR = 1.18, 95% CI 1.04–1.34, P = .009). Psychological distress ORs were also higher for those who worked at home and lived with family members requiring care, or with preschool children (OR = 1.52, 95% CI 1.18–1.97, P = .001, and OR = 1.27, 95% CI 1.02–1.58, P = .031, respectively). The multivariate analysis showed a similar pattern (OR = 1.52, 95% CI 1.17–1.97, P = .002; OR = 1.28, 95% CI 1.03–1.59, P = .028).
TABLE 2.
Association between family cohabiting situation, telecommuting, and psychological distress.
| Age–sex adjusted | Multivariate a | |||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | P‐value | OR | 95% CI | P‐value | |||
| Family cohabiting situation | ||||||||
| Without family members requiring care | Reference | Reference | ||||||
| With family members requiring care | 1.45 | 1.26 | 1.68 | <.001 | 1.38 | 1.19 | 1.59 | <.001 |
| Without preschool children | Reference | Reference | ||||||
| With preschool children | 0.81 | 0.73 | 0.89 | <.001 | 0.77 | 0.69 | 0.85 | <.001 |
| Without elementary school children | Reference | Reference | ||||||
| With elementary school children | 1.02 | 0.93 | 1.13 | .641 | 0.95 | 0.86 | 1.04 | .271 |
| Without spouse | Reference | Reference | ||||||
| With spouse | 0.74 | 0.70 | 0.79 | <.001 | 0.80 | 0.75 | 0.86 | <.001 |
| Without telecommuting | Reference | Reference | ||||||
| With telecommuting | 1.05 | 0.93 | 1.19 | .413 | 1.18 | 1.04 | 1.34 | .009 |
| Interaction between family cohabiting situation and telecommuting | ||||||||
| Telecommuting × with family members requiring care | 1.52 | 1.18 | 1.97 | .001 | 1.52 | 1.17 | 1.97 | .002 |
| Telecommuting × with preschool children | 1.27 | 1.02 | 1.58 | .031 | 1.28 | 1.03 | 1.59 | .028 |
| Telecommuting × with elementary school children | 1.18 | 0.95 | 1.45 | .132 | 1.19 | 0.96 | 1.47 | .109 |
| Telecommuting × with spouse | 0.93 | 0.82 | 1.06 | .280 | 0.91 | 0.80 | 1.03 | .140 |
Abbreviations: CI, confidence interval; OR, odds ratio.
Adjusted for age, sex, marital status, job type, annual equivalent household income, education, current smoking status, alcohol consumption, and telecommuting preference.
Table 3 shows telecommuting workers' psychological distress ORs stratified by whether they lived with a family member requiring care, preschool children, elementary school children, or a spouse. Workers who lived with family members requiring care, preschool children, or elementary school children had higher psychological distress ORs than those who did not. The multivariate analysis showed a similar trend. Psychological distress ORs among telecommuting workers did not differ according to whether they lived with a spouse, and the multivariate analysis showed a similar trend.
TABLE 3.
Association between family cohabiting situation and psychological distress during telecommuting.
| Age–sex adjusted | Multivariate a | |||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | P‐value | OR | 95% CI | P‐value | |||
| Stratified by existence of family members requiring care | ||||||||
| Telecommuting without a family member requiring care | 0.99 | 0.93 | 1.06 | .791 | 1.09 | 1.02 | 1.17 | .015 |
| Telecommuting with a family member requiring care | 1.52 | 1.18 | 1.96 | .001 | 1.53 | 1.15 | 2.04 | .004 |
| Stratified by existence of preschool children | ||||||||
| Telecommuting without preschool children | 1.02 | 0.95 | 1.08 | .629 | 1.10 | 1.02 | 1.18 | .009 |
| Telecommuting with preschool children | 1.23 | 1.01 | 1.50 | .042 | 1.26 | 1.02 | 1.56 | .031 |
| Stratified by existence of elementary school children | ||||||||
| Telecommuting without elementary school children | 1.01 | 0.95 | 1.08 | .791 | 1.09 | 1.02 | 1.17 | .012 |
| Telecommuting with elementary school children | 1.24 | 1.02 | 1.50 | .028 | 1.24 | 1.01 | 1.52 | .039 |
| Stratified by existence of spouse | ||||||||
| Telecommuting without spouse | 1.03 | 0.95 | 1.13 | .452 | 1.11 | 1.01 | 1.23 | .029 |
| Telecommuting with spouse | 1.02 | 0.94 | 1.11 | .663 | 1.11 | 1.01 | 1.21 | .027 |
Note: Reference for comparison is without telecommuting.
Abbreviations: CI, confidence interval; OR, odds ratio.
Adjusted for age, sex, marital status, job type, annual equivalent household income, education, current smoking status, alcohol consumption, and telecommuting preference.
4. DISCUSSION
This study found that workers who telecommuted during the COVID‐19 pandemic experienced higher levels of psychological distress than those who did not. The results also showed a significant interaction between workers' family cohabiting situation and telecommuting, where the degree of psychological distress varied, depending on whether the workers lived with family members requiring care or with preschool children. Telecommuting workers who resided with family members requiring care or with children reported higher psychological distress than those who did not. These results reveal psychological distress associated with telecommuting from the perspective of workers' family cohabiting situation.
The relationship between telecommuting and psychological distress may vary by family cohabiting situation because of conflicts in family relationships. Telecommuting can increase the conflict between work and family because it is difficult to establish boundaries between professional and personal lives. The increased flexibility offered by telecommuting may also result in increased stress related to family responsibilities, difficulty separating work and home, and family conflicts. 10 , 14 , 21 Telecommuting workers often need to interrupt work activities to deal with family demands and frequently continue to participate in work roles and activities after work hours. 14 These situations may involve “family–work conflicts” when family responsibilities affect work activities and “work–family conflicts” when work obligations affect family care. 22 The blurred boundaries can lead to longer work hours, less spare time, and burnout. 23
This study showed that living with a family member in need of care prompted an association between telecommuting and psychological distress. Soubelet‐Fagoaga et al. showed that workers with caregiving responsibilities—especially women who telework—experience significant difficulties with balancing work and home life. The inability to balance care and telework creates particularly stressful situations. 17 Caregivers who telecommute have significantly higher stress levels and significantly lower satisfaction with telecommuting than non‐caregivers, and nearly 30% of caregivers cite their home environment as the biggest challenge to telecommuting. 24
This study also found that preschool children's presence strengthens the association between telecommuting and psychological distress. Before the COVID‐19 pandemic, telecommuting workers with children scored higher on satisfaction and family well‐being than those without children; however, during the COVID‐19 pandemic, telecommuting workers with children were not significantly more satisfied with their telecommuting. 9 , 25 Reports showed that, during the COVID‐19 lockdown, telecommuting resulted in increased domestic difficulties, such as school closure, childcare, and child health responsibilities; increased housework; blurred boundaries between home and work; and longer working hours. Mental health issues emerged, including anxiety, depression, fatigue, burnout, and lack of an outlet for stress. 26 Furthermore, approximately half of telecommuting women with children under age 18 reported that their children's age affected their performance. 27
Telecommuting challenges associated with children and family members requiring care were further emphasized during the COVID‐19 pandemic period, when day‐care centers, nursing homes, and elderly day services were closed. This may have impaired workers' control over their jobs, causing distress related to caring for family members or preschool children who lived with them. 28 , 29 In the absence of an appropriate workspace, workers and children must adapt to sharing the same work and childcare environment; connectivity issues and lack of focus can increase the challenge. 26 Moreover, middle‐aged and older adults who work from home full time while providing emotional and financial support to their minor children, may simultaneously be providing physical, financial, and legal support to their older parents. This can lead to high stress and long work hours as they juggle the demands of caring for both their children and their parents. 30 Although these workers could previously refresh themselves by going to their workplace, telecommuting made this difficult; many were then forced to simultaneously work and care for family members at home. The burden of family caregiving has been shown to cause psychological distress and loneliness 31 , 32 ; those who live with family members who require care are even more likely to experience distress related to caregiving. 33
Our findings indicate that telecommuting workers who live with family members requiring care or preschool children are likely to experience psychological distress. Several studies have evaluated the impact of telecommuting on mental health, but the conclusions have been inconsistent. 12 , 34 , 35 , 36 To the best of our knowledge, this is the first study to examine the impact of telecommuting by considering the family's cohabitation status. Studies conducted before the COVID‐19 pandemic showed that telecommuting's flexibility gives workers greater control over their lives and improves life–work balance 37 , 38 ; therefore, regular telecommuters showed fewer work–family conflicts and fewer stressors. 21 , 39 In addition, time spent with family was believed to contribute to well‐being through social integration, increased self‐importance, and easier access to social support. 40 There are no previous reports of telecommuting during other pandemics, such as the severe acute respiratory syndrome (SARS) or the Middle East respiratory syndrome (MERS) pandemics; therefore, we could not make direct comparisons. However, there may be similarities among respiratory infections that lead to global pandemics. COVID‐19 emerged unexpectedly, leaving companies and workers inadequately prepared for telecommuting, which may have contributed to our findings.
Most companies do not have telecommuting work rules, and some have no online access to company resources. Many workers were forced to telecommute because they needed to care for family members who lived with them, but many did not have space to perform their work or lived in an environment that was not optimal for work. Therefore, it is important to consider the work environment and family situation when introducing telecommuting. Furthermore, it is necessary to understand the psychological distress workers face when working from home and provide them with the option of working in the office to obtain psychological support. Companies should also consider measures to reduce distress experienced by workers who live with family members requiring care when working from home. It can be difficult to separate work and personal lives during telecommuting; therefore, to separate work and home in relation to time and space, it may be necessary to hang up the work phone at the end of the day, avoid receiving calls or calling outside of work hours, and to secure a home office. Telecommuting may also affect workers' spare time; therefore, it may be helpful to establish routines for regular eating, sleeping, and exercise, to prevent overwork and mental anguish resulting from less resting time. After implementing infection control measures, continuing business operations that provide social service resources, such as nursing care and childcare, would also help support telecommuting workers living with someone who needs care.
This study has several limitations. First, because this was an Internet survey, selection bias was inevitable. To reduce bias as much as possible, we selected a diverse sample of participants in terms of sex, occupation, and region, based on COVID‐19 incidence. Second, because of the cross‐sectional design, unmeasured confounders and causal relationships could not be clarified. Third, the study was conducted during the COVID‐19 pandemic, and it is unclear how the pandemic and associated changes in daily life and occupational environment affected the results. Fourth, common method bias was unavoidable because of the large number of standard questionnaire items used in Internet surveys. However, the K6 self‐report outcome measure has a variance explained by Harman's single factor test of 25%, which is below 50%; therefore, the effect of common method bias was assumed to be small. Fifth, the telecommuting designation validity and reliability are unknown because telecommuting status was examined with a simple question.
5. CONCLUSIONS
Associations between telecommuting and psychological distress depend on workers' family living situations. During the COVID‐19 pandemic, workers living with family members requiring care experienced higher psychological distress, while those living with a spouse or preschool children had lower psychological distress. Telecommuting was associated with increased psychological distress among those living with family members requiring care or young children. This may be partly because telecommuting was introduced in an emergency without consideration of workers' family cohabiting situations. In telecommuting during an emergency, such as the COVID‐19 pandemic, it is important to provide psychological and social support that considers workers' situations regarding family members living with them.
AUTHOR CONTRIBUTIONS
Atsuko Ikenouchi: Conceptualization, investigation, data curation, and writing—original draft preparation. Yoshihisa Fujino: Conceptualization, methodology, software, formal analysis, investigation, data curation, writing—original draft preparation, project administration, and funding acquisition. Ryutaro Matsugaki: Investigation, data curation, and writing—review and editing. Kosuke Mafune: Investigation, data curation, and writing—review and editing. Hajime Ando: Investigation, data curation, and writing—review and editing. Tomohisa Nagata: Investigation, data curation, writing—review and editing, and funding acquisition. Seiichiro Tateishi: Investigation, data curation, writing—review and editing, and funding acquisition. Reiji Yoshimura: Investigation, data curation, and writing—original draft preparation. Mayumi Tsuji: Investigation, data curation, writing—review and editing, and funding acquisition.
FUNDING INFORMATION
This study was supported and partly funded by a research grant from the University of Occupational and Environmental Health, Japan (no grant number); the Japanese Ministry of Health, Labour and Welfare (H30‐josei‐ippan‐002, H30‐roudou‐ippan‐007, 19JA1004, 20JA1006, 210301–1, and 20HB1004); Anshin Zaidan (no grant number); the Collabo‐Health Study Group (no grant number); Hitachi Systems, Ltd. (no grant number); and scholarship donations from Chugai Pharmaceutical Co., Ltd. (no grant number). The funders were not involved in the study design, collection, analysis, interpretation of data, writing of this article, or the decision to submit it for publication.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interests for this article.
DISCLOSURE
This study was approved by the Ethics Committee of the University of Occupational and Environmental Health, Japan (reference No. R2‐079 and R3‐006). All participants provided informed consent after completing a form on the survey website.
ACKNOWLEDGMENTS
The current members of the CORoNaWork Project, in alphabetical order, are: Dr. Akira Ogami, Dr. Ayako Hino, Dr. Hajime Ando, Dr. Hisashi Eguchi, Dr. Keiji Muramatsu, Dr. Koji Mori, Dr. Kosuke Mafune, Dr. Makoto Okawara, Dr. Mami Kuwamura, Dr. Mayumi Tsuji, Dr. Ryutaro Matsugaki, Dr. Seiichiro Tateishi, Dr. Shinya Matsuda, Dr. Tomohiro Ishimaru, Dr. Tomohisa Nagata, Dr. Yoshihisa Fujino (present chairperson of the study group), and Dr. Yu Igarashi. All members were affiliated with the University of Occupational and Environmental Health in Japan.
Ikenouchi A, Fujino Y, Matsugaki R, et al. The effects of telecommuting and family cohabiting situation on psychological distress in Japanese workers during the COVID‐19 pandemic: A cross‐sectional study. J Occup Health. 2023;65:e12391. doi: 10.1002/1348-9585.12391
Contributor Information
Yoshihisa Fujino, Email: zenq@med.uoeh-u.ac.jp.
for the CORoNaWork Project:
Akira Ogami, Ayako Hino, Hisashi Eguchi, Keiji Muramatsu, Koji Mori, Makoto Okawara, Mami Kuwamura, Shinya Matsuda, Tomohiro Ishimaru, and Yu Igarashi
DATA AVAILABILITY STATEMENT
Data are not available owing to ethical restrictions and the need to preserve participants' anonymity.
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Data Availability Statement
Data are not available owing to ethical restrictions and the need to preserve participants' anonymity.