Abstract
Objectives: This study aimed to prospectively investigate the association between work environment improvements and multiple mental health outcomes in a large sample of Japanese employees.
Methods: A web-based longitudinal study surveyed 20 000 Japanese employees, 7970 of whom completed a follow-up after 1 year. Various types of work environment improvements experienced by workers were assessed using a 24-item checklist. Three mental health outcomes (poor mental health, presenteeism, and high psychosocial stress) were assessed and defined using standardized questionnaires.
Results: Overall, as the total number of work environment improvements increased, the odds ratio for mental health outcomes in the follow-up survey decreased by several percentage points, even after adjusting for demographic and occupational factors. Analysis of the types of work environment improvements showed that mutual support improvements were particularly effective in reducing mental health issues. The subgroup analyses also showed that the effectiveness of workplace environment improvements might vary between secondary and tertiary industry workers depending on the types of improvements and mental health outcomes.
Conclusions: The study suggests that workplace improvements can significantly affect mental health. The effectiveness of these improvements may vary according to the type of intervention, industry of the targeted workers, and mental health outcomes. This study provides basic data on the effectiveness of workplace environment improvements that can be used for future intervention trials.
Keywords: mental health, work environment improvement, stress check
Key points:
What is already known on this topic: Previous observational and intervention studies have shown that work environment improvements might contribute to reducing the risk of mental health issues. However, these studies vary widely in their intervention content, participant demographics, and outcomes used, making it difficult to obtain an overall picture of the effectiveness of work environment improvements.
What this study adds: This prospective study systematically demonstrated the association between 4 types of work environment improvements and 3 mental health outcomes and showed that the improvements contributed to an overall reduction in psychosocial stress and that some improvements (eg, mutual support) might further reduce the risk of mental health problems.
How this study might affect research, practice, or policy: The results of this study could be used for intervention trials of work environment improvement in the future and provide useful information for the dissemination of workplace environment improvements in the Stress Check Program in Japan.
1. Introduction
Mental health issues are widespread among the working population. Over half of employees in Japan have experienced anxiety, worry, and distress in their professional lives, and 13% of Japanese companies reported cases in which employees had to take leave of absence and/or leave their jobs owing to mental health problems in the previous year.1 In response, the Japanese government initiated the Stress Check Program in December 2015.2 This program mandates annual assessments of workers’ psychological stress and ensures consultation with a physician for those with high stress levels upon request. Additionally, employers must analyze stress check data within relevant groups (eg, departments and units) and use the results to improve the psychosocial work environment. This program underscores the importance of improving work environments as a primary preventive measure against mental health problems. However, the low implementation rate of such improvements in the workplace in Japan highlights the need to promote the spread of work environment improvements.1
Several observational and intervention studies have been conducted on the effects of work environment improvements on mental health; however, the scientific evidence is not robust. For example, Watanabe et al3 examined the association between work-related stress and the implementation of workplace environmental improvements in a study of 17 500 workers in 1745 worksites and reported that implementation of workplace environmental improvements was cross-sectionally associated with lower work-related stress in men but not in women. In a prospective study, Imamura et al4 reported that workers who took stress checks and experienced improvements in their work environment reported slightly lower psychological distress at the follow-up survey. These studies inquired about work environment improvements using a single item, and the relationship between specific types of workplace environment improvements and the outcomes was unclear. For intervention studies, a systematic review of 39 studies of organization-level interventions previously reported that half of the studies failed to find significant effects.5 In Japan, some intervention studies have been conducted in samples of manufacturing workers and nurses.6,7 Overall, intervention studies have shown a wide variation in intervention content (eg, improvements in physical and chemical factors, working time-related conditions, psychosocial factors), industries and occupations of targeted workers (eg, manufacturing workers, office workers, health care workers), and outcomes used (eg, physical health, well-being, work performance, psychosocial stress), and the overall picture of intervention effects is not clear.
In this study, we prospectively investigated the association between workers’ experiences of work environment improvements and mental health problems in a large sample of Japanese employees. Considering the results of previous studies, we assessed work environment improvements using multiple items and examined not only the association between overall workplace environmental improvements and mental health, but also the association between specific types of workplace environmental improvements and multiple indicators of mental health problems (poor mental health, presenteeism, and high psychosocial stress). Furthermore, taking advantage of the large sample size, we also examined the relationship between work environment improvement and mental health by industry (ie, secondary vs tertiary industries) as a stratified analysis, because it was speculated that differences in working styles between industries would affect these associations.
2. Methods
2.1. Participants
This prospective study, called the “Web-based Longitudinal Study of the Work Environment and Daily Lifestyle” (WELWEL; details for the previous study8), involved Japanese employees registered with an internet-based survey company. The sampling was based on the distribution ratios of business categories, age groups (20-29, 30-39, 40-49, 50-59), and gender among all employees in Japan. We excluded (1) agriculture, forestry, fishery, mining, and quarry workers; (2) those who were self-employed; (3) those who had multiple jobs; and (4) those who worked less than 20 h/wk because workers who met these criteria could have different work styles and working environments compared with other workers. In the first year (February 2022), 20 000 employees agreed to participate and completed the survey. In the second year (February 2023), the same 20 000 participants were invited to participate in the follow-up survey and 7970 agreed to participate and completed the survey. Considering that longer follow-up periods generally result in more dropouts from the study and past findings on the time-lagged association between occupational stress and negative affectivity,9 a 1-year follow-up period was set for this study.
Participants who were followed up (n = 7970) and those who dropped out from the study (n = 12 030) differed significantly with respect to demographic and psychosocial factors; participants who dropped out were more likely to be female, younger, have poorer mental health, and be more stressed than those who could be followed (Table S1). Informed consent was obtained from all participants, and the study was approved by the Research Ethics Committee of the National Institute of Occupational Safety and Health, Japan (2021 N-1-19).
2.2. Measurements
2.2.1. Improvements of the work environment
Participants were asked about their experiences with work environment improvement activities using a detailed 24-item checklist, which included specific measures such as improved lighting, noise reduction, and enhanced social support mechanisms (see Table S2). Each item was designed to capture a distinct aspect of the work environment, with reference to “Locally Adjustable Mental Health Action Checklist for a Better Workplace Environment,” a 24-item checklist for work environment improvement.10 In this study, 5 options were provided for each item with reference to the previous study11: “Experienced for more than a year,” “Recently experienced in the past year,” “Not experienced but necessary in the future,” “Not experienced and not particularly necessary,” and “Not applicable to my workplace.” We calculated the number of “Experienced for more than a year” or “Recently experienced in the past year” responses and used the number for the statistical analyses (ranging from 0 to 24). Further, these 24 items were reportedly divided into 4 types (work methods and planning arrangement, physical environment, mutual support, and preparedness for better mental health, each with 6 items), and we calculated the number of experiences of improvements for each type (each ranging from 0 to 6). The method for calculating the number of improvements experienced was based on a previous study on the working environment and mental health.12
2.2.2. Mental health
Mental health was assessed using the Japanese version of the Kessler Psychological Distress Scale (K6 scale).13 It has 6 items inquiring about frequently experienced symptoms of psychological distress during the past 30 days by using 5 response options from 0 (none of the time) to 4 (all the time). In this study, poor mental health was defined as a K6 score of 13 or higher, according to a previous study.
2.2.3. Presenteeism
Presenteeism, characterized by a decline in work performance due to illness or other medical conditions, was evaluated using a single item from the Japanese version of the World Health Organization Health and Work Performance Questionnaire (HPQ) short form.14 Participants were asked to rate their work performance over the past 4 weeks (28 days) from 0 (worst performance) to 10 (best performance). Presenteeism scores were calculated by multiplying the scale scores by 10 (range: 0-100). Based on the finding of previous studies,15 this study defined presenteeism as a presenteeism score of 40 or less.
2.2.4. Psychosocial stress
The Brief Job Stress Questionnaire (BJSQ) was used to assess psychosocial stress in the workplace. The BJSQ has 57 items that ask about job stressors, stress reactions, and social support during the past month using a 4-point Likert scale. All BJSQ scales were reported to exhibit acceptable levels of internal consistency reliability and factor-based validity.16 In the Stress Check Program of Japan, the BJSQ is used to screen the workers with high stress levels. In the present study, according to the manual of the Stress Check Program, high psychosocial stress was defined as having the highest level of stress reaction (criterion A) or having a moderate level of stress reaction, along with having the highest job stressor (or lowest social support in the workplace, criterion B).17
2.2.5. Other demographic and occupational factors
Participants were asked about their demographic and occupational details, including age, gender, academic history, annual household income, business category (eg, manufacturing and retailing), occupation (eg, managerial position, clerical position), company size (ie, the number of employees in the participants’ offices or branches), employment status (eg, regular employee, part-time job), and about remote work and night work.
2.3. Statistical analysis
Multiple logistic regression analyses were performed to estimate the odds ratios (ORs) for poor mental health (K6 score ≥13), presenteeism (HPQ score ≤40), and high psychosocial stress defined by BJSQ at follow-up survey, using number of work environment improvements at baseline survey as independent variables. In these analyses, the total number of work environment improvements (ranging from 0 to 24) and the number of work environment improvements for the 4 types (each ranging from 0 to 6) were entered separately. In this survey, those who were unemployed during the follow-up survey (n = 118) did not respond to the HPQ and BJSQ items, and those who were on leave during the follow-up survey (n = 410) did not respond to the HPQ items. Therefore, 7970, 7442, and 7852 individuals were included in the analyses of K6, HPQ, and BJSQ, respectively.
In model 1, we calculated the ORs adjusted for demographic factors (age, gender, education, and annual household income). Furthermore, poor mental health, presenteeism, and high psychosocial stress assessed at the baseline survey were adjusted in the analyses of poor mental health, presenteeism, and high psychosocial stress at the follow-up survey, respectively. In model 2, we calculated the ORs, additionally adjusting for occupational factors (occupation, company size, employment status, remote working from home, and night working). In these analyses, education was dichotomized into 2 categories: high school and below (12 years or less) and college and above (12 years or more). Household income was categorized as <2 million yen, 2-6 million yen, and ≥6 million yen. Occupation was dichotomized into managerial and nonmanagerial workers, company size was grouped into ≤49 persons, 50-999 persons, and ≥1000 persons, employment status was dichotomized into regular and irregular employee, and remote working was dichotomized into ≥5 d/wk (full-remote) and ≤4 d/wk. These demographic and occupational factors could possibly alter mental health status and the experience of work environment improvements; we included these factors as possible confounding factors.
In addition, multiple logistic regression analyses were conducted separately for workers in the secondary and tertiary industries as a stratified analysis. Furthermore, independent t tests and χ2 tests were employed to compare the demographic and occupational factors between secondary and tertiary industry workers. All statistical analyses were performed using SPSS version 27 (IBM, Chicago, IL, USA), and P < .05 was considered statistically significant.
3. Results
The demographic and occupational characteristics of the participants are presented in Table 1. Logistic regression analysis showed that each increase in the total number of work environment improvements was associated with decreases in the odds of poor mental health (OR = 0.99; 95% CI, 0.97-1.00; P = .033), presenteeism (OR = 0.98; 95% CI, 0.97-1.00; P = .016), and psychosocial stress (OR = 0.98; 95% CI, 0.97-0.98; P < .001) after adjustments of demographic and occupational factors (Table 2).
Table 1.
Characteristics of the participants (n = 7970).
| Total | Secondary industries | Tertiary industries | P | |
|---|---|---|---|---|
| Number | 7970 | 2277 | 5693 | |
| Gender (male), n (%) | 4709 (59.1) | 1631 (71.6) | 3078 (54.1) | <.001 |
| Age, mean (SD) | 45.0 (9.1) | 45.6 (8.7) | 44.8 (9.2) | <.001 |
| Education (>12 y), n (%) | 5910 (74.2) | 1608 (70.6) | 4302 (75.6) | <.001 |
| Annual household income, n (%) a | <.001 | |||
| <2 million yen | 400 (5.0) | 87 (3.8) | 313 (5.5) | |
| 2-6 million yen | 3366 (46.0) | 1003 (44.0) | 2633 (46.8) | |
| ≥6 million yen | 3904 (49.0) | 1187 (52.1) | 2717 (47.7) | |
| Occupation (managerial workers), n (%) | 1083 (13.6) | 423 (18.6) | 660 (11.6) | <.001 |
| Company size, n (%) | <.001 | |||
| ≤49 persons | 2636 (33.1) | 665 (29.2) | 1971 (34.6) | |
| 50-999 persons | 3253 (40.8) | 935 (41.1) | 2318 (40.7) | |
| ≥1000 persons | 2081 (26.1) | 677 (29.7) | 1404 (24.7) | |
| Irregular employment, n (%) | 1838 (23.1) | 350 (15.4) | 1488 (26.1) | <.001 |
| Telework (≥5 d/wk), n (%) | 433 (5.4) | 157 (6.9) | 276 (4.8) | <.001 |
| Night work, n (%) | 750 (9.4) | 156 (6.9) | 592 (10.4) | <.001 |
| Number of work environment improvements, mean (SD) | ||||
| Total | 7.5 (7.3) | 7.9 (7.7) | 7.3 (7.0) | .001 |
| Work methods and planning arrangements | 1.9 (2.1) | 1.9 (2.1) | 1.8 (2.0) | .033 |
| Physical environment | 1.6 (1.8) | 1.9 (2.0) | 1.5 (1.7) | <.001 |
| Mutual support | 2.1 (2.2) | 2.1 (2.3) | 2.1 (2.2) | .537 |
| Preparedness for better mental health | 1.9 (2.2) | 2.0 (2.3) | 1.9 (2.2) | .040 |
| Poor mental health (K6 score ≥13), n (%) | 862 (10.8) | 234 (10.3) | 628 (11.0) | .327 |
| Presenteeism (HPQ score ≤40), n (%) | 634 (8.5) | 178 (8.3) | 456 (8.6) | .636 |
| High psychosocial stress, n (%) | 1590 (20.2) | 445 (19.8) | 1145 (20.4) | .534 |
Abbreviations: HPQ, Japanese version of the World Health Organization Health and Work Performance Questionnaire; K6, Japanese version of the Kessler Psychological Distress Scale.
Table 2.
Risk of mental health outcomes (poor mental health, presenteeism, and high psychosocial stress) and number of work environment improvements.a
| Model 1 b | Model 2 c | |||
|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | |
| Poor mental health | ||||
| Total number [0-24] | 0.99 (0.97-1.00) | .025 | 0.99 (0.97-1.00) | .033 |
| Work methods and planning arrangement [0-6] | 0.97 (0.92-1.01) | .140 | 0.97 (0.93-1.01) | .180 |
| Physical environment [0-6] | 0.96 (0.91-1.01) | .102 | 0.96 (0.91-1.01) | .123 |
| Mutual support [0-6] | 0.94 (0.90-0.98) | .005 | 0.94 (0.90-0.98) | .006 |
| Preparedness for better mental health [0-6] | 0.96 (0.92-1.00) | .074 | 0.96 (0.92-1.01) | .098 |
| Presenteeism | ||||
| Total number [0-24] | 0.98 (0.97-1.00) | .015 | 0.98 (0.97-1.00) | .016 |
| Work methods and planning arrangement [0-6] | 0.97 (0.93-1.01) | .191 | 0.97 (0.93-1.02) | .210 |
| Physical environment [0-6] | 0.94 (0.89-0.99) | .018 | 0.94 (0.89-0.99) | .021 |
| Mutual support [0-6] | 0.94 (0.90-0.98) | .004 | 0.94 (0.90-0.98) | .005 |
| Preparedness for better mental health [0-6] | 0.96 (0.92-1.00) | .052 | 0.96 (0.91-1.00) | .055 |
| High psychosocial stress | ||||
| Total number [0-24] | 0.98 (0.97-0.99) | <.001 | 0.98 (0.97-0.98) | <.001 |
| Work methods and planning arrangement [0-6] | 0.94 (0.91-0.96) | <.001 | 0.93 (0.90-0.96) | <.001 |
| Physical environment [0-6] | 0.95 (0.92-0.98) | .004 | 0.94 (0.91-0.98) | .002 |
| Mutual support [0-6] | 0.92 (0.90-0.95) | <.001 | 0.92 (0.89-0.95) | <.001 |
| Preparedness for better mental health [0-6] | 0.93 (0.91-0.96) | <.001 | 0.92 (0.90-0.96) | <.001 |
Abbreviation: OR, odds ratio.
Logistic regression analyses were conducted to estimate the adjusted ORs and 95% CI of mental health outcomes in a follow-up survey (poor mental health, presenteeism, and high psychosocial stress). The total number of work environment improvements for each of the 4 types of improvement were separately entered as continuous variables, and the ranges of the continuous variables appear in parentheses. Significant ORs (P < .05) are indicated in bold.
Adjusted for demographic factors (age, gender, education, household income) and each outcome (poor mental health, presenteeism, or high psychosocial stress) assessed at the baseline survey.
Adjusted for psychosocial factors (occupation, company size, employment status, remote working, and night working).
The results of the logistic regression analysis for the 4 types of work environment improvements are also shown in Table 2. The number of improvements of all types was robustly associated with lower ORs for high psychosocial stress, and work environment improvement in mutual support was more effective in decreasing the ORs for poor mental health (OR = 0.94; 95% CI, 0.90-0.98; P = .006) and presenteeism (OR = 0.94; 95% CI, 0.90-0.98; P = .005). Additionally, improvement in the physical environment was effective in decreasing the ORs for presenteeism (OR = 0.94; 95% CI, 0.89-0.99; P = .021).
The results of the subgroup analyses of secondary and tertiary industry workers are shown in Tables S3 and S4, respectively. The total number of work environment improvements and the number of most types of improvements were robustly associated with lower ORs for high psychosocial stress in workers from both types of industries. The number of improvements in mutual support (OR = 0.89; 95% CI, 0.81-0.97; P = .008) and preparedness for better mental health (OR = 0.87; 95% CI, 0.79-0.96; P = .004) were associated with lower ORs for presenteeism in workers in the secondary industries, and the number of improvements in mutual support was associated with lower ORs for poor mental health in workers in the tertiary industries (OR = 0.94; 95% CI, 0.89-0.99; P = .014).
4. Discussion
In this 1-year prospective study, we investigated the associations between workers’ experiences of improvements in their work environment and mental health outcomes, including poor mental health, presenteeism, and high psychosocial stress. Overall, as the total number of work environment improvements increased, the OR for mental health outcomes decreased by several percentage points, even after adjusting for demographic and occupational factors. The analyses of the 4 types of work environment improvements revealed that all 4 were associated with lower ORs for high psychosocial stress. Furthermore, some improvements were associated with lower ORs for other mental health outcomes. The results of the subgroup analyses showed that the effectiveness of workplace environment improvements may vary across industries, depending on the types of improvement and mental health outcomes.
This study demonstrated that as the total number of work environment improvements increased, the OR for mental health outcomes decreased by several percent. These results are consistent with findings from previous studies examining the relationship between workplace environmental improvements and psychological distress.3,4 However, previous studies asked about the implementation of workplace environment improvements using a single item, whereas this study used 24 items from multiple perspectives, which was considered a strength of this study.
In the analyses of the 4 types of work environment improvements, all 4 were associated with lower ORs for high psychosocial stress, and mutual support improvement was further associated with lower ORs for the remaining 2 mental health outcomes. A recent review of organizational-level interventions for the psychosocial work environment reported that interventions that allow employees more control over their work schedules, such as shift changes, have shown strong evidence of effectiveness.18 In this study, the improvement of mutual support included such items (Table S2), which might be a consistent result. However, previous intervention studies have reported that both the content and outcomes of work environment improvements varied across studies, and that half of them did not yield significant results.5 This study systematically demonstrated the association between 4 types of work environment improvements and 3 mental health outcomes; it showed that the improvements contributed to an overall reduction in psychosocial stress and that some improvements might further reduce the risk of mental health problems.
In the subgroup analyses, the effectiveness of workplace environment improvements can vary across industries depending on the types of improvement and mental health outcomes. For example, it may be that improvements in the physical environment (eg, noise and hazardous substances) were more effective in reducing psychosocial stress in secondary industries such as manufacturing, whereas enhancements in mutual support were particularly beneficial in reducing the risk of poor mental health in tertiary industries such as services. Additionally, an association was seen between work environment improvement and presenteeism in the secondary industries, and between work environment improvement and poor mental health in the tertiary industries. This could be because in the secondary industries, improvement of the work environment might have an effect on indicators related to job performance, or that differences in background factors between the secondary and tertiary industries (eg, more men in the secondary industries) might alter the results. Although past studies have reported inconsistent effects of workplace environment improvements,5 future studies may need to focus on factors such as industry type to select methods for workplace environment improvement, and indicators of mental health and psychosocial stress.
This study has several limitations. First, 20 000 participants were invited to participate in the baseline survey; however, only 7970 were retained in the final sample, which is a rather high dropout rate. The dropouts included workers who did not agree to participate in the follow-up survey and those who were not registered with monitors of the internet-based survey company at the time of the follow-up survey. Participants who dropped out were more likely to have poorer mental health and be more stressed than those who could be followed up; these results should be carefully interpreted. Furthermore, participants were recruited from an internet-based survey company, which might limit the generalizability of the findings. Second, it was the participants who reported improvements in their work environment. Therefore, there might have been improvements in the work environment that the participants were unaware of or did not remember. Although some of the statistical characteristics of the workplace improvement data obtained in this study were consistent with those of the national survey (data not shown), caution should be exercised when interpreting these results. Furthermore, the items were based on previous checklists for work environment improvement, which have not been validated psychometrically. Assessment of work environment improvements, including methods for calculating the number of improvements, should be studied in the future. Third, this observational study provides valuable insights into the association between work environment improvements and mental health outcomes. However, to establish a clearer causal relationship, future research should incorporate intervention designs that control for confounding variables and provide a more robust assessment of the direct effects of specific environmental improvements on mental health.
5. Conclusion
This study investigated the impact of work environment improvements on mental health outcomes over a 1-year period. The results revealed that as workplace conditions improved, the risk of mental health issues decreased. Notably, improvements in mutual support were associated not only with reduced psychological stress, but also with positive effects on other mental health outcomes. Furthermore, the effectiveness of workplace environment improvements may vary across industries depending on the types of improvement and mental health outcomes. For instance, improvements in the physical environment (eg, noise reduction) were more effective in secondary industries such as manufacturing. In contrast, enhancements in mutual support were particularly beneficial in tertiary industries such as services. This study provides basic data on the effectiveness of workplace environment improvements that can be used for future intervention trials.
Supplementary Material
Acknowledgments
This study was approved by the Research Ethics Committee of the National Institute of Occupational Safety and Health, Japan (2021 N-1-19). Web-based informed consent was obtained from all participants.
Author contributions
All the authors contributed to the study design. S.I. analyzed the data and prepared the first version of the manuscript with the advice of T.Y. All authors read and approved the final manuscript.
Supplementary material
Supplementary material is available at Journal of Occupational Health online.
Funding
This study was supported by a research grant from the National Institute of Occupational Safety and Health of Japan (N-P03-02).
Conflicts of interest
All authors report no financial or other relationships that represent actual or potential conflicts of interest relevant to the content of this paper.
Data availability
The data are available upon reasonable request from the corresponding author.
Contributor Information
Shuhei Izawa, Occupational Stress and Health Management Research Group, National Institute of Occupational Safety and Health, Kawasaki, Japan.
Toru Yoshikawa, Research Center for Overwork-Related Disorders, National Institute of Occupational Safety and Health, Kawasaki, Japan.
Nanako Nakamura-Taira, Department of Psychology, Faculty of Letters, Chuo University, Tokyo, Japan.
Chihiro Moriishi, Human Informatics and Interaction Research Institute, The National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan.
Rie Akamatsu, Natural Science Division, Faculty of Core Research, Ochanomizu University, Tokyo, Japan.
Hiroki Ikeda, Ergonomics Research Group, National Institute of Occupational Safety and Health, Kawasaki, Japan.
Tomohide Kubo, Occupational Stress and Health Management Research Group, National Institute of Occupational Safety and Health, Kawasaki, Japan.
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