Effectiveness of a Workplace-Based Intervention Program to Promote Mental Health among Employees in Privately Owned Enterprises in China

Abstract

This study aims to examine the effectiveness of a workplace-based intervention program to improve mental health, work ability, and work productivity in privately owned enterprises in China. A prospective cohort intervention study design was employed in which the intervention program was implemented for 30 months (from July 2009 to December 2012). Nine privately owned retail enterprises in China participated in the intervention study. Researchers administered a self-report survey to 2768 employees. The research team measured participants' job stress, resilience, work ability, absenteeism, depression, and work performance. A comprehensive Health Promotion Enterprise Program was implemented that entailed the following components: policies to support a healthy work environment, psychosocial interventions to promote mental health, provision of health services to people with mental illness, and professional skills training to deal with stress and build resilience. Analysis of variance was used to examine preintervention versus postintervention differences in stress, resilience, and work ability. Logistic regression was used to examine absenteeism related to depression. The results suggest that the intervention program was effective at improving participants' ability to work, their sense of control over their jobs, and, in particular, their ability to meet the mental demands of work. The intervention program also reduced participants' job stress levels and reduced the probability of absenteeism related to depression. The intervention programs incorporating both individual-level and organizational-level factors to promote mental health were effective and have implications for both practice and policy regarding enterprises taking more responsibility for the provision of mental health services to their employees. (Population Health Management 2013;16:406–414)

Introduction

Depression can have a negative effect on both quality of life and workplace functioning for employees.^1,2 Studies of workplace depression show that it is related to chronic disease³ and disability,^4

–7 and that it impairs work capacity in areas such as timekeeping,^8
–10 physical and psychological ability to meet work demands,¹¹ and job performance and productivity.¹² This can arise as a result of both presenteeism (days when an employee is at work but performs poorly) and absenteeism (sick leave and absence from work related to depression and anxiety).

Depression and other mental health conditions are a significant economic burden to employers. For example, presenteeism and absenteeism associated with mental health issues cost Australian employers over $10 billion per year,¹³ which is consistent with international literature that recognizes the significant indirect costs of workplace mental health that are associated with reduced productivity, absenteeism, and staff turnover.^14,15 Further, Birnbaum and colleagues⁸ reported that disability costs for depressed workers were 4.5 times greater than those for nondepressed employees.

Previous studies have consistently demonstrated that certain job factors, specifically those associated with high demand and low control, greatly increase the risk of mental illness, including anxiety and depression.^16
–18 For example, Karasek¹⁶ and Siegrist¹⁹ developed a model showing that an imbalance between the mental effort expended for work and the recognition and rewards received was linked to a variety of mental and physical problems. Further, Kelloway and Day²⁰ suggested that mental health is negatively affected by a number of work factors, including job-related stresses (eg, working overtime), role stressors (eg, conflict with managers and coworkers), ambiguity and inter-role conflict, perceived job control, poor quality leadership, and aggression in the workplace (eg, harassment, bullying).

Given the important relationship between mental health and work, and the central role of employment in peoples' lives, the workplace is now recognized by the Ottawa Charter as an important setting for health promotion interventions for depression.²¹ Within this context, “healthy organizations” can be viewed as systems that can promote employees' mental health through developing participatory workplace cultures.²² Such organizations can improve mental health and change health behaviors through multiple levels of influence. These include direct efforts (eg, counseling, stress-reduction programs, opportunities for physical activity) and indirect measures (eg, policy promoting a healthy physical and social environment, social support). It is also feasible to focus workplace health promotion efforts on system-level care by using integrated approaches that consider earlier detection, increased access to high-quality health care, earlier return to work, improved clinical and occupational outcomes,²³ disability management programs,²⁴ and employee assistance programs.²⁵

Depression in the workplace has recently gained the attention of Chinese researchers because of its increasing incidence and its economic and social impact. For example, an epidemiological study of the incidence of depression in the Beijing, He Nan, and He Bei provinces found that the workplace depression rate was 40.2% among employees,¹⁸ which is significantly higher than that in both the United States (6.4%)¹⁷ and Europe (33%).²⁶ Given the costs of depression to Chinese society, applying an effective treatment to reduce the length of depressive episodes (or prevent episodes) and reduce suicide rates is needed to ensure a significant reduction in the total burden of disease. Many effective management protocols are available in Western societies to improve the symptoms of depression²⁷ in the workplace. Depression treatment also has been shown to be cost-effective,²⁸ to keep depressed people employed,²⁹ and is capable of improving the productivity of people suffering from depression who are already employed.³⁰ However, only approximately 20% of people with major depression are treated adequately in China.³¹ The possible reasons for the low rate of treatment may relate to the fact that mental illness is stigmatized in traditional Chinese culture³²; therefore, Chinese people tend not to seek treatment from mental health professionals.³² This is compounded by the lack of medical and social support services.³³

It is increasingly evident that the incidence of depression in China can no longer be ignored because of its pervasive impact on the workplace and society. In this context it is particularly important to study the incidence and management of depression in privately owned enterprises because of the rapid growth in this sector, which now contributes to more than 80% of employment and gross domestic product.³⁴ Because these enterprises are rapidly developing, with high-pressure work cultures yet underdeveloped management systems,³⁵ mental health issues among employees are becoming increasingly evident.^36,37 Mental health services to address these issues are underdeveloped in China, with a lack of training programs and professionals in disciplines such as psychiatric rehabilitation.^36,38 Further, most employees who transfer from state-owned enterprises or migrate from rural areas to work in private enterprises often need to adapt and adjust to different management systems and an “enterprise culture.” This situation also may contribute to stress and depression among these employees. However, few studies have empirically examined depression and its relation to employees' productivity in these enterprises. Furthermore, few intervention or treatment programs have been made available in the enterprise context in China to assist depressed employees. The present study aims to address this research gap by examining the effectiveness of a workplace-based intervention program aimed at improving employees' mental health and job performance in a private enterprise through the use of a comprehensive and multilevel health promotion framework that addresses a number of job-related risk factors.

Methods

Participants and procedures

The Credibility Retail Enterprise is one of the largest and fastest-growing retail companies in China. It has been frequently cited in economic and development research as a typical example of a contemporary Chinese retail enterprise development. The company was established in 1984 with only 30 employees in one city. It has expanded to 13 companies in 13 cities across He Bei and Shan Dong provinces with over 20,000 employees. The Credibility Retail Enterprise is a comprehensive retail outlet, selling a range of products including basic commodities and China national branded goods. The company was chosen for the current study because of management's concerns regarding employees' mental health problems. This led to the company contacting Peking University to provide solutions to these health problems.

A 2-stage cluster sampling method was used to recruit a sample of firms in this enterprise. Following approval of the study by the company's management board, 9 firms located in small- to mid-sized cities in the He Bei (6 firms) and Shandong (3 firms) provinces were invited to participate in the study (Table 1). Three hundred employees from each firm were randomly selected to complete a questionnaire measuring depression, job stressors, resilience, work ability, and job performance before and following a workplace health intervention program. Baseline data were collected “preintervention” in July 2009 using the questionnaire, and “postintervention” in June 2012. In 2009, a total of 2700 employees and 68 chief managers across the 9 firms participated in the survey, with a response rate of 100%. In 2012, a total of 1652 people from the baseline cohort completed the postintervention survey, representing a retention rate of 60% over the 3-year period of 2009 to 2012.

Table 1.

Number of Participants from Each City

	City name	Preintervention N(%)	Postintervention N(%)	Total N(%)
Shandong Province	Ken Li	308 (11.2)	193 (9.7)	501 (10.92)
	Lai Wu	308 (11.2)	190 (9.5)	498 (10.85)
	Huan Tai	315 (11.1)	314 (15.7)	629 (13.70)
He Bei Province	Bai Tou	307 (11.1)	206 (10.3)	513 (11.18)
	Ye Cheng	308 (11.2)	194 (9.7)	502 (10.94)
	Huang Hua	316 (11.5)	190 (9.5)	506 (11.02)
	Qing Xian	302 (10.9)	191 (9.6)	493 (10.74)
	Zhao Qiang	300 (10.9)	187 (9.4)	487 (10.61)
	Zhao Xian	304 (11.0)	157 (7.9)	461 (10.04)
	Total	2768 (100)	1652 (100)	4590 (100)

The project was approved by the Peking University School of Management Research Committee Board. At preintervention, 21% of respondents were male and 79% female. The majority (92.2%) of participants were between 18 to 35 years of age, with 7.9% between 36 and 54 years of age. In terms of marital status, 57% of participants were married, 44.7% single, 1.6% divorced, and 0.8% separated. Participants represented a wide range of job levels, including sales/marketing (51.3%), clerical/administrative support (20.4%), middle- and top-level management (14.5%), professional/technical (2.4%), first-level management (0.8%), and other staff positions (8.2%). Ninety-nine percent of participants were employed full-time. In terms of education, 53% of participants had reached middle school or below, 5.7% had vocational-level education, 31.1% had a college certificate, 9.4% had a university degree, 0.3% had postgraduate qualifications, and 0.5% had less than a primary school-level education.

Measurement

The General Health Questionnaire (GHQ30)³⁹ was used to measure depression and anxiety. This questionnaire comprises 5 subscales: somatic complaints, depression, inability to cope, social dysfunction, and anxiety. The 5 components were found to have satisfactory reliability, with Cronbach alpha coefficients of 0.76, 0.76, 0.59, 0.43, and 0.36, respectively, and an overall Cronbach alpha of 0.80. The GHQ30 has been validated in a general Chinese sample,³⁶ but has not been used previously in Chinese samples in private enterprise settings. The 30 items on the scale were translated by the third author into Chinese, and then translated back into English to check the clarity of the translation. The questions were answered using a 4-point Likert scale (“better than before,” “same as before,” “worse than before,” and “much worse than before”). The scoring system, developed by Goldenberg,³⁹ was used to score 0, 0, 1, 1 for positively worded questions, and 0, 1, 1, 1 for negatively worded questions. A confirmatory factor analysis was conducted to evaluate the factor structure of the 30 items. The chi-square of the 5-factor model was 22 (df=573, P<0.001). The goodness-of-fit index, comparative fit index, and normed fit index were 0.92, 0.90, and 0.88, respectively, and the root-mean-square error of approximation was 0.05. Even though fit indexes of 0.90 are considered acceptable, indexes >0.95 are preferable, according to Hu and Bentler.⁴⁰ The results indicated that the 30-item, 5-factor scale provided a fair fit to the data. A summation of mean scores for each subscale represented a depression measure, with high scores indicating higher levels of depression. The coefficient alpha was 0.80, and the total variance explained by the questionnaire was 47.3%. The cutoff score of 13 was used to classify people as having depression (those with a higher score than 13), and anything below (0–12.9) was considered normal.⁴¹

Work-related stressors

A culturally appropriate tool was developed, using a needs assessment, to measure work-related stress. Two hundred employees from 2 of the firms were asked to rank items from a list of work-related stressors from “high frequent” occurrence to “low frequent” occurrence. Items with a 50% response rate were included in the work-related stressors measure. These items were clustered on 3 dimensions:

1. Job factors relating to changes in job responsibility, increased work time, work environment change, and job location change;

2. Perceived conflicts with managers and coworkers;

3. Low salary

The total score for each respondent was derived by adding the stressor scores for each of the 3 dimensions. A higher score indicated a higher level of stress. A reliability analysis conducted on the scale indicated a reasonable level of reliability (Cronbach alpha of 0.74).

Work ability and job control

Two items from the Work Ability Index (WAI)⁴² were used to assess employees' psychological and physical ability to work. These items were: “How do you rate your current work ability with respect to the physical demands of your work?” and “How do you rate your current work ability with respect to the psychological demands of your work?” A 5-point Likert scale was used, with 1=“very poor” and 5=“very good.”

Absenteeism

The World Health Organization (WHO) Health and Work Performance Questionnaire (HPQ) was used to measure health and absenteeism.⁴² Four items were used to assess absenteeism in relation to loss of hours of work because of physical and mental health problems. An example item is: “In the last 4 weeks, how many times did you miss an entire workday because of problems with your physical or mental health?” Absenteeism because of illness was recoded using categorical variables of “no absence,” “1 day absence,” and “2 days or more absence.” This was done to reflect the quartile-based distribution of the data.

Work performance and Productivity

Three items from the WHO HPQ also were used to measure job performance.⁴² These were: “How would you rate the usual performance of most workers in a job similar to yours?” “How would you rate your usual job performance over the past year or two?” and “How would you rate your overall job performance on the days you worked during the past four weeks (28 days)?” The scoring was from zero to 10, with a higher score indicating a higher level performance.

Other disease-related factors

Information was collected on other diseases and conditions reported by employees, including diabetes, heart disease, hypertension, cancer, asthma, anxiety, schizophrenia, other psychoses, eating disorders, and injury.

Intervention strategy

The Health Promotion Enterprise (HPE) Program was developed by the research team and used as the intervention. This program applies the Ottawa Charter approach for improving the quality of organizational care and implementing health promotion activities for employees at the individual level. The program addressed job-related factors found to be related to depression, including the workplace physical and psychosocial environment, overtime work hours, conflicts with managers and coworkers, and work stressors. The strategies entailed developing clear policies about anti-bullying, nondiscrimination, nonsmoking, and drug use, and providing the modified intervention strategies based on the intervention model that the authors have developed for secondary school settings.⁴³ These strategies are detailed in Table 2.

Table 2.

The Intervention Program

Organizational-level intervention: Interactive workshops for managers	Individual-level intervention: Intervention strategies for employees with activities to enhance resilience
• Objectives:– Managers and group leaders were empowered with skills and competency to promote resilience and mental health, and build a healthy physical and psycho-social environment, and healthy policy.• Training format:– Weekly 3-hour interactive sessions for the first year of the intervention, then 3-hour sessions every 2 months in the second and third year of the intervention, sharing the concepts of resilience, stress management, effective communication, conflict management, problem solving, goal setting, and creating health promoting enterprise policy.• Responsible professional:– A psychologist who is well trained in organizational psychology• Major topics covered:– Enterprise Culture, Learning Management Skills in an Enterprise Context, Employee Social-Emotional Learning, Employee Mentoring, Family Relationships, Manager Capability Building, and Community Involvement.• Specific activities and topics:(1) Skills necessary to stay calm and manage own emotions, such as to stop getting extremely stressed, depressed, or worried when something “bad” happens.(2) Skill in being able to distinguish between one's negative/irrational and positive/rational thoughts, and being able to generate positive, rational thoughts in adverse circumstances.(3) Skill in being able to regulate the intensity of one's feelings, including the use of a variety of coping and adaptive skills in management process and family context.(4) The foundations for success and well-being (confidence, persistence, organization, getting along, emotional resilience) including self-awareness of strengths and weaknesses.	• Objectives:– Help enterprise to identify their needs and priorities for action; plan for activities to create an environment of value, support, and mutual respect.• Training format:– Monthly 3-hour discussions for the first year of the intervention program, then 3-hour sessions every 2 months in the second and third year of the intervention with employees in each enterprise; to plan enterprise activities, develop a system to promote a friendly and caring environment, and to help employees with special needs.• Responsible professional:– A psychologist who is well trained in organizational psychology• Major topics covered:– To facilitate enterprise, family, and community involvement in enterprise activities to promote emotional health and build resilience; to facilitate the enterprise to be more proactive in linking with other enterprises and local community.• Specific activities and topics:(1) Resiliency building for employeesIndividual resilience skills building: confidence, stress, and anger control, self-esteem, problem solving.Mentoring program: enabling the older employees to appreciate their growing competencies as well as the pleasure of being genuinely helpful to younger employees. The newly employed employees, on the other hand, would develop closer relationships with the older employees to experience models of helpfulness.(2) Family support group:Enterprise advised to set up a family support group so that families can share information about enterprise issues and other health-related issues. The support group is expected to meet every month to facilitate communication within the group and with enterprises.(3) Enterprise-family activitiesEnterprise advised to organize enterprise-family activities like community service, health promotion day, sports, recreational activities, travel, fitting in their own needs and enterprise schedule.(4) Enterprise partnerships and linkages with other enterprisesSet up link with other enterprises to share good practices and to facilitate a proactive linkage between the participating enterprise and local community agencies.

Organizational-level intervention: Interactive workshops for managers

Individual-level intervention: Intervention strategies for employees with activities to enhance resilience

• Objectives:– Managers and group leaders were empowered with skills and competency to promote resilience and mental health, and build a healthy physical and psycho-social environment, and healthy policy.• Training format:– Weekly 3-hour interactive sessions for the first year of the intervention, then 3-hour sessions every 2 months in the second and third year of the intervention, sharing the concepts of resilience, stress management, effective communication, conflict management, problem solving, goal setting, and creating health promoting enterprise policy.• Responsible professional:– A psychologist who is well trained in organizational psychology• Major topics covered:– Enterprise Culture, Learning Management Skills in an Enterprise Context, Employee Social-Emotional Learning, Employee Mentoring, Family Relationships, Manager Capability Building, and Community Involvement.• Specific activities and topics:(1) Skills necessary to stay calm and manage own emotions, such as to stop getting extremely stressed, depressed, or worried when something “bad” happens.(2) Skill in being able to distinguish between one's negative/irrational and positive/rational thoughts, and being able to generate positive, rational thoughts in adverse circumstances.(3) Skill in being able to regulate the intensity of one's feelings, including the use of a variety of coping and adaptive skills in management process and family context.(4) The foundations for success and well-being (confidence, persistence, organization, getting along, emotional resilience) including self-awareness of strengths and weaknesses.

• Objectives:– Help enterprise to identify their needs and priorities for action; plan for activities to create an environment of value, support, and mutual respect.• Training format:– Monthly 3-hour discussions for the first year of the intervention program, then 3-hour sessions every 2 months in the second and third year of the intervention with employees in each enterprise; to plan enterprise activities, develop a system to promote a friendly and caring environment, and to help employees with special needs.• Responsible professional:– A psychologist who is well trained in organizational psychology• Major topics covered:– To facilitate enterprise, family, and community involvement in enterprise activities to promote emotional health and build resilience; to facilitate the enterprise to be more proactive in linking with other enterprises and local community.• Specific activities and topics:(1) Resiliency building for employeesIndividual resilience skills building: confidence, stress, and anger control, self-esteem, problem solving.Mentoring program: enabling the older employees to appreciate their growing competencies as well as the pleasure of being genuinely helpful to younger employees. The newly employed employees, on the other hand, would develop closer relationships with the older employees to experience models of helpfulness.(2) Family support group:Enterprise advised to set up a family support group so that families can share information about enterprise issues and other health-related issues. The support group is expected to meet every month to facilitate communication within the group and with enterprises.(3) Enterprise-family activitiesEnterprise advised to organize enterprise-family activities like community service, health promotion day, sports, recreational activities, travel, fitting in their own needs and enterprise schedule.(4) Enterprise partnerships and linkages with other enterprisesSet up link with other enterprises to share good practices and to facilitate a proactive linkage between the participating enterprise and local community agencies.

The HPE was implemented over a 30-month period (from July 2009 to December 2011), and was tailored to each organization based on a needs assessment.

Data analysis

Analysis of variance was used to compare the difference in working ability between preintervention and postintervention in the intervention group of employees. Confounding factors, including income, education, employment status, marital status, sex, and age also were entered into the analysis. A chi-square test was used to compare differences between preintervention and postintervention data with respect to absenteeism, work performance, and prevalence of depression. A logistic regression test was used to compare and analyze the relationship between absenteeism and depression in both pre- and postintervention, controlling for: (a) demographic variables including age, sex, education, income, employment status, marital status; and (b) diseases and conditions including injury, diabetes, heart disease, hypertension, cancer, asthma, anxiety, schizophrenia, psychosis, and eating disorders.

Results

An analysis of those people who participated in the preintervention survey compared to those who remained in the study and completed the postintervention survey showed that there were no statistically significant differences in terms of age (t=2.18, P>0.08), sex (χ²=3.61, P=0.06), marital status (χ²=0.21, P=0.34), and full-time employment status (99.6% vs. 99.0%, χ²=0.41, P=0.51) when the large sample size is taken into consideration and significance level is adjusted to the 0.01 level. This suggests that the postintervention sample retained the same characteristics as the preintervention sample, despite the drop-out rate, and increases in income (χ²=286.05, P<0.001) and education level (χ2=14.14, P=0.003) over the intervention period. As income and education have the potential to confound the relationship between psychosocial factors and depression, they were controlled for in the multivariate analysis of variance model in terms of examining preintervention versus postintervention differences.

Table 3 demonstrates that there were significant differences preintervention versus postintervention for the intervention group participants in terms of reduced job stressors, increased work ability, and improved job performance after the intervention. Thus there were significant improvements in participants' work ability, particularly their overall ability to meet work demands, including job-related mental demands. There also were significant improvements in participants' perceptions of their job performance over the previous year or 2 years, and in the previous 4 weeks. There were no significant differences between preintervention and postintervention in intervention group participants in terms of financial problems, ability to meet the physical demands of their work, and their perception of other workers' job performance.

Table 3.

Difference in Job Stressors, Resilience, Work Ability, and Job Performance Between Preintervention and Postintervention in Intervention Participants

		Preintervention (N=2768)	Postintervention (N=1997)	Mean Difference	F	P
Job stressors	Stressor 1: Job change	1.49 (1.33)	1.22 (1.35)	−0.27	−6.81	<0.001^b
	Stressor 2: Conflict with manager	0.86 (1.07)	0.71 (0.91)	−0.15	−5.04	<0.001^b
	Stressor 3: Low pay	1.35 (1.04)	1.30 (1.11)	−0.05	−1.69	0.09
Resilience	Resilience total score	21.74 (3.21)	21.70 (3.15)	−0.04	−0.41	0.68
Work ability	How do you rate your current work ability compared with your lifetime best? (score 0-10)	8.07 (1.48)	8.32 (1.29)	−0.25	6.08	<0.001^b
	How do you rate your current work ability with respect to the physical demands of your work? (score 0–10)	4.23 (0.79)	4.24 (0.78)	−0.01	0.59	0.55
	How do you rate your current work ability with respect to the mental demands of your work? (score 0–10)	4.09 (0.80)	4.15 (0.79)	−0.06	2.60	0.01^a
Job performance	How would you rate the usual performance of most workers in a job similar to yours? (score 0–10)	7.79 (1.27)	7.86 (1.21)	−0.07	2.01	0.04
	How would you rate your usual job performance over the past year or two? (score 0–10)	7.82 (1.41)	8.09 (1.20)	−0.27	6.94	<0.001^b
	How would you rate your overall job performance on the days you worked during the past four weeks (28 days)? (score 0–10)	8.00 (1.37)	8.17 (1.30)	–0.16	4.14	<0.001^b

Univariate analysis of variance was used to analyze the difference between preintervention and postintervention while confounding factors including education and income were controlled for in the models.

To reduce the type 1 error related to the large sample size, the significance level of probability was adjusted to P<0.01.

Significance: ^a P<0.01; ^b P<0.001.

The difference between preintervention and postintervention in the proportion of people who were absent was compared by using a chi-square test (Table 4). The chi-square test results indicated an overall reduction in the proportion of people who were absent from work during the postintervention. Specifically, there was an overall reduction in the number of people who missed more than 4 entire workdays, and an overall increase in the number of people who were not absent in the postintervention. There also were significant reductions in the proportion of people who missed half days at work, and overall increases in the number of people who were not absent for full workdays in the last 4 weeks, and those who indicated that they did not need to attend work early and leave work late.

Table 4.

Difference in Absenteeism Between Preintervention and Postintervention

Questions		Preintervention	Postintervention	χ²	p
1. In the last four weeks, how many days did you miss an entire workday because of problems with your physical or mental health?	No sick leave	2,234 (81.3)	1,616 (81.2)	0.14	0.93
	1 day	239 (8.4)	171 (8.6)
	2 days and more	284 (10.3)	202 (10.2)
2. In the last four weeks, how many days did you miss an entire workday for any other reason?	No leave	667 (24.3)	749 (37.8)	209.25	<0.001^a
	1–3 days leave	699 (25.5)	518 (26.2)
	4 days	1,119 (40.8)	441 (22.3)
	5 days and more	257 (9.4)	272 (13.7)
3. In the last four weeks, how many days did you miss part of a workday because of problems with your physical or mental health?	No leave	2,482 (90.1)	1,800 (90.1)	1.64	0.44
	1 day	176 (6.4)	139 (7.0)
	2 days and more	95 (3.5)	58 (2.9)
4. In the last four weeks, how many days did you miss part of a workday for any other reason?	No leave	1,920 (69.7)	1,373 (68.8)	21.25	<0.001^a
	1 day	363 (13.2)	346 (17.3)
	2 days and more	470 (17.1)	276 (13.9)

Chi-square test was used to compare difference in absenteeism between preintervention and postintervention. Statistical significance: P<0.01; Significance: ^a P<0.001.

Table 5 presents the results of the relationship between depression and absenteeism preintervention versus postintervention using a multiple logistic regression model. Absence from work because of physical and mental health problems was significantly related to depression at both preintervention and postintervention. Specifically, employees who had 2 entire workdays or more absence had a reduced probability of having symptoms of depression, with an odds ratio of 1.58 at preintervention reduced to 1.29 postintervention. The intervention program also reduced the probability of depression postintervention for those who had 1 partial day absence per month.

Table 5.

Relationship Between Depression and Absenteeism at Preintervention and Postintervention

Questions		Preintervention OR (95% CI)	Pre P	Postintervention OR (95% CI)	Post P
1. In the last four weeks, how many days did you miss an entire workday because of problems with your physical or mental health?	No sick leave	1		1
	1 day	1.32 (0.94–1.87)	0.11	1.55 (1.01–2.38)	0.05^b
	2 days and more	1.58 (1.17–2.14)	0.003^c	1.29 (0.86–1.92)	0.22
2. In the last four weeks, how many days did you miss an entire workday for any other reason (including vacation)?	No leave	1		1
	1–3 days leave	1.22 (0.92–1.61)	0.17	1.27 (0.92–1.76)	0.15
	4 days	0.95 (0.73–1.23)	0.71	1.02 (0.71–1.45)	0.93
	5 days and more	0.95 (0.64–1.41)	0.80	0.82 (0.52–1.29)	0.39
3. In the last four weeks, how many days did you miss part of a workday because of problems with your physical or mental health?	No leave	1		1
	1 day	1.51 (1.04–2.19)	0.03^a	0.85 (0.50–1.45)	0.06
	2 days and more	1.27 (0.76–2.18)	0.36	1.57 (0.77–3.20)	0.21
4. In the last four weeks, how many days did you miss part of a workday for any other reason?	No leave	1		1
	1 day	1.31 (0.99–1.74)	0.06	0.99 (0.69–1.42)	0.95
	2 days and more	0.91 (0.69–1.21)	0.52	1.36 (0.94–1.98)	0.10

Logistic regression was used to compare and analyze the relationship between absenteeism and depression. Statistical significance: P<0.05. Education, income, and disease factors including injury, diabetes, type 2 diabetes, heart disease, hypertension, cancer, asthma, anxiety, schizophrenia, other psychosis, eating disorders, and other diseases, were controlled for in the model.

P<0.05; ^b P<0.01; ^c P<0.001; CI, confidence interval; OR, odds ratio.

Table 6 indicates that there are statistically significant differences between preintervention versus postintervention in the proportion of people who had depression. Specifically, there were more people with depression at preintervention than postintervention in the intervention group. The results suggest that the intervention program was effective in improving mental health and preventing depression for the intervention group participants. There also were reductions in other diseases linked to mental health, including significant reductions in eating disorders and other psychoses.

Table 6.

Difference in Prevalence of Health Problems Between Preintervention and Postintervention

	Depression	Preintervention N=2758 n(%)	Postintervention n(%)	Reduction of prevalence	χ²	p
Depression	No	2,221 (80.5)	1,660 (83.0%)
	Yes	537 (19.5)	340 (17.0)	2.5%	10.57	0.005
Injury	No	2568 (93.2)	1881 (94.1)
	Yes	188 (6.8)	117 (5.9)	0.9%	1.80	0.10
Asthma	No	2731 (99.1)	1988 (99.4)
	Yes	26 (0.9)	11 (0.6)	0.3%	2.32	0.08
Eating disorder	No	2303 (83.6)	1771 (88.6)
	Yes	453 (16.4)	227 (11.4)	5.0%	24.34	<0.001
Anxiety	No	2638 (95.7)	1922 (96.1)
	Yes	119 (4.3)	77 (3.9)	0.4%	0.63	0.24
Other psychosis	No	2694 (97.8)	1975 (98.8)
	Yes	62 (2.2)	24 (1.2)	1.0%	7.18	0.004
Other diseases (arthritis, body pain, chronic obstructive pulmonary disease)	No	2429 (88.3)	1780 (89.1)
	Yes	323 (11.7)	218 (10.9)	0.8%	0.78	0.20

Chi-square test was used for data analysis. Statistical significance: P<0.05.

Discussion

These results suggest that the HPE intervention program significantly improved participants' overall ability to meet the demands of work, particularly the mental requirements, and to meet job performance requirements. This indicates that good organizational management and health promotion activities focusing on resilience and coping skills training (including the development of social and emotional well-being skills, self-esteem, and problem solving) enhance employees' ability to work and meet the demands of their work.^44,45 These results are consistent with previous studies conducted in Western countries that demonstrate the correlation between healthy organizational culture and employee well-being.

The HPE health promotion program was aimed specifically at dealing with workplace stressors, as these have been significantly related to depression. It is notable, therefore, that the intervention program significantly reduced participants' work stress level and the frequency of stressors experienced related to job changes and conflicts with managers and coworkers. Providing employees with personal and group-based strategies for coping with stress through stress management programs designed to help them adapt to job changes (eg, changes in job responsibility, work time, work environment, location) was, therefore, an important intervention in the enterprise. In contrast to previous studies in which efforts to reduce the effect of work stressors on health have focused solely on personal stress management,⁴⁶ the current intervention also targeted organizational-level stress management, including creating healthy cultures and psychosocial environments, having reasonable job expectations, encouraging collaborative team efforts in the workplace, and respecting and encouraging employees' achievements and successes. Intervention at the organizational level is increasingly being viewed as essential to manage workplace stress and improve mental health, as evidenced by the recent growth in disability management programs in many Western countries.⁴⁷

The HPE intervention program was effective in improving employees' work performance, reducing absenteeism, and reducing the incidence of depression. However, the reduction in absenteeism was not related solely to the reduced incidence of depression. The comprehensive nature of the intervention program, which addressed a range of physical and mental issues, resulted in a reduction in the incidence of eating disorders, other psychoses, anxiety, injury, and other diseases. Addressing these issues also contributed to reducing absenteeism rates. These results support the view that a range of strategies should be integrated into any work-based health promotion program, including health education, supportive environments, appropriate policy measures, linkage to external support services, recreational programs, and workplace stress reduction. This is consistent with previous studies that have shown that interventions using multilevel approaches, incorporating both organizational-level and individual-level strategies, are effective in reducing absenteeism and enhancing job productivity.^30,48

Although stress management programs can have positive benefits, most have limited follow-up periods (only 23% are >6 months). Thus, it is not known whether or how long the benefits last. The current study implemented the intervention program for over 30 months and demonstrated that HPE, using a combination of personal- and organizational-level strategies, was effective in reducing the stress levels of employees. This suggests that longer term intervention programs at both the personal and organizational level are effective in reducing employees' job stress. Opportunities to encourage employees to be involved in decision-making processes proved effective in gaining employees' participation in health promotion activities. The inclusive nature of the program created a sense of equality in the workplace by inviting all employees, including low-income and blue-collar employees (eg, drivers, outdoor laborers), to engage in the intervention activities.

There are several limitations to this study. First, work ability and work performance were assessed based on self-report, which might not reflect the actual level of employees' work capacities. Second, there was a high attrition rate in the intervention group, which potentially may have led to bias in the results. Finally, the study was conducted with only non-state-owned enterprises, and in only 2 provinces; thus, caution must be taken when generalizing the results and applying them to other provinces and state-owned enterprises. Despite these limitations, this is the first study in China to focus on ways that privately owned enterprises can use a comprehensive approach to promote mental health and prevent depression in order to improve work productivity.

Further research should be conducted that uses direct measures to assess employees' work ability and work performance, and focuses on the relationship between mental health and employees' intention to leave their workplace, and identifies whether a high staff turnover rate is related to depression. A representative sample of privately owned enterprises and state-owned enterprises is needed in the next stage of the study to determine the generalizability of the findings to a wide range of enterprises in different industry sectors. In particular, it is recommended that these issues be examined in manufacturing industries, given the high levels of growth in this sector over the last 10 years. Finally, the effectiveness of a comprehensive health promotion program, as indicated by the HPE program in this study, should be compared to clinical-level intervention programs to assess whether the HPE program is more effective.

This study has significant implications for both practice and policy in China. An important step in reducing the risk of depression is to reduce both individual-level and organizational stresses to reduce employees' increased risk of experiencing mental health issues. This could occur in a number of ways, including a focus on participatory mental health promotion initiatives at the enterprise level that can build individual-level resilience skills, confidence, and coping ability. Enterprises should consider embedding mental health counseling and treatment into their on-site health services or more effectively providing such services using accessible community agencies. At policy level, Chinese governments at both the state and provincial levels should consider legislative provisions that require employers to provide better occupational health and safety and rehabilitation services to employees with mental health conditions.

In conclusion, the evidence from the study suggests that workplace health promotion programs may be effective in preventing and managing depression across a range of work settings in China. Programs to promote mental health can be readily integrated into workplaces; with the rapid growth of Chinese private enterprises, such programs will be increasingly important to the country's economic success. It is imperative that further research is conducted on the ways in which comprehensive workplace health promotion programs can support healthy and productive employees within various organizations.

Footnotes

Acknowledgment

The authors wish to acknowledge all participants in the study.

Disclosure Statement

Drs. Sun, Buys, and Wang declared no conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors received the following financial support for the research, authorship, and/or publication of this article: Funding for data collection work was provided by the Peking University.

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