Abstract
The relationship between workplace justice and nonfatal occupational accidents in a single-payer healthcare system has rarely been explored. As countries strive to achieve and sustain universal health coverage, healthcare workers’ occupational safety and health require greater concerns. We used the data from a national survey conducted on randomly sampled Taiwanese workers. One hundred forty eight males and 567 females, with a total of 715 healthcare workers aged 20 to 65, were analyzed. The workplace scale consisted of 4 subcomponents, including distributive justice, interpersonal justice, information justice, and procedural justice, and was dichotomized into low and high groups in each dimension. Logistic regression models examined the relationship between workplace justice and self-evaluated occupational accidents among healthcare employees. The prevalence of self-evaluated occupational accidents in healthcare employees was 15.54% and 11.64% for men and women, respectively. After adjusting variables such as sociodemographic variables, physical job demands, shift work status, work contract, and psychological job demands, regression analyses indicated that health employees with lower distributive justice, interpersonal justice, information justice, and procedural justice were significantly associated with self-evaluated occupational accidents both in males and females. Expanding the study to include healthcare systems in different countries could enhance the generalizability of the findings. Offering specific recommendations for policymakers and healthcare administrators to improve workplace justice and reduce occupational accidents.
Keywords: healthcare employee, self-evaluated occupational accidents, Taiwan, workplace justice
1. Introduction
An occupational accident is a critical occupational safety and health (OSH) issue that draws worldwide attention. This means that unexpected and unplanned events, including acts of violence, occur at work or in connection with work, which results in personal injuries, illnesses, or deaths within one or more workers.[1] Universal health coverage (UHC) refers to everyone having access to the health services they need without the pitfalls of poverty or financial hardship.[2] As countries strive to achieve and sustain universal health coverage, healthcare workers play an important role. Thus, the OSH of healthcare workers requires greater concern. Several studies regarding occupational accidents, gender, and age among sociodemographic variables were correlated with nonfatal occupational accidents.[3,4] It was possibly due to differences in occupational exposure risk by gender.[5] The relationships between age and nonfatal occupational accidents were inconsistent. Some literature showed that young people tended to have a higher risk of nonfatal occupational disasters than the elderly, while others found the opposite. Still, others considered that there was no association between age and occupational disaster risk.[6,7] The status of shift work and employee relationships in work contracts were also associated with nonfatal occupational accidents,[8,9] which was possibly due to the disturbed social life and shortened, disturbed sleep caused by shift work. On top of that, those with unstable hires are more likely to engage in high-risk jobs due to less experience and poorer mental health.[10,11] Psychosocial factors in workplaces, including physical load demands, psychological demands of work, and workplace justice, were also associated with nonfatal occupational accidents,[12,13] which were potentially due to physical and psychological stress, load, and dissatisfaction.
Workplace or organizational justice refers to whether employees are treated fairly, equitably, honestly, and respectfully.[14–16] Based on previous contributions, justice at work can be divided into 3 aspects: distributive justice, procedural justice, and interactional justice, which can be separated into interpersonal justice and informational justice.[17,18] The concept of distributive justice originated from sociological theory, referring to whether feedback and methods of distributing rewards, resources, and outcomes in the workplace are fair.[19] Procedural justice concerns the justice or fairness of the processes and standards used to make policy decisions.[16] Interactional justice focuses on the quality of interpersonal treatment received in performing their duties, including interpersonal and informational justice. Interpersonal justice signifies the ability of management to consider the views of subordinates without personal preferences, along with handling their affairs respectfully with fairness, while information justice represents whether the relevant information is communicated to the workers in a timely and honest manner during the tasks.[14,18]
Taiwan, a country with a population of 23 million located in the eastern part of Asia, has been implementing universal health insurance since 1994, with 99% coverage, low deductibles, short waiting times, and the freedom to go to any medical institution of one’s choice without a referral.[20,21] The single insurer system and the point-based gross payment system are also adopted to manage its health expenditure growth. Service providers apply to insurers for payment based on the number of service points, and each point value conversion fluctuates according to the current year’s total amount, making Taiwan’s health expenditure payment a much lower percentage of GDP than that of OECD countries.[20–22] However, with an aging population, unlimited expenditures, and limited benefits, this healthcare system is shifting the risk of healthcare costs to all healthcare providers rather than the insured,[22] which makes workplace justice of healthcare workers a greater concern.
Through the literature review, we found that workplace justice research was mostly limited to correlating justice with job performance, managerial satisfaction, and health.[15,23] The correlation between workplace justice and nonfatal workplace injuries was also noted but often focused on high-risk construction.[13] In addition to traditional occupational hazards, the healthcare industry has a higher risk of work-related infections, giving rise to blood-borne pathogens.[24] The relationships between workplace justice and nonfatal occupational accidents in a single-payer healthcare system have rarely been explored. The hypothesis of this study is that there is no relationship between workplace justice and occupational accidents in the healthcare industry under a single-payer system. Consequently, the results of this study can make up for the deficiency in examining the relationship between workplace justice and occupational accidents among Taiwanese healthcare workers.
2. Materials and methods
2.1. Study setting and sample
The study utilizes data from a 2013 nationwide survey conducted by the Institute of Occupational Safety and Health, Ministry of Labor, Taiwan. A 2-stage random sampling process was conducted to get a representative sample of the working population. First, all villages and districts in Taiwan were grouped into strata according to their level of urbanization, and random selection was conducted in each stratum. Subsequently, a random sample of households with working residents from selected districts and villages were asked to take part in the survey. Trained interviewers then administered standardized self-administered questionnaires to selected households and verified the completed questionnaires on-site after 1 week. A variety of aspects, including gender, age, shift working status, work contract, physical load, psychological demands of work, workplace justice, and self-evaluated nonfatal occupational accidents, were also revealed. A total of 28,677 people were sampled, 25,480 (88.9%) of whom completed the questionnaire. We analyzed employees aged 20 to 65 in the healthcare industry. According to the data provided by the government of Taiwan, the population of the healthcare industry was 427,000 in the survey year. A sample size 384 was determined by calculating a 95% confidence level with a plus or minus 5% confidence interval (https://www.surveysystem.com/sscalc.htm). Our sampling size was much larger. It was also found that the incidence of occupational accidents varied according to gender; consequently, the data were stratified by gender. Thus, we analyzed 148 men and 567 women and considered the ethical review process waived since the information extracted from the government survey was anonymous, with no personal information.
2.2. Instruments
The Chinese version of the Job Justice Scale derived from questionnaires originally developed by Moorman and Colquitt assesses justice in the workplace.[18,25] The scale commonly used in the employees of the Chinese-speaking population reliably and validly indicated the psychometric properties of satisfaction assessment.[13,19] The scale comprises 7 items, including 4 dimensions. Distributive justice, measured by the following questions, states the equity or fairness of work arrangements and compensation systems: in my company, employees’ work duties and responsibilities are arranged fairly; in my company, employees’ monetary rewards, benefits, and welfare are arranged fairly; in my company, employees’ performance is evaluated fairly. Interpersonal justice refers to the subordinates’ perception of the authorities’ behavior toward them. It was measured by the following questions: my supervisor and management treat employees with respect; my supervisor and management trust employees. Information justice concerns the degree of immediate and accurate information on essential decisions affecting the company provided by the employer. It was measured by a single-item question: Information released by my supervisor and management is reliable procedural justice refers to the degree of fairness in decision-making, which was evaluated with a single question: “During the process of making important decisions, my supervisor and management inform employees and provide sufficient information.” Each item was measured through a 4-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). The mean scores of each dimension and the degree of workplace justice summing up each dimension were then calculated and standardized from 0 to 100. These scores were ranked and divided into low and high based on the dichotomy in regression models. The method for cutting groups using statistical software is also commonly found in other articles.[11,13]
2.3. Measures
2.3.1. Self-evaluated nonfatal occupational accidents
Self-evaluated nonfatal occupational accidents were the dependent variable in this study, which was assessed by a single question whose answer was yes or no: “Have you ever suffered a work-related injury or illness in the last 12 months prior to the survey?.”
2.3.2. Sociodemographic and physical job demands variables
Various sociodemographic variables were sought, including sex and age. For analyses, we assessed variables like sex (male or female) and age (20–29, 30–39, 40–49, or 50–65 years). On the other hand, physical job demands were measured by a single question: “My job requires a lot of physical effort.” All responses were sorted with a 4-point scale ranging from 1 to 4, which represented, in increasing order, strongly disagree to strongly agree. We classified “strongly agree” and “agree” as “Yes,” while “disagree” and “strongly disagree” were classified as “No” in the analysis of this study.
2.3.3. Status of shift work and work contract
We also collected the type of work shift of the week before the time of the survey. Only the following shift types, fixed morning, afternoon, and evening, are included, except those extending till midnight. Nonstandard shifts are inclusive of evening shifts, night shifts, rotating shifts, and unscheduled shifts. For analyses, we dichotomized responses into 2 types: fixed day and evening shifts, including fixed morning, afternoon, and evening except those extending till midnight, and rotating and graveyard shifts, while nonstandard shifts included evening, night, rotating, and unscheduled shifts. Information on employment type was collected through questionnaires and classified into 4 categories: (i) permanent employment, usually with contract renewal available; (ii) contract employment, temporary work, short-term and seasonal contracts; (iii) temporary employment, part-time student work, substitute work, and other nonpermanent employees without a defined employment period; and (iv) others. We classified (i) as standard and (ii) and (iii) as nonstandard and included them in this study’s analysis.
2.3.4. Psychological demands of work
Self-report of psychological job demands was assessed using the Chinese version of the Job Content Questionnaire based on Karasek job strain model. The job strain model postulates that high job demands give rise to high levels of job stress, contributing to health consequences.[26,27] The job demand scale is a 7-item instrument consisting of the following questions: my work requires me to work fast; my work requires me to work hard; my workloads are not excessive; I have enough time to get the job done; my work requires me to concentrate on my job for a long time; I am very hectic at work; there are insufficient personnel in my workplace. The answer to each inventory item was ranked from 1 for strongly disagree to 4 for strongly agree. Items stated in reverse are reverse coded. The scale was also verified with excellent reliability and validation in previous articles.[26] For analyses, scores of psychosocial work demands were calculated and standardized, ranging from 0 to 100, and divided into tertiles (low, medium, and high) by statistical software to allow comparison with other literature using this scale.[12,28]
2.4. Statistical analysis
SAS version 9.4 (SAS Institute, Cary, NC) set at a 5% significance level conducted all analyses. Descriptive statistics were presented as percentages, means, and standard deviations (SDs). The chi-square test was used in bivariate analysis. A multivariate logistic regression model was constructed without missing data to investigate the relationship between workplace justice and self-reported nonfatal occupational accidents after adjusting for sociodemographic variables, physical job demands, shift status, work contracts, and psychological job demands.
3. Results
A total of 715 healthcare professionals partook in the study. A correlation was identified between workplace justice and occupational accidents in the healthcare industry under a single-payer system. Table 1 indicates the descriptive statistics of gender, age, physical work demands, shift work status, work contracts, psychological work demands, workplace justice, and nonfatal work accidents. The prevalence of self-evaluated occupational accidents in healthcare employees was 15.54% and 11.64% for men and women, respectively. Among the surveyed, variables such as physical load at work (79 men, 53.38%; 301 women, 53.09%), fixed day and evening shifts (104 men, 70.75%; 364 women, 64.54%), and standard work contracts (121 men, 81.76%; 465 women, 83.04%) were predominantly for both genders. The respondents were predominantly between 50 and 65 years old in men (n = 46, 31.08%) and 30 to 39 years old in women (n = 205, 36.16%).
Table 1.
Descriptive statistics of sex, ages, physical job demands, status of shift work, work contract, psychological demands of work, workplace justice, and nonfatal occupational accidents of healthcare employees.
| Variables | Frequency, n (%) | ||
|---|---|---|---|
| Total (N = 715) | Men (N = 148) | Women (N = 567) | |
| Nonfatal occupational accidents | |||
| Yes | 89 (12.45) | 23 (15.54) | 66 (11.64) |
| No | 626 (87.55) | 125 (84.46) | 501 (88.36) |
| Age groups | |||
| 20 to 29 yrs | 199 (27.83) | 25 (16.89) | 174 (30.69) |
| 30 to 39 yrs | 243 (33.99) | 38 (25.68) | 205 (36.16) |
| 40 to 49 yrs | 149 (20.84) | 39 (26.35) | 110 (19.4) |
| 50 to 65 yrs | 124 (17.34) | 46 (31.08) | 78 (13.76) |
| χ2 value | 3.66 | 0.7 | 2.33 |
| Physical load demands | |||
| Yes | 380 (53.15) | 79 (53.38) | 301 (53.09) |
| No | 335 (46.85) | 69 (46.62) | 266 (46.91) |
| χ2 value | 12.70*** | 2.87 | 9.85** |
| Status of shift work | |||
| Fixed day and evening shifts | 468 (65.82) | 104 (70.75) | 364 (64.54) |
| Rotating and graveyard shifts | 243 (34.18) | 43 (29.25) | 200 (35.46) |
| Missing value | 4 | 1 | 3 |
| χ2 value | 1.85 | 5.38* | 0.13 |
| Work contract | |||
| Standard | 586 (82.77) | 121 (81.76) | 465 (83.04) |
| Nonstandard | 122 (17.23) | 27 (18.24) | 95 (16.96) |
| Missing value | 7 | 7 | |
| χ2 value | 2.13 | 2.71 | 0.48 |
| Psychological demands of work: mean score (standard deviation) | 43.73 (13.44) | 42.37 (13.85) | 44.09 (13.32) |
| Low | 203 (28.55) | 55 (37.41) | 148 (26.24) |
| Medium | 316 (44.44) | 54 (36.73) | 262 (46.45) |
| High | 192 (27) | 38 (25.85) | 154 (27.3) |
| Missing value | 4 | 1 | 3 |
| χ2 value | 17.89*** | 1.49 | 20.26*** |
| Distributive justice: mean score (standard deviation) | 58.31 (17.28) | 59.18 (17.65) | 58.08 (17.19) |
| Low | 454 (63.94) | 101 (68.71) | 353 (62.7) |
| High | 256 (36.06) | 46 (31.29) | 210 (37.3) |
| Missing value | 5 | 1 | 4 |
| χ2 value | 38.83*** | 16.38*** | 24.80*** |
| Procedural justice: mean score (standard deviation) | 62.1 (15.77) | 62.93 (14.31) | 61.88 (16.13) |
| Low | 534 (75.21) | 115 (78.23) | 419 (74.42) |
| High | 176 (24.79) | 32 (21.77) | 144 (25.58) |
| Missing value | 5 | 1 | 4 |
| χ2 value | 255*** | 12.11*** | 11.15*** |
| Interactional justice: mean score (standard deviation) | 61.55 (15.45) | 62.47 (14.31) | 61.31 (15.73) |
| Low | 567 (79.75) | 119 (80.95) | 448 (79.43) |
| High | 144 (20.25) | 28 (19.05) | 116 (20.57) |
| Missing value | 4 | 1 | 3 |
| χ2 value | 29.53*** | 8.02*** | 21.86*** |
| Workplace justice: mean score (standard deviation) | 60.31 (15.02) | 61.19 (14.67) | 60.08 (15.11) |
| Low | 425 (59.94) | 97 (65.99) | 328 (58.36) |
| High | 284 (40.06) | 50 (34.01) | 234 (41.64) |
| Missing value | 6 | 1 | 5 |
| χ2 value | 25.56*** | 13.46*** | 14.89*** |
P < .05.
P < .01.
P < .001.
Among the surveyed men, the mean scores for psychological demands of work, distributive justice, procedural justice, interactional justice, and total workplace justice were 42.37 (SD = 13.85), 59.18 (SD = 17.65), 62.93 (SD = 14.31), 62.47 (SD = 14.31), and 61.19 (SD = 14.67), respectively, while those of the women were 44.09 (SD = 13.32), 58.08 (SD = 17.19), 61.88 (SD = 16.13), 61.31 (SD = 15.73), and 60.08 (SD = 15.11).
Bivariate analysis showed that nonfatal occupational accidents correlated with the status of shift work toward male employees, while that correlated with physical load and psychological demand of work toward female employees. It also indicated that occupational accidents correlated with distributive justice, procedural justice, interactional justice, and total workplace justice, whether male or female. Consequently, nonfatal occupational accidents were added to the multiple logistic regression models. As the data are shown in Table 2, while adjusting variables like age, status of shift work, work contract, physical load and psychological demands of work, those with lower scores in distributive justice (male: OR: 4.19; female: OR: 11.09), procedural justice (male: OR: 3.24; female: OR: 4.25), interactional justice (male: OR: 2.85; female: OR: 6.31) and total workplace justice (male: OR: 3.18; female: OR: 8.28) had higher chances of occupational accidents than those with higher scores no matter male or female. We could also tell from the data shown in Table 2 that when nonfatal occupational accidents were added to the multiple logistic regression models, both male and female healthcare industry employees had higher chances of occupational accidents in workplaces when scores were lower in distributive justice (male: OR: 4.19; female: OR: 11.09), procedural justice (male: OR: 3.24; female: OR: 4.25), interactional justice (male: OR: 2.85; female: OR: 6.31), and total workplace justice (male: OR: 3.18; female: OR: 8.28) after control of sociodemographic variables, physical job demands, status of shift work, work contract, and psychological demands of work. In comparison with the following variables, high distributive justice, high procedural justice, high interactional justice, and high total workplace justice, the odds of nonfatal occupational accidents were more significantly related to low distributive justice (male: OR: 4.19; female: OR: 11.09), low procedural justice (male: OR: 3.24; female: OR: 4.25), low interactional justice (male: OR: 2.85; female: OR: 6.31), and low total workplace justice (male: OR: 3.18; female: OR: 8.28) to both male and female healthcare industry employees.
Table 2.
Multiple logistic regression analysis of workplace justice and occupational accidents; adjusting age, physical job demands, status of shift work, work contract, and psychological demands of work; categorized by gender.
| Variables | Result of multiple logistic regression | |||||
|---|---|---|---|---|---|---|
| Total (N = 715) | Men (N = 148) | Women (N = 567) | ||||
| OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | |
| Distributive justicea | ||||||
| Low | 4.19 (2.52–6.96) | <.0001 | 11.09 (3.34–36.88) | <.0001 | 3.25 (1.82–5.81) | <.0001 |
| High | 1 | 1 | 1 | |||
| Procedural justicea | ||||||
| Low | 3.24 (1.97–5.32) | <.0001 | 4.25 (1.40–12.87) | .0106 | 3.03 (1.71–5.37) | .0002 |
| High | 1 | 1 | 1 | |||
| Interactional justicea | ||||||
| Low | 2.85 (1.75–4.64) | <.0001 | 6.31 (2.14–18.55) | .0008 | 2.21 (1.26–3.89) | .0060 |
| High | 1 | 1 | 1 | |||
| Workplace justicea | ||||||
| Low | 3.18 (1.93–5.25) | <.0001 | 8.28 (2.62–26.19) | .0003 | 2.44 (1.38–4.32) | .0023 |
| High | 1 | 1 | 1 | |||
OR = odds ratio.
Distributive justice, procedural justice, interactional justice, and workplace justice were automatically dichotomized (low and high) through statistical software.
4. Discussion
This study revealed vital relationships between workplace justice and self-reported nonfatal occupational accidents among Taiwanese healthcare workers. This is consistent with previous studies except for females.[13] The inconsistent results for female employees are possibly due to a lower gender-related exposure risk gap in the healthcare sector compared to the construction sector. Bakker and Demerouti[29] proposed the job demands-resources (JD-R) theoretical model, which challenges existing stress models and focuses on negative and positive employee well-being indicators. In a subsequent study, Derdowski and Mathisen[30] employed the JD-R theoretical model to ascertain preliminary evidence of a link between exposure to workplace psychosocial factors and safety in high-risk industries. Workplace justice represents one of the psychosocial factors within the workplace. We also used the JD-R theoretical model concept to examine the relationship between workplace justice and workplace accidents in healthcare, a low-risk sector. Workplace justice, including distributive justice, procedural justice, and interactional justice, was also related to self-evaluated nonfatal occupational accidents. This finding is a novel discovery to my knowledge.
The various facets of workplace justice are some of the psychological factors used for measuring the fairness or equality of the reward system, the decision-making process, interpersonal relationships, and timely and truthful information about major decisions.[15] Any dimension with lower workplace justice has a higher risk of nonfatal workplace disasters, possibly due to other psychosocial hazards, which easily increase dissatisfaction at work and thus increase the risk of nonfatal workplace disasters.[12,31] Future studies can trace this pathway longitudinally and further determine the causal relationships.
The following are several study limitations. To begin with, because of this study’s cross-sectional nature, it was impossible to determine the causal relationship between justice in the workplace and self-reported nonfatal work accidents. Furthermore, the effect of social choice was unavoidable since workers with a history of accidents may have been forced to work with low workplace justice. Future researchers should administer longitudinal study designs that follow the career pathways to confirm causal relationships between workplace justice and self-evaluated nonfatal occupational accidents. On top of that, by dint of the self-report nature of the survey, the results of workplace justice may have been influenced by respondents’ subjective perceptions even though the validity and reliability of the questionnaire items were supported by previous research. It may be the case that self-report of occupational accidents presents a similar situation. Consequently, it is possible to reduce the bias and limitations of this section by involving an impartial third party in identifying occupational hazards and self-identifying the respondents. Moreover, recall bias may have affected the results, as respondents were asked to recall whether they had suffered from a work-related injury or illness in the previous 12 months. Thus, it is possible to reduce the bias and limitations of this section by involving an impartial third party in identifying occupational hazards and self-identifying the respondents. Last but not least, on the grounds of limitations in the survey questionnaire design, no adjustment was made for factors like personality or obstructive sleep apnea.[32,33] Accordingly, the correlation between workplace justice and self-reported nonfatal occupational injuries among healthcare workers may have been overestimated in this study. Future studies should measure additional variables to capture a wider range of associations. Recommend longitudinal studies to better establish causality and explore the effects of interventions aimed at improving workplace justice. This study exclusively analyzed healthcare workers and excluded the self-employed and employers, limiting the generalizability of the study’s findings.
Despite the above limitations, the results of this study demonstrate the prevalence of nonfatal occupational accidents and their association with workplace justice among healthcare professionals.
5. Conclusions
Workplace justice is one of the psychosocial factors in the workplace. Previous studies have indicated that enhancing positive psychosocial factors can help to reduce occupational hazards. Consequently, when employers or policymakers endeavor to enhance fairer distribution, smoother communication channels, and more respect and trust, the occurrence of occupational disasters will naturally decrease. We also found that workplace justice in the healthcare sector was correlated with nonfatal occupational accidents in a single-payer universal health insurance system. In controlling the expenditure on health care, policymakers should not lose sight of the workplace justice of promoting the healthcare industry.
6. Practical implications
Expanding the study to include healthcare systems in different countries could enhance the generalizability of the findings. Offering specific recommendations for policymakers and healthcare administrators to improve workplace justice and reduce occupational accidents.
Acknowledgments
Thanks to all peer reviewers for their opinions and suggestions.
Author contributions
Conceptualization: Ching-Mei Hsieh, Sheryl Chen, Chieh-Jan Chen.
Formal analysis: Ching-Mei Hsieh, Chieh-Jan Chen.
Software: Ching-Mei Hsieh, Albert Chen, Chieh-Jan Chen.
Writing – original draft: Ching-Mei Hsieh.
Data curation: Sheryl Chen, Tsu-Te Peng, Po-Han Chen, Albert Chen.
Methodology: Sheryl Chen, Tsu-Te Peng, Po-Han Chen, Albert Chen.
Supervision: Chieh-Jan Chen.
Validation: Chieh-Jan Chen.
Writing – review & editing: Chieh-Jan Chen.
Abbreviations:
- GDP
- gross domestic product
- JD-R
- job demands-resources
- OECD
- organisation for economic cooperation and development
- OR
- odds ratio
- OSH
- occupational safety and health
- SD
- standard deviation
- UHC
- universal health coverage.
The authors have no funding and conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Hsieh C-M, Chen S, Peng T-T, Chen P-H, Chen A, Chen C-J. The relationship between workplace justice and self-evaluated nonfatal occupational accidents among healthcare employees in Taiwan: An observational study. Medicine 2024;103:32(e39215).
Contributor Information
Ching-Mei Hsieh, Email: cm.ns10@nycu.edu.tw.
Tsu-Te Peng, Email: D99521018@ntu.edu.tw.
Po-Han Chen, Email: d00848003@ntu.edu.tw.
References
- [1].International Labour Organization (ILO). Occupational Safety and Health Statistics (OSH) database. https://ilostat.ilo.org/methods/concepts-and-definitions/description-occupational-safety-and-health-statistics/. Accessed June 15, 2024. [Google Scholar]
- [2].World Health Organization (WHO). Universal health coverage (UHC). Geneva: WHO; 2023. https://www.who.int/news-room/fact-sheets/detail/universal-health-coverage-(uhc). Accessed June 15, 2024. [Google Scholar]
- [3].Stoesz B, Chimney K, Deng C, et al. Incidence, risk factors, and outcomes of non-fatal work-related injuries among older workers: a review of research from 2010 to 2019. Saf Sci. 2020;126:104668. [Google Scholar]
- [4].Win KN, Trivedi A, Lai A, et al. Non-fatal occupational accidents in Brunei Darussalam. Ind Health. 2021;59:193–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Biswas A, Harbin S, Irvin E, et al. Sex and gender differences in occupational hazard exposures: a scoping review of the recent literature. Curr Environ Health Rep. 2021;8:1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Cabello AT, Martínez-Rojas M, Carrillo-Castrillo JA, et al. Occupational accident analysis according to professionals of different construction phases using association rules. Saf Sci. 2021;144:105457. [Google Scholar]
- [7].Peng L, Chan AHS. A meta-analysis of the relationship between ageing and occupational safety and health. Saf Sci. 2019;112:162–72. [Google Scholar]
- [8].Nai’em MF, Darwis AM, Maksun SS. Trend analysis and projection of work accidents cases based on work shifts, workers age, and accident types. Gac Sanit. 2021;35:S94–7. [DOI] [PubMed] [Google Scholar]
- [9].Koranyi I, Jonsson J, Rönnblad T, et al. Precarious employment and occupational accidents and injuries – a systematic review. Scand J Work Environ Health. 2018;44:341–50. [DOI] [PubMed] [Google Scholar]
- [10].Baby T, Madhu G, Renjith VR. Occupational electrical accidents: assessing the role of personal and safety climate factors. Saf Sci. 2021;139:105229. [Google Scholar]
- [11].Hsieh CM, Chen S, Peng TT, et al. Relationships among burnout, job dissatisfaction, psychosocial work conditions and minor mental disorders of precarious employment in Taiwan. J Men’s Health. 2022;18:146. [Google Scholar]
- [12].Chen CJ, Cheng Y, Ho JJ. Prevalence, distribution, and correlates of self-reported non-fatal occupational injuries or diseases among employees in Taiwan [in Chinese]. Taiwan J Public Health. 2015;30:391–402. [Google Scholar]
- [13].Hsieh CM, Chen CJ, Peng TT, et al. The relationship between workplace justice and self-reported occupational accidents in construction employees of Taiwan. Ind Health. 2020;58:282–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Donovan MA, Drasgow F, Munson LJ. The perceptions of fair interpersonal treatment scale: development and validation of a measure of interpersonal treatment in the workplace. J Appl Psychol. 1998;83:683–92. [DOI] [PubMed] [Google Scholar]
- [15].Elovainio M, Kivimäki M, Vahtera J. Organizational justice: evidence of a new psychosocial predictor of health. Am J Public Health. 2002;92:105–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Tufail MS, Mahesar HA, Pathan SK. Organizational justice, task and contextual performance: empirical analysis for front line managers. Grassroots. 2017;51:17260396. [Google Scholar]
- [17].Colquitt JA, Conlon DE, Wesson MJ, et al. Justice at the millennium: a meta-analytic review of 25 years of organizational justice research. J Appl Psychol. 2001;86:425–45. [DOI] [PubMed] [Google Scholar]
- [18].Moorman RH. Relationship between organizational justice and organizational citizenship behaviors: do fairness perceptions influence employee citizenship? J Appl Psychol. 1991;76:845–55. [Google Scholar]
- [19].Cheng Y, Huang HY, Li PR, et al. Employment insecurity, workplace justice and employees’ burnout in Taiwanese employees: a validation study. Int J Behav Med. 2011;18:391–401. [DOI] [PubMed] [Google Scholar]
- [20].Chan WSH. Taiwan’s healthcare report 2010. EPMA J. 2010;1:63–585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [21].Lee YH, Ang TFA, Chiang TC, et al. Growing concerns and controversies to Taiwan’s National Health Insurance – what are the lessons from mainland China, South Korea and Singapore? Int J Health Plann Manage. 2018;33:e357–66. [DOI] [PubMed] [Google Scholar]
- [22].Yip WC, Lee YC, Tsai SL, et al. Managing health expenditure inflation under a single-payer system: Taiwan’s National Health Insurance. Soc Sci Med. 2019;233:272–80. [DOI] [PubMed] [Google Scholar]
- [23].Matteson ML, Ming Y, Silva DE. The relationship between work conditions and perceptions of organizational justice among library employees. Libr Inform Sci Res. 2021;43:101093. [Google Scholar]
- [24].Mengistu DA, Tolera ST. Prevalence of occupational exposure to needle-stick injury and associated factors among healthcare workers of developing countries: systematic review. J Occup Health. 2020;62:e12179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [25].Colquitt JA. On the dimensionality of organizational justice: a construct validation of a measure. J Appl Psychol. 2001;86:386–400. [DOI] [PubMed] [Google Scholar]
- [26].Cheng Y, Luh WM, Guo YL. Reliability and validity of the Chinese version of the job content questionnaire in Taiwanese workers. Int J Behav Med. 2002;10:15–30. [DOI] [PubMed] [Google Scholar]
- [27].Karasek RA. Job demands, job decision latitude, and mental strain: implications for job redesign. Admin Sci Quart. 1979;24:285–308. [Google Scholar]
- [28].Chung PH, Cheng Y. Prevalence of self-reported work-related injuries and their association with psychological symptoms in general working population of Taiwan. J Occup Rehabil. 2017;27:195–201. [DOI] [PubMed] [Google Scholar]
- [29].Bakker AB, Demerouti E. The job demands-resources model: state of the art. J Manag Psychol. 2007;22:309–28. [Google Scholar]
- [30].Derdowski LA, Mathisen GE. Psychosocial factors and safety in high-risk industries: a systematic literature review. Saf Sci. 2023;157:105948. [Google Scholar]
- [31].Özer O, Özkan O, Özmen S, et al. Investigation of the perception of occupational safety, work stress and happiness in healthcare workers. J Health Manag. 2023;25:813–9. [Google Scholar]
- [32].Ma L, Guo H, Fang Y. Analysis of construction workers’ safety behavior based on Myers-Briggs Type Indicator Personality Test in a bridge construction project. J Constr Eng Manag. 2021;147:04020149. [Google Scholar]
- [33].Shaik L, Cheema MS, Subramanian S, et al. Sleep and safety among healthcare workers: the effect of obstructive sleep apnea and sleep deprivation on safety. Medicina (Kaunas). 2022;58:1723. [DOI] [PMC free article] [PubMed] [Google Scholar]