All published articles of this journal are available on ScienceDirect.
Work Performance Among Workers without Disabilities after Industrial Accidents: A Longitudinal Study
Abstract
Background
Industrial accidents are work-related accidents and these accidents can result in disability. However, if workers receive appropriate treatment after an accident, they often recover without disability. Most of them return to their daily lives and work. When they return to work, they are expected to perform at the same level asbefore the accident.
Aim
This study was to identify the factors affecting the performance of workers resuming work without disability after industrial accidents.
Methods
This study was designed as a longitudinal study. Among workers who completed their industrial accident care, 2000 stratified random samples were investigated through a cohort survey by the Korea Workers' Compensation & Welfare Service, Labor Welfare Research Institute. The analysis of this study was conducted using data from 264 subjects without disabilities selected from among 2000 subjects. This study analyzed the data of the following variables: age, gender, education, marital status, health status before an industrial accident, occupational classification, claim duration, chronic disease, work performance, current health status, daily life satisfaction, self-esteem, and self-efficacy of the subjects.
Results
The current health status, having a chronic disease, daily life satisfaction,overall life, and claim duration of less than 3 months accounted for 39.9% influence on work performance (F = 42.972, p ≤ 0.001), and the current health status influenced work performance the most.
Conclusions
It is important to support the workers so they can accomplish their work without failing. A system should be established to manage workers' health and chronic diseases. This may reduce health-threatening risks and prevent further industrial accidents and could improve the work performance of workers resuming work after an industrial accident.
1. INTRODUCTION
An industrial accident is a work-related accident involving injuries, disease, disability, or even death while performing duties [1]; it can be called an occupational or workplace accident. According to the Ministry of Employment and Labor, the industrial accident rate from 2001 to 2013 in Korea was 0.59%–0.9% [2], which decreased to 0.48–0.54% from 2014 to 2018 [2]. However, it increased to 0.58% in 2019 and 0.57% in 2020, and the total number of workers who suffered an industrial accident was 108,379 in 2020 [3]. Industrial accidents greatly impact the physical, social, mental, and economic aspects of workers [4, 5], as well as quality of life [6]. They also affect their participation in the labor market by partially or completely compromising their work capacity [7].
According to the Enforcement Decree of the Industrial Accident Compensation Insurance Act [8], if any disability occurs from an industrial accident, it is classified on a disability scale of 1–14, with smaller numbers reflecting higher levels of physical disability. If there is a disability, workers may need assistance with activities of daily life, and if health is compromised to this extent, they may lose labor ability. In the case of a disability scale score of 14, the working capacity was only mildly compromised. As the disability scale score moves toward 1, the loss of labor capacity becomes severe, and at a score of 1, 90%–100% of the labor ability is lost [9]. However, there are many cases wherein workers have no disability after proper post-accident treatment. In 2012, 50,340 out of 82,493 workers, amounting to 61%, had no disability after industrial accidents [10]. Most of them return to their daily lives and work.
The industrial accident compensation insurance system helps workers who have suffered an industrial accident in Korea. According to the Industrial Accident Compensation Insurance Act article 1 [1], the system is designed to ensure that adequate care is provided when workers are injured or sick from occupational accidents so that they can eventually return to work. It should help workers resume work and minimize any compromise in their working ability after industrial accidents. If and when they return to work, they also need help getting reacquainted with their job and displaying their ability at work.
Workers who have suffered industrial accidents may have difficulty returning to work, therefore, it is important to provide support to help them regain their work performance. However, there is limited literature available on factors influencing the work ability of workers who have experienced industrial accidents, making it challenging to explore strategies for enhancing their work performance. Therefore, this study aimed to identify the effect of variables on the work performance of industrial accident victims who resumed work with no disability.
2. MATERIALS AND METHODS
2.1. Design and Sample
This study used data from the Industrial Accident Compensation Panel Survey (1st–5th) conducted by the Korea Workers' Compensation & Welfare Service, Labor Welfare Research Institute. The Industrial Accident Compensation Panel Survey was a cohort survey conducted annually. The first survey started in 2013, and the fifth survey was conducted in 2017. Data collection were conducted by a professional interviewer who visited the subjects and performed a computer-assisted personal interview after obtaining written consent from them. Two thousand subjects were randomly sampled out of 89,921 workers who completed their industrial accident care program in 2012. The subjects were selected using stratified random sampling based on their disability scale score, residential area, age, gender, and use of rehabilitation services. The data from subjects with incomplete data collection over 4 years were excluded from the analysis of this study. The analysis was conducted using data from 264 subjects without disabilities. The sample size was determined based on a power analysis using G*Power software. With an anticipated effect size of 0.15, a significance level (alpha) of 0.05, and power (1-beta) set at 0.95, the required sample size was calculated to be 172 participants. It was confirmed that the sample size for this study was appropriate.
The data of the Industrial Accident Compensation Panel Survey had obtained the National Statistical Office approval statistical qualification, and its approval number was 439001. Regarding ethical considerations, this study received an IRB review exemption (ewha-201907-0010-01) before commencing the study.
2.2. Measures
In this study, the following variables were analyzed: age, gender, education, marital status, health status before the industrial accident, occupational classification, claim duration, chronic disease, work performance, current health status, daily life satisfaction, self-esteem, and self-efficacy of the subjects. The details for the last six elements of the above-mentioned list are as follows:
2.2.1. Chronic Disease
Subjects were asked to answer yes or no to whether they had any of the following diseases: Cancer, arthritis, back pain, sciatic pain, slip disc, gastritis, gastric ulcer, duodenal ulcer, chronic hepatitis, cirrhosis, diabetes, thyroid disease, hypertension, hypotension, stroke, cerebrovascular disease, myocardial infarction, angina, chronic bronchitis, tuberculosis, asthma, cataract, glaucoma, chronic otitis media, chronic renal failure, chronic kidney disease, fracture, dislocation and aftermath of accident, osteoporosis, and any other disease.
2.2.2. Work Performance
The subjects were asked to answer the following on a scale of 1–10: “If your work performance just before an industrial accident was '10', how much do you think your current work performance is?”
2.2.3. Current Health status
The subjects were asked, “How is your health condition?” and had to score their health status as 1 (very bad), 2 (bad), 3 (good), and 4 (very good).
2.2.4. Self-esteem
For measuring self-esteem, the scale described by Jeon [11] was used, which was a revised form of the Rosenberg self-esteem [12]. This scale comprised 10 items, each scored on a four-point Likert scale. Higher scores indicated higher self-esteem. The reliability of this scale was Cronbach’s α = 0.768–0.800 in this study.
2.2.5. Self-efficacy
The scale of Hong [13] was used to measure self-efficacy in this study. The scale of Hong (1995) was a revised form of the self-efficacy scale (SES) by Sherer et al. [14]. The scale included 23 items, and it was rated on a five-point Likert scale. Higher scores indicated higher self-efficacy. The reliability of this scale in this study was Cronbach’s α = 0.906–0.920.
2.2.6. Daily Life Satisfaction
Daily life satisfaction was measured by asking, “How satisfied are you with ____?” and the following seven items were placed in the blank: overall life, family income, leisure life, residential environment, family relationships, relative relationships, and social relationships. The satisfaction level of daily life was 1: “very satisfied,” 2: “satisfied,” 3: “undecided,” 4: “not satisfied,” and 5: “not very satisfied.” Lower scores indicated higher daily life satisfaction.
2.3. Analytic Strategy
The data were analyzed using the SPSS 27.0 program in this study. It utilized frequency and percentage to describe demographic characteristics and the morbidity of chronic disease annually. Mean and standard deviation were used to explore work performance, current health status, self-esteem, self-efficacy, and daily life satisfaction. Multiple regression analysis, including the assessment of multicollinearity, was conducted to identify the impact variables on work performance. The level of statistical significance was set at p < 0.05.
3. RESULTS
3.1. General Characteristics
The subjects of this study were 264, as shown in Fig. (1). General characteristics of the subjects are shown in Table 1. There were 198 men (75%) and 66 women (25%). Regarding the question about health conditions before the industrial accident, 79.5% of the respondents responded that they were “healthy” or “very healthy.”
The respondents' occupational classification showed that 34.7% were skilled workers and 24.6% were manual laborers. The claim duration was less than 3 months at 54.2% and 3 to 6 months at 31.4%.
3.2. Chronic Disease Morbidity
The proportion of subjects who reported having chronic disease was 15.9% (42 people) in the first survey; however, the rate gradually increased with the years, and in the fifth survey, it showed values as high as 34.1% (90 people), as shown in Table 2 and Fig. (2). Among the respondents who said they had a chronic disease in the fifth survey, hypertension and hypotension were the most prevalent, with a combined occurrence rate of 41.1%. Furthermore, the occurrence rate was 25.6% for diabetes and 30% for arthritis, back pain, sciatic pain, and slip disc combined.
| - | - | 1st Survey 2013 |
2nd Survey 2014 |
3rd Survey 2015 |
4th Survey 2016 |
5th Survey 2017 |
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | n | % | |||
| Gender | Male | 198 | 75 | same | ||||||||
| Female | 66 | 25 | ||||||||||
| Age, Year | ≤29 | 26 | 9.8 | 22 | 8.3 | 19 | 7.2 | 16 | 6.1 | 12 | 4.5 | |
| 30–39 | 49 | 18.6 | 48 | 18.2 | 43 | 16.3 | 40 | 15.2 | 40 | 15.2 | ||
| 40–49 | 64 | 24.2 | 60 | 22.7 | 60 | 22.7 | 55 | 20.8 | 53 | 20.1 | ||
| 50–59 | 81 | 30.7 | 87 | 33.0 | 80 | 30.3 | 77 | 29.2 | 78 | 29.5 | ||
| ≥60 | 44 | 16.7 | 47 | 17.8 | 62 | 23.5 | 76 | 28.8 | 81 | 30.7 | ||
| Education | Uneducated | 9 | 3.4 | 9 | 3.4 | 9 | 3.4 | 9 | 3.4 | 9 | 3.4 | |
| Elementary school | 43 | 16.3 | 43 | 16.3 | 44 | 16.7 | 44 | 16.7 | 44 | 16.7 | ||
| Middle school | 45 | 17.0 | 45 | 17.0 | 44 | 16.7 | 44 | 16.7 | 44 | 16.7 | ||
| High school | 114 | 43.2 | 114 | 43.2 | 114 | 43.2 | 114 | 43.2 | 113 | 42.8 | ||
| College and above | 53 | 20.1 | 53 | 20.1 | 53 | 20.1 | 53 | 20.1 | 54 | 20.5 | ||
| Marital status | Unmarried | 53 | 20.1 | 51 | 19.3 | 47 | 17.8 | 47 | 17.8 | 45 | 17.0 | |
| Married | 179 | 67.8 | 179 | 67.8 | 183 | 69.3 | 180 | 68.2 | 184 | 69.7 | ||
| Separated | 2 | 0.8 | 2 | 0.8 | 4 | 1.5 | 4 | 1.5 | 3 | 1.1 | ||
| Divorced | 18 | 6.8 | 19 | 7.2 | 19 | 7.2 | 21 | 8.0 | 20 | 7.6 | ||
| Bereaved | 12 | 4.5 | 13 | 4.9 | 11 | 4.2 | 12 | 4.5 | 12 | 4.5 | ||
| Health status before an accident | Very healthy | 80 | 30.3 | - | ||||||||
| Healthy | 130 | 49.2 | ||||||||||
| Moderate | 43 | 16.3 | ||||||||||
| Not healthy | 11 | 4.2 | ||||||||||
| Occupational classification | Manager | 9 | 3.4 | - | ||||||||
| Professional | 16 | 6.1 | - | |||||||||
| Clerical staff | 8 | 3.0 | - | |||||||||
| Service sector worker | 29 | 11.0 | - | |||||||||
| Salesperson | 8 | 3.0 | - | |||||||||
| Agricultural skilled worker | 6 | 2.3 | - | |||||||||
| Skilled worker (Manufacturing or Construction, etc.) | 90 | 34.1 | - | |||||||||
| Machine Operators | 33 | 12.5 | - | |||||||||
| Manual laborer | 65 | 24.6 | - | |||||||||
| Claim duration | Less than 3 months | 143 | 54.2 | - | ||||||||
| 3 to 6 month | 83 | 31.4 | - | |||||||||
| 6 to 9 month | 22 | 8.3 | - | |||||||||
| 9 to 12 month | 5 | 1.9 | - | |||||||||
| More than 1 year | 11 | 4.2 | - | |||||||||
3.3. Work Performance, Current Health Status, Self-esteem, Self-efficacy, and Daily Life Satisfaction
The changes in scores of the variables from the first to the fifth survey are shown in Table 3.
3.4. Factors Affecting Work Performance
Considering age, occupational classification, claim duration, current health status, having a chronic disease, self-esteem, self-efficacy, and daily life satisfaction as independent variables, multiple regression analysis was conducted to identify factors that affect work performance. This analysis was performed with data from the fifth and last survey conducted in 2017. Daily life satisfaction in terms of overall life, family income, leisure life, residential environment, family relationship, relative relationship, and social relationship were included in daily life satisfaction, and they were separately set as seven independent variables.
| - | 1st Survey 2013 |
2nd Survey 2014 |
3rd Survey 2015 |
4th Survey 2016 |
5th Survey 2017 |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | n | % | |
| Presence of chronic disease | 42 | 15.9 | 53 | 20.1 | 66 | 25.0 | 73 | 27.7 | 90 | 34.1 |
Consequently, current health status, having a chronic disease, daily life satisfaction_overall life, and claim duration of less than 3 months accounted for 39.9% of work performance (F = 42.972, p ≤ 0.001), as shown in Tables 4 and 5. The current health status was the most influential factor in work performance.
The best-fit model was represented by the equation:
Work Performance = 5.615 + 1.293(Current health status) − 0.654(Having a chronic disease) − 0.409(Daily life satisfaction_overall life) + 0.375 (Claim duration of less than 3 months)
| - | 1st Survey 2013 |
2nd Survey 2014 |
3rd Survey 2015 |
4th Survey 2016 |
5th Survey 2017 |
Possible Range |
|---|---|---|---|---|---|---|
| M ± SD | M ± SD | M ± SD | M ± SD | M ± SD | - | |
| Work performance | 7.29±2.35 | 7.95±2.12 | 8.16±1.92 | 8.29±1.76 | 8.25±1.83 | 0–10 |
| Current health status | 2.79±0.70 | 2.78±0.67 | 2.80±0.64 | 2.83±0.64 | 2.84±0.63 | 1–4 |
| Self-esteem | 30.47±4.44 | 30.45±4.53 | 30.7±4.13 | 31.23±4.00 | 30.99±4.06 | 10–40 |
| Self-efficacy | 80.71±11.33 | 81.15±11.00 | 81.03±10.59 | 80.38±11.32 | 80.00±10.61 | 23–115 |
| Daily life satisfaction_ overall life | - | 2.58 ± 0.62 | 2.48 ± 0.55 | 2.43 ± 0.55 | 2.5 ± 0.62 | 1–5 |
| Daily life satisfaction_ family income | 3.15±0.82 | 3.18±0.87 | 3.08±0.82 | 2.99±0.76 | 3.09±0.78 | 1–5 |
| Daily life satisfaction_ leisure life | 2.92±0.76 | 2.87±0.77 | 2.88±0.66 | 2.82±0.65 | 2.85±0.75 | 1–5 |
| Daily life satisfaction_ residential environment | 2.68±0.73 | 2.68±0.77 | 2.59±0.66 | 2.61±0.69 | 2.24±0.68 | 1–5 |
| Daily life satisfaction_ family relationship | 2.28±0.73 | 2.31±0.70 | 2.28±0.61 | 2.22±0.60 | 2.24±0.68 | 1–5 |
| Daily life satisfaction_ relative relationship | 2.42±0.66 | 2.43±0.69 | 2.39±0.62 | 2.36±0.62 | 2.41±0.66 | 1–5 |
| Daily life satisfaction_ social relationship | 2.42±0.61 | 2.42±0.61 | 2.40±0.56 | 2.33±0.59 | 2.39±0.64 | 1–5 |
| Explanatory Variables | Model 1 | Model 2 | Model 3 | Model 4 | ||||
|---|---|---|---|---|---|---|---|---|
| B | p | B | p | B | p | B | p | |
| Current health status | 1.704 | 0.000 | 1.506 | 0.000 | 1.311 | 0.000 | 1.293 | <0.001 |
| Having a chronic disease | - | - | -0.645 | 0.002 | -0.635 | 0.002 | −0.654 | 0.001 |
|
Daily life satisfaction_ overall life
|
- | - | - | - | -0.468 | 0.004 | −0.409 | 0.012 |
| Claim duration of less than 3 months | - | - | - | - | - | - | 0.375 | 0.039 |
| R 2 | 0.345 | 0.369 | 0.389 | 0.399 | ||||
| adj.R 2 | 0.343 | 0.364 | 0.382 | 0.390 | ||||
| Explanatory Variables | Unstandardized Coefficient | Standardized Coefficient | t | p | Durbin-Watson | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| B | SE | Beta | |||||||||||||
| Current health status | 1.293 | 0.167 | 0.446 | 7.755 | <0.001 | 2.108 | |||||||||
| Having a chronic disease | −0.654 | 0.203 | −0.170 | −3.218 | 0.001 | ||||||||||
| Daily life satisfaction_ overall life | −0.409 | 0.161 | −0.138 | −2.540 | 0.012 | ||||||||||
| Claim duration of less than 3 months | 0.375 | 0.181 | 0.102 | 2.074 | 0.039 | ||||||||||
| Constant | 5.615 | 0.766 | - | 7.327 | <0.001 | ||||||||||
In this equation, the unstandardized coefficients for the explanatory variables were as follows:
(1) For current health status (X1), the coefficient was 1.293.
(2) For having a chronic disease (X2), the coefficient was -0.654.
(3) For daily life satisfaction_overall life (X3), the coefficient was -0.409.
(4) For a claim duration of less than 3 months (X4), the coefficient was 0.375. Additionally, the constant term in the equation was 5.615.
4. DISCUSSION
We examined the factors affecting the work performance of industrial accident victims who resumed work with no disabilities.
After finishing the treatment of the injury caused by industrial accidents, workers without disabilities must return to work and engage in economic activities. In this case, it is important to maintain their ability to perform as they did before the industrial accident. According to the results of this study, factors influencing work performance were overall current health status, having a chronic disease, overall satisfaction with daily life, and a claim duration of less than 3 months. In addition, the current health status was the most influential factor in work performance. This result suggests the significance of proper health in performing workers' tasks. However, when treatment is completed after an industrial accident, it is not easy to encounter a system that can manage their health at work [15, 16]. Some companies hire an occupational health nurse [17, 18]; however, it is possible when the company has the economic capacity to afford it [19]. Having a dedicated department or staff to manage the health of workers at work would certainly be helpful; however, many companies are small-sized and cannot sustain this due to the financial burden.
In addition, this study found that having a chronic disease was a factor that affected working ability. Based on this result, the system to manage chronic diseases for workers may also contribute to improving their work performance. Moreover, the morbidity of chronic disease increased from 15.9% in 2013 to 34.1% in 2017, showing a two-fold increase in four years in this study. Although the rate of 15.9% in 2013 was not too high, it increased to a markedly higher rate of 34.1% in four years, which is a drastic increase even considering the increase in the age of subjects over this period. Furthermore, because chronic health conditions may increase the risk of occupational accidents in a workplace [20], a system should be established to manage chronic diseases of industrial accident victims returning to work; this system may reduce the threat to the subject's health and prevent the recurrence of industrial accidents.
Many workers may not meet healthcare professionals in the workplace. In addition, it is not easy for workers to take out time and schedule an appointment with healthcare professionals to address any discomfort in their body or promote their health during working hours. In these cases, telemedicine can help manage proper health among workers [21]. However, the use of telemedicine in Korea is not widespread due to situational and legal restrictions [22, 23]. The introduction of telemedicine, which can systematically and regularly manage workers’ health, will lead to more efficient improvements in health and help manage and prevent chronic diseases. The implementation of such a system would greatly improve their performance.
This study found that the “daily life satisfaction_ overall life” of the subjects affected the improvement of job performance. If they were satisfied with this parameter, they were less likely to be distracted by another problem and could concentrate on their work and improve their working performance. This study recommends forming peer groups that are organized and operated according to the common interests of workers. Through such groups, they can share information about any specific experience they have had, and they will be able to consult among themselves when problems or concerns arise.
In conclusion, the significance of this study lies in its investigation of the impact of variables on the work performance of industrial accident victims who were re-employed. By exploring factors that influence work performance, this study contributes to the development of strategies to help workers after accidents and provides valuable insights to health professionals.
This study has the following limitations and suggestions. First, work types are classified into various types observed in the current modern industry. However, this aspect was not considered in this study. The data used in this study were obtained from the stratified random sampling survey on the total number of industrial accident victims in 2012 in Korea; thus, the types of jobs and injuries included were diverse and varied. Accordingly, it was very difficult to find patterns between job types and injuries from the data. However, a study on industrial accidents based on injury type and occupational group is essential. Further studies incorporating these aspects should be conducted. Second, this study was analyzed using data obtained from Koreans. Therefore, it is unclear whether the results of this study can be generalized to subjects of other nationalities than Korea. Therefore, additional research is needed to determine whether the results of this study can be applied to population groups or regions other than Korea. Third, we propose that developing a system that can help those who return to work would be greatly helpful; it is important that its effectiveness should be evaluated so that more efficient systems can be implemented in workplaces. To achieve this, positive and active discussions on the introduction of telemedicine should be advanced for more efficient healthcare workers.
CONCLUSION
The purpose of this study was to determine the influence of variables on the work performance of industrial accident victims who returned to work without disability. The subjects of this study were 264 individuals without disabilities selected from the Industrial Accident Compensation Panel Survey(1st–5th) out of 2,000 who recovered after industrial accidents. As a result of this study, the morbidity rate of subjects with chronic diseases increased from 15.9% to 34.1% during four years. In addition, “current health status,” “having a chronic disease,” “daily life satisfaction_overall life,” and “claim duration of less than 3 months” affected the work performance. The most influential factor in work performance was the current health status. Age, occupational classification, self-esteem, and self-efficacy were not factors that affected the subjects' work performance. This result is meaningful as it helps workers adapt to their work when they resume after experiencing an industrial accident.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
The data of the Industrial Accident Compensation Panel Survey had obtained the National Statistical Office approval statistical qualification, and its approval number was 439001. Regarding ethical considerations, this study received an IRB review exemption (ewha-201907-0010-01) before commencing the study.
