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Article

A Comparison of Occupational Safety Perceptions among Domestic and Migrant Workers in Turkey

by
Tufan Öztürk
Occupational Health and Safety Programme, Istanbul Esenyurt University, 34510 Istanbul, Türkiye
Sustainability 2023, 15(21), 15245; https://doi.org/10.3390/su152115245
Submission received: 14 July 2023 / Revised: 22 October 2023 / Accepted: 23 October 2023 / Published: 25 October 2023
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Abstract

:
Due to a lack of stability, there has been an increase in migration from neighboring countries to Turkey since 2012. Hence, with the rising rate of migrant workers, issues concerning the employment and occupational safety of migrant workers have emerged. This study aims to compare the occupational safety perceptions and occupational accident levels of domestic and immigrant workers and to offer suggestions for helping immigrant workers work in a sustainable environment in terms of health and safety. The questionnaire was preferred as the data collection method for the research. A total of 11 questions were prepared to obtain information about the workers, and 25 questions were designed to determine their perceptions of occupational safety, for the 125 immigrants and 937 domestic workers who participated in the study. An independent sample t-test, ANOVA, Pearson correlation, and linear regression analysis were used. According to the results of this analysis, the safety perception level of migrant workers is lower than that of domestic workers. The safety perception levels of male, young, and inexperienced individuals are lower than all other groups. Age and education level reduce the occupational accident rate of migrant workers. Conversely, while age decreases the occupational accident level, sectorial experience increases the occupational accident rate for domestic workers. The study also offers some suggestions to boost the health and occupational safety level of immigrant workers sustainably.

1. Introduction

Anti-government protests and uprisings in Tunisia in 2010 soon turned into civil war, and the government was overthrown [1,2]. These events in Tunisia spread quickly to other North African and Middle Eastern countries [2,3]. People living in these regions had to migrate to relatively safer countries [4,5]. A mass migration movement has started from North African countries. Those from Syria mainly migrated to Turkey [5]. Furthermore, due to political instability, civil wars and financial reasons, many have migrated to neighboring countries over the last 50 years [6]. These migrations escalated in 2018, especially after the Taliban took over the administration again. Some Afghan immigrants preferred Turkey as a transit route to Europe or permanent settlement [7,8,9]. Due to such migration waves, Turkey hosts approximately 3.7 million Syrians and more than 320 thousand immigrants from other countries and, thus, ranks first in the world regarding the number of immigrants [10]. This immigration wave has had a considerable impact on the population and, thus, employment figures within the country. The unemployment rate, which used to have a decreasing trend in Turkey, until 2012, has been rising again [11]. There are many social and economic reasons for this trend; however, it must be noted that many immigrants seeking refuge in the country yet refusing to live in refugee camps directly take part in the labor market as unregistered workers [12], as it is difficult for them to be recruited officially with proper working conditions ensured. Since the country has a high unemployment rate, migrant workers are willing to do labor-intensive, unhealthy, polluted, dangerous, difficult, and low-paid jobs that local workers refuse to do [13]. In general, migrant workers often work in sectors such as recycling, construction, textile, vehicle repair, and transportation of physical goods. In addition, the concept of child labor has returned, as immigrant families’ children generally work in the recycling industry [14]. As a result, factors such as unemployment, unregistered employment, and the obligation to make a living cause migrant workers to experience more occupational health and safety problems than domestic workers do [15,16,17]. Considering Turkey’s rising number of immigrants, a permanent and sustainable solution is necessary. One such solution includes legal and public regulations to protect immigrants. Within this framework, some legal and public regulations are available in Turkey. First and foremost, Turkey is a party to the 1951 Convention on the Status of Refugees and its 1967 Protocol. In addition, Turkey enacts laws and makes institutional changes regarding refugees. The “Foreigners and International Protection Act” was passed in this context on 11 April 2014. As per this law, the Directorate of Migration Management was established as an institution responsible for refugee procedures. In addition, the “Temporary Protection Regulation” was issued on 22 October 2014 to regulate the situation of persons under temporary protection [18]. However, despite these regulations, migrant workers suffer from language and cultural barriers and past experiences.
According to the Turkish Social Security Institution data, 18,399,864 workers were employed in Turkey in 2021; 511,084 migrant employees had a work accident, and 1382 died due to an accident [19]. These statistics refer only to the registered workers in the country. When unregistered employment is considered, the figures will be more outstanding. Although the exact number of migrant workers in registered and unregistered employment is not precise, it can be assumed that a significant number of migrant workers died due to occupational accidents since Turkey hosts the highest number of immigrants in the world [10].
Therefore, detecting the factors influencing immigrant workers’ occupational security and offering sustainable suggestions is essential. In particular, migrant workers show different characteristics from domestic workers in terms of language, culture, and past experiences. For this reason, it is very important to identify the occupational problems of migrant workers, whose number is increasing in countries, and to offer solutions to these problems. Corvalan, Driscoll, and Harrison (1994) investigated the relationship between the characteristics of migrant workers in Australia and the work-related deaths of these workers. In this research, they analyzed annual labor force survey data. As a result of these analyses, they concluded that an increase in the language level of migrant workers and the length of residence in Australia reduces the work-related mortality rate [20]. Carangan, Tham, and Seow (2004) compared the work-related injury cases of domestic and migrant workers in Singapore. In their research, they applied questionnaires to injured workers who were treated in hospitals or to relatives of injured workers. They analyzed this survey data using the chi-square test and t-test. They found that the form and severity of injuries were similar in domestic and migrant workers, but migrant workers were injured more than domestic workers [21]. Elders, Burdorf, and Öry (2004) compared the disability status of Dutch workers and Turkish immigrant workers in terms of ethnic and demographic characteristics of the workers. They used the health file data of the workers in their research. They analyzed these data using Poisson regression and the t-test. They concluded that the risk of disability of Turkish workers is higher than that of Dutch workers [22]. Loh and Richardson (2004) compared migrant workers and domestic workers in the United States in terms of fatal occupational injuries. They analyzed the data belonging to the Bureau of Labor Statistics institution. Researchers have stated that migrant workers are forced to choose risky jobs due to their lack of language and education. They concluded that the risk of fatal occupational injuries in migrant workers is higher than that of domestic workers [15]. Ahonen and Benavides (2006) compared the occupational injury situations of migrant workers and domestic workers in Spain. The researchers analyzed the data obtained from the records of the Ministry of Labor and Social Problems. They concluded that the risk of occupational injuries is higher in migrant workers than in domestic workers. Researchers have noted that the risk of occupational injuries is remarkably high, especially in migrant women workers and older workers [23]. Orrenius and Zavodny (2009) compared migrant workers and domestic workers in the United States in terms of working status in risky jobs. The researchers used data from official institutions. They created a regression model with these data. They concluded that migrant workers prefer riskier jobs and that the work-related mortality rate of migrant workers is higher than that of domestic workers. However, the researchers noted that as the level of education and language level of migrant workers increased, the occupational mortality rate decreased [24]. Son, Yang, and Soares (2013) applied a survey to workers in Korea and used the AHP method in the analysis of the data. Researchers identified the dangers affecting migrant workers. They proposed measures to reduce the dangers affecting migrant workers [25]. Moyce and Schenker (2018) examined the occupational health and safety problems of migrant workers. The researchers noted that migrant workers are employed in unhealthy, long-term, dangerous jobs and are deprived of human rights due to reasons such as language inadequacies and cultural differences [26]. Caffaro et al. (2020) aimed to develop training material to enable the provision of occupational safety trainings and occupational safety information to migrant workers working on farms in Italy. The researchers developed training material by conducting a focus group study with migrant workers and instructors. The researchers conducted an initial test and a final test of the migrant workers and found that this educational material was effective [27].
Drydakis (2022) conducted a survey on migrant workers in Greece and used the t-test and correlation and regression methods in the analysis of the data. At the end of the study, they determined that job application trainings have a positive effect on migrant workers [28].
Yanar et al. (2022) applied a survey to employers in order to ensure the safe and sustainable adaptation of newly arrived migrant workers to Canada. Researchers have emphasized that it is important to increase the language levels of migrant workers and to take into account the cultural differences of these workers in the education of migrant workers in order to create a safer workplace in terms of occupational health and safety. In addition, it is also important to determine and raise the occupational safety climate in the workplace and the perception levels of occupational safety of employees in the recent period [29]. In this context, the NOSACQ-50 questionnaire developed by Kines et al. (2011) enables comparative studies on the safety environment in the workplace [30]. Fargnoli and Lombardi (2020) applied the NOSACQ-50 questionnaire to the workers to determine the occupational safety perception levels of farmers in Italy. They used the t-test in the analysis of survey data. The researchers found that the occupational safety perception levels of the farmers in the sample were low. They also determined that the attitudes of these farmers towards occupational safety varied according to their position in the workplace and gender [31]. In addition, Fargnoli and Lombardi (2021) conducted another study on farmers in Italy using the NOSACQ-50 survey. In the study, they concluded that concerns about the COVID-19 pandemic increased the interest in occupational safety [32]. Mailan, Arachchige, Don, and Hong (2021) applied the survey questions they designed to Sri Lankan migrant workers in Korea and tried to determine their awareness of workplace hazards and occupational safety perceptions. They revealed that the language level of migrant workers affects their occupational safety perceptions [17]. Similarly, Korkmaz and Park (2018) compared the occupational safety perceptions of domestic workers and migrant workers in Korea with self-designed survey questions. The researchers used the t-test, ANOVA and correlation and regression methods in the analysis of the survey data. In the study, it was revealed that the accident rate of migrant workers is affected by their level of language and education, and it was recommended that occupational safety rules should be presented in different languages [33].
Although Turkey ranks first among the world countries in the number of immigrants, the literature lacks a sufficient number of comprehensive studies on detecting the occupational health and safety levels of immigrant workers and boosting occupational health and safety to a sustainable level. The objective of this work is to compare domestic and immigrant workers’ occupational safety perceptions and accident levels, to determine the factors influencing their perceptions and workplace accidents, and to make suggestions so that immigrant workers’ occupational safety levels can be detected and become sustainable.

2. Method

The study data were collected through a questionnaire designed by Korkmaz and Park (2018) and first used in a survey of construction workers in Korea [33]. Korkmaz and Park (2018) analyzed the occupational safety perception levels of domestic and foreign workers and the factors affecting the success of occupational health and safety practices in the workplace [33]. Cronbach’s Alpha value has yet to be included in the study text as part of the reliability analysis of the questionnaire. This survey consists of two sections. The first section was prepared to obtain information about the participants (Appendix A). In this section: the participant’s nationality, gender, age, sectorial experience, education level, type of sector, years spent in Turkey, OHS training background, work accident history, and Turkish language level. The second section was prepared to analyze the occupational safety perception levels of the workers and the success of occupational health and safety practices in the workplace (Appendix B). In this section, where a 5-point Likert scale was used, some questions describe positive and negative situations. Questions describing positive situations were scaled as Strongly Disagree 1, Disagree 2, Undecided 3, Agree 4, and Completely Agree 5. The questions that describe negative situations (5, 9, 11, 18, 20, 22, 23) were scaled as Strongly Disagree 5, Disagree 4, Undecided 3, Agree 2, and Completely Agree 1. This section is also divided into four groups within itself. (1–5) The first group consists of five questions and evaluates the importance that workplace management attaches to the concept of occupational health and safety. (6–11) The second group consists of six questions and evaluates the factors affecting the behavior of workers regarding occupational safety. (12–17) The third group consists of six questions and evaluates the methods to be used to improve workers’ perceptions of occupational health and safety. (18–25) The fourth group consists of eight questions. It evaluates the internal and external factors affecting workers’ occupational health and safety.
This study also considered the unregistered workers’ existence while determining the target audience. Notably, during the interviews, the informal workers expressed their concerns about the emergence of unregistered working situations. As a measure to help them feel comfortable while responding, participants were ensured of their anonymity. In this context, the participants were not determined according to any demographic or occupational variables, and the anonymity of all workers participating in the research was ensured.
Istanbul is Turkey’s most populous city, with the most immigrants. This city also ranks first in employment in Turkey and has received worker migration from all provinces for many years [34]. For this reason, it has been evaluated that the city can adequately reflect the overall employment situation in Turkey. Hence, the study was carried out on local and migrant workers in Istanbul. Since many migrant workers in Turkey are of Arab and Afghan origins, the questionnaire was prepared in Turkish, Arabic, Pashto, and English. On 6 May 2022, the research plan was submitted to the ethics committee with its details. On 17 June 2022, the ethics committee approved the research plan. As of 30 June 2022, the survey was submitted to a WhatsApp group of Occupational Safety Experts in a Google Form, advising them to share the questionnaires with the workers in their business organizations through their own WhatsApp application and encourage participation. Thus, the questionnaire forms were successfully distributed to the workers in various sectors operating in Istanbul, and employees were encouraged to participate through occasional field visits and messages via WhatsApp groups. Until 25 December 2022, workers participated in the surveys at different intervals. Therefore, active data collection occurred between 30 June 2022 and 25 December 2022.
It is estimated that approximately 10% of the population of 53 countries in the European region and about 12% of the working population are immigrants [35,36]. On the other hand, the exact rate of migrant workers in the Turkish population is unknown. However, since Turkey is in the European region, the rate of domestic workers in the country is approximately 88%, and the rate of migrant workers is around 12%. For this reason, a stratified random sampling technique was used to select the participants to represent domestic and migrant workers in proportion to their ratios. In this context, 125 immigrants and 937 domestic workers participated in the survey. However, the responses of 56 workers with either insufficient or inconsistent responses were excluded from the study. As a result, the study was conducted with 1006 survey responses, of which 110 were immigrants and 896 native participants. Therefore, attention was paid to the fact that approximately 88% of the participants in the study were local, and 12% were immigrant workers. Since 384 observations can be considered sufficient in case the exact number of universe elements is unclear, 1006 participants in our study are thought to represent the universe [37].
Cronbach’s Alpha values, confirming the reliability of the questionnaire, were calculated with the data prepared for analysis. A Cronbach’s Alpha value of 0.7 and above points to a sufficient level of internal consistency for the questionnaire questions. Then, parametric statistical methods were used in the study. For this reason, the normal distribution of the data, the assumption of parametric analysis, was checked first. The fact that the skewness and kurtosis values of the data are in the range of −1 and +1 is considered sufficient for the normal distribution condition [38,39]. The data were made ready for analysis with these processes. The data prepared for analysis were passed through the stages in the summary diagram in Figure 1, and descriptive analyses were made.
As can be seen from the diagram in Figure 1, an independent sample t-test and ANOVA were used to compare the safety perceptions of the workers in the study. The independent sample t-test is a method used to compare the means of two independent groups [40,41]. ANOVA is a frequently preferred method to compare the group’s mean when the number of groups is three or more [42,43]. In the study, the subgroups of gender, OHS training, and occupational accident status were compared with the independent sample t-test regarding safety perception averages. The differences in the safety perception averages of the subgroups of nationality, age, education level, life expectancy in Turkey, Turkish language level, sector, and experience in the sector were investigated by ANOVA. Pearson correlation analysis was used to determine the relationship between the workers’ demographic characteristics and the questionnaire questions. Pearson correlation analysis is also a method frequently used in research to reveal the relationship between two numerical data sets [38,39]. Finally, linear regression analysis was used to predict the occupational accident status of the workers. Linear regression is a preferred method to determine the dependent variable with the help of two or more independent variables or to reveal how much the independent variables predict the dependent variable [38,39]. All study analyses were performed using the trial version of SPSS 25.

3. Results

As a result of the reliability analysis performed to control the internal consistency of the questionnaire questions, the Cronbach’s Alpha value was 0.908 for domestic workers and 0.816 for migrant workers, confirming that the internal consistency of the questionnaire questions was ideal for both groups.
Table 1 illustrates numerical and percentage distributions, arithmetic averages of occupational safety perception levels, standard deviation values, independent sample t-test and ANOVA results, and statistical significance levels of the analysis concerning the demographic features of the study participants domestic and migrant workers.
Table 1 provides data on the following:
Of the study participants, 896 are domestic, and 110 are migrant workers. Furthermore, it is also noteworthy that domestic workers have a higher safety perception level on average (mean = 3.819, standard deviation = 0.706) than migrant workers (mean = 3.204, standard deviation = 0.573), which is also statistically significant (t = 8.779, p = 0.000).
A nationality-based analysis of migrant workers’ number, ratio, and average safety perception levels reveals that of all the migrant workers participating in the research, 44 are Syrians (40%) and 22 Afghans (20%), while 44 (40%) do not specify their nationality, which means that Syrians constitute the majority of migrant workers while Afghans are the minority. Syrian workers have lower average safety perception levels (mean = 3.117, standard deviation = 0.527) than Afghan workers (mean = 3.247, standard deviation = 0.513). However, these differences are not considered statistically significant (F = 0.867, p = 0.423).
A gender-based analysis of domestic and migrant workers’ number, ratio, and average safety perception levels reveals that of all the domestic workers participating in the research, 864 are male (96%) and 32 are female (4%). In comparison, there are 74 male workers (67%) and 36 female workers (33%) among migrant workers. Notably, the rate of working women is lower in domestic groups than in migrant groups. The average safety perception level is higher for domestic male workers (mean = 3.824, standard deviation = 0.711) than for domestic female workers (mean = 3.684, standard deviation = 0.563), which is not statistically significant (t = 1.100, p = 0.272). In contrast, the average safety perception level is higher for female migrant workers (mean = 3.241, standard deviation = 0.562) than for male migrant workers (mean = 3.187, standard deviation = 0.582), which is also not statistically significant (t = -0.462, p = 0.645).
An age-based analysis of domestic and migrant workers’ number, ratio, and average safety perception levels reveals that 4 domestic workers (0%) and 10 migrant workers (9%) are in the 15–20 age group; 104 domestic workers (12%) and 30 migrant workers (27%) in the 20–25 age group; 140 domestic workers (16%) and 20 migrant workers (18%) in the 25–30 age group; 170 domestic workers (19%) and 22 migrant workers (20%) in the 30–35 age group; 152 domestic workers (17%) and 12 migrant workers (11%) in the 35–40 age group; 160 domestic workers (18%) and 6 migrant workers (5%) in the 40–45 age group; 116 domestic workers (13%) and 2 migrant workers (2%) in the 45–50 age group; 50 domestic workers (6%) and 8 migrant workers (7%) in the age group of 50 and over 50. Considering the figures for age groups varying from ages 15 to 35, the rate of the young population is higher in migrant workers than domestic ones; however, when figures from ages 35 to 50 are considered, domestic workers are younger than migrant workers in those age groups. Although the average safety perception level for each age group does not differ statistically in domestic workers (F = 1.778, p = 0.088), the average safety perception level of domestic workers is highest in the 45–50 age group (mean = 3.906, standard deviation = 0.673) and the lowest in the 30–35 age group (mean = 3.661, standard deviation = 0.737). The mean level of safety perception of migrant workers is highest in those 50 and over (mean = 3.670, standard deviation = 0.681) and lowest in the 25–30 age group (mean = 2.896, standard deviation = 0.341). However, each age group’s average safety perception level differs statistically significantly among migrant workers (F = 2.299, p = 0.032).
An analysis based on the educational background of domestic and migrant workers’ number, ratio, and average safety perception levels reveals that primary school graduates account for 28 domestic workers (3%) and 12 migrant workers (11%), while secondary school graduates account for 56 domestic workers (6%) and 4 migrant workers (4%). High school graduates account for 536 domestic workers (60%) and 40 migrant workers (36%), while university graduates account for 272 domestic workers (30%) and 54 migrant workers (49%). The higher the education level for domestic workers, the higher the safety perception level. However, there is no statistically significant difference in domestic workers’ mean safety perception level based on their educational background (F = 2.429, p = 0.064). Domestic workers’ average safety perception level is highest among university graduates (mean = 3.876, standard deviation = 0.682) and lowest among primary school graduates (mean = 3.509, standard deviation = 0.667). The average safety perception level of migrant workers does not change depending on the change in education level. Furthermore, there is no statistically significant difference in migrant workers’ mean safety perception level based on their educational background (F = 0.922, p = 0.433). The mean safety perception level of migrant workers is highest among secondary school graduates (mean = 3.580, standard deviation = 0.162) and lowest among high school graduates (mean = 3.120, standard deviation = 0.594).
An analysis of migrant workers’ number, ratio, and average safety perception levels based on the number of years spent in Turkey reveals that 20 (18%) account for that being a period of less than a year, 18 (16%) for 1–2 years, 26 (24%) for 2–5 years, 36 (33%) for 5–10 years, 10 (9%) for more than ten years. However, there is no statistically significant difference in migrant workers’ mean safety perception level based on the years spent in Turkey (F = 1.358, p = 0.254). The mean level of safety perception is highest in those who have been living in Turkey for 5–10 years (mean = 3.275, standard deviation = 0.612) and the lowest in those who have been living in Turkey for less than a year (mean = 2.937, standard deviation = 0.531).
An analysis of migrant workers’ number, ratio, and average safety perception levels based on Turkish language skills reveals that of migrant workers, 12 (11%) have very bad, 8 (7%) have bad, 38 (35%) have not bad, 18 (16%) have good, 34 (31%) have very good Turkish language skills. However, there is no statistically significant difference in migrant workers’ mean safety perception level based on their Turkish language skills (F = 1.084, p = 0.368). The mean level of perception of safety was highest in those with poor Turkish language levels (mean = 3.382, standard deviation = 0.529) and the lowest in those with very poor language levels (mean = 3.071, standard deviation = 0.555).
A sector-based analysis of domestic and migrant workers’ number, ratio, and average safety perception levels reveals that 20 domestic workers (2%) and 22 migrant workers (20%) work in the construction industry; only 478 domestic workers (53%) work in the metal industry; 12 domestic workers (1%) and 4 migrant workers (4%) work in the sales storage sector; 22 domestic workers (2%) and 18 migrant workers (16%) work in the textile sector, 364 domestic workers (41%) and 62 migrant workers (56%) did not specify their sectors. The sectorial difference in the average safety perception level among domestic workers is statistically significant (F = 2.830, p = 0.024). Domestic workers’ average safety perception level is the highest in the metal industry (mean = 3.871, standard deviation = 0.710) and the lowest in the textile industry (mean = 3.429, standard deviation = 0.845). On the other hand, there is no statistically significant sectorial difference in the average safety perception level of migrant workers (F = 0.222, p = 0.881). However, the average safety perception level of migrant workers is highest in the sales warehousing industry (mean = 3.280, standard deviation = 0.185) and the lowest in the construction industry (mean = 3.141, standard deviation = 0.602).
An experienced-based (year-based) analysis of domestic and migrant workers’ number, ratio, and average safety perception levels reveals that 28 domestic workers (3%) and 38 migrant workers (35%) have less than one year of experience; 382 domestic workers (43%) and 48 migrant workers (44%) have 1 to 10 years of experience; 270 domestic workers (30%) and 10 migrant workers (9%) have 10–20 years of experience; 208 domestic workers (23%) and 6 migrant workers (5%) have more than 20 years of experience. Domestic workers have a higher mean safety perception level than migrant workers. The mean safety perception level differs according to the years of experience of domestic workers. However, this difference is not statistically significant (F = 2.496, p = 0.059). Migrant workers with less than a year of experience have the lowest average safety perception level (mean = 3.027, standard deviation = 0.515). The more experienced the migrant workers are, the higher the mean safety perception is. Furthermore, the mean safety perception level in each experience group differs significantly and statistically for migrant workers (F = 3.509, p = 0.018).
An analysis of migrant and domestic workers’ number, ratio, and average safety perception levels based on OHS training status reveals that 864 (96%) domestic workers and 36 (33%) migrant workers received OHS training. A total of 28 (3%) domestic workers and 74 (67%) migrant workers did not receive OHS training. The mean safety perception level for domestic workers is higher in those with OHS training (mean = 3.832, standard deviation = 0.699) and lower in those without OHS training (mean = 3.347, standard deviation = 0.783). There is a statistically significant difference in the domestic workers’ mean safety perception level based on their OHS training status (t = 3.604, p = 0.000). Like the case of domestic workers, migrant workers’ mean safety perception level is higher in those with OHS training (mean = 3.392, standard deviation = 0.703) and lower in those without OHS training (mean = 3.113, standard deviation = 0.477). Likewise, there is a statistically significant difference in the migrant workers’ mean safety perception level based on their OHS training status (t = 2.450, p = 0.016).
An occupational accident-based analysis of migrant and domestic workers’ number, ratio, and average safety perception levels reveals that 200 (22%) domestic workers and 20 (18%) migrant workers had an occupational accident, while 692 (77%) domestic workers and 88 (80%) migrant workers had no occupational accidents. The mean safety perception level for domestic workers is higher in those with a history of an occupational accident (mean = 3.846, standard deviation = 0.657) and lower in those without a history of an occupational accident (mean = 3.816, standard deviation = 0.717). However, there is no statistically significant difference in domestic workers’ mean safety perception level based on their history of occupational accidents (t = 0.540, p = 0.589). As in domestic workers, migrant workers’ mean safety perception level is higher in those with a history of an occupational accident (mean = 3.308, standard deviation = 0.450) and lower in those without a history of an occupational accident (mean = 3.200, standard deviation = 0.590). Likewise, there is no statistically significant difference in migrant workers’ mean safety perception level based on their history of occupational accidents (t = 0.767, p = 0.445).
The relationships between the answers concerning the participant’s age, education level, and accident status have also been studied for domestic and migrant workers with Pearson correlation analysis.
In order to avoid confusion in this correlation analysis, all items with positive and negative meanings were coded as Strongly Disagree 1, Disagree 2, Undecided 3, Agree 4, and Totally Agree 5. Table 2 points to the statistically significant results for domestic and migrant groups with different characteristics from each other.
Table 2 provides data on the following:
The correlation coefficient between the items “Briefings on workplace risks are truly useful” and “Some occupational health and safety rules are merely issued to protect the managers” is 0.335 ** for migrant workers and 0.080 * for domestic workers. Between these two items, there is a positive and moderately significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “Managers are committed to occupational health and safety” and “Some occupational health and safety rules are merely issued to protect the managers” is 0.311 ** for migrant workers and 0.006 for domestic workers. Between these two items, there is a positive and moderately significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “Managers care about my opinions on occupational health and safety” and “Some occupational health and safety rules are merely issued to protect the managers” is 0.371 ** for migrant workers and −0.017 for domestic workers. Between these two items, there is a positive and moderately significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “Participant’s Educational Background” and “Participant’s likelihood of experiencing an occupational accident” is −0.268 ** for migrant workers and 0.033 for domestic workers. Between these two items, there is a negative and weakly significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “Participant’s Age” and “Participant’s likelihood of experiencing an occupational accident” is −0.290 ** for migrant workers and 0.005 for domestic workers. Between these two items, there is a negative and weakly significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “ My friends would warn me if I did not follow occupational health and safety regulations” and “Participant’s likelihood of experiencing an occupational accident” is 0.273 ** for migrant workers and 0.011 for domestic workers. Between these two items, there is a positive and weakly significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “There is no need for a serious measure to prevent accidents until someone is hurt” and “Participant’s likelihood of experiencing an occupational accident” is 0.257 ** for migrant workers and 0.007 for domestic workers. Between these two items, there is a positive and weakly significant relationship for migrant workers, yet no significant relationship for domestic workers.
The correlation coefficient between the items “No matter how careful you are, small bumps and sprains can happen at work” and “Participant’s likelihood of experiencing an occupational accident” is 0.156 ** for domestic workers and 0.079 for migrant workers. Between these two items, there is a positive and weakly significant relationship for domestic workers, yet no significant relationship for migrant workers.
Linear regression analysis was used to determine the independent variables and contribution levels impacting the occupational accident status of domestic and migrant workers. Table 3 shows the regression analysis results.
Table 3 provides data on the following:
It is seen that the domestic workers’ likelihood of experiencing an occupational accident is affected negatively by age (t = −3.234, p = 0.001) and positively by seniority in the sector (t = 4.492, p = 0.000), which is statistically significant (F = 10.102, p = 0.00). Age and seniority in the sector explain 2% of domestic workers’ likelihood of experiencing an occupational accident (R2 = 0.023). The migrant workers’ likelihood of experiencing an occupational accident is affected negatively by the participant’s age (t = −2.898, p = 0.005) and educational background (t = −2.635, p = 0.010), which is statistically significant (F = 8.596, p = 0.00). Age and educational level explain 12.5% of migrant workers’ likelihood of experiencing occupational accidents (R2 = 0.125).

4. Discussion

The rising number of immigrant workers has led to occupational security issues in Turkey. As a result, there emerged a need for academic studies and precautions to ensure a safe and sustainable working environment for immigrant workers. This study aims to compare the immigrant workers’ occupational safety perceptions and workplace accident levels so that suggestions can be put forward to create a sustainable occupational health and safety environment for immigrant workers. A survey with 125 migrant and 937 domestic workers operating in various sectors in Istanbul, where the migrant worker population is dense, was carried out. The survey, designed by Korkmaz and Park (2018) [33], was used to learn about workers’ demographic characteristics and their attitudes towards occupational safety. Independent sample t-test, Pearson correlation, and regression analyses were performed using questionnaire responses from 110 migrant and 896 domestic workers.
The analysis results suggest the following:
  • Migrant workers’ safety perception level is statistically significantly lower than domestic workers. Therefore, there is a growing need for reformative studies to boost immigrant workers’ safety perceptions sustainably.
  • Domestic female workers have a lower safety perception level than their male counterparts, and female immigrant workers have a higher safety perception level than their male counterparts. This finding suggests that some reformative work must be conducted to improve the immigrant male workers’ safety perception levels.
  • The average safety perception level for each age group is lower for migrant workers than for domestic workers. In addition, there is a statistically significant difference in migrant workers’ safety perception levels depending on the age groups. The safety perception level of those migrant workers between the ages of 25–30 is at the lowest level. Further studies should be carried out to increase the safety perception of this age group, which is densely employed.
  • The average safety perception level for each education level is lower for migrant workers than for domestic workers. In particular, the safety perception level of migrant workers with a high school degree is at the lowest level. Further studies should be conducted to improve the safety perception of migrant workers with high school degrees who are densely employed.
  • Migrant workers living in Turkey for less than a year have the lowest level of safety perception compared to those who have been living in the country longer. For this reason, studies should be carried out to accelerate the adaptation of migrant workers, who are likely to be employed, to the country.
  • The safety perception level of migrant workers with poor Turkish language skills is at the lowest level. For this reason, language teaching programs should be organized to increase the level of Turkish for migrant workers who are likely to be employed.
  • The average safety perception level in each sector is lower for migrant workers than for domestic workers. The safety perception level of migrant workers, especially in the construction sector, is the lowest. Considering that construction activities involve high-risk and dangerous conditions, the situation of migrant workers should be evaluated separately in risk assessments.
  • The average safety perception level in each experience group is lower for migrant workers than for domestic workers. In particular, the safety perception level of migrant workers with less than a year of experience is the lowest. In addition, the safety perception level of migrant workers increases with experience. For this reason, inexperienced migrant workers should be given experience through in-service training.
  • The rate of migrant workers with OHS training is relatively lower than that of domestic workers, since migrant workers are recruited informally. OHS training status is statistically significant in increasing the perception of safety of both migrant and domestic workers. Safety perceptions of migrant workers with no OHS training, in particular, are low. For this reason, the rate of receiving OHS training among migrant workers should be increased.
  • Among both migrant and domestic workers, the safety perception level of those with a history of occupational accidents is higher than those without a history of occupational accidents, which may suggest that workers with a history of occupational accidents take occupational safety rules more seriously. Safety perceptions of migrant workers with no history of occupational accidents are very low. For this reason, migrant workers with no history of occupational accidents should be provided with educational information about the consequences of occupational accidents through realistic scenarios.
  • Considering briefings on workplace risks being beneficial and whether their managers are committed to occupational health and safety and care for the workers’ opinions, migrant workers also report that some occupational health and safety rules are merely issued to protect the managers, which may suggest that migrant workers are not sure of the sincerity of their managers. For this reason, safety measures should be regulated to protect only the workers, and they should not be issued to make the manager less accountable in the eyes of the law.
  • Migrant workers warned more frequently by their friends about occupational safety violations had experienced significantly more occupational accidents than those not warned. Notifying the management of migrant workers who do not comply with the rules is essential so that measures can be taken to reduce occupational accidents.
  • Migrant workers who think there is no need for severe measures to prevent accidents until someone is hurt have statistically more occupational accidents than other groups. Therefore, the effect of risk assessments and the measures taken to reduce occupational accidents should be demonstrated with real-scenario training.
  • Domestic workers who think that no matter how careful they are, minor bumps and sprains can happen at work have statistically more occupational accidents than other groups. Therefore, both domestic and migrant workers should be given risk assessment training.
  • Both correlation and regression analysis results suggest that the higher the education level or age of migrant workers, the lower the occupational accident rate is. In other words, the younger the migrant worker or the lower the educational level is, the more occupational accidents they will have compared to those who are older or have a higher education level. Therefore, migrant workers with low education levels should be offered programs to improve their education, and young migrant workers should be employed in less risky jobs.
  • For domestic workers, the impact of age and sectorial experience on the occupational accident rate is statistically significant. The higher the age, the lower the occupational accident rate. However, the higher the sectorial experience, the higher the occupational accident rate. Therefore, young domestic workers should be employed in less risky jobs. In addition, domestic workers with a higher sectorial experience should be retrained and be employed in less risky jobs.
To ensure their recruitment in healthy and safe conditions, immigrant workers must be provided with language training, opportunities to improve overall and occupational educational levels, training to create an awareness of near-miss situations, and safety training with simple, realistic, and visual materials. These reformative activities might be sustained when procedures are issued in writing, included in workplace risk assessment, and supported by legal regulations. Within this scope, the article is thought to solve the occupational health and safety problems in recruitment for current and future immigrant workers in Turkey. As a result, the study is believed to offer reformative contributions to sustainable development in the country and a sustainable social policy system.
This study focuses on overall sectors in Turkey. Further research with similar studies is required for specific sectors and countries.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Istanbul Esenyurt University. The ethical committee protocol code for this study is E-12483425-299-18433 (2022/06-3), and the approval date is 17 June 2022.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Conflicts of Interest

The author declares no conflict of interest.

Appendix A

Nationalitya. Afghanistanb. Syriac. Others
Sexa. Maleb. Female
Agea. 15 ≤ … < 20b. 20 ≤ … < 25c. 25 ≤ … < 30
d. 30 ≤ … < 35e. 35 ≤ … < 40f. 40 ≤ … < 45
g. 45 ≤ … < 50h. 50 and over 50
Educational backgrounda. Primary schoolb. Elementary schoolc. High school
d. University
Years spent in Turkeya. Less than one yearb. 1≤ … <2 yearsc. 2≤ … <5 years
d. 5≤ … <10 yearse. More than 10
Turkish language skillsa. Really badb. Badc. Not bad
d. Goode. Really good
Employment sectora. Constructionb. Metalc. Sales storage
d. Textilee. Others
Seniority in the sector (in years)a. Less than 1 yearb. 1≤ … <10 yearsc. 10≤ … <20 years
d. More than 20 years
Training background in occupational health and safetya. Yesb. No
Any work accident experiencea. Yesb. No

Appendix B [33]

QuestionStrongly DisagreeDisagreeUndecidedAgreeCompletely Agree
1. Senior management is fully committed to safety and health.
2. Staff are blamed when they make mistakes.
3. The company is interested in my opinions about safety and health.
4. Management places a high priority on safety and health.
5. Supervisors turn a blind eye to unsafe behavior.
6. Safety and health procedures are much too stringent in relation to the risk.
7. My colleagues would criticize me for breaking the safety and health rules.
8. I am given adequate safety and health trainings.
9. Little should be done to prevent accidents until someone gets injured.
10. Everyone wears their protective equipment when they are supposed to.
11. Action should be rarely taken when someone breaks the safety and health rules.
12. I fully understand the safety and health instructions that relate to my job.
13. Time pressures for completing jobs are reasonable.
14. I was involved in risk assessments relating to my work.
15. Staff are praised for working safely.
16. Action has been taken on the basis of risk assessment findings.
17. The risk controls do not get in the way of my doing my job.
18. Knocks and bruises are bound to happen at work no matter how careful you are.
19. Safety and health briefings are very useful.
20. I take risks that my colleagues would not take.
21. Accidents that happen here are always reported.
22. Some safety and health rules are only there to protect management.
23. The permit-to-work system leads to unnecessary delays in getting the job done.
24. I know that if I follow the safety procedures I will not get hurt.
25. The use of personal protective equipment is strictly enforced.

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Sustainability 15 15245 g001
Figure 1. A systematic overview of research methodology.
Figure 1. A systematic overview of research methodology.
Sustainability 15 15245 g001
Table 1. Numerical and percentage distributions, arithmetic averages of occupational safety perception levels, standard deviation values, independent sample t-test and ANOVA results for the demographic characteristics of domestic and migrant workers.
Table 1. Numerical and percentage distributions, arithmetic averages of occupational safety perception levels, standard deviation values, independent sample t-test and ANOVA results for the demographic characteristics of domestic and migrant workers.
Demographic FeaturesDomesticMigrantMeanStandard Deviationt/Fp (Significance)
Main CategorySubcategoryNumberPercentageNumberPercentageDomesticMigrantDomesticMigrantDomesticMigrantDomesticMigrant
NationalityAfghanistan--2220%-3.247-0.513-0.867-0.423
Syria--4440%-3.117-0.527
Others--4440%-3.271-0.643
SexMale86496%7467%3.8243.1870.7110.5821.100−0.4620.2720.645
Female324%3633%3.6843.2410.5630.562
Age15 ≤ … < 2040%109%3.6893.2160.8880.5151.7782.2990.0880.032
20 ≤ … < 2510412%3027%3.8813.1910.7200.574
25 ≤ … < 3014016%2018%3.8532.8960.6650.341
30 ≤ … < 3517019%2220%3.6613.1380.7370.437
35 ≤ … < 4015217%1211%3.8573.3200.7190.797
40 ≤ … < 4516018%65%3.8043.5450.6970.709
45 ≤ … < 5011613%22%3.9063.5830.6730.000
50 and over 50506%87%3.8733.6700.6940.681
Educational backgroundPrimary school283%1211%3.5093.2160.6670.3382.4290.9220.0640.433
Elementary school566%44%3.7993.5800.7660.162
High school53660%4036%3.8183.1200.7040.594
University27230%5449%3.8763.2370.6820.611
Years spent in TurkeyLess than one year--2018%-2.937-0.531-1.358-0.254
1≤ … <2 years--1816%-3.267-0.304
2≤ … <5 years--2624%-3.261-0.587
5≤ … <10 years--3633%-3.275-0.612
More than 10--109%-3.227-0.774
Turkish language skillsReally bad--1211%-3.071-0.555-1.084-0.368
Bad--87%-3.382-0.529
Not bad--3835%-3.252-0.671
Good--1816%-3.346-0.237
Really good--3431%-3.082-0.588
Employment sectorConstruction202%2220%3.7473.1410.6950.6022.8300.2220.0240.881
Metal47853%00%3.871 0.710
Sales storage121%44%3.6333.2801.0490.185
Textile222%1816%3.4293.2730.8450.392
Others36441%6256%3.7843.2400.6720.625
Seniority in the sector (in years)Less than 1 year283%3835%3.8663.0270.7190.5152.4963.5090.0590.018
1≤ … <10 years38243%4844%3.7623.2860.7360.515
10≤ … <20 years27030%109%3.8293.4960.6840.520
More than 20 years20823%65%3.9263.6000.6601.045
Training background in occupational health and safetyYes86496%3633%3.8323.3920.6990.7033.6042.4500.0000.016
No283%7467%3.3473.1130.7830.477
Any work accident experienceYes20022%2018%3.8463.3080.6570.4500.5400.7670.5890.445
No69277%8880%3.8163.2000.7170.590
Total 896 110 3.8193.2040.7060.5738.7790.000
Others: Iraq, Turkmenistan, Uzbekistan, Morocco, Algeria, Yemen.
Table 2. Analysis of Pearson correlation findings.
Table 2. Analysis of Pearson correlation findings.
ItemItemDomesticMigrant
Briefings on workplace risks are truly useful.Some occupational health and safety rules are merely issued to protect the managers0.080 *0.335 **
Managers are committed to occupational health and safetySome occupational health and safety rules are merely issued to protect the managers0.0060.311 **
Managers care about my opinions on occupational health and safetySome occupational health and safety rules are issued to protect merely the managers−0.0170.371 **
Participant’s Educational BackgroundParticipant’s likelihood of experiencing an occupational accident0.033−0.268 **
Participant’s AgeParticipant’s likelihood of experiencing an occupational accident0.005−0.290 **
My friends would warn me if I did not follow occupational health and safety regulations.Participant’s likelihood of experiencing an occupational accident0.0110.273 **
There is no need of severe measures to prevent accidents until someone is hurt.Participant’s likelihood of experiencing an occupational accident0.0070.257 **
No matter how careful you are, small bumps and sprains can happen at work.Participant’s likelihood of experiencing an occupational accident0.156 **0.079
* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).
Table 3. Linear regression analysis results.
Table 3. Linear regression analysis results.
ModelUnstandardized CoefficientsStandardized CoefficientstSig.
BStd. ErrorBeta
Domestic(Constant)0.1770.034 5.1780.000
Age−0.0380.012−0.161−3.2340.001
Seniority in the Sector0.1100.0240.2244.4920.000
Migrant(Constant)0.5430.098 5.5520.000
Age−0.0540.019−0.264−2.8980.005
Educational Background−0.0980.037−0.240−2.6350.010
R2 = 0.023, F = 10.102 (Domestic), p = 0.00. R2 = 0.125, F = 8.596 (Migrant), p = 0.00.
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Öztürk, T. A Comparison of Occupational Safety Perceptions among Domestic and Migrant Workers in Turkey. Sustainability 2023, 15, 15245. https://doi.org/10.3390/su152115245

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