D. Moya, R. Manzanera, J. Ortner, Marta Torres, Joan Carles Serfaty, Carme Sauri, Lourdes Jimenez, J. Mira
Background: Given the lack of previous studies on adverse events (AEs) in the area of occupational healthcare in Spain, it is very important to begin to understand this phenomenon in order to act on it. The objective was to accurately quantify AE occurring in occupational healthcare in MC Mutual during May 2021. Methods: We conducted a review of a representative random sample of 250 clinical records to identify AEs through an active search audit, focused on the frequency, type, severity, and preventability of these events, categorized using standardized scales. Results: We detected seven AEs in the sample of clinical records, representing 3% AEs per clinical record, while in the APEAS Spanish Study, they were detected in 10% of patients. The most frequent AE type was postoperative, followed by medication and diagnostic delay. The AEs were of intermediate severity and high severity and with a variable degree of being preventable. Conclusions: The detection of AEs has been useful in the development of projects and action plans such as specific training courses, safety patient newsletters, ambulatory risk maps, and treatment plans framed in the official certification of patient safety. These results should be evaluated in other companies similar to MC Mutual.
{"title":"Enhancing Patient Safety in Spain: Streamlining Adverse Event Detection in Occupational Healthcare Records","authors":"D. Moya, R. Manzanera, J. Ortner, Marta Torres, Joan Carles Serfaty, Carme Sauri, Lourdes Jimenez, J. Mira","doi":"10.3390/safety10010013","DOIUrl":"https://doi.org/10.3390/safety10010013","url":null,"abstract":"Background: Given the lack of previous studies on adverse events (AEs) in the area of occupational healthcare in Spain, it is very important to begin to understand this phenomenon in order to act on it. The objective was to accurately quantify AE occurring in occupational healthcare in MC Mutual during May 2021. Methods: We conducted a review of a representative random sample of 250 clinical records to identify AEs through an active search audit, focused on the frequency, type, severity, and preventability of these events, categorized using standardized scales. Results: We detected seven AEs in the sample of clinical records, representing 3% AEs per clinical record, while in the APEAS Spanish Study, they were detected in 10% of patients. The most frequent AE type was postoperative, followed by medication and diagnostic delay. The AEs were of intermediate severity and high severity and with a variable degree of being preventable. Conclusions: The detection of AEs has been useful in the development of projects and action plans such as specific training courses, safety patient newsletters, ambulatory risk maps, and treatment plans framed in the official certification of patient safety. These results should be evaluated in other companies similar to MC Mutual.","PeriodicalId":509460,"journal":{"name":"Safety","volume":" 53","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139619234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Melania Zamorano García, Gema Santamaría, Marina Seco-Casares, Ana M. Celorrio San Miguel, Eva M Lantarón-Caeiro, Juan F. García, Diego Fernández-Lázaro
Lower back pain (LBP) describes pain of indeterminate duration between the lower edge of the ribs and the buttocks. LBP hinders movement, quality of life, and mental well-being, and limits work activities and engagement with family and friends. LBP represents a public health problem, and most workers are expected to experience LBP symptoms throughout their working lives. The study’s main objective was to characterize LBP in the hospitality population of the province of León, Spain, determining the risk factors. A pilot study with a cross-sectional observational design was developed following the guidelines of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for 150 Spanish hotel workers. Sociodemographic and lifestyle, occupational, and clinical data related to LBP were obtained through surveys. The annual prevalence of LBP in this study was 87.1% which was higher in women. A significant relationship (p < 0.05) was obtained between sex, income, smoking, sleep quality, and all labor variables with LBP. In addition, the Fear Avoidance Beliefs Questionnaire (FABQ) results revealed that 49% of the participants had a score > 14. Also, 83.3% of patients with >6 annual LBP crises suffered from sciatica. Once the results were known, preventive intervention would be needed to reduce these main risk factors for LBP for hospitality workers.
{"title":"A Cross-Sectional Observational Pilot Study of the Main Risk Factors Related to Lower Back Pain in Spanish Hospitality Workers","authors":"Melania Zamorano García, Gema Santamaría, Marina Seco-Casares, Ana M. Celorrio San Miguel, Eva M Lantarón-Caeiro, Juan F. García, Diego Fernández-Lázaro","doi":"10.3390/safety10010012","DOIUrl":"https://doi.org/10.3390/safety10010012","url":null,"abstract":"Lower back pain (LBP) describes pain of indeterminate duration between the lower edge of the ribs and the buttocks. LBP hinders movement, quality of life, and mental well-being, and limits work activities and engagement with family and friends. LBP represents a public health problem, and most workers are expected to experience LBP symptoms throughout their working lives. The study’s main objective was to characterize LBP in the hospitality population of the province of León, Spain, determining the risk factors. A pilot study with a cross-sectional observational design was developed following the guidelines of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for 150 Spanish hotel workers. Sociodemographic and lifestyle, occupational, and clinical data related to LBP were obtained through surveys. The annual prevalence of LBP in this study was 87.1% which was higher in women. A significant relationship (p < 0.05) was obtained between sex, income, smoking, sleep quality, and all labor variables with LBP. In addition, the Fear Avoidance Beliefs Questionnaire (FABQ) results revealed that 49% of the participants had a score > 14. Also, 83.3% of patients with >6 annual LBP crises suffered from sciatica. Once the results were known, preventive intervention would be needed to reduce these main risk factors for LBP for hospitality workers.","PeriodicalId":509460,"journal":{"name":"Safety","volume":" 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139625648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study explores the complex connections among various socioeconomic, demographic, and technological aspects and their impact on fatal traffic accidents. Utilizing the Lasso polynomial regression model, this study explores the impact of demographic variables, including income, education, unemployment rates, and family size. Additionally, socioeconomic factors such as Gross Domestic Product (GDP) per capita, inflation rate, minimum wage, and government spending on transportation and infrastructure are examined for their impact on the occurrence of fatal accidents. This study also investigates the influence of technological advances in vehicles on the outcomes of traffic safety. The findings of this research reveal that certain factors, such as average, alcohol consumption, unemployment rate, minimum wage, and vehicle miles traveled (VMT), among others, have a substantial impact on the multifactorial model and play a considerable role in the frequency of fatal accident rates. The research results have significant implications for policymakers, highlighting the need for a comprehensive approach that accounts for the interdependence of economic indicators, behavioral patterns, and traffic safety outcomes. This study underscores the importance of considering a wide range of socioeconomic, demographic, and technological factors to develop effective policies and strategies to reduce fatal traffic accidents.
{"title":"Nonlinear Analysis of the Effects of Socioeconomic, Demographic, and Technological Factors on the Number of Fatal Traffic Accidents","authors":"Nassim Sohaee, Shahram Bohluli","doi":"10.3390/safety10010011","DOIUrl":"https://doi.org/10.3390/safety10010011","url":null,"abstract":"This study explores the complex connections among various socioeconomic, demographic, and technological aspects and their impact on fatal traffic accidents. Utilizing the Lasso polynomial regression model, this study explores the impact of demographic variables, including income, education, unemployment rates, and family size. Additionally, socioeconomic factors such as Gross Domestic Product (GDP) per capita, inflation rate, minimum wage, and government spending on transportation and infrastructure are examined for their impact on the occurrence of fatal accidents. This study also investigates the influence of technological advances in vehicles on the outcomes of traffic safety. The findings of this research reveal that certain factors, such as average, alcohol consumption, unemployment rate, minimum wage, and vehicle miles traveled (VMT), among others, have a substantial impact on the multifactorial model and play a considerable role in the frequency of fatal accident rates. The research results have significant implications for policymakers, highlighting the need for a comprehensive approach that accounts for the interdependence of economic indicators, behavioral patterns, and traffic safety outcomes. This study underscores the importance of considering a wide range of socioeconomic, demographic, and technological factors to develop effective policies and strategies to reduce fatal traffic accidents.","PeriodicalId":509460,"journal":{"name":"Safety","volume":" 43","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139627960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kui Yang, C. Al Haddad, Rakibul Alam, Tom Brijs, Constantinos Antoniou
Advanced driver assistance systems (ADASs) have recently gained popularity as they assist vehicle operators in staying within safe boundaries, helping them thereby to prevent possible collisions. However, despite their success and development, most ADAS use common and deterministic warning thresholds for all drivers in all driving environments. This may occasionally lead to the issuance of annoying inadequate warnings, due to the possible differences between drivers, the changing environments and driver statuses, thus reducing their acceptance and effectiveness. To fill this gap, this paper proposes adaptive algorithms for commonly used warnings based on real-time traffic environments and driver status including distraction and fatigue. We proposed adaptive algorithms for headway monitoring, illegal overtaking, over-speeding, and fatigue. The algorithms were then tested using a driving simulator. Results showed that the proposed adaptive headway warning algorithm was able to automatically update the headway warning thresholds and that, overall, the proposed algorithms provided the expected warnings. In particular, three or four different warning types were designed to distinguish different risk levels. The designed real-time intervention algorithms can be implemented in ADAS to provide warnings and interventions tailored to the driver status to further ensure driving safety.
{"title":"Adaptive Intervention Algorithms for Advanced Driver Assistance Systems","authors":"Kui Yang, C. Al Haddad, Rakibul Alam, Tom Brijs, Constantinos Antoniou","doi":"10.3390/safety10010010","DOIUrl":"https://doi.org/10.3390/safety10010010","url":null,"abstract":"Advanced driver assistance systems (ADASs) have recently gained popularity as they assist vehicle operators in staying within safe boundaries, helping them thereby to prevent possible collisions. However, despite their success and development, most ADAS use common and deterministic warning thresholds for all drivers in all driving environments. This may occasionally lead to the issuance of annoying inadequate warnings, due to the possible differences between drivers, the changing environments and driver statuses, thus reducing their acceptance and effectiveness. To fill this gap, this paper proposes adaptive algorithms for commonly used warnings based on real-time traffic environments and driver status including distraction and fatigue. We proposed adaptive algorithms for headway monitoring, illegal overtaking, over-speeding, and fatigue. The algorithms were then tested using a driving simulator. Results showed that the proposed adaptive headway warning algorithm was able to automatically update the headway warning thresholds and that, overall, the proposed algorithms provided the expected warnings. In particular, three or four different warning types were designed to distinguish different risk levels. The designed real-time intervention algorithms can be implemented in ADAS to provide warnings and interventions tailored to the driver status to further ensure driving safety.","PeriodicalId":509460,"journal":{"name":"Safety","volume":"49 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139442044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shahzeb Ansari, Haiping Du, F. Naghdy, Ayaz Ahmed Hoshu, David Stirling
Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle measurement methods. However, the literature lacks the implementation of hybrid approaches that combine the strength of individual approaches to develop a robust fatigue detection system. In this regard, a hybrid temporal approach is proposed in this paper to detect driver mental fatigue through the combination of driver postural configuration with vehicle longitudinal and lateral behavior on a study sample of 34 diverse participants. A novel fully adaptive symbolic aggregate approximation (faSAX) algorithm is proposed, which adaptively segments and assigns symbols to the segmented time-variant fatigue patterns according to the discrepancy in postural behavior and vehicle parameters. These multivariate symbols are then combined to prepare the bag of words (text format dataset), which is further processed to generate a semantic report of the driver’s status and vehicle situations. The report is then analyzed by a natural language processing scheme working as a sequence-to-label classifier that detects the driver’s mental state and a possible outcome of the vehicle situation. The ground truth of report formation is validated against measurements of mental fatigue through brain signals. The experimental results show that the proposed hybrid system successfully detects time-variant driver mental fatigue and drowsiness states, along with vehicle situations, with an accuracy of 99.6% compared to state-of-the-art systems. The limitations of the current work and directions for future research are also explored.
{"title":"A Semantic Hybrid Temporal Approach for Detecting Driver Mental Fatigue","authors":"Shahzeb Ansari, Haiping Du, F. Naghdy, Ayaz Ahmed Hoshu, David Stirling","doi":"10.3390/safety10010009","DOIUrl":"https://doi.org/10.3390/safety10010009","url":null,"abstract":"Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle measurement methods. However, the literature lacks the implementation of hybrid approaches that combine the strength of individual approaches to develop a robust fatigue detection system. In this regard, a hybrid temporal approach is proposed in this paper to detect driver mental fatigue through the combination of driver postural configuration with vehicle longitudinal and lateral behavior on a study sample of 34 diverse participants. A novel fully adaptive symbolic aggregate approximation (faSAX) algorithm is proposed, which adaptively segments and assigns symbols to the segmented time-variant fatigue patterns according to the discrepancy in postural behavior and vehicle parameters. These multivariate symbols are then combined to prepare the bag of words (text format dataset), which is further processed to generate a semantic report of the driver’s status and vehicle situations. The report is then analyzed by a natural language processing scheme working as a sequence-to-label classifier that detects the driver’s mental state and a possible outcome of the vehicle situation. The ground truth of report formation is validated against measurements of mental fatigue through brain signals. The experimental results show that the proposed hybrid system successfully detects time-variant driver mental fatigue and drowsiness states, along with vehicle situations, with an accuracy of 99.6% compared to state-of-the-art systems. The limitations of the current work and directions for future research are also explored.","PeriodicalId":509460,"journal":{"name":"Safety","volume":"21 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139443762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dwitya Harits Waskito, L. P. Bowo, Siti Hidayanti Mutiara Kurnia, Indra Kurniawan, Sinung Nugroho, Novi Irawati, Mutharuddin, T. S. Mardiana, Subaryata
Truck accidents are a prevalent global issue resulting in substantial economic losses and human lives. One of the principal contributing factors to these accidents is driver error. While analysing human error, it is important to thoroughly examine the truck’s condition, the drivers, external circumstances, the trucking company, and regulatory factors. Therefore, this study aimed to illustrate the application of HFACS (Human Factor Classification System) to examine the causal factors behind the unsafe behaviors of drivers and the resulting accident consequences. Bayesian Network (BN) analysis was adopted to discern the relationships between failure modes within the HFACS framework. The result showed that driver violations had the most significant influence on fatalities and multiple-vehicle accidents. Furthermore, the backward inference with BN showed that the mechanical system malfunction significantly impacts driver operating error. The result of this analysis is valuable for regulators and trucking companies striving to mitigate the occurrence of truck accidents proactively.
{"title":"Analysing the Impact of Human Error on the Severity of Truck Accidents through HFACS and Bayesian Network Models","authors":"Dwitya Harits Waskito, L. P. Bowo, Siti Hidayanti Mutiara Kurnia, Indra Kurniawan, Sinung Nugroho, Novi Irawati, Mutharuddin, T. S. Mardiana, Subaryata","doi":"10.3390/safety10010008","DOIUrl":"https://doi.org/10.3390/safety10010008","url":null,"abstract":"Truck accidents are a prevalent global issue resulting in substantial economic losses and human lives. One of the principal contributing factors to these accidents is driver error. While analysing human error, it is important to thoroughly examine the truck’s condition, the drivers, external circumstances, the trucking company, and regulatory factors. Therefore, this study aimed to illustrate the application of HFACS (Human Factor Classification System) to examine the causal factors behind the unsafe behaviors of drivers and the resulting accident consequences. Bayesian Network (BN) analysis was adopted to discern the relationships between failure modes within the HFACS framework. The result showed that driver violations had the most significant influence on fatalities and multiple-vehicle accidents. Furthermore, the backward inference with BN showed that the mechanical system malfunction significantly impacts driver operating error. The result of this analysis is valuable for regulators and trucking companies striving to mitigate the occurrence of truck accidents proactively.","PeriodicalId":509460,"journal":{"name":"Safety","volume":"26 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139445256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Keall, N. Pierse, Chris W. Cunningham, Michael G. Baker, Sarah Bierre, P. Howden-Chapman
(1) Background: Fall injuries in the home present a major health burden internationally for all age groups. One effective intervention to prevent falls is home modification, but safety is only increased if opportunities to install safety modifications are taken up. This study sought to identify factors that may lead to a higher uptake of no-cost home modifications when these are offered to people living in the community. (2) Methods: We studied 1283 houses in the New Zealand cities of New Plymouth and Wellington. Using logistic regression, we modelled the odds of uptake according to the number of access steps, the provider who was undertaking the modifications, occupant ethnicity, prior fall injury history, and age group. (3) Results: Homes with older residents (age 65+) had higher uptake rates (35% vs. 27% for other homes). Larger numbers of access steps were associated with higher uptake rates. There was indicative evidence that homes with Indigenous Māori occupants had a higher uptake of the modifications for one of the two providers, but not the other. (4) Conclusions: No-cost home safety modifications offered via cold calling are likely to have relatively low uptake rates but the households that do consent to the modifications may be those who are more likely to benefit from the concomitant increased safety.
{"title":"Factors Associated with Uptake of No-Cost Safety Modifications to Home Access Steps: Implications for Equity and Policy","authors":"M. Keall, N. Pierse, Chris W. Cunningham, Michael G. Baker, Sarah Bierre, P. Howden-Chapman","doi":"10.3390/safety10010007","DOIUrl":"https://doi.org/10.3390/safety10010007","url":null,"abstract":"(1) Background: Fall injuries in the home present a major health burden internationally for all age groups. One effective intervention to prevent falls is home modification, but safety is only increased if opportunities to install safety modifications are taken up. This study sought to identify factors that may lead to a higher uptake of no-cost home modifications when these are offered to people living in the community. (2) Methods: We studied 1283 houses in the New Zealand cities of New Plymouth and Wellington. Using logistic regression, we modelled the odds of uptake according to the number of access steps, the provider who was undertaking the modifications, occupant ethnicity, prior fall injury history, and age group. (3) Results: Homes with older residents (age 65+) had higher uptake rates (35% vs. 27% for other homes). Larger numbers of access steps were associated with higher uptake rates. There was indicative evidence that homes with Indigenous Māori occupants had a higher uptake of the modifications for one of the two providers, but not the other. (4) Conclusions: No-cost home safety modifications offered via cold calling are likely to have relatively low uptake rates but the households that do consent to the modifications may be those who are more likely to benefit from the concomitant increased safety.","PeriodicalId":509460,"journal":{"name":"Safety","volume":"93 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139386208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Facing the threat of SARS-CoV-2, several countries implemented protective measures to annihilate the waves of the pandemic. Apart from quarantine, social distancing, frequent disinfection, and the use of a face mask, vaccination against COVID-19 soon became available. The measures taken in the workplace to inhibit the spread of the virus were important, as some controversial policies emerged regarding the vaccination status of employees. The “health pass” changed the workplace environment immensely, as in many job sectors vaccination became mandatory. Unvaccinated employees were required to undergo specific COVID-19 tests to access their workplace, while other specialized workers such as health workers were removed from their work altogether. Such measures would be justified if it was certain that vaccinated people cannot transmit the virus, but over the course of years this hypothesis seems to have faded. The main aim of this study is the confirmation (or the non-validation) of this hypothesis and of the specific applied measures through the elaboration and statistical analysis of vaccination data from 35 countries in relation to their daily announced infections over the time frame from the forty-fourth week of 2021 to the fourth week of 2022. This is examined from an occupational safety and health (OSH) perspective (taking into account the three pillars of sustainability) concerning risk management and safety assessment at the workplaces of sustainable engineering systems (SES). The findings imply that this hypothesis is contestable. Therefore, it is doubtful whether workplace segregation measures were socially and economically sustainable. It is deduced that (i) the complete freedom of vaccinated employees was a situation which intensified occupational risk, degraded the safety level at the workplaces of sustainable engineering systems, and increased the OSH risk management difficulties, and, on the other hand, (ii) the financial burden of mandatory unemployment and frequent testing was not justified and economically sustainable for the unvaccinated individuals in the middle of a worldwide economic crisis.
{"title":"Elaboration and Analysis of SARS-CoV-2 Data in the Frame of Occupational Safety and Health Assessment in Sustainable Engineering Systems","authors":"Stefania F. Tatli, P. Marhavilas","doi":"10.3390/safety10010006","DOIUrl":"https://doi.org/10.3390/safety10010006","url":null,"abstract":"Facing the threat of SARS-CoV-2, several countries implemented protective measures to annihilate the waves of the pandemic. Apart from quarantine, social distancing, frequent disinfection, and the use of a face mask, vaccination against COVID-19 soon became available. The measures taken in the workplace to inhibit the spread of the virus were important, as some controversial policies emerged regarding the vaccination status of employees. The “health pass” changed the workplace environment immensely, as in many job sectors vaccination became mandatory. Unvaccinated employees were required to undergo specific COVID-19 tests to access their workplace, while other specialized workers such as health workers were removed from their work altogether. Such measures would be justified if it was certain that vaccinated people cannot transmit the virus, but over the course of years this hypothesis seems to have faded. The main aim of this study is the confirmation (or the non-validation) of this hypothesis and of the specific applied measures through the elaboration and statistical analysis of vaccination data from 35 countries in relation to their daily announced infections over the time frame from the forty-fourth week of 2021 to the fourth week of 2022. This is examined from an occupational safety and health (OSH) perspective (taking into account the three pillars of sustainability) concerning risk management and safety assessment at the workplaces of sustainable engineering systems (SES). The findings imply that this hypothesis is contestable. Therefore, it is doubtful whether workplace segregation measures were socially and economically sustainable. It is deduced that (i) the complete freedom of vaccinated employees was a situation which intensified occupational risk, degraded the safety level at the workplaces of sustainable engineering systems, and increased the OSH risk management difficulties, and, on the other hand, (ii) the financial burden of mandatory unemployment and frequent testing was not justified and economically sustainable for the unvaccinated individuals in the middle of a worldwide economic crisis.","PeriodicalId":509460,"journal":{"name":"Safety","volume":"41 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139390595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although notable efforts have been made in the past to improve Occupational Health and Safety (OHS), the overall performance has not significantly improved as high-level injuries, risks, and fatalities continue to occur. Earlier studies have shown that implementing an Occupational Health and Safety Management System (OHSMS) ensures a reduction in accidents on site, which is, however, not easy due to the many challenges arising during its implementation. The research objectives were to identify, in order of importance, factors that affect the implementation of an OHSMS on construction sites and to analyse how an OHSMS can be implemented in the construction industry of the Western Cape, South Africa, using the Plan Do Check Act (PDCA) method. The research questionnaire obtained online opinions from construction professionals. The data were analysed using the Statistical Package for Social Sciences (SPSS) software version 27.0. The data were interpreted through Cronbach’s alpha coefficient, frequencies, descriptive statistics, and a multi-regression analysis. A multi-regression test was conducted to determine the relationship between internal and external factors and the implementation of an OHSMS, including the use of the PDCA method. The findings reveal that both internal and external factors affected the implementation of the OHSMS. The most important internal factors were risk control strategies, senior management commitment, and support and communication channels. The most common external factors were pressure from clients on project delivery, company reputation, OHS enforcement, and government legislation. A framework was developed to outline how an OHSMS can be implemented using the PDCA approach based on the findings from this study. The framework can be adopted by the construction industry to improve effectiveness when implementing their OHSMS.
{"title":"Perceived Factors Affecting the Implementation of Occupational Health and Safety Management Systems in the South African Construction Industry","authors":"Rejoice Kunodzia, Luviwe Bikitsha, Rainer Haldenwang","doi":"10.3390/safety10010005","DOIUrl":"https://doi.org/10.3390/safety10010005","url":null,"abstract":"Although notable efforts have been made in the past to improve Occupational Health and Safety (OHS), the overall performance has not significantly improved as high-level injuries, risks, and fatalities continue to occur. Earlier studies have shown that implementing an Occupational Health and Safety Management System (OHSMS) ensures a reduction in accidents on site, which is, however, not easy due to the many challenges arising during its implementation. The research objectives were to identify, in order of importance, factors that affect the implementation of an OHSMS on construction sites and to analyse how an OHSMS can be implemented in the construction industry of the Western Cape, South Africa, using the Plan Do Check Act (PDCA) method. The research questionnaire obtained online opinions from construction professionals. The data were analysed using the Statistical Package for Social Sciences (SPSS) software version 27.0. The data were interpreted through Cronbach’s alpha coefficient, frequencies, descriptive statistics, and a multi-regression analysis. A multi-regression test was conducted to determine the relationship between internal and external factors and the implementation of an OHSMS, including the use of the PDCA method. The findings reveal that both internal and external factors affected the implementation of the OHSMS. The most important internal factors were risk control strategies, senior management commitment, and support and communication channels. The most common external factors were pressure from clients on project delivery, company reputation, OHS enforcement, and government legislation. A framework was developed to outline how an OHSMS can be implemented using the PDCA approach based on the findings from this study. The framework can be adopted by the construction industry to improve effectiveness when implementing their OHSMS.","PeriodicalId":509460,"journal":{"name":"Safety","volume":"33 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139390633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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