Health and safety representatives (HSR) have the power to issue provisional improvement notices (PIN) to their employer for safety breaches. This paper examines how PINs influence workplace dynamics or employee voice. Semi-structured interviews were conducted with HSRs and other key stakeholders. They provided details of their organisations which were used to form three case studies. Some HSRs did not believe PINS would be required as management had implemented a positive safety culture. Other HSRs feared retaliation and were afraid to issue PINs. Overall, how PINs influence employee voice was primarily driven by workplace dynamics, management attitudes as well as broader economic and political factors. There was evidence that PINs increased the confidence of HSRs to perform their duties.
{"title":"How Provisional Improvement Notices Influence Employee Voice and Silence","authors":"Phillip Ho","doi":"10.3390/safety9020025","DOIUrl":"https://doi.org/10.3390/safety9020025","url":null,"abstract":"Health and safety representatives (HSR) have the power to issue provisional improvement notices (PIN) to their employer for safety breaches. This paper examines how PINs influence workplace dynamics or employee voice. Semi-structured interviews were conducted with HSRs and other key stakeholders. They provided details of their organisations which were used to form three case studies. Some HSRs did not believe PINS would be required as management had implemented a positive safety culture. Other HSRs feared retaliation and were afraid to issue PINs. Overall, how PINs influence employee voice was primarily driven by workplace dynamics, management attitudes as well as broader economic and political factors. There was evidence that PINs increased the confidence of HSRs to perform their duties.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49463501","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}
Milad Delavary, Zahra Ghayeninezhad, M. Lavallière
The risk of dying or being injured as a result of traffic collisions is higher for medical emergency responders than for other professional drivers. This systematic review synthesizes the literature regarding the collisions of ambulances, focusing on the prevalence and characteristics surrounding such events. Keywords including paramedics and traffic collisions were searched in papers available in PubMed from January 1990 to July 2021. Two independent reviewers screened the abstracts of 2494 papers and ended up with 93 full-text articles to assess for eligibility, of which 26 papers were finally kept for this review. There was a total of 18 studies conducted in the United States, followed by 3 in Turkey, 2 in Taiwan, 1 in both the United States and Canada, 1 in France, and 1 in Poland. There is a high record of injury and fatal collisions for ambulances compared to other commercial or similarly sized vehicles. Drivers less than 35 years old with low experience and a history of citations are more likely to be involved in such collisions. Ambulance collisions are more likely to happen in urban areas and intersections are the riskiest locations. Most collisions occur when the ambulance is responding to an emergency call (i.e., going to the patient or the hospital) and using lights and sirens. Tailored preventive policies and programs for improving paramedics’ safety should be sought to reduce the burden of these occupational collisions.
{"title":"Prevalence and Characteristics of Ambulance Collisions, a Systematic Literature Review","authors":"Milad Delavary, Zahra Ghayeninezhad, M. Lavallière","doi":"10.3390/safety9020024","DOIUrl":"https://doi.org/10.3390/safety9020024","url":null,"abstract":"The risk of dying or being injured as a result of traffic collisions is higher for medical emergency responders than for other professional drivers. This systematic review synthesizes the literature regarding the collisions of ambulances, focusing on the prevalence and characteristics surrounding such events. Keywords including paramedics and traffic collisions were searched in papers available in PubMed from January 1990 to July 2021. Two independent reviewers screened the abstracts of 2494 papers and ended up with 93 full-text articles to assess for eligibility, of which 26 papers were finally kept for this review. There was a total of 18 studies conducted in the United States, followed by 3 in Turkey, 2 in Taiwan, 1 in both the United States and Canada, 1 in France, and 1 in Poland. There is a high record of injury and fatal collisions for ambulances compared to other commercial or similarly sized vehicles. Drivers less than 35 years old with low experience and a history of citations are more likely to be involved in such collisions. Ambulance collisions are more likely to happen in urban areas and intersections are the riskiest locations. Most collisions occur when the ambulance is responding to an emergency call (i.e., going to the patient or the hospital) and using lights and sirens. Tailored preventive policies and programs for improving paramedics’ safety should be sought to reduce the burden of these occupational collisions.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45726597","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}
Hearing loss is one of the more common occupation health hazards across the globe yet is preventable. Extensive research has been done across a number of industries measuring the magnitude and frequency of hearing impairment. This study uses the National Health and Nutrition Examination Survey data to analyze hearing impairment in the United States. Regression and structural equation models were developed utilizing this publicly available data. A statistically significant correlation exists between general hearing condition and ethnicity, χ2 (30, N = 8897) = 264.817, p < 0.001. A statistically significant correlation exists in this database between general hearing condition and gender, χ2 (6, N = 8897) = 40.729, p < 0.001. An ordinal logistic regression was significant between the general health and ethnicity, χ2 (30, N = 5968) = 212.123, p < 0.001. A structural equation model presents the first of its type for this area of research. Focusing on addressing diversity issues may be the foundation for hearing health improvement. Tools such as smartphone apps may be useful for tracking hearing loss within the workforce.
{"title":"Workforce Diversity and Occupational Hearing Health","authors":"David W. Nadler","doi":"10.3390/safety9020023","DOIUrl":"https://doi.org/10.3390/safety9020023","url":null,"abstract":"Hearing loss is one of the more common occupation health hazards across the globe yet is preventable. Extensive research has been done across a number of industries measuring the magnitude and frequency of hearing impairment. This study uses the National Health and Nutrition Examination Survey data to analyze hearing impairment in the United States. Regression and structural equation models were developed utilizing this publicly available data. A statistically significant correlation exists between general hearing condition and ethnicity, χ2 (30, N = 8897) = 264.817, p < 0.001. A statistically significant correlation exists in this database between general hearing condition and gender, χ2 (6, N = 8897) = 40.729, p < 0.001. An ordinal logistic regression was significant between the general health and ethnicity, χ2 (30, N = 5968) = 212.123, p < 0.001. A structural equation model presents the first of its type for this area of research. Focusing on addressing diversity issues may be the foundation for hearing health improvement. Tools such as smartphone apps may be useful for tracking hearing loss within the workforce.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42060057","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}
John W. Ricketts, Dave Barry, Weisi Guo, Jonathan Pelham
Safety occurrence reports can contain valuable information on how incidents occur, revealing knowledge that can assist safety practitioners. This paper presents and discusses a literature review exploring how Natural Language Processing (NLP) has been applied to occurrence reports within safety-critical industries, informing further research on the topic and highlighting common challenges. Some of the uses of NLP include the ability for occurrence reports to be automatically classified against categories, and entities such as causes and consequences to be extracted from the text as well as the semantic searching of occurrence databases. The review revealed that machine learning models form the dominant method when applying NLP, although rule-based algorithms still provide a viable option for some entity extraction tasks. Recent advances in deep learning models such as Bidirectional Transformers for Language Understanding are now achieving a high accuracy while eliminating the need to substantially pre-process text. The construction of safety-themed datasets would be of benefit for the application of NLP to occurrence reporting, as this would allow the fine-tuning of current language models to safety tasks. An interesting approach is the use of topic modelling, which represents a shift away from the prescriptive classification taxonomies, splitting data into “topics”. Where many papers focus on the computational accuracy of models, they would also benefit from real-world trials to further inform usefulness. It is anticipated that NLP will soon become a mainstream tool used by safety practitioners to efficiently process and gain knowledge from safety-related text.
{"title":"A Scoping Literature Review of Natural Language Processing Application to Safety Occurrence Reports","authors":"John W. Ricketts, Dave Barry, Weisi Guo, Jonathan Pelham","doi":"10.3390/safety9020022","DOIUrl":"https://doi.org/10.3390/safety9020022","url":null,"abstract":"Safety occurrence reports can contain valuable information on how incidents occur, revealing knowledge that can assist safety practitioners. This paper presents and discusses a literature review exploring how Natural Language Processing (NLP) has been applied to occurrence reports within safety-critical industries, informing further research on the topic and highlighting common challenges. Some of the uses of NLP include the ability for occurrence reports to be automatically classified against categories, and entities such as causes and consequences to be extracted from the text as well as the semantic searching of occurrence databases. The review revealed that machine learning models form the dominant method when applying NLP, although rule-based algorithms still provide a viable option for some entity extraction tasks. Recent advances in deep learning models such as Bidirectional Transformers for Language Understanding are now achieving a high accuracy while eliminating the need to substantially pre-process text. The construction of safety-themed datasets would be of benefit for the application of NLP to occurrence reporting, as this would allow the fine-tuning of current language models to safety tasks. An interesting approach is the use of topic modelling, which represents a shift away from the prescriptive classification taxonomies, splitting data into “topics”. Where many papers focus on the computational accuracy of models, they would also benefit from real-world trials to further inform usefulness. It is anticipated that NLP will soon become a mainstream tool used by safety practitioners to efficiently process and gain knowledge from safety-related text.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44263999","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}
Some old-order Anabaptist communities rely on animal-drawn vehicles for transportation and farm work. This research examines reports involving horse-drawn vehicles found in the AgInjuryNews dataset, which provides a publicly accessible collection of agricultural injury reports primarily gathered from news media. The goals of this research are to characterize the reports and to compare results with previous research to assess the utility of using AgInjuryNews to examine horse-drawn vehicle incidents. A total of 38 reports representing 83 victims were identified. Chi-square tests comparing victim and incident traits for fatal and nonfatal injuries were significant for the victim’s role in the incident, vehicle type, presence of a motor vehicle, rear-ending by a motor vehicle, spooked horses, a victim being run over or struck by a vehicle, and a victim being ejected or falling from a vehicle. Additional analysis of incidents involving horse-drawn farm equipment showed that a significantly higher proportion of off-road incidents were fatal compared to on-road incidents. The proportion of fatal injuries in the AgInjuryNews dataset was approximately 10 times higher than observed in a study using Pennsylvania Department of Transportation (DOT) data. Compared to previous research, the AgInjuryNews reports contained a higher proportion of incidents where a motor vehicle rear-ended a horse-drawn vehicle, and fewer cases of horse-drawn vehicles being struck by motor vehicles while crossing or entering a main road and making left turns. Reports of buggy crashes found in AgInjuryNews differed from those found in a Nexis Uni search in that the bulk of the articles from Nexis Uni referred to cases involving criminal charges for impaired driving or hit-and-run crashes. While it is evident that the reports included in the sample are incidents that media sources find compelling rather than comprehensive injury surveillance, it is possible to gain new insights using the AgInjuryNews reports.
{"title":"An Assessment of Horse-Drawn Vehicle Incidents from U.S. News Media Reports within AgInjuryNews","authors":"N. Becklinger","doi":"10.3390/safety9020021","DOIUrl":"https://doi.org/10.3390/safety9020021","url":null,"abstract":"Some old-order Anabaptist communities rely on animal-drawn vehicles for transportation and farm work. This research examines reports involving horse-drawn vehicles found in the AgInjuryNews dataset, which provides a publicly accessible collection of agricultural injury reports primarily gathered from news media. The goals of this research are to characterize the reports and to compare results with previous research to assess the utility of using AgInjuryNews to examine horse-drawn vehicle incidents. A total of 38 reports representing 83 victims were identified. Chi-square tests comparing victim and incident traits for fatal and nonfatal injuries were significant for the victim’s role in the incident, vehicle type, presence of a motor vehicle, rear-ending by a motor vehicle, spooked horses, a victim being run over or struck by a vehicle, and a victim being ejected or falling from a vehicle. Additional analysis of incidents involving horse-drawn farm equipment showed that a significantly higher proportion of off-road incidents were fatal compared to on-road incidents. The proportion of fatal injuries in the AgInjuryNews dataset was approximately 10 times higher than observed in a study using Pennsylvania Department of Transportation (DOT) data. Compared to previous research, the AgInjuryNews reports contained a higher proportion of incidents where a motor vehicle rear-ended a horse-drawn vehicle, and fewer cases of horse-drawn vehicles being struck by motor vehicles while crossing or entering a main road and making left turns. Reports of buggy crashes found in AgInjuryNews differed from those found in a Nexis Uni search in that the bulk of the articles from Nexis Uni referred to cases involving criminal charges for impaired driving or hit-and-run crashes. While it is evident that the reports included in the sample are incidents that media sources find compelling rather than comprehensive injury surveillance, it is possible to gain new insights using the AgInjuryNews reports.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47359773","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}
One way to reduce road crashes is to determine the main influential factors among a long list that are attributable to driver behavior, environmental conditions, vehicle features, road type, and traffic signs. Hence, selecting the best modelling tool for extracting the relations between crash factors and their outcomes is a crucial task. To analyze the road crash data of Milan City, Italy, gathered between 2014–2017, this study used artificial neural networks (ANNs), generalized linear mixed-effects (GLME), multinomial regression (MNR), and general nonlinear regression (NLM), as the modelling tools. The data set contained 35,182 records of road crashes with injuries or fatalities. The findings showed that unbalanced and incomplete data sets had an impact on outcome performance, and data treatment methods could help overcome this problem. Age and gender were the most influential recurrent factors in crashes. Additionally, ANNs demonstrated a superior capability to approximate complicated relationships between an input and output better than the other regression models. However, they cannot provide an analytical formulation, but can be used as a baseline for other regression models. Due to this, GLME and MNR were utilized to gather information regarding the analytical framework of the model, that aimed to construct a particular NLM.
{"title":"A Crash Data Analysis through a Comparative Application of Regression and Neural Network Models","authors":"L. Mussone, Mohammadamin Alizadeh Meinagh","doi":"10.3390/safety9020020","DOIUrl":"https://doi.org/10.3390/safety9020020","url":null,"abstract":"One way to reduce road crashes is to determine the main influential factors among a long list that are attributable to driver behavior, environmental conditions, vehicle features, road type, and traffic signs. Hence, selecting the best modelling tool for extracting the relations between crash factors and their outcomes is a crucial task. To analyze the road crash data of Milan City, Italy, gathered between 2014–2017, this study used artificial neural networks (ANNs), generalized linear mixed-effects (GLME), multinomial regression (MNR), and general nonlinear regression (NLM), as the modelling tools. The data set contained 35,182 records of road crashes with injuries or fatalities. The findings showed that unbalanced and incomplete data sets had an impact on outcome performance, and data treatment methods could help overcome this problem. Age and gender were the most influential recurrent factors in crashes. Additionally, ANNs demonstrated a superior capability to approximate complicated relationships between an input and output better than the other regression models. However, they cannot provide an analytical formulation, but can be used as a baseline for other regression models. Due to this, GLME and MNR were utilized to gather information regarding the analytical framework of the model, that aimed to construct a particular NLM.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41728056","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}
Working on elevated surfaces without prior experience can be dangerous, particularly for young people, who are significantly more at risk of developing fear and anxiety, which might lead to falls and fatalities. This critical problem has, however, received limited research attention. The present study aimed to demonstrate the associations among physiological responses, fear, and anxiety in Thai teenagers at various height levels. Sixty teenagers (30 males and 30 females) between the ages of 15 and 18 who had no labor skills were recruited to perform the task at 11 levels, starting at zero meters and increasing by one meter at each level. The measurements were examined and recorded once the task at each level was finished. The main results indicated that heart rate was partially positively associated with mean arterial pressure, fear, and anxiety (with all p values < 0.001) in all teenagers (after controlling for level and sex), as well as male and female teenagers (after controlling for level). The present study suggested monitoring heart rate data in teenagers conducting activities at heights, which can be triggered by fear and anxiety, as a strategy for preventing falls from height hazards.
{"title":"Physiological Stress Responses to Fear and Anxiety in a Height Change Experiment among Non-Labor Teenagers","authors":"Apiruck Wonghempoom, Warawoot Chuangchai, Pattamon Selanon","doi":"10.3390/safety9020019","DOIUrl":"https://doi.org/10.3390/safety9020019","url":null,"abstract":"Working on elevated surfaces without prior experience can be dangerous, particularly for young people, who are significantly more at risk of developing fear and anxiety, which might lead to falls and fatalities. This critical problem has, however, received limited research attention. The present study aimed to demonstrate the associations among physiological responses, fear, and anxiety in Thai teenagers at various height levels. Sixty teenagers (30 males and 30 females) between the ages of 15 and 18 who had no labor skills were recruited to perform the task at 11 levels, starting at zero meters and increasing by one meter at each level. The measurements were examined and recorded once the task at each level was finished. The main results indicated that heart rate was partially positively associated with mean arterial pressure, fear, and anxiety (with all p values < 0.001) in all teenagers (after controlling for level and sex), as well as male and female teenagers (after controlling for level). The present study suggested monitoring heart rate data in teenagers conducting activities at heights, which can be triggered by fear and anxiety, as a strategy for preventing falls from height hazards.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43766160","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}
The proliferation of Unmanned Aircraft Systems (UAS) in the United States National Airspace System (NAS) has resulted in an increasing number of close encounters between manned aircraft and UAS, which correlates with the increasing number of remote pilots in the Federal Aviation Administration (FAA) airmen database. This research explores spatial patterns of registered airmen using Geographic Information Systems (GIS) analyses that provide notable spatial distribution patterns of pilots and how they relate to UAS sightings and airspace categories. The application of GIS to these aviation data may assist safety practitioners with identifying geographic patterns, areas of higher risk, and ultimately improve safety management. The authors analyzed publicly available airmen data to examine spatial distribution patterns, data correlations, and inferences. Airmen addresses were first geocoded into ArcPro 10.4 GIS software as a vector data layer containing attribute values of the database. The spatial analysis tool set was then utilized to establish clustering, density patterns, and spatial relationships between various categories of registered airmen. These density analyses revealed implicitly that commercial registered pilots tend to have the highest clustering near major commercial use controlled airspace, yet registered remote (UAS) pilots are also clustered in these and other densely populated areas. UAS sighting data were also geocoded using zip code values of the reported city to potentially correlate UAS sighting with registered remote pilots, yet the lack of spatial precision in the database made establishing any type of spatial relationship ineffective. The implicit spatial relationships between commercial and remote registered pilots revealed further research is needed to integrate UAS safely and effectively into the national airspace. The poor quality of UAS sighting data also demonstrates the need to better utilize GIS to monitor and track UAS flights within the context of an Unmanned Traffic Management System.
{"title":"Exploring the Use of Geographic Information Systems to Identify Spatial Patterns of Remote UAS Pilots and Possible National Airspace Risk","authors":"Damon J. Lercel, J. Hupy","doi":"10.3390/safety9010018","DOIUrl":"https://doi.org/10.3390/safety9010018","url":null,"abstract":"The proliferation of Unmanned Aircraft Systems (UAS) in the United States National Airspace System (NAS) has resulted in an increasing number of close encounters between manned aircraft and UAS, which correlates with the increasing number of remote pilots in the Federal Aviation Administration (FAA) airmen database. This research explores spatial patterns of registered airmen using Geographic Information Systems (GIS) analyses that provide notable spatial distribution patterns of pilots and how they relate to UAS sightings and airspace categories. The application of GIS to these aviation data may assist safety practitioners with identifying geographic patterns, areas of higher risk, and ultimately improve safety management. The authors analyzed publicly available airmen data to examine spatial distribution patterns, data correlations, and inferences. Airmen addresses were first geocoded into ArcPro 10.4 GIS software as a vector data layer containing attribute values of the database. The spatial analysis tool set was then utilized to establish clustering, density patterns, and spatial relationships between various categories of registered airmen. These density analyses revealed implicitly that commercial registered pilots tend to have the highest clustering near major commercial use controlled airspace, yet registered remote (UAS) pilots are also clustered in these and other densely populated areas. UAS sighting data were also geocoded using zip code values of the reported city to potentially correlate UAS sighting with registered remote pilots, yet the lack of spatial precision in the database made establishing any type of spatial relationship ineffective. The implicit spatial relationships between commercial and remote registered pilots revealed further research is needed to integrate UAS safely and effectively into the national airspace. The poor quality of UAS sighting data also demonstrates the need to better utilize GIS to monitor and track UAS flights within the context of an Unmanned Traffic Management System.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42479009","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}
A. Vuorio, R. Bor, A. Sajantila, A. Suhonen-Malm, Bruce Budowle
Background: The number of aircraft-assisted suicides can only be considered a rough estimate because it is difficult and, at times, impossible to identify all cases of suicide. Methods: Four recent reports of accidents occurring in 1997 in Indonesia, 1999 in Massachusetts in the United States, 2013 in Namibia, and 2015 in France related to commercial aircraft-assisted suicides were analyzed. This analysis relied on data extracted from the accident reports that supported aircraft-assisted suicide from the: (a) cockpit voice recorder (CVR) and flight data recorder (FDR), (b) medical history, (c) psychosocial history, (d) toxicology, (e) autopsy, and (f) any methodology that utilized aviation medicine. There are some limitations in this study. Although all analyzed accident investigations followed ICAO Annex 13 guidelines, there is variability in their accident investigations and reporting. In addition, accident investigation reports represent accidents from 1997 to 2015, and during this time, there has been a change in the way accidents are reported. The nature of this analysis is explorative. The aim was to identify how the various aircraft accident investigators concluded that the accidents were due to suicidal acts. Results: In all four accident reports, FDR data were available. CVR data were also available, except for one accident where CVR data were only partially available. Comprehensive medical and psychosocial histories were available in only one of four of the accident reports. Conclusion: To prevent accidents involving commercial aircraft, it is necessary to identify the causes of these accidents to be able to provide meaningful safety recommendations. A detailed psychological autopsy of pilots can and likely will assist in investigations, as well as generate recommendations that will substantially contribute to mitigating accidents due to pilot suicide. Airborne image recording may be a useful tool to provide additional information about events leading up to a crash and thus assist in accident investigations.
{"title":"Commercial Aircraft-Assisted Suicide Accident Investigations Re-Visited—Agreeing to Disagree?","authors":"A. Vuorio, R. Bor, A. Sajantila, A. Suhonen-Malm, Bruce Budowle","doi":"10.3390/safety9010017","DOIUrl":"https://doi.org/10.3390/safety9010017","url":null,"abstract":"Background: The number of aircraft-assisted suicides can only be considered a rough estimate because it is difficult and, at times, impossible to identify all cases of suicide. Methods: Four recent reports of accidents occurring in 1997 in Indonesia, 1999 in Massachusetts in the United States, 2013 in Namibia, and 2015 in France related to commercial aircraft-assisted suicides were analyzed. This analysis relied on data extracted from the accident reports that supported aircraft-assisted suicide from the: (a) cockpit voice recorder (CVR) and flight data recorder (FDR), (b) medical history, (c) psychosocial history, (d) toxicology, (e) autopsy, and (f) any methodology that utilized aviation medicine. There are some limitations in this study. Although all analyzed accident investigations followed ICAO Annex 13 guidelines, there is variability in their accident investigations and reporting. In addition, accident investigation reports represent accidents from 1997 to 2015, and during this time, there has been a change in the way accidents are reported. The nature of this analysis is explorative. The aim was to identify how the various aircraft accident investigators concluded that the accidents were due to suicidal acts. Results: In all four accident reports, FDR data were available. CVR data were also available, except for one accident where CVR data were only partially available. Comprehensive medical and psychosocial histories were available in only one of four of the accident reports. Conclusion: To prevent accidents involving commercial aircraft, it is necessary to identify the causes of these accidents to be able to provide meaningful safety recommendations. A detailed psychological autopsy of pilots can and likely will assist in investigations, as well as generate recommendations that will substantially contribute to mitigating accidents due to pilot suicide. Airborne image recording may be a useful tool to provide additional information about events leading up to a crash and thus assist in accident investigations.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46119537","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}
A. Saptari, P. Ng, Michelle Junardi, Andira Taslim
In manufacturing companies, manual material handling (MMH) involves lifting, pushing, pulling, carrying, moving, and lowering objects, which can lead to musculoskeletal disorders (MSDs) among workers, resulting in high labor costs due to excessive overtime incurred for manual product preparation. The aim of this study was to show how ergonomic measures were used to reduce the risk of MSDs and to reduce operating costs in the warehouse department of an oil and gas service company. A preliminary study using the Nordic Body Map survey showed that the workers experienced pain in various parts of the body, indicating the presence of MSDs. The researchers then used methods such as the Rapid Upper Limb Assessment (RULA), Rapid Entire Body Assessment (REBA), and National Institute for Occupational Safety and Health (NIOSH) assessments to verify whether the MMH activities had an acceptable level of risk. The results revealed that certain manual material handling (MMH) activities were assessed as low–very high risk, with RULA scores ranging from 3 to 7 and REBA scores ranging from 4 to 11. An immediate solution was to replace the manual process with a semi-automatic process using a vacuum lifter. A feasibility study was conducted using the net present value (NPV), internal rate of return (IRR), and payback period to justify the economic viability of the solution. The analysis indicated that implementing the vacuum lifter not only mitigated the risk of MSDs but also reduced the operating costs, demonstrating its viability and profitability. Overall, this study suggests that implementing a vacuum lifter as an assistive device in the warehouse would be a beneficial investment for both the workers and the company, improving both well-being and finances.
{"title":"A Feasibility Study on the Conversion from Manual to Semi-Automatic Material Handling in an Oil and Gas Service Company","authors":"A. Saptari, P. Ng, Michelle Junardi, Andira Taslim","doi":"10.3390/safety9010016","DOIUrl":"https://doi.org/10.3390/safety9010016","url":null,"abstract":"In manufacturing companies, manual material handling (MMH) involves lifting, pushing, pulling, carrying, moving, and lowering objects, which can lead to musculoskeletal disorders (MSDs) among workers, resulting in high labor costs due to excessive overtime incurred for manual product preparation. The aim of this study was to show how ergonomic measures were used to reduce the risk of MSDs and to reduce operating costs in the warehouse department of an oil and gas service company. A preliminary study using the Nordic Body Map survey showed that the workers experienced pain in various parts of the body, indicating the presence of MSDs. The researchers then used methods such as the Rapid Upper Limb Assessment (RULA), Rapid Entire Body Assessment (REBA), and National Institute for Occupational Safety and Health (NIOSH) assessments to verify whether the MMH activities had an acceptable level of risk. The results revealed that certain manual material handling (MMH) activities were assessed as low–very high risk, with RULA scores ranging from 3 to 7 and REBA scores ranging from 4 to 11. An immediate solution was to replace the manual process with a semi-automatic process using a vacuum lifter. A feasibility study was conducted using the net present value (NPV), internal rate of return (IRR), and payback period to justify the economic viability of the solution. The analysis indicated that implementing the vacuum lifter not only mitigated the risk of MSDs but also reduced the operating costs, demonstrating its viability and profitability. Overall, this study suggests that implementing a vacuum lifter as an assistive device in the warehouse would be a beneficial investment for both the workers and the company, improving both well-being and finances.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47954465","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：