Human factors and education: evolution and contributions

OBJECTIVE: The major contributions of human factors to education are highlighted. BACKGROUND: Over the past 50 years, the education of human factors specialists has evolved, as well as the application of human factors and ergonomic knowledge to education. METHOD: Human factors and ergonomics professional documentation and literature were reviewed to identify major events relevant to human factors education or the application of human factors to education. RESULTS: Human factors education has evolved from training in experimental psychology to highly specialized accredited human factors programs and a number of undergraduate programs, leading to program accreditation and the certification of professionals. In addition, human factors specialists have applied their knowledge to human factors education and, more recently, to educational systems in general. The greatest focus has been on technology such as multimedia. Others have evaluated the design of the physical environment, focusing primarily on seating. The research also often targets undergraduate or graduate education. Therefore, it has been proposed that a greater focus is needed at the K-12 educational level, especially given the advancement and implementation of technology in the classroom. CONCLUSION: Human factors and ergonomic expertise can benefit the educational system. Yet, there is a need to constantly evaluate the benefits of new technology in the classroom as well as the environmental design aspects of the educational environment while considering learners of different age groups, ethnicities, and sexes. APPLICATION: Better application of human factors and ergonomics to the learning environment could enhance the educational experience for all learners.     

Simulation optimization of an emergency department by modeling human errors

Emergency department (ED) is considered as one of the most critical elements in healthcare systems. This paper describes a simulation optimization of an emergency department in a general hospital in Iran by modeling human error. Human error is defined as combination of committed errors by nurses and technicians. In this study three types of errors are evaluated including repeated venipuncture, unsafe transportation and sampling errors. These errors are considered in simulation model. Seventy appropriate scenarios approved by experts in ED are defined to assess various alternatives. Scenarios are examined and evaluated by stochastic data envelopment analysis (SDEA). Then, the optimum scenarios are identified. In this study, expense cost, number of nurses and physicians are considered as inputs whilst patient duration, queue length, and number of three different committed errors are considered as outputs of SDEA and DEA model. The results show that addition of nurse and physician in ED would reduce the human errors, patient duration and queue length. Then, proposed approach is validated and verified by statistical test. Finally, queue length is identified as the most important indicator through sensitivity analysis. To the best of our knowledge this is the first paper that examines human errors in a general hospital by simulation, DEA, and SDEA approaches. Moreover, human errors are classified based on skill, rule, and knowledge (SRK) based behavior to help decision makers in order to improve the quality of care for this particular ED.     

Improving cardiac surgical care: A work systems approach

Over the past 50 years, significant improvements in cardiac surgical care have been achieved. Nevertheless, surgical errors that significantly impact patient safety continue to occur. In order to further improve surgical outcomes, patient safety programs must focus on rectifying work system factors in the operating room (OR) that negatively impact the delivery of reliable surgical care. The goal of this paper is to provide an integrative review of specific work system factors in the OR that may directly impact surgical care processes, as well as the subsequent recommendations that have been put forth to improve surgical outcomes and patient safety. The important role that surgeons can play in facilitating work system changes in the OR is also discussed. The paper concludes with a discussion of the challenges involved in assessing the impact that interventions have on improving surgical care. Opportunities for future research are also highlighted throughout the paper.     

Predicting unsafe behaviors at nuclear power plants: An integration of Theory of Planned Behavior and Technology Acceptance Model

Unsafe behaviors, including both errors and violations, have been identified as key contributors to accidents at nuclear power plants. However, the mechanisms behind such unsafe behaviors are not fully understood. This study aimed to investigate how workers' attitude and perception factors would predict errors and violations at nuclear power plants by proposing and validating an unsafe behavior model. The proposed model applied the Theory of Planned Behavior as the ground theoretical model and added factors from Technology Acceptance Model to capture workers’ perception of work regulations. To examine the validity of the proposed model, a total of 178 questionnaires were distributed at two nuclear power plants in China and 171 valid questionnaires were returned. The Structured Equation Modeling (SEM) analysis indicated that the proposed model fitted the data well. The results showed that perceived ease of use and perceived usefulness in following work regulations contributed to a positive attitude, which helped reduce the occurrence of both errors and violations. Moreover, errors were further affected by subjective norm while violations were not. Perceived behavior control was not a significant factor of either errors or violations.These findings suggest that to reduce errors and violations, policymakers should focus on methods to improve the perceived usefulness and perceived ease of use of work regulations, and promote a positive attitude towards safety.     

Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts

Abstract

Human Factors Analysis and Classification System (HFACS) is based upon Reason’s organizational model of human error which suggests that there is a ‘one to many’ mapping of condition tokens (HFACS level 2 psychological precursors) to unsafe act tokens (HFACS level 1 error and violations). Using accident data derived from 523 military aircraft accidents, the relationship between HFACS level 2 preconditions and level 1 unsafe acts was modelled using an artificial neural network (NN). This allowed an empirical model to be developed congruent with the underlying theory of HFACS. The NN solution produced an average overall classification rate of ca. 74% for all unsafe acts from information derived from their level 2 preconditions. However, the correct classification rate was superior for decision- and skill-based errors, than for perceptual errors and violations.

Practitioner Summary: A model to predict unsafe acts (HFACS level 1) from their preconditions (HFACS level 2) was developed from the analysis of 523 military aircraft accidents using an artificial NN. The results could correctly predict approximately 74% of errors.     

Human factors in patient safety as an innovation

The use of Human Factors and Ergonomics (HFE) tools, methods, concepts and theories has been advocated by many experts and organizations to improve patient safety. To facilitate and support the spread of HFE knowledge and skills in healthcare and patient safety, we propose to conceptualize HFE as innovations whose diffusion, dissemination, implementation and sustainability need to be understood and specified. Using Greenhalgh et al. (2004) model of innovation, we identified various factors that can either hinder or facilitate the spread of HFE innovations in healthcare organizations. Barriers include lack of systems thinking, complexity of HFE innovations and lack of understanding about the benefits of HFE innovations. Positive impact of HFE interventions on task performance and the presence of local champions can facilitate the adoption, implementation and sustainability of HFE innovations. This analysis concludes with a series of recommendations for HFE professionals, researchers and educators.     

Computer simulation for ergonomic improvements in laparoscopic surgery

It is the aim of this study to reduce the stress and strain of the medical staff during laparoscopic operations, and, simultaneously, to increase the safety and efficiency of an integrated operation room (OR) by an ergonomic redesign. This was attempted by a computer simulation approach using free modelling of the OR and 3D human models (manikins). After defining ergonomically "ideal" postures, optimal solutions for key elements of an ergonomic design of the OR (position and height of the image displays, height of the OR table and the Mayo stand) could be evaluated with special regard to the different individual body size of each member of the team. These data should be useful for the development of team adapted, user friendly integrated OR suites of the future.     

Associations of ergonomic and psychosocial work hazards with musculoskeletal disorders of specific body parts: A study of general employees in Taiwan

Background and aimsMusculoskeletal disorders (MSDs) are major occupational health concerns. This study examined the associations of ergonomic and psychosocial work hazards with the risks of MSDs of specific body parts and their distribution across a wide range of occupational groups.MethodsStudy participants comprised 8,937 male and 7,052 female employees aged 20–65 years from a nationwide survey in 2016. A self-report questionnaire was administered to obtain information regarding demographic characteristics, work conditions, ergonomic and psychosocial work hazards, and MSDs of different body parts in 12 months. Multivariate logistic regression models were used to estimate prevalence ratios of MSDs in relation to ergonomic and psychosocial work hazards.ResultsIn professionals and skilled workers, MSDs of the neck and shoulders were more prevalent, whereas in manual workers, MSDs of the hands, wrists, and lower back were more prevalent. Psychosocial work hazards, including high psychological demand and low workplace justice, were major work-related risk factors for shoulder and neck disorders, whereas ergonomic hazards were major work-related risk factors for lower back and wrist or hand disorders.ConclusionDifferent workplace hazards contribute to the risks of different MSDs. To prevent the development of MSDs, occupational health professionals should evaluate both ergonomic and psychosocial work hazards and develop health prevention programs tailored to the risk profiles of working populations.     

Analysis of truck drivers’ unsafe driving behaviors using four machine learning methods

Unsafe driving behaviors are the leading causes of truck crashes. Therefore, an enhanced understanding of truck drivers' unsafe driving behaviors is of considerable significance for preventing truck crashes. However, previous studies have rarely encompassed proactive factors such as safety management. Therefore, a classification framework for truck drivers' unsafe driving behaviors was established according to a survey of 2000 truck drivers using four machine learning models (CART, RT, AdaBoost, and GBDT). The classification framework included six first-level input dimensions, 51 s-level input indicators, covering both objective and proactive factors. Nine types of unsafe driving behaviors were determined as outputs. Unique risk factors associated with each of nine unsafe driving behaviors were identified. The results showed that the model's predictive performance varies with different driving behaviors (Classification Accuracy ranges from 0.64 to 0.95, F1-score ranges from 0.52 to 0.72), which was caused by different formation mechanisms of different driving behaviors. Similarly, the results related to factor importance for different driving behaviors were also significantly different, regardless of the first-level and second-level factors. Furthermore, the correlation analysis and OR value strengthened the interpretability of the factor importance, revealing possible reasons for the differences between various driving behaviors.     

浅析虚拟现实技术在座椅设计人机工效分析中的应用

针对当前座椅设计时进行人机分析时存在的周期长、投入大的不足,将虚拟现实技术应用到座椅设计当中。井以JACK软件为例。对虚拟现实技术在座椅设计人机工效分析中的应用进行实例验证。结果表明：虚拟现实技术能够有效地加快座椅设计的开发进程,提高了人机分析的效率,满足了座椅设计人机研究的需求,具有较高的先进性与实用性。     

Cross-sectional study of risk factors for symptoms in the neck and shoulder area

Abstract

This study was performed in order to evaluate how individual characteristics, as well as ergonomic, organizational and psychosocial factors in the work situation are associated with early symptoms in the neck and shoulder area. Nine hundred randomly drawn subjects of the working population in a semi-rural community in Sweden were mailed a questionnaire comprising the Nordic questionnaire on musculoskeletal symptoms, questions on ergonomic, organizational and psychosocial work conditions, life style factors, and background factors. The total response rate was 73% ( n = 637). Questions on ergonomic work conditions and on organizational and psychosocial work conditions provided the measures of exposure. Prevalence ratios (PR) were calculated for symptoms in the neck and shoulder area as reported by 303 subjects. Significant determinants for early symptoms were being a female and being an immigrant, as were repetitive movements demanding precision. High work pace, low work content and work role ambiguity were significant organizational risk factors while life style characteristics did not appear as risk factors. The results suggest that symptoms are signals not only of ergonomic deficiencies in the work situation, but in particular of work organizational conditions. Special attention should be given to the work conditions of women and immigrants in preventive interventions.     

Development of a software package for ergonomic assessment of manufacturing industry

A computer software package has been developed to be used as a self-assessment tool to evaluate ergonomic improvement potential of production systems by engineers, managers and safety professionals. Production managers of manufacturing industries with no prior knowledge of ergonomics were able to identify ergonomic deficiencies successfully (81%) in the shop floors as a result of the application of the ergonomic assessment tool. This enabled them to formulate intervention strategies to improve ergonomic conditions in their industries. The software package is user friendly, self-explanatory and provides relevant information, data and guidelines. It is unique, as the users will have access to necessary ergonomics information, which is often lacking in the manufacturing industries, especially in developing countries.     

Unsafe acts and unsafe outcomes in aircraft maintenance

Road safety studies using the Driver Behaviour Questionnaire (DBQ) have provided support for a three-way distinction between violations, skill-based errors and mistakes, and have indicated that a tendency to commit driving violations is associated with an increased risk of accident involvement. The aims of this study were to examine whether the three-way distinction of unsafe acts is applicable in the context of aircraft maintenance, and whether involvement in maintenance safety occurrences can be predicted on the basis of self-reported unsafe acts. A Maintenance Behaviour Questionnaire (MBQ) was developed to explore patterns of unsafe acts committed by aircraft maintenance mechanics. The MBQ was completed anonymously by over 1300 Australian aviation mechanics, who also provided information on their involvement in workplace accidents and incidents. Four factors were identified: routine violations, skill-based errors, mistakes and exceptional violations. Violations and mistakes were related significantly to the occurrence of incidents that jeopardized the quality of aircraft maintenance, but were not related to workplace injuries. Skill-based errors, while not related to work quality incidents, were related to workplace injuries. The results are consistent with the three-way typology of unsafe acts described by Reason et al. (1990) and with the DBQ research indicating an association between self-reported violations and accidents. The current findings suggest that interventions addressed at maintenance quality incidents should take into account the role of violations and mistakes, and the factors that promote them. In contrast, interventions directed at reducing workplace injury are likely to require a focus on skill-based errors.     

Big data and IoT solution for patient behaviour monitoring

ABSTRACT

The study of patient behaviours (vital sign, physical action and emotion) is crucial to improve one’s quality of life. The only solution for handling and managing millions of people’s behaviours and health would be big data and IoT technology because most of the countries are lack of medical professionals. In this paper, a big data and IoT-based patient behaviour monitoring system have proposed. Qualitative studies are carried out on the selected behaviours analytics, cardiovascular disease identification and fall detection. At last, authors have summarised the general challenges like trust, privacy, security and interoperability as well as special challenges in various sectors: government, legislators, research institutions, information technology companies and patients.     

Risk factors analysis: Work-related musculoskeletal disorders among male traffic policemen using high-powered motorcycles

IntroductionThe occupational safety and health issues for police riders and other professional riders are often related to ergonomic hazards and risks. The purpose of this research was to identify the factors that contribute to the health effects in developing work-related musculoskeletal disorders (WMSDs) among male traffic policemen using high-powered motorcycles.Materials and methodsA cross-sectional study was conducted using 137 police riders. A set of questionnaires including the Standardised Nordic Questionnaire (SNQ) and human vibration meter (Svantek 106) was used in this study.ResultsThe prevalence of WMSDs was 67.9%. Multiple logistic regression analysis revealed that the duration of riding a motorcycle (OR = 0.175, 95% CI:0.052, 0.581), years of service (OR = 0.152, 95% CI: 0.040, 0.567), and hand-arm vibration, HAV (OR = 3.053, 95% CI: 1.126, 8.280) were significant risk factors for the prevalence of WMSDs.DiscussionThe majority of riders reported symptoms of WMSDs within the past 12 months. Riding duration, years of service, and hand-arm vibration (HAV) were found to be the most important risk factors for WMSDs in this rider group. The results highlight that in the context of ergonomic interaction, high-powered motorcycles and the police riders are not a good fit. Hence, further study is needed to improve the safety and health of the police riders.     

试论我国网络出版业的人才培养与教育战略

网络出版这种全新的数字化出．版方式，有着传统出版无可比拟的优点，它给中国出版业实现跨越式发展带来了前所未有的机遇。但是，由于网络出版的技术基础、工作流程等与传统出版有很大的差异，我国出版业现行运行机制和人员配置还很难顺利实施网络出版，网络出版人才的缺失尤其显著。本文提出，人才资源是发展网络出版最重要的战略资源，应尽早做好网络出版人才的开发培训工作，为快速发展的网络出版业提供充足的智力支持。     

Unsafe acts and unsafe outcomes in aircraft maintenance

Road safety studies using the Driver Behaviour Questionnaire (DBQ) have provided support for a three-way distinction between violations, skill-based errors and mistakes, and have indicated that a tendency to commit driving violations is associated with an increased risk of accident involvement. The aims of this study were to examine whether the three-way distinction of unsafe acts is applicable in the context of aircraft maintenance, and whether involvement in maintenance safety occurrences can be predicted on the basis of self-reported unsafe acts. A Maintenance Behaviour Questionnaire (MBQ) was developed to explore patterns of unsafe acts committed by aircraft maintenance mechanics. The MBQ was completed anonymously by over 1300 Australian aviation mechanics, who also provided information on their involvement in workplace accidents and incidents. Four factors were identified: routine violations, skill-based errors, mistakes and exceptional violations. Violations and mistakes were related significantly to the occurrence of incidents that jeopardized the quality of aircraft maintenance, but were not related to workplace injuries. Skill-based errors, while not related to work quality incidents, were related to workplace injuries. The results are consistent with the three-way typology of unsafe acts described by Reason et al. (1990) and with the DBQ research indicating an association between self-reported violations and accidents. The current findings suggest that interventions addressed at maintenance quality incidents should take into account the role of violations and mistakes, and the factors that promote them. In contrast, interventions directed at reducing workplace injury are likely to require a focus on skill-based errors.     

Application of HFACS and grounded theory for identifying risk factors of air traffic controllers’ unsafe acts

Unsafe acts of air traffic controllers (ATCers) are caused by various factors. Based on interview data and case reports, human factors analysis and classification system (HFACS) and the grounded theory were adopted to identify the risk factors of ATCers’ unsafe acts comprehensively. The interview data and the case data issued by the authority were first collected. Then, the above data were encoded to obtain the relevant concepts and categories based on the grounded theory, and the HFACS model is used to classify the concepts and categories. Finally, the relationship between the core category and the secondary category was sorted out in the way of storyline. The results show that the risk factors include environmental factors, organizational influences, unsafe supervision and controllers’ states, and the unsafe acts manifest as errors and violations. Among them, the controllers’ states are intermediate variable, and other factors indirectly affect the controllers’ unsafe acts. The first three risk factors with high frequency in unsafe incidents are technical environment, mental states and business ability. The three most common unsafe acts are giving the wrong order, insufficient situational awareness, and poor work order on-site. Through combining HFACS framework and grounded theory to analyze data, a more clear and comprehensive conceptual model of risk factors of ATCers’ unsafe acts can be obtained.