Prediction of accident-proneness among a sample of Iranian workers: usefulness of an adjusted version of the Health Belief Model with spiritual health.

BACKGROUND: Workforce health is one of the primary and challenging issues, especially in industrialized countries. The purpose of the present study was to evaluate the ability to predict accident-proneness among Saveh Industry workers in Iran, based on an extended Health Belief Model, that included the construct of spiritual health. METHOD: This descriptive-analytical study was conducted in 2022 on 384 workers in Saveh, Iran. The study aimed to explore relationships between accident proneness behavior, spiritual health, and health beliefs. The accident-proneness questionnaire consisted of two parts: the first part included demographic questions, and the second part comprised 9 sections covering personality traits, workplace harmful factors, miscellaneous factors, musculoskeletal disorders, safety culture, safety attitudes, job stress, organization interest, and degree of risk-taking. The Health Belief Model included 31 questions, while spiritual health was measured with the 20-question Paloutzian and Ellison questionnaire. The collected data were analyzed using SPSS version 26 software. RESULTS: In terms of accident proneness, 229 (59.6%), exhibited high levels, 148 (38.5%) had medium levels, and 7 (1.8%) showed low levels of accident-proneness. Hierarchical multiple regression analysis showed that in the first model, variables of perceived self-efficacy, vulnerability, and severity independently predicted workers accident proneness, explaining a total of 43% of variance in accident proneness behavior. In the second step, perceived self-efficacy (ß = 34%), perceived sensitivity (ß = 27%), spiritual health (ß = 16%), and perceived severity (ß = 12%) were included, respectively, which explained a total of 46% of the variance of accident-prone behavior of workers. CONCLUSION: Given the high rate of accident proneness observed in this study, there is a critical need for policymakers and health planners to design policies aimed at mitigating the risks associated with occupational accidents. Furthermore, the findings highlight the potential of integrating spiritual health into the Health Belief Model, as a conceptual framework for planning effective intervention programs to enhance workplace safety.

The effect of COVID-19 anxiety on nurses' productivity determinants through perceived workload and individual job performance: A Bayesian mediation analysis.

This study aims to predict how COVID-19 anxiety affects productivity determinants by examining the role of perceived workload and individual job performance as mediators using Bayesian mediation analysis. To achieve the study's objectives, all nurses working at Imam Reza Hospital were recruited to participate. To gather data, all eligible and voluntary nurses were asked to complete questionnaires that included the Corona Disease Anxiety Scale (CDAS), Individual Job Performance Questionnaire (IJPQ), NASA Task Load Index (NASA-TLX), and Workforce Productivity Questionnaire. Of the total number of nurses employed, 222 (126 women and 96 men) nurses fully completed the questionnaires. Out of these, 140 individuals were married and 82 were single. The mean ± standard deviation (SD) of the age and experience were 28.56 ± 5.78 and 8.49 ± 6.50, respectively. GeNIe software version 2.0 utilized to analyze the Bayesian network. The results showed that for the high COVID-19 anxiety and high workload states, with a probability of 100 %, the probability of high evaluation and high environment increased by 16.6 % and 16.3 %, respectively, but low evaluation and low environment decreased by 22.4 % and 22 %, respectively. In the high COVID-19 anxiety and low IJP states with a probability of 100 %, most change was related to the high ability (6 % increase), low evaluation (3.9 % increase), high incentive (3.8 % increase), low ability (4.6 % decrease) and low support (2 % decrease). Regarding COVID-19 anxiety (high 100 %), workload (high 100 %) and IJP (low 100 %), most of the increase was related to high environment and high evaluation by an increase of 17.3 and 17.2 %, respectively. Also, the value of low evaluation and low environment was reduced by 24 and 23.4 %, respectively. The study's findings confirm that nurses have been more productive during the COVID-19 pandemic, despite facing high workloads and the COVID-19 anxiety.

Persistent effects of mobile phone conversation while driving after disconnect: Physiological evidence and driving performance.

Cognitive workload has been known as a key factor in traffic accidents, which can be highly increased by talking on the phone while driving. A wide range of studies around the world investigated the effects of mobile phone conversations on driving performance and traffic accidents. But less noticed is the durability of cognitive effects of mobile phone conversations. This study aimed to determine the effects of different types of mobile phone conversations on physiological response and driving performance during and after the conversation. Heart rate, heart rate variability (physiological response), Standard deviation of lane position (SDLP), and the relative distance between two cars (driving performance) of 34 samples (male and female) in the driving simulator were recorded. In this study, three types of conversations (neutral, cognitive, and arousal) were used. Neutral conversation did not pursue specific purpose questions. Cognitive conversations were simple mathematical problem-solving questions and arousal conversations aimed at arousing participant emotions. Each conversation was used as a secondary task in a condition. The study had three conditions; in each condition the participant drove for 15 min. Each condition consisted of 5 min of driving (Background), 5 min of driving and conversation (dual tasks) and 5 min of driving after conversation to trace the effects of the conversation. Vehicle speed was 110 km/h in each of the three conditions using car-following scenario. The results showed that neutral conversations had no significant effects on physiological response. Though, arousal conversations had significant effects on physiological responsiveness and driving performance during conversations, where it was even more significant after disconnection. Therefore, the content of the conversation determines the amount of cognitive load imposed on the driver. Considering the persistence of cognitive effects caused by conversation, the risk of traffic accidents is still high even after disconnection.

Willingness to Receive a COVID-19 Vaccine in an Iranian Population: Assessment of Attitudes, Perceived Benefits, and Barriers.

Background: To significantly reduce the disease and mortality from the novel Coronavirus Disease (COVID-19), a safe and effective vaccine must be widely delivered to the community. However, the availability of a vaccine for COVID-19 does not ensure that individuals will want to be vaccinated. The present study investigated the attitudes, perceived barriers, and benefits of the COVID-19 vaccine, as well as vaccination intentions, among a sample of Iranian adults. Methods: Demographic data were categorized in this study based on whether or not participants received the vaccine. Drawn from a multistage sampling protocol in 2021, a descriptive-analytical study was conducted on 1350 adults in Saveh, Iran. A survey with 5 different sections inquired about eligible participants' sociodemographic information, their attitudes, perceived benefits, and barriers, as well as their intentions to get vaccinated for COVID-19. Multiple logistic regression analysis (enter method) was performed to assess factors related to vaccination intent. Results: The mean age of those who intended to receive the COVID-19 vaccine (57.9±19.2) was significantly higher than those who did not intend to receive the vaccine (43.4±16.8) ( p =0.00). Additionally, married individuals were significantly more likely to receive the vaccine than individuals who were single and/or widowed. Additionally, (n=663) substantially more homemakers and retirees received vaccinations than workers and self-employed individuals (n=481) ( p =0.001). Findings revealed that 78% of participants intended to receive the COVID-19 vaccine. Multiple unconditional logistic regression analyses showed that age and marital status, as well as the behavioral variables (attitude odds ratio [OR]=1.73, benefits OR=1.78, and perceived Barriers OR=0.52), had a significant relationship with vaccination intentions ( p =0.001). Conclusion: This study demonstrated that to increase intentions to receive the COVID-19 vaccine, public health campaigns and interventions should focus on promoting the benefits of the vaccine, improving the attitudes toward the vaccine, as well as reducing the perceived barriers.

A Bayesian network model to predict the role of hospital noise, annoyance, and sensitivity in quality of patient care.

BACKGROUND: Hospital noise can adversely impact nurses' health, their cognitive function and emotion and in turn, influence the quality of patient care and patient safety. Thus, the aim of this study was to predict the contributing roles of exposure to hospital noise, staff noise-sensitivity and annoyance, on the quality of patient care. METHODS: This descriptive and cross-sectional study was carried out among nurses in an Iranian hospital. To determine nurses' noise exposure level, the noise was measured in 1510 locations across the hospital in accordance with ISO 9612 standards using KIMO DB 300/2 sound level meter and analyzer. An online survey was used to collect nurses' individual data. Study questionnaires included demographics, Weinstein noise sensitivity scale, noise annoyance scale, and quality of patient care scale. Finally, to analyze the data, Bayesian Networks (BNs), as probabilistic and graphical models, were used. RESULTS: For the high noise exposure state, high noise sensitivity, and high annoyance, with the probability of 100%, the probability of delivering a desirable quality of patient care decreased by 21, 14, and 23%, respectively. Moreover, at the concurrently high noise exposure and high noise sensitivity with the probability of 100%, the desirable quality of patient care decreased by 26%. The Bayesian most influence value was related to the association of noise exposure and annoyance (0.636). Moreover, annoyance had the highest association with the physical aspect of quality of care (0.400) and sensitivity had the greatest association with the communication aspect (0.283). CONCLUSION: Annoyance induced from environmental noise and personal sensitivity affected the quality of patient care adversely. Moreover, noise and sensitivity had a separate direct adverse effect upon the quality of patient care, and their co-occurrence reduced the potential for delivering quality patient care.

The effects of psychological risk factors at work on cognitive failures through the accident proneness.

BACKGROUND: Various agents such as psychosocial items and accident proneness can affect cognitive failures through different paths. The probable paths are the direct effects of workplace psychosocial items on cognitive failures and their indirect effects on cognitive failures through the mediator variable of accident proneness, which has not yet been studied by others. Thus, the present study aimed to investigate these paths. METHODS: This cross-sectional study was conducted on 164 male employees of Karoon Sugar Company in 2018. The participants were asked to complete a background and demographic questionnaire, Broadbent cognitive failures scale, accident proneness questionnaire, and Copenhagen psychosocial questionnaire. Obtained data were analyzed and modeled using the statistical descriptive method, ANOVA, independent t-test, Pearson correlation test, and path analysis in the SPSS and AMOS software. RESULTS: The results of the path analysis showed that, not only, some psychosocial risk items had a significant direct effect on cognitive failures, but also, they could affect cognitive failures through the accident proneness, indirectly. Work-family conflict and social support from supervisors by coefficients of 0.188 and - 0.187 had the highest direct effects, respectively. The highest indirect effects belonged to justice and respect, and work-family conflict by coefficients of - 0.220 and 0.199, respectively. The highest total effects were also related to the work-family conflict and justice and respect by coefficients of 0.387 and - 0.381, respectively. CONCLUSIONS: In total, our results showed that some psychological items could, directly and indirectly, increase cognitive failure through accident proneness.

Development of leading indicators for the assessment of occupational health performance using Reason's Swiss cheese model.

BACKGROUND: The Swiss cheese model of accident causation is a model used in risk analysis and risk management, including aviation safety, engineering, healthcare, and emergency service organizations, and as the principle behind layered security, as used in computer security and defense in-depth. This study aimed to develop and weight the occupational health leading indicators using the Swiss cheese model. MATERIALS AND METHODS: The present study was a descriptive, cross-sectional study; occupational health performance assessment indicators were classified into five main groups of chemical, physical, ergonomic, psychosocial, and biological harmful agents. In addition, potential hazards and their prevention methods were identified using the Swiss cheese model. The leading performance measurement indicators (n = 64) were developed based on preventive methods and were weighted and rated by fuzzy analytic hierarchy process. RESULTS: Thirty-six out of 64 indicators were related to the management measures, 25 indicators were related to exposure to harmful occupational agents, and the remaining indicators were occupational-related illnesses and diseases rate. Considering the importance and frequency of indicators, psychological agents were the most important indicators (40%) and physical agents had the greatest frequency (59%). CONCLUSIONS: Process of indicators' development has demonstrated that the major occupational health prevention measures in the oil and gas industry are concentrated on physical, psychological, and chemical agents, respectively. Thus, to provide protection for employees against occupational diseases and improve health performance indicators, paying special attention to mentioned agents is essential in the oil and gas industry.

Effects of whole body vibration and backrest angle on perceived mental workload and performance.

Mental Workload (MWL) and human performance are widely contributing concepts in human factors. The objective of the current study is to investigate the perceived MWL and human performance during whole-body vibration (WBV) exposure while seated at different backrest angles. Nineteen healthy male participants completed both the NASA-TLX and rating scale mental effort (RSME) after performing two difficulty levels of computerized dual tasks. The participants' performance was measured in these conditions while seated with a backrest angle of 100 and 120 degrees and exposed to WBV (intensity: 0.5 m/s2; frequency 3-20 Hz) for 5 minutes. No significant effect on performance or perceived MWL (p<0.05) was found when changes were made to the backrest angles. Exposure to WBV under two backrest angles increased mental demand (p=0.04), effort (p=0.03) and frustration (p=0.03) and negatively affected human performance (p<0.05). The present study showed that exposure to WBV could be an important variable for designing work environments that require a high level of performance and mental demand while seated. However, the findings exhibited no association between inclining backrest angle and human performance or perceived MWL.

Multi-dimensional model for determining the leading performance indicators of safety management systems.

BACKGROUND: Health and safety performance measurements aimed to provide information on the progress and current situation of organizational strategies and activities. OBJECTIVES: We developed a model to determine and select safety key performance indicators in order to assess safety management systems. METHODS: This study has been designed in six steps aiming at defining a model of leading performance indicators (LPIs) and selecting key performance indicators (KPIs) using the AHP method. RESULTS: According to the results analysis, 116 structural and operational indicators were defined based on the components of the OHSAS 18001 management system. For this purpose, 19 structural, 27 operational and 33 active KPIs were selected by AHP and BN techniques. CONCLUSION: Development of LPIs is influenced by various organizational, managerial, and operational factors. LPIs extracted from the components of the OHS-MS deployed in an organization are often passive and cannot show the changes in the safety status of a workplace in a short period. The model presented in this study was designed with an emphasis on extraction of active and operational indicators, as they were capable of detecting performance changes in construction industries.

Using fuzzy logic approach to predict work-related musculoskeletal disorders among automotive assembly workers.

Background: Musculoskeletal disorders (MSDs) are considered an important health concern, particularly in automotive assembly industries. Evaluation of the effects of all MSDs risk factors is difficult due to its multifactorial nature. In addition, the risk factors cannot be detected accurately when they are only based on individual opinions. Thus, in this study, fuzzy logic tool was used to evaluate the combined effects of all risk factors on MSDs. Methods: This cross sectional study was conducted on 100 male workers in an automotive industry. Job satisfaction, job stress, job fatigue, and body posture were evaluated by a self-reported questionnaire. Body posture was evaluated using Rapid Entire Body Assessment (REBA). Primary data analysis on extracting the input variables of MATLAB was performed by SPSS 22, with a significant level of 0.05. T test, one-way Anova, and Pearson correlation analysis were used to extract the input variables for the fuzzy logic model. The results obtained from the Nordic questionnaire was selected as the output of the fuzzy model. Fuzzy logic assessment was performed using MATLAB software version 7.0. Results: There were significant differences between WMSDs factors, including job fatigue, strain, working posture, and the REBA final score, and pain in all limbs of the body (p<0.05). A significant difference was also found between working posture with wrist score (p<0.05). The findings on defuzzification showed a strong correlation between real and modelling results. Conclusion: The results showed that many factors such as posture, fatigue, and strain affect MSDs. Based on the obtained results, all categories of risk factors, including personal, psychosocial, and occupational, should be considered to predict MSDs, which can be achieved by a modeling approach.