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.

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.

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.

Tracing the physiological response and behavioral performance of drivers at different levels of mental workload using driving simulators.

INTRODUCTION: The use of mobile phones while driving is known to be a distraction factor and a cause of accidents. The way in which different kinds of conversations affect the behavioral performance of the driver as well as the persistence of the effects are not yet fully understood. METHOD: In this study, in addition to comparing brain function and behavioral function in dual task conditions in three conversations types, the persistent effects of these types of conversations have also been traced. RESULTS: The results show that the content of the mobile phone conversation while driving is the cause of the persistent changes in behavioral and brain functions. Increased time headway and lane departure was observed during and up to 5 min after the emotional conversation was finished. EEG bands also varied in different types of conversations. Cognitive conversations caused an increase in the activity of the alpha and beta bands while emotional conversations enhanced the rate of gamma and beta bands. A meaningful correlation was found between changes in the theta and alpha bands and changes in behavioral performance both during the dual task condition and after the conversation was finished, was also observed. CONCLUSIONS: The content of the conversation is one of the most important factors that increase the risk of road accidents. This can also deteriorate the behavioral performance of the driver and can have persistent effects on behavioral performance and the brain. Practical applications: The findings of this study provide a basis to measure and tracing drivers' cognitive distractions induced by different levels of mental workload through physiological and behavioral performances.

The Effect of Road Traffic Noise on Reaction Time.

BACKGROUND: Traffic noise is one of the main important sources in urban noise pollution, which causes various physiological and psychological effects that can cause disturbs in performance, sleep disturbances, hearing loss and impact on job performance. This study was conducted to verify the impact of road traffic noise on reaction time in terms of extraversion and sex. METHODS: Traffic noise was measured and recorded in 10 arterial streets in Tehran, and then the recorded noise was emitted towards participants in an acoustic room. The participants were 80 (40 cases and 40 controls) students. Personality type was determined by Eysenck Personality Inventory (EPI) questioner. Reaction time before and after exposure to traffic noise was measured. RESULTS: Reaction time before exposure to traffic noise did not differ (P=0.437) significantly between introverts and extraverts. However, it was increased significantly in both groups after exposure to traffic noise (P<0.01). Introvert's reaction time was more increased than that of extraverts. CONCLUSION: Traffic noise augmented reaction time of both males and females. This study also revealed that exposure to traffic noise leads to increase in reaction time.