Search

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.

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.