Effects of nocturnal railway noise on subjective ratings of sleep and subsequent cognitive performance

Determining the optimal human reliability analysis (HRA) method in healthcare systems using Fuzzy ANP and Fuzzy TOPSIS

Purpose

As one of the leading causes of deaths and injuries, medical errors constitute a veritable threat to patient safety. Despite this fact, no unique method has yet been established to identify and evaluate medical errors. This study was conducted to select an optimal human reliability analysis method compatible with healthcare systems from available methods. Design/methodology/approach: In order to select the optimal method for the identification and evaluation of medical errors, different criteria and sub-criteria were determined by reviewing the literature and based on experts’ opinions. Next, weights of criteria and sub-criteria were specified by using the fuzzy analytical network process (ANP). Finally, fuzzy technique for order preference by similarity to ideal solution method was used to prioritize the methods.

Findings

Six criteria and 21 sub-criteria for choosing the optimal method were determined. The utility, usability, and structure of a method had the highest influence with weights of 0.262, 0.191, and 0.187, respectively. Based on the results of fuzzy technique for order preference by similarity to ideal solution, the Human Error Assessment and Reduction Technique method with a closeness coefficient of 0.576 was selected as the optimal method for identifying medical errors. The Human Factors Analysis and Classification System and Systematic Human Error Reduction and Prediction Approach methods ranked second and third, respectively. Originality/value: To date, no studies have attempted to determine the optimal methods for identification and assessment of medical errors. This paper aimed to fill this gap by using fuzzy analytical network process and fuzzy technique for order preference by similarity to ideal solution techniques.

Comparing the Effects of Road, Railway, and Aircraft Noise on Sleep: Exposure⁻Response Relationships from Pooled Data of Three Laboratory Studies

Objectives: Air, road, and railway traffic, the three major sources of traffic noise, have been reported to differently impact on annoyance. However, these findings may not be transferable to physiological reactions during sleep which are considered to decrease nighttime recovery and might mediate long-term negative health effects. Studies on awakenings from sleep indicate that railway noise, while having the least impact on annoyance, may have the most disturbing properties on sleep compared to aircraft noise. This study presents a comparison between the three major traffic modes and their probability to cause awakenings. In combining acoustical and polysomnographical data from three laboratory studies sample size and generalizability of the findings were increased. Methods: Data from three laboratory studies were pooled, conducted at two sites in Germany (German Aerospace Center, Cologne, and Leibniz Research Centre for Working Environment and Human Factors, Dortmund). In total, the impact of 109,836 noise events on polysomnographically assessed awakenings was analyzed in 237 subjects using a random intercept logistic regression model. Results: The best model fit according to the Akaike Information Criterion (AIC) included different acoustical and sleep parameters. After adjusting for these moderators results showed that the probability to wake up from equal maximum A-weighted sound pressure levels (SPL) increased in the order aircraft < road < railway noise, the awakening probability from road and railway noise being not significantly different (p = 0.988). At 70 dB SPL, it was more than 7% less probable to wake up due to aircraft noise than due to railway noise. Conclusions: The three major traffic noise sources differ in their impact on sleep. The order with which their impact increased was inversed compared to the order that was found in annoyance surveys. It is thus important to choose the correct concept for noise legislation, i.e., physiological sleep metrics in addition to noise annoyance for nighttime noise protection.

Nocturnal air, road, and rail traffic noise and daytime cognitive performance and annoyance

Various studies indicate that at the same noise level and during the daytime, annoyance increases in the order of rail, road, and aircraft noise. The present study investigates if the same ranking can be found for annoyance to nocturnal exposure and next day cognitive performance. Annoyance ratings and performance change during combined noise exposure were also tested. In the laboratory 72 participants were exposed to air, road, or rail traffic noise and all combinations. The number of noise events and LAS,eq were kept constant. Each morning noise annoyance questionnaires and performance tasks were administered. Aircraft noise annoyance ranked first followed by railway and road noise. A possible explanation is the longer duration of aircraft noise events used in this study compared to road and railway noise events. In contrast to road and rail traffic, aircraft noise annoyance was higher after nights with combined exposure. Pooled noise exposure data showed small but significant impairments in reaction times (6 ms) compared to nights without noise. The noise sources did not have a differential impact on performance. Combined exposure to multiple traffic noise sources did not induce stronger impairments than a single noise source. This was reflected also in low workload ratings.