INTRODUCTION: Delirium in critically-ill patients is a common multifactorial disorder that is associated with various negative outcomes. It is assumed that sleep disturbances can result in an increased risk of delirium. This study hypothesized that implementing a protocol that reduces overall nocturnal sound levels improves quality of sleep and reduces the incidence of delirium in Intensive Care Unit (ICU) patients.METHODS: This interrupted time series study was performed in an adult mixed medical and surgical 24-bed ICU. A pre-intervention group of 211 patients was compared with a post-intervention group of 210 patients after implementation of a nocturnal sound-reduction protocol. Primary outcome measures were incidence of delirium, measured by the Intensive Care Delirium Screening Checklist (ICDSC) and quality of sleep, measured by the Richards-Campbell Sleep Questionnaire (RCSQ). Secondary outcome measures were use of sleep-inducing medication, delirium treatment medication, and patient-perceived nocturnal noise.RESULTS: A significant difference in slope in the percentage of delirium was observed between the pre- and post-intervention periods (-3.7% per time period, p=0.02). Quality of sleep was unaffected (0.3 per time period, p=0.85). The post-intervention group used significantly less sleep-inducing medication (p<0.001). Nocturnal noise rating improved after intervention (median: 65, IQR: 50-80 versus 70, IQR: 60-80, p=0.02).CONCLUSIONS: The incidence of delirium in ICU patients was significantly reduced after implementation of a nocturnal sound-reduction protocol. However, reported sleep quality did not improve.
from the article: Abstract Based on a review of recent literature, this paper addresses the question of how urban planners can steer urban environmental quality, given the fact that it is multidimensional in character, is assessed largely in subjective terms and varies across time. The paper explores three questions that are at the core of planning and designing cities: ‘quality of what?’, ‘quality for whom?’ and ‘quality at what time?’ and illustrates the dilemmas that urban planners face in answering these questions. The three questions provide a novel framework that offers urban planners perspectives for action in finding their way out of the dilemmas identified. Rather than further detailing the exact nature of urban quality, these perspectives call for an approach to urban planning that is integrated, participative and adaptive. ; ; sustainable urban development; trade-offs; quality dimensions
Nightshift workers go against the natural sleep–wake rhythm. Light can shift the circadian clock but can also induce acute alertness. This placebo-controlled exploratory field study examined the effectiveness of light glasses to improve alertness while reducing the sleep complaints of hospital nurses working nightshifts. In a crossover within-subjects design, 23 nurses participated, using treatment glasses and placebo glasses. Sleepiness and sleep parameters were measured. A linear mixed model analysis on sleepiness revealed no significant main effect of the light intervention. An interaction e ect was found indicating that under the placebo condition, sleepiness was significantly higher on the first nightshift than on the last night, while under the treatment condition, sleepiness remainedstable across nightshift sessions. Sleepiness during the commute home also showed a significant interaction effect, demonstrating that after the first nightshift, driver sleepiness was higher for placebo than for treatment. Subjective sleep quality showed a negative main effect of treatment vs. placebo, particularly after the first nightshift. In retrospect, both types of light glasses were self-rated as effective. The use of light glasses during the nightshift may help to reduce driver sleepiness during the commute home, which is relevant, as all participants drove home by car or (motor) bike.
-Chatbots are being used at an increasing rate, for instance, for simple Q&A conversations, flight reservations, online shopping and news aggregation. However, users expect to be served as effective and reliable as they were with human-based systems and are unforgiving once the system fails to understand them, engage them or show them human empathy. This problem is more prominent when the technology is used in domains such as health care, where empathy and the ability to give emotional support are most essential during interaction with the person. Empathy, however, is a unique human skill, and conversational agents such as chatbots cannot yet express empathy in nuanced ways to account for its complex nature and quality. This project focuses on designing emotionally supportive conversational agents within the mental health domain. We take a user-centered co-creation approach to focus on the mental health problems of sexual assault victims. This group is chosen specifically, because of the high rate of the sexual assault incidents and its lifetime destructive effects on the victim and the fact that although early intervention and treatment is necessary to prevent future mental health problems, these incidents largely go unreported due to the stigma attached to sexual assault. On the other hand, research shows that people feel more comfortable talking to chatbots about intimate topics since they feel no fear of judgment. We think an emotionally supportive and empathic chatbot specifically designed to encourage self-disclosure among sexual assault victims could help those who remain silent in fear of negative evaluation and empower them to process their experience better and take the necessary steps towards treatment early on.
