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Factors Influencing Quality of Sleep among Critically Ill Patients in Selected Hospitals in Western Kenya |
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Factors Influencing Quality of Sleep among Critically Ill Patients in Selected Hospitals in Western Kenya |
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Journal Article |
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Year |
2018 |
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Journal of Health, Medicine and Nursing |
Abbreviated Journal |
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56 |
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Keywords |
Human Health |
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Abstract |
Sleep is essential for rest, repair, well-being, and survival of the patient. Sleep quality varies in critically ill patients and is measured by patient's satisfaction of the sleep experience, integrating aspects of sleep initiation, sleep maintenance, quantity of sleep and the refreshment upon awakening. Altered sleep is a common problem experienced by patients in critical care units. This alterations may lead to physiological and psychological dysfunctions that may affect recovery. Critically ill patients frequently experience poor sleep, characterized by frequent disruptions and loss of circadian rhythms. This study investigated factors influencing the quality of sleep among critically ill patients in hospitals in Western Kenya. A cross-sectional descriptive research design was used to examine these factors. A total of 142 patients above 18 years who were admitted to the Intensive Care Unit (ICU) and those transferred from the ICU to the general ward during the study period were conveniently selected for participation in the study. For triangulation, 10 nurses who worked in the ICU also participated in the study. A structured questionnaire was used to collect data from patients while a checklist was used to observe nursing interventions. Descriptive statistical techniques used were frequencies and percentages, while chi-square was used with the p-value set at 0.05 to test the association between factors and quality of sleep. The study results showed that frequent, nursing care activities 96.5% (n=137) noise from ventilator alarms 83.1% (n=118), feeling thirsty 57.7% (n= 82) and pain 52.8% (n=75) were among the major factors influencing the quality of sleep in ICU. A one-way analysis of variance (ANOVA) revealed patient factors significantly associated with quality sleep were age p=.006 and marital status p=.02, environmental factors significantly affecting sleep were presence of light at night with a p <0.0001 and noise from alarms p=.01. Physiological factors included feeling of thirst and hunger (p=0.03). This study recommends optimal use of analgesics and sedatives for pain management, adequate fluid replacement and hydration, noise reduction strategies, including minimizing monitor and ventilator alarms, reducing staff and telephone conversations and use of ear plugs for patients in ICU. Further, nurses should implement clustered procedures to reduce disruption of sleep among critically ill patients. |
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IDA @ intern @ |
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2974 |
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Kersavage, K.; Skinner, N.P.; Bullough, J.D.; Garvey, P.M.; Donnell, E.T.; Rea, M.S. |
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Title |
Investigation of flashing and intensity characteristics for vehicle-mounted warning beacons |
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Journal Article |
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2018 |
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Accident Analysis & Prevention |
Abbreviated Journal |
Accident Analysis & Prevention |
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119 |
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23-28 |
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Security; Public Safety; Lighting |
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Reducing the potential for crashes involving front line service workers and passing vehicles is important for increasing worker safety in work zones and similar locations. Flashing yellow warning beacons are often used to protect, delineate, and provide visual information to drivers within and approaching work zones. A nighttime field study using simulated workers, with and without reflective vests, present outside trucks was conducted to evaluate the effects of different warning beacon intensities and flash frequencies. Interactions between intensity and flash frequency were also analyzed. This study determined that intensitiesof 25/2.5 cd and 150/15 cd (peak/trough intensity) provided the farthest detection distances of the simulated worker. Mean detection distances in response to a flash frequency of 1 Hz were not statistically different from those in response to 4 Hz flashing. Simulated workers wearing reflective vests were seen the farthest distances away from the trucks for all combinations of intensity and flash frequency. |
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0001-4575 |
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GFZ @ kyba @ |
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1950 |
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Wood, J.M.; Isoardi, G.; Black, A.; Cowling, I. |
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Night-time driving visibility associated with LED streetlight dimming |
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Journal Article |
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2018 |
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Accident; Analysis and Prevention |
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Accid Anal Prev |
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121 |
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295-300 |
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Public Safety |
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New LED streetlighting designs and dimming are being introduced worldwide, however, while their cost savings are well established, their impact on driving performance has received little attention. This study investigated the effect of streetlight dimming on night-time driving performance. Participants included 14 licensed drivers (mean age 34.2 +/- 4.9 years, range 27-40 years) who drove an instrumented vehicle around a closed circuit at night. Six LED streetlights were positioned along a 250 m, straight section and their light output varied between laps (dimming levels of 25%, 50%, 75% and 100% of maximum output; L25, L50, L75 and L100 respectively; at 100% average road surface luminance of 1.14 cd/m(2)). Driving tasks involved recognition distances and reaction times to a low contrast, moving target and a pedestrian walking at the roadside. Participants drove at an average driving speed of 55 km/hr in the streetlight zone. Streetlight dimming significantly delayed driver reaction times to the moving target (F3,13.06 = 6.404; p = 0.007); with an average 0.4 s delay in reaction times under L25 compared to L100, (estimated reduction in recognition distances of 6 m). Pedestrian recognition distances were significantly shorter under dimmed streetlight levels (F3,12.75 = 8.27; p = 0.003); average pedestrian recognition distances were 15 m shorter under L25 compared to L100, and 11 m shorter under L50 compared to L100. These data suggest that streetlight dimming impacts on driver visibility but it is unclear how these differences impact on safety; future studies are required to inform decisions on safe dimming levels for road networks. |
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School of Chemistry, Physics and Mechanical Engineering, Faculty of Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia |
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0001-4575 |
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PMID:30317014 |
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GFZ @ kyba @ |
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2160 |
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Hasler, B.P. |
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Commentary on Bedroom Light Exposure at Night and the Incidence of Depressive Symptoms: A Longitudinal Study of the HEIJOKYO Cohort (Obayashi et al) |
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Journal Article |
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2018 |
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American Journal of Epidemiology |
Abbreviated Journal |
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187 |
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3 |
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435-438 |
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Commentary; Human Health |
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In modern society, we are increasingly disconnected from natural light/dark cycles and beset by round-the-clock exposure to artificial light. Light has powerful effects on physical and mental health, in part via the circadian system, and thus the timing of light exposure dictates whether it is helpful or harmful. In their compelling paper, Obayashi and colleagues offer evidence that light at night can prospectively predict an elevated incidence of depressive symptoms in older adults. Strengths of the study include the longitudinal design and direct, objective assessment of light levels, as well as accounting for multiple plausible confounders during analyses. Follow-up studies should address the study's limitations, including reliance on a global self-report of sleep quality and a two-night assessment of light exposure that may not reliably represent typical light exposure. In addition, experimental studies including physiological circadian measures will be necessary to determine if the light effects on depression are mediated through the circadian system or are so-called “direct†effects of light. In any case, these exciting findings could inform novel new approaches to preventing depressive disorders in older adults. |
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0002-9262 |
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LoNNe @ kyba @ |
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1716 |
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Obayashi, K.; Saeki, K.; Kurumatani, N. |
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Obayashi et al. Respond to “Light at Night Predicts Depression—What Next?” |
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Journal Article |
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2018 |
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American Journal of Epidemiology |
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187 |
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3 |
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439-440 |
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Commentary; Human Health |
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Our research includes some strengths and limitations. The most important strength is objective measurement of light at night (LAN) intensity using a bedside light meter. Most previous studies evaluating the association between LAN and health outcomes have assessed indoor LAN levels using a self-reported questionnaire or outdoor LAN levels using satellite data; however, self-reported indoor LAN levels has not yet been validated with objective measurement and outdoor LAN levels are surrogates for an individual LAN exposure. The second strength of our study includes its longitudinal design using multivariable methods to adjust for confounders, which indicated LAN exposure may be a cause of the incidence of depressive symptoms. Indeed, the depressive score evaluated by questionnaires may be above or below the cut-off value over the short term; therefore, a long-term study considering such unstable outcomes should be conducted. In the current study, LAN exposure was measured for only two nights; thus, an amplitude of LAN intensity has been focused. However, multiple measurements over time in the future study would allow an analysis of fluctuations in LAN exposure, which might be important for circadian physiology. |
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0002-9262 |
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LoNNe @ kyba @ |
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1717 |
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