Monday Morning Blues: The Risk of No Show for out-Patient Endoscopy by Time of Day and Day of the Week

The article presents the results of correlation analysis of the causes of road accidents in such a modern metropolis as Minsk. Has been identified the most frequent causes of road accidents, including pedestrian collisions caused by drivers, collisions at intersections, incidents at controlled and unregulated pedestrian crossings, as well as on the roadway. The dependence of transport incidents on the time of day, day of the week and month of the year was investigated. Shows the periods when road traffic incidents occur from 3.00 to 6.00 h, from 15.00 to 18.00 and from 21.00 to 24.00 on Monday, Friday and Sunday in January, March, June, September, October and November. Methods of correlation and multiple regression analysis can be the basis of preventive traffic safety management in a modern metropolis.

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Variation among Mechanical Turk Workers Across Time of Day Presents an Opportunity and a Challenge for Research

10.31234/osf.io/p8bns ◽

2019 ◽

Author(s):

Nathan Fordsham ◽

Aaron J Moss ◽

Sam Krumholtz ◽

Thomas Roggina ◽

Jonathan Robinson ◽

...

Keyword(s):

Disordered Eating ◽

Sampling Methods ◽

Time Of Day ◽

Mechanical Turk ◽

Behavioral Characteristics ◽

Online Platforms ◽

Day Of The Week ◽

Amazon's Mechanical Turk ◽

Online Sampling ◽

Anxiety Depression

Conducting behavioral research online allows researchers to gather more data in less time than conducting studies in person. But this efficiency may sometimes have a cost. Specifically, when researchers gather data within just a few hours, their study may be subject to a time of day bias. Because participants in online platforms are generally free to complete studies whenever they want, people who take studies in the morning may be different in important ways than those who take studies at night. We explored this possibility in two studies conducted on Amazon’s Mechanical Turk. In both studies, we sampled participants at different times of the day and examined whether morning and evening active people differed on a variety of psychological and behavioral characteristics known to correlate with a preference for either morningness or eveningness. We found that participants active in the morning and the evening reported different circadian typologies. Additionally, we found that participants active in the morning reported more conscientiousness and less anxiety, depression, procrastination, internet compulsion, disruptive sleep behaviors, disordered eating, and neuroticism than those sampled in the evening. Study 2 demonstrated that many signs of sub-clinical behavior were uniquely high among evening oriented people and that differences between morning and evening oriented people remained robust after controlling for local time zones and day of the week. Overall, our findings have important implications for online sampling methods and indicate that time of day differences in the composition of online samples represent both an opportunity and a challenge for research.

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Nothing good happens after dark: the influence of temporal factors on motor carrier crash severity

Journal of Transportation Management ◽

10.22237/jotm/1541030520 ◽

2018 ◽

Vol 28 (2) ◽

pp. 7-18

Author(s):

Misty Moody ◽

S Scott Nadler ◽

Doug Voss

Keyword(s):

Public Policy ◽

Time Of Day ◽

Regulatory Agencies ◽

Future Research ◽

Crash Severity ◽

Property Damage ◽

Motor Carrier ◽

Temporal Factors ◽

Safety Outcomes ◽

Day Of The Week

Motor carrier safety is a topic of great importance for both industry and makers of public policy. Regulatory agencies, such as the Federal Motor Carrier Safety Administration (FMCSA), regularly publish data detailing the circumstances surrounding roadway accidents. FMCSA’s Large Truck and Bus Crash Facts (LTBCF) data demonstrate an increase in accidents during daylight hours and on weekdays. Roadway risks are ever-present but differ by time of day and day of the week. These differences may potentially engender crashes of different severities at different times. This study analyzes FMCSA LTBCF data to determine when crashes of different severities are more likely to occur. Findings indicate that crashes resulting in property damage are more likely to occur during the day and on weekdays. However, fatal and injury crashes are significantly more likely during nights and weekends. Recommendations to improve safety outcomes are provided along with suggestions for future research.

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For Preventative Automated Driving System (PADS): Traffic Accident Context Analysis Based on Deep Neural Networks

Electronics ◽

10.3390/electronics9111829 ◽

2020 ◽

Vol 9 (11) ◽

pp. 1829

Author(s):

Minhee Kang ◽

Jaein Song ◽

Keeyeon Hwang

Keyword(s):

Traffic Accident ◽

Traffic Accidents ◽

Deep Neural Networks ◽

Time Of Day ◽

Automated Driving ◽

Context Analysis ◽

Driving System ◽

Vehicle Type ◽

Fast Development ◽

Day Of The Week

Automated Vehicles (AVs) are under development to reduce traffic accidents to a great extent. Therefore, safety will play a pivotal role to determine their social acceptability. Despite the fast development of AVs technologies, related accidents can occur even in an ideal environment. Therefore, measures to prevent traffic accidents in advance are essential. This study implemented a traffic accident context analysis based on the Deep Neural Network (DNNs) technique to design a Preventive Automated Driving System (PADS). The DNN-based analysis reveals that when a traffic accident occurs, the offender’s injury can be predicted with 85% accuracy and the victim’s case with 67%. In addition, to find out factors that decide the degree of injury to the offender and victim, a random forest analysis was implemented. The vehicle type and speed were identified as the most important factors to decide the degree of injury of the offender, while the importance for the victim is ordered by speed, time of day, vehicle type, and day of the week. The PADS proposed in this study is expected not only to contribute to improve the safety of AVs, but to prevent accidents in advance.

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Economic Value of Improving Natural Gas Supply Reliability for Residential Consumers in South Korea

Sustainability ◽

10.3390/su11020515 ◽

2019 ◽

Vol 11 (2) ◽

pp. 515 ◽

Cited By ~ 1

Author(s):

Hyo-Jin Kim ◽

Sung-Min Kim ◽

Seung-Hoon Yoo

Keyword(s):

Natural Gas ◽

Economic Value ◽

Time Of Day ◽

Economic Damage ◽

South Korean Government ◽

South Korean ◽

Day Of The Week ◽

Gas Supply ◽

Supply Reliability ◽

Residential Consumers

An interruption to residential natural gas (NG) may cause considerable economic damage of the entire country. Thus, the South Korean government requires information about the economic value of improving residential NG supply reliability for planning NG supply. This article aims to measure the value using a specific case of South Korean residential consumers. The choice experiment (CE) approach was adopted for this purpose. The selected four attributes are the duration of interruption, the season of interruption, the time of day, and the day of the week. The value trade-off works among the four attributes and price attribute were sought and completed in a nationwide CE survey of 1000 households. The respondents revealed statistically significant willingness to pay for a decrease in the duration of interruption, avoiding interruption during winter rather than non-winter, and preventing interruption during off-daytime (18:00 to 09:00) rather than daytime (09:00 to 18:00). For example, they accepted a 0.10% increase in the residential NG bill for a one-minute reduction in interruption during NG supply interruption, a 5.16% increase in residential NG bill for avoiding interruption during winter rather than non-winter, and a 2.94% increase in residential NG bill for preventing interruption during off-daytime rather than daytime. However, they placed no importance on the day of the week. These results can be useful for policy-making and decision-making to improve residential NG supply reliability. It is necessary to conduct a study at regular intervals on the value of NG supply reliability because regarding NG supply reliability, it is difficult to maintain a specific value.

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Accelerometer-Measured Diurnal Patterns of Sedentary Behavior among Japanese Workers: A Descriptive Epidemiological Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17113814 ◽

2020 ◽

Vol 17 (11) ◽

pp. 3814

Author(s):

Sayaka Kurosawa ◽

Ai Shibata ◽

Kaori Ishii ◽

Mohammad Javad Koohsari ◽

Koichiro Oka

Keyword(s):

Sedentary Behavior ◽

Multivariate Regression ◽

Sedentary Time ◽

Time Of Day ◽

Work Related ◽

Diurnal Patterns ◽

Time Period ◽

Japanese Workers ◽

Sociodemographic Correlates ◽

Day Of The Week

Increased sedentary behavior (SB) can adversely affect health. Understanding time-dependent patterns of SB and its correlates can inform targeted approaches for prevention. This study examined diurnal patterns of SB and its sociodemographic associations among Japanese workers. The proportion of sedentary time (% of wear time) and the number of breaks in SB (times/sedentary hour) of 405 workers (aged 40–64 years) were assessed using an accelerometer. SB patterns and sociodemographic associations between each time period (morning, afternoon, evening) on workdays and nonworkdays were examined in a series of multivariate regression analyses, adjusting for other sociodemographic associations. On both workdays and nonworkdays, the proportion of sedentary time was lowest in the morning and increased towards evening (b = 12.95, 95% CI: 11.28 to 14.62; b = 14.31, 95% CI: 12.73 to 15.88), with opposite trend for breaks. Being male was consistently correlated with SB. Other sociodemographic correlates differed depending on time-of-day and day-of-the-week. For instance, desk-based workstyles and urban residential area were associated with SB during workday mornings and afternoons, being single was related to mornings and evenings, workdays and nonworkdays. Initiatives to address SB should focus not only on work-related but time-of-day contexts, especially for at-risk subgroups during each period.

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Utilization of Warning Lights and Siren Based on Hospital Time-Critical Interventions

Prehospital and Disaster Medicine ◽

10.1017/s1049023x0000830x ◽

2010 ◽

Vol 25 (4) ◽

pp. 335-339 ◽

Cited By ~ 18

Author(s):

Andreia Marques-Baptista ◽

Pamela Ohman-Strickland ◽

Kimberly T. Baldino ◽

Michael Prasto ◽

Mark A. Merlin

Keyword(s):

Life Support ◽

Advanced Life Support ◽

Time Of Day ◽

Average Difference ◽

Transport Time ◽

Day Of The Week ◽

Medical Transport ◽

Critical Patients ◽

Time Critical ◽

Warning Lights

AbstractObjective:The objective of this study was to evaluate the time saved by usage of lights and siren (L&S) during emergency medical transport and measure the total number of time-critical hospital interventions gained by this time difference.Methods:A retrospective study was performed of all advanced life support (ALS) transports using lights and siren to this university emergency department during a three-week period. Consecutive times were measured for 112 transports and compared with measured transport times for a personal vehicle traveling the same day of the week and time of day without lights and siren. The time-critical hospital interventions are defined as procedures or treatments that could not be performed in the prehospital setting requiring a physician. The project assessed whether the patients received the hospital interventions within the average time saved using lights and siren transport.Results:The average difference in time with versus without L&S was -2.62 minutes (95% CI: -2.60− -2.63, paired t-test p <0.0001). The average transport time with L&S was 14.5 ±7.9 minutes (min) (1 standard deviation/minute (min), range = 1–36 min.). The average transport time without L&S was 17.1 ±8.3 min (range = 1−40 min). Of the 112 charts evaluated, five patients (4.5%) received time-critical hospital interventions. No patients received time-critical interventions within the time saved by utilizing lights and siren. Longer distances did not result in time saved with lights and siren.Conclusions:Limiting lights and siren use to the patients requiring hospital interventions will decrease the risks of injury and death, while adding the benefit of time saved in these critical patients.

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Analysing the daily, weekly and yearly cycles of births and their implications for the NHS using linked data

International Journal for Population Data Science ◽

10.23889/ijpds.v1i1.298 ◽

2017 ◽

Vol 1 (1) ◽

Author(s):

Gill Harper ◽

Alison MacFarlane ◽

Nirupa Dattani ◽

Miranda Dodwell ◽

Rod Gibson ◽

...

Keyword(s):

Gestational Age ◽

Hospital Admissions ◽

Time Of Day ◽

Birth Registration ◽

Hospital Discharges ◽

Discharge Data ◽

England And Wales ◽

Mortality And Morbidity ◽

Linkage Quality ◽

Day Of The Week

ABSTRACT ObjectivesThis project builds on previous work linking routinely collected data from birth registration, birth notification, death registration and hospital discharges, extending it to six million births in England and Wales from 2005 to 2014. This linkage is creating a new dataset to investigate previously unanswerable questions about variations in time of birth and its outcome which are highly contested in the health service in England and Wales: 1. How do numbers of births vary according to time of day, day of the week and time of year of birth and how does this relate to modes of onset of labour and delivery?2. How do patterns of birth vary between maternity services in relation to variations in medical and midwifery staffing, patterns of intervention and size of unit?3. How does the outcome of pregnancy, in terms of mortality and morbidity rates at birth and in the first year of life, vary according to time of birth in relation to gestational age, and intervention in the onset of labour and delivery?4. Have the patterns changed over the years 2005 to 2014? ApproachRoutinely collected national datasets for 2005-14 have been linked using patient identifiable data items. They differ in the way data items are recorded. Methods of linkage, quality assurance and data cleaning have been improved, compared with those developed in the original project. This unique approach links clinical data from hospital admissions with more reliable data on birthweight from birth registration and with gestational age and time of birth from birth notification. This enables investigation of the associations between day and time of birth with its outcome. This is also the first study to link mothers’ and babies’ hospital discharge data for England and Wales and to draw on public and patient involvement to include outcome measures specifically designed to be women-centred. Overall, the linkage has created a fuller range of data. ResultsResults will be available by the time of the conference. Initial results already clearly illustrate differences in timings of birth by time of day and day of the week by mothers’ age, gestational age and birth setting and for singleton and multiple births. ConclusionThe study has created a valuable linked dataset that will uniquely enable analyses of associations between timing of birth and its outcome. These results will potentially be able to inform and impact NHS service provision.

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Personalized Behavior Prediction: An Idiographic Person-Situation Test

10.31234/osf.io/syhw5 ◽

2021 ◽

Author(s):

Emorie D Beck ◽

Joshua James Jackson

Keyword(s):

Prediction Accuracy ◽

Time Of Day ◽

Learning Approaches ◽

Behavior Prediction ◽

Affective States ◽

Intensive Longitudinal Data ◽

Psychological Phenomena ◽

Diurnal Cycles ◽

Future Behavior ◽

Day Of The Week

A longstanding goal of psychology is to predict the things people do, but tools to accurately predict future behaviors remain elusive. In the present study, we used intensive longitudinal data (N = 104; total assessments = 5,971) and three machine learning approaches to investigate the degree to which two behaviors – loneliness and procrastination – could be predicted from past psychological (i.e. personality and affective states), situational (i.e. objective situations and psychological situation cues), and time (i.e. trends, diurnal cycles, time of day, and day of the week) phenomena from an idiographic, person-specific perspective. Rather than pitting persons against situations, such an approach allows psychological phenomena, situations, and time to jointly predict future behavior. We find (1) a striking degree of prediction accuracy across participants, (2) that a majority of participants’ future behaviors are predicted by both person and situation features, and (3) that the most important features vary greatly across people.

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Temporal changes in anthropogenic seismic noise levels associated with economic and leisure activities during the COVID-19 pandemic

Scientific Reports ◽

10.1038/s41598-021-00063-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hiro Nimiya ◽

Tatsunori Ikeda ◽

Takeshi Tsuji

Keyword(s):

Seismic Noise ◽

Ambient Noise ◽

Anthropogenic Activities ◽

Leisure Activities ◽

Time Of Day ◽

Noise Levels ◽

Economic Activities ◽

State Of Emergency ◽

Tokyo Metropolitan Area ◽

Day Of The Week

AbstractSeismic ambient noise with frequencies > 1 Hz includes noise related to human activities. A reduction in seismic noise during the COVID-19 pandemic has been observed worldwide, as restrictions were imposed to control outbreaks of the SARS-CoV-2 virus. In this context, we studied the effect of changes in anthropogenic activities during COVID-19 on the seismic noise levels in the Tokyo metropolitan area, Japan, considering time of day, day of the week, and seasonal changes. The results showed the largest reduction in noise levels during the first state of emergency under most conditions. After the first state of emergency was lifted, the daytime noise reverted to previous levels immediately on weekdays and gradually on Sundays. This was likely because economic activities instantly resumed, while non-essential outings on Sundays were still mostly avoided. Furthermore, the daytime noise level on Sundays was strongly reduced regardless of changes on weekdays after the second state of emergency, which restricted activities mainly at night. Sunday noise levels gradually increased from the middle of the second state of emergency, suggesting a gradual reduction in public concern about COVID-19 following a decrease in the number of infections. Our findings demonstrate that seismic noise can be used to monitor social activities.

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