How is Daylight Saving Time still a thing?: Disruptions from Daylight Saving Time transitions lead to cognitive performance deficits

Visual search, looking for targets among distractors, underlies many critical professions and must often be performed optimally regardless of the time of day, week, or year. However, external events can disrupt the ability to perform. The current study examined one such specific event: Daylight Saving Time (DST) transitions—when the clock shifts forward or backward by one hour. Performance on a visual search task was assessed using “big data” from the mobile app Airport Scanner (Kedlin Co.), wherein players serve as airport security screeners searching for prohibited items among allowed items. Performance was compared between individuals who played a specific level during the week leading up to a DST transition (pre-DST transition) and those who played that same level during the week following a transition (post-DST transition). Analyses of data gathered over seven years revealed that, relative to the pre-DST group, the post- DST group was significantly slower, less likely to complete the level, more likely to fail due to running out of time, and had more false alarms. A control set of data (between individuals who played the level before or after a Sunday without a DST transition) revealed no significant differences. These results suggest that even minor, one-hour time shifts can create problems as they can adversely affect cognitive functioning; when an entire workforce simultaneously undergoes a sudden time shift (e.g., a DST transition), problems can potentially be exacerbated for the broader society. The current study lends support for existing efforts to end the archaic practice of DST.

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Predicting Airport Screening Officers’ Visual Search Competency With a Rapid Assessment

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/0018720817743886 ◽

2017 ◽

Vol 60 (2) ◽

pp. 201-211 ◽

Cited By ~ 4

Author(s):

Stephen R. Mitroff ◽

Justin M. Ericson ◽

Benjamin Sharpe

Keyword(s):

Visual Search ◽

Job Performance ◽

Assessment Tool ◽

Rapid Assessment ◽

Aviation Security ◽

Mobile App ◽

Airport Security ◽

Search Performance ◽

Critical Question ◽

X Ray

Objective The study’s objective was to assess a new personnel selection and assessment tool for aviation security screeners. A mobile app was modified to create a tool, and the question was whether it could predict professional screeners’ on-job performance. Background A variety of professions (airport security, radiology, the military, etc.) rely on visual search performance—being able to detect targets. Given the importance of such professions, it is necessary to maximize performance, and one means to do so is to select individuals who excel at visual search. A critical question is whether it is possible to predict search competency within a professional search environment. Method Professional searchers from the USA Transportation Security Administration (TSA) completed a rapid assessment on a tablet-based X-ray simulator (XRAY Screener, derived from the mobile technology app Airport Scanner; Kedlin Company). The assessment contained 72 trials that were simulated X-ray images of bags. Participants searched for prohibited items and tapped on them with their finger. Results Performance on the assessment significantly related to on-job performance measures for the TSA officers such that those who were better XRAY Screener performers were both more accurate and faster at the actual airport checkpoint. Conclusion XRAY Screener successfully predicted on-job performance for professional aviation security officers. While questions remain about the underlying cognitive mechanisms, this quick assessment was found to significantly predict on-job success for a task that relies on visual search performance. Application It may be possible to quickly assess an individual’s visual search competency, which could help organizations select new hires and assess their current workforce.

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Long-Term Visual Search

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931213601364 ◽

2016 ◽

Vol 60 (1) ◽

pp. 1579-1579

Author(s):

Justin M. Ericson ◽

Stephen R. Mitroff ◽

Ben Sharpe

Keyword(s):

Visual Search ◽

Response Time ◽

Cognitive Task ◽

Mobile App ◽

Learning Curves ◽

Airport Security ◽

Peak Performance ◽

Search Performance ◽

Critical Question

Most professional visual searchers (e.g., radiologists, baggage screeners) face an interesting conundrum—they must be highly accurate while also performing in a timely fashion. Airport security personnel, for example, are tasked with preventing any and all dangerous items from getting aboard a plane, but they must also be speedy to keep the passengers flowing through the checkpoint. It is not easy to simultaneously prioritize two primary job requirements (accuracy and speed) that are in direct contrast to one another. While a certain level of error is inevitable in almost any cognitive task, it is arguable that many professional search environments might be even more vulnerable to error given the contradictory goals imposed upon the searchers. As such, it is critical to explore every means possible to minimize mistakes. One critical question when exploring means to improve search performance in professional settings is how do professional searchers develop the ability to search for, and steadily learn to reliably detect, targets. How do searchers improve their search efficacy over the course of repeatedly discovering an item (or by receiving feedback when missing it)? This process of iterative learning across exposures to targets is referred to here as “long-term visual search” (LTVS). To investigate LTVS the current study utilized “big data” from the mobile app Airport Scanner (Kedlin Co.; see Mitroff et al., 2015) to assess search ability improvements. Airport Scanner is a publicly available mobile app, where the users serve as airport security officers looking for prohibited items in simulated X-ray baggage images. Over 10 million users have downloaded the app, creating over 2.6 billion trials of data (see Mitroff et al., 2015). Airport Scanner contains hundreds of different targets—granting the possibility to look at how search performance develops, both generally and item-by-item, across a large number of target types and with immense power. To effectively measure search improvement, only Airport Scanner users with a minimum of 250 target-present trials were included in this study. The first analysis collapsed performance across 26 distinct targets that varied in salience, frequency, and when they were introduced into gameplay. Despite variability, uniform patterns to overall search improvement were found—detection rate and response speed both revealed steep learning curves followed by a uniform plateau in performance. Second, performance assessments were conducted individually on the 26 target items. Specifically, accuracy and response time values were standardized (z-scored) to place items on a level-playing field despite differences in target characteristics (e.g., salience, frequency). There was variability in improvement and peak performance for search accuracy across targets, but very little variability in response time performance. While individual target types led to an array of required target observations to obtain mean accuracy (i.e., reach plateau), there was general uniformity for response time with most items taking approximately 14 target-present trials to reach mean proficiency in search speed. Understanding the development of LTVS is critical for reducing errors in professional visual searches, and the current study demonstrated the iterative nature of learning, providing potential insights for improving training procedures.

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0201 Medical Malpractice Payments Following Mild Sleep Loss and the Daylight Saving Time Shift

SLEEP ◽

10.1093/sleep/zsaa056.199 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A79-A79

Author(s):

C Lage ◽

C Gao ◽

M K Scullin

Keyword(s):

Medical Errors ◽

Medical Error ◽

Emotional Regulation ◽

Medical Malpractice ◽

Emotional Reactions ◽

Medical Liability ◽

Time Shift ◽

Daylight Saving Time ◽

Daylight Saving ◽

Malpractice Claims

Abstract Introduction The national cost of the medical liability system exceeds $10 billion/year, but not all medical errors result in a malpractice claim or payment. Malpractice claims are more likely if the medical error is perceived as severe, if the physician is perceived as lacking empathy, and if negative emotional reactions are triggered in the patient (due to individual or contextual factors). In recent experimental work, participants who were mildly sleep restricted showed an increased propensity to want to punish physicians for medical errors and compensate patients the maximum allowed. Building upon this laboratory work, we evaluated 30 years of medical malpractice claims to determine whether the judgment of final compensation increased after the Spring daylight saving time (DST) shift. Methods We obtained medical malpractice payment data on 373,643 United States cases from the National Practitioner Data Bank (NPDB). We contrasted inflation-adjusted payments across states that have DST shifts relative to non-DST control states (e.g., Arizona, Hawaii). We compared post-Spring DST payments to payments during the two weeks before/after the DST, and averaged payments for the remainder of the year. Results The total number of claims was unrelated to Spring DST, however, the size of malpractice payments significantly increased the week following the spring DST shift relative to non-DST control states and relative to the averaged payments for the remainder of the year. Spring DST was associated with an inflation-adjusted relative increase in malpractice payments by $7,836 to $61,809 per case (depending on comparison). Malpractice payments did not change in relation to the Fall DST shift. Conclusion Mild sleep restriction alters the cognitive and emotional regulation processes that underpin perceptions of medical error severity, willingness to punish, and judgments of appropriate compensation for medical errors. Support N/A

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Measurable health effects associated with the daylight saving time shift

PLoS Computational Biology ◽

10.1371/journal.pcbi.1007927 ◽

2020 ◽

Vol 16 (6) ◽

pp. e1007927 ◽

Cited By ~ 2

Author(s):

Hanxin Zhang ◽

Torsten Dahlén ◽

Atif Khan ◽

Gustaf Edgren ◽

Andrey Rzhetsky

Keyword(s):

Health Effects ◽

Time Shift ◽

Daylight Saving Time ◽

Daylight Saving

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Transitions in daylight saving time negatively affect visual search performance

Journal of Vision ◽

10.1167/jov.21.9.2750 ◽

2021 ◽

Vol 21 (9) ◽

pp. 2750

Author(s):

Samoni Nag ◽

Alfred Yu ◽

Stephen Mitroff

Keyword(s):

Visual Search ◽

Search Performance ◽

Daylight Saving Time ◽

Daylight Saving

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Impact of DST (Daylight Saving Time) on Major Trauma: A European Cohort Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182413322 ◽

2021 ◽

Vol 18 (24) ◽

pp. 13322

Author(s):

André Nohl ◽

Christine Seelmann ◽

Robert Roenick ◽

Tobias Ohmann ◽

Rolf Lefering ◽

...

Keyword(s):

Major Trauma ◽

Weather Conditions ◽

Time Of Day ◽

Daylight Saving Time ◽

Daylight Saving ◽

Before And After ◽

Multi Center Study ◽

Injured Patients ◽

Policy Setting ◽

Center Study

(1) Background: Approximately 73 countries worldwide implemented a daylight saving time (DST) policy: setting their clocks forward in spring and back in fall. The main purpose of this practice is to save electricity. The aim of the present study was to find out how DST affects the incidence and impact of seriously injured patients. (2) Methods: In a retrospective, multi-center study, we used the data recorded in the TraumaRegister DGU® (TR-DGU) between 2003 and 2017 from Germany, Switzerland, and Austria. We compared the included cases 1 week before and after DST. (3) Results: After DST from standard time to summertime, we found an increased incidence of accidents of motorcyclists up to 51.58%. The result is consistent with other studies. (4) Conclusion: However, our results should be interpreted as a tendency. Other influencing factors, such as time of day and weather conditions, were not considered.

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