Research delves into link between test anxiety and poor sleep

UNIVERSITY OF KANSAS

Research News

LAWRENCE -- College students across the country struggle with a vicious cycle: Test anxiety triggers poor sleep, which in turn reduces performance on the tests that caused the anxiety in the first place.

New research from the University of Kansas just published in the International Journal of Behavioral Medicine is shedding light on this biopsychosocial process that can lead to poor grades, withdrawal from classes and even students who drop out. Indeed, about 40% of freshman don't return to their universities for a second year in the United States.

"We were interested in finding out what predicted students' performance in statistics classes -- stats classes are usually the most dreaded undergrad class," said lead author Nancy Hamilton, professor of psychology at KU. "It can be a particular problem that can be a sticking point for a lot of students. I'm interested in sleep, and sleep and anxiety are related. So, we wanted to find out what the relationship was between sleep, anxiety and test performance to find the correlation and how it unfolds over time."

Hamilton and graduate student co-authors Ronald Freche and Ian Carroll and undergraduates Yichi Zhang and Gabriella Zeller surveyed the sleep quality, anxiety levels and test scores for 167 students enrolled in a statistics class at KU. Participants completed an electronic battery of measures and filled out Sleep Mood Study Diaries during the mornings in the days before a statistics exam. Instructors confirmed exam scores. The study showed "sleep and anxiety feed one another" and can hurt academic performance predictably.

"We looked at test anxiety to determine whether that did predict who passed, and it was a predictor," Hamilton said. "It was a predictor even after controlling for students' past performance and increased the likelihood of students failing in class. When you look at students who are especially anxious, it was almost a five-point difference in their score over students who had average levels of anxiety. This is not small potatoes. It's the difference between a C-minus abd a D. It's the difference between a B-plus and an A-minus. It's real."

Beyond falling grades, a student's overall health could suffer when test anxiety and poor sleep reinforce each other.

"Studies have shown students tend to cope with anxiety through health behaviors," Hamilton said. "Students may use more caffeine to combat sleep problems associated with anxiety, and caffeine can actually enhance sleep problems, specifically if you're using caffeine in the afternoon or in the evening. Students sometimes self-medicate for anxiety by using alcohol or other sedating drugs. Those are things that we know are related."

Hamilton said universities could do more to communicate to students the prevalence of test anxiety and provide them with resources.

"What would be really helpful for a university to do is to talk about testing anxiety and to talk about the fact that it's very common and that there are things that can be done for students who have test anxiety," she said. "A university can also talk to instructors about doing things that they can do to help minimize the effect of testing anxiety."

According to Hamilton, instructors are hindered by the phenomenon as well: Anxiety and associated sleep problems actually distort instructors' ability to measure student knowledge in a given subject.

"As an instructor, my goal when I'm writing a test is to assess how much a student understands," she said. "So having a psychological or an emotional problem gets in the way of that. It actually impedes my ability to effectively assess learning. It's noise. It's unrelated to what they understand and what they know. So, I think it behooves all of us to see if we can figure out ways to help students minimize the effects of anxiety on their performance."

The KU researcher said testing itself isn't the problem and suggested an increase in regular tests might reduce anxiety through regular exposure. However, she said a few small changes to how tests are administered also could calm student anxiety.

"In classes that use performance-based measures like math or statistics, classes that tend to really induce a lot of anxiety for some students, encouraging those students to take five minutes right before an exam to physically write about what they're anxious about can help -- that's cheap, that's easy," Hamilton said. "Also, eliminating a time limit on a test can help. There's just really nothing to be gained by telling students, 'You have an hour to complete a test and what you don't get done you just don't get done.' That's really not assessing what a student can do -- it's only assessing what a student can do quickly."

Hamilton said going forward she'd like research into the link between test anxiety and poor sleep broadened to include a more diverse group of students and also to include its influence on remote learning.

"The students in this study were mostly middle-class, Caucasian students," she said. "So, I hesitate to say these results would generalize necessarily to universities that have a more heterogeneous student body. I also would hesitate to say how this would generalize into our current Zoom environment. I don't know how that shakes out because the demands of doing exams online are likely to be very different."

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Research gives trees an edge in landfill clean-up

USDA FOREST SERVICE - NORTHERN RESEARCH STATION

Research News

 

IMAGE: A RESEARCH TEAM FROM THE USDA FOREST SERVICE AND THE UNIVERSITY OF MISSOURI HAS DEVELOPED A NEW CONTAMINANT PRIORITIZATION TOOL THAT HAS THE POTENTIAL TO INCREASE THE EFFECTIVENESS OF ENVIRONMENTAL... view more 

CREDIT: PAUL MANLEY, MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY; USED WITH PERMISSION

Rhinelander, Wis., April 28, 2021-- A research team from the USDA Forest Service and the University of Missouri has developed a new contaminant prioritization tool that has the potential to increase the effectiveness of environmental approaches to landfill clean-up.

Phytoremediation - an environmental approach in which trees and other plants are used to control leachate and treat polluted water and soil - hinges on matching the capability of different tree species with the types of contaminants present in soil and water. Identifying the worst contaminants within the dynamic conditions of a landfill has been challenging.

"Thousands of contaminants can be present in landfill leachate, and contamination can vary by location and over time, so it can be difficult to determine what needs to be, or even can be targeted with environmental remediation," said Elizabeth Rogers, a USDA Forest Service Pathways intern and the lead author of the study. "This tool allows site managers to prioritize the most hazardous contaminants or customize the tool to address local concerns."

Rogers and co-authors Ron Zalesny, Jr., a supervisory research plant geneticist with the Northern Research Station, and Chung-Ho Lin, a Research Associate Professor at the University of Missouri's Center for Agroforestry, combined multiple sources of data to develop a pollutant prioritization tool that systematically prioritizes contaminants according to reported toxicity values. The study, "A systematic approach for prioritizing landfill pollutants based on toxicity: Applications and opportunities," is available through the Northern Research Station at: https://www.nrs.fs.fed.us/pubs/62410

Knowing which contaminants are the most hazardous allows scientists like Zalesny to better match trees and tree placement in landfills. "Phytoremediation research has focused on discovering which trees work best in particular soils and sites," Zalesny said. "The ability to home in on specific contaminants will enhance phytoremediation outcomes."

The pollutant prioritization tool allows for greater transparency on the benefits of phytoremediation. "When you know what you are targeting, you can provide better information to your community on how long remediation will take and how effective it is," Lin said.

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Business school research is broken - here's how to fix it

News from the Journal of Marketing

AMERICAN MARKETING ASSOCIATION

Research News

 

Researchers from Erasmus School of Economics, IESE Business School, and New York University published a new paper in the Journal of Marketing that examines what business schools do wrong when conducting academic research and what changes they can make so that research contributes to improving society.

The study, forthcoming in the Journal of Marketing, is titled "Faculty Research Incentives and Business School Health: A New Perspective from and for Marketing" and is authored by Stefan Stremersch, Russell Winer, and Nuno Camacho.

In February 2020, an article in the Financial Times stated that business schools' research model is "ill," with faculty increasingly focusing on "abstract, abstruse and overly academic topics with little resonance beyond the higher education sector."

The researchers demonstrate that business schools use the wrong research metrics and incentives with research faculty. As Stremersch explains, "We show that business schools focus excessively on the quantity of research and insufficiently on other critical aspects such as the quality, rigor, relevance, and creativity of such research." To gauge whether research incentives in business schools are indeed badly designed, they surveyed 234 marketing professors in business schools across 20 countries and completed 22 interviews with 14 (associate) deans and eight external institution stakeholders.

Results show that business schools' research incentives are badly designed for three main reasons. First, business schools use the wrong research metrics to monitor their faculty's research, often harming the quality (rigor and relevance) of the research produced by their research faculty. Second, research with lower-than-desired practical importance may hurt teaching quality, which negatively impacts business school health. Third, while research faculty feel undercompensated for the research they do, (associate) deans feel that the current compensation levels for faculty are not sustainable.

The researchers assert that business schools need to recalibrate their faculty research incentives. To do so, business schools can start with three concrete actions. First, business schools need to develop better research metrics. "Schools need to reduce the weight they place in low-effort metrics (such as the mere number of publications or citations) and increase the weight they place in effortful metrics such as awards, research creativity, literacy, and relevance to non-academic audiences," says Winer.

Second, business schools need to develop a high commitment working environment where research faculty internalize and actively contribute to the health of the business school. Such high commitment environments should improve alignment between schools and their research faculty in terms of compensation.

Third, business schools need to improve the practical importance of their faculty's research. Several (associate) deans at top business schools whom the researchers interviewed report that the business schools they lead have made more progress on rigor than on practical importance and that they are concerned about a further decline in such practical importance in recent years.

In sum, business schools need to revise their faculty research incentives to ensure their faculty produce research that lives up to society's expectations and improves managers and firms' decision making.

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Full article and author contact information available at: https://doi.org/10.1177/00222429211001050

Driving behaviors harbor early signals of dementia

Researchers develop highly accurate algorithms for early detection of mild cognitive impairment and dementia using naturalistic driving data

COLUMBIA UNIVERSITY'S MAILMAN SCHOOL OF PUBLIC HEALTH

Research News

April 28, 2021 -- Using naturalistic driving data and machine learning techniques, researchers at Columbia University Mailman School of Public Health and Columbia's Fu Foundation School of Engineering and Applied Science have developed highly accurate algorithms for detecting mild cognitive impairment and dementia in older drivers. Naturalistic driving data refer to data captured through in-vehicle recording devices or other technologies in the real-world setting. These data could be processed to measure driving exposure, space and performance in great detail. The findings are published in the journal Geriatrics.

The researchers developed random forests models, a statistical technique widely used in AI for classifying disease status, that performed exceptionally well. "Based on variables derived from the naturalistic driving data and basic demographic characteristics, such as age, sex, race/ethnicity and education level, we could predict mild cognitive impairment and dementia with 88 percent accuracy, "said Sharon Di, associate professor of civil engineering and engineering mechanics at Columbia Engineering and the study's lead author.

The investigators constructed 29 variables using the naturalistic driving data captured by in-vehicle recording devices from 2977 participants of the Longitudinal Research on Aging Drivers (LongROAD) project, a multisite cohort study sponsored by the AAA Foundation for Traffic Safety. At the time of enrollment, the participants were active drivers aged 65-79 years and had no significant cognitive impairment and degenerative medical conditions. Data used in this study spanned the time period from August 2015 through March 2019.

Among the 2977 participants whose cars were instrumented with the in-vehicle recording devices, 33 were newly diagnosed with mild cognitive impairment and 31 with dementia by April 2019. The researchers trained a series of machine learning models for detecting mild cognitive impairment/dementia and found that the model based on driving variables and demographic characteristics was 88 percent accurate, much better than models based on demographic characteristics only (29 percent) and driving variables only (66 percent). Further analysis revealed that age was most predictive of mild cognitive impairment and dementia, followed by the percentage of trips traveled within 15 miles of home, race/ethnicity, minutes per trip chain (i.e., length of trips starting and ending at home), minutes per trip, and number of hard braking events with deceleration rates ≥ 0.35 g.

"Driving is a complex task involving dynamic cognitive processes and requiring essential cognitive functions and perceptual motor skills. Our study indicates that naturalistic driving behaviors can be used as comprehensive and reliable markers for mild cognitive impairment and dementia," said Guohua Li, MD, DrPH, professor of epidemiology and anesthesiology at Columbia Mailman School of Public Health and Vagelos College of Physicians and Surgeons, and senior author. "If validated, the algorithms developed in this study could provide a novel, unobtrusive screening tool for early detection and management of mild cognitive impairment and dementia in older drivers."

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Co-authors are Carolyn DiGuiseppi, Colorado School of Public Health; David W. Eby and Lisa Molnar, University of Michigan Transportation Research Institute; Linda Hill, University of California San Diego School of Public Health; Thelma J. Mielenz, Columbia Mailman School of Public Health; David Strogatz, Bassett Research Institute; Howard Andrews, Terry Goldberg, Barbara Lang, and Minjae Kim, Columbia Vagelos College of Physicians and Surgeons.

The study was supported by the AAA Foundation for Traffic Safety.

Columbia University Mailman School of Public Health

Founded in 1922, the Columbia University Mailman School of Public Health pursues an agenda of research, education, and service to address the critical and complex public health issues affecting New Yorkers, the nation and the world. The Columbia Mailman School is the seventh largest recipient of NIH grants among schools of public health. Its nearly 300 multi-disciplinary faculty members work in more than 100 countries around the world, addressing such issues as preventing infectious and chronic diseases, environmental health, maternal and child health, health policy, climate change and health, and public health preparedness. It is a leader in public health education with more than 1,300 graduate students from 55 nations pursuing a variety of master's and doctoral degree programs. The Columbia Mailman School is also home to numerous world-renowned research centers, including ICAP and the Center for Infection and Immunity. For more information, please visit http://www.mailman.columbia.edu.

Columbia Engineering, based in New York City, is one of the top engineering schools in the U.S. and one of the oldest in the nation. Also known as The Fu Foundation School of Engineering and Applied Science, the School expands knowledge and advances technology through the pioneering research of its more than 220 faculty, while educating undergraduate and graduate students in a collaborative environment to become leaders informed by a firm foundation in engineering. The School's faculty are at the center of the University's cross-disciplinary research, contributing to the Data Science Institute, Earth Institute, Zuckerman Mind Brain Behavior Institute, Precision Medicine Initiative, and the Columbia Nano Initiative. Guided by its strategic vision, "Columbia Engineering for Humanity," the School aims to translate ideas into innovations that foster a sustainable, healthy, secure, connected, and creative humanity.

 

Study finds people of color more likely to participate in cancer clinical trials

Findings counter belief that minorities are less like to participate in health research

UNIVERSITY OF MISSOURI-COLUMBIA

Research New

   

People of color, those with a higher income and younger individuals are more likely to participate in clinical trials during their cancer treatment according to a new study from the University of Missouri School of Medicine.

Clinical trials are research studies that involve people who volunteer to take part in tests of new drugs, current approved drugs for a new purpose or medical devices.

The study analyzed data collected from the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System Survey, which is an annual national telephone survey designed to collect health-related data from U.S. adults. Survey years selected included the question, "Did you participate in a clinical trial as part of your cancer treatment?" The analysis of 20,053 respondents revealed an average overall clinical trial participation rate of 6.51%. Among 17,600 white respondents, participation was 6.24%; among 445 Hispanic respondents, participation was 11%; and among 943 Black respondents, participation was 8.27%.

"This study informs our understanding of who is participating in cancer clinical trials," said Lincoln Sheets, MD, PhD, assistant research professor at the MU School of Medicine. "We found people of color were more likely to participate in cancer clinical trials than white cancer patients when controlling for other demographic factors. It could be that in previous studies, the effects of income, sex or age were muddling the true picture."

Sheets said the analysis also indicated people who earn more than the national median household income of $50,000 annually and the young were more likely to participate in clinical trials during cancer treatment.

"Taken in total, the results of this study help confirm that there are sociodemographic disparities in cancer clinical trials, indicating there are deficiencies in the system as it stands now," Sheets said. "We must lessen financial barriers to participation, improve logistical accessibility of cancer clinical trials and loosen restrictions on the enrollment of patients with comorbidities."

Sheets said improving access to transportation, childcare and health insurance would remove some of the structural and logistical barriers that prevent people from participating in cancer clinical trials.

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Sheets collaborated on the study with MU School of Medicine student Shelby Meyer.

Their study, "Sociodemographic diversity in cancer clinical trials: New findings on the effect of race and ethnicity," was published by the journal Contemporary Clinical Trials Communications. The authors of the study declare that they have no conflicts of interest.

 NEWS RELEASE 28-APR-2021

El Niño can help predict cacao harvests up to 2 years in advance

Long-term weather data is absent in many places, complicating rain predictions for crops. Researchers found that the El Niño climate cycle can be a reliable substitute for weather data

THE ALLIANCE OF BIOVERSITY INTERNATIONAL AND THE INTERNATIONAL CENTER FOR TROPICAL AGRICULTURE

Research News

 

IMAGE: A WOMAN INSPECTS HARVESTED CACAO BEANS DRYING IN THE SUN IN SOPPENG, SOUTH SULAWESI, INDONESIA. view more 

CREDIT: COCOA CARE AND T. OBERTHU?R

When seasonal rains arrive late in Indonesia, farmers often take it as a sign that it is not worth investing in fertilizer for their crops. Sometimes they opt out of planting annual crops altogether. Generally, they're making the right decision, as a late start to the rainy season is usually associated with the state of El Niño Southern Oscillation (ENSO) and low rainfall in the coming months.

New research published in the Nature journal Scientific Reports shows that ENSO, the weather-shaping cycle of warming and cooling of the Pacific Ocean along the Equator, is a strong predictor of cacao harvests up to two years before a harvest.

This is potentially very good news for smallholder farmers, scientists, and the global chocolate industry. The ability to predict harvest sizes well in advance could shape on-farm investment decisions, improve tropical crop research programs, and reduce risk and uncertainty in the chocolate industry.

Researchers say that the same methods - which pair advanced machine learning with rigorous, short-term data collection on farmer practices and yields - can apply to other rain-dependent crops including coffee and olives.

"The key innovation in this research is that you can effectively substitute weather data with ENSO data," said Thomas Oberthür, a co-author and business developer at the African Plant Nutrition Institute (APNI) in Morocco. "Any crop that shares a production relationship with ENSO can be explored using this method."

About 80 percent of global cropland depends on direct rainfall (as opposed to irrigation), accounting for almost 60 percent of production. But rainfall data is sparse and highly variable in many of these regions, making it difficult for scientists, policymakers and farmers groups to adapt to the vagaries of the weather.

No weather data? No problem

For the study, researchers used a type of machine learning that did not require weather records for the Indonesian cacao farms that participated in the research.

Rather, they relied on data on fertilizer application, yields and farm type, which they plugged into a Bayesian Neural Network (BNN) and found that ENSO phases predicted 75 % of the variation in yields.

In other words, the sea-surface temperature of the Pacific accurately predicted cacao harvests in a large majority of cases for the farms in the study. In some cases, accurate predictions were possible 25 months before the harvest.

For the uninitiated, a model that can accurately predict 50% of yield variation is usually cause to celebrate. And such long-range predictive accuracy for crop yields crops is rare.

"What this allows us to do is superimpose different management practices - such as fertilization regimes - on farms and deduce, with a high level of confidence, those interventions that work," said James Cock, a co-author and emeritus researcher at the Alliance of Bioversity International and CIAT. "This is a whole paradigm shift toward operational research."

Cock, a plant physiologist, said that while randomized control trials (RCTs) are generally considered the gold standard in research, these are extremely costly and consequently often impossible to perform in developing tropical agricultural areas. The approach used here is much lower cost, requires no expensive collection of weather records and provides useful guidelines on how to better manage crops under variable weather.

Ross Chapman, a data analyst and the study's lead author, explained some of the key benefits of machine learning methods over conventional data analysis approaches:

"The BNN modeling differs from standard regression modeling because the algorithm takes input variables, such as sea-surface temperature and farm type, and then automatically 'learns' to recognize responses in other variables, such as crop yield," Chapman said. "The learning process uses the same fundamental process that the human mind learns to recognize objects and patterns from real-life experience. In contrast, standard models require manual supervision of different variables via human-generated equations."

The value of shared data

While machine learning may promise better crop yield predictions in the absence of weather data, scientists - or farmers themselves - still need to accurately collect certain production information and have that data readily available if machine-learning models are going to work.

In the case of the Indonesian cacao farms in the study, farmers had been part of a major chocolate company's training program on best practices. They kept track of inputs such as fertilizer application, freely shared that data for analysis, and an organization with a local presence, the International Plant Nutrition Institute (IPNI), kept tidy records for researchers to use.

In addition, scientists had previously divided their farms into ten similar groups, where topography and soil conditions were similar. The researchers used data on harvests, fertilizer applications and yields from 2013 to 2018 to build their model.

The knowledge gained by cacao growers gives them confidence on how and when to invest in fertilizers. The agronomic skills this vulnerable group acquired shields them against a loss in their investment, which typically occurs when weather is adverse.

Thanks to their collaboration with the researchers, now their knowledge can be, in a way, shared with growers of other crops in other regions of the world.

"This research could not have happened without dedicated farmers, IPNI and a strong farmers' support organization, Community Solutions International, to pull everyone together," Cock said, emphasizing the importance of multidisciplinary collaboration and balancing stakeholder's different needs.

"What scientists want is to know why something happens," he said. "Farmers want to know what works."

APNI's Oberthür said strong predictive modeling could benefit both farmers and researchers, and fuel further collaboration.

"You need to have tangible results if you're a farmer who is also collecting data, which is a lot of work," Oberthür said. "This modeling, which can provide farmers with beneficial information, may help incentivize data collection since farmers will see that they are contributing to something that provides benefits to them on their farms."

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About the Alliance

The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people's lives. Alliance solutions address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation.

The Alliance is part of CGIAR, a global research partnership for a food-secure future.

http://www.bioversityinternational.org http://www.ciat.cgiar.org http://www.cgiar.org

HEY KENNEY & MOE

Inactive oil wells could be big source of methane emissions

Geologist studies greenhouse gas emissions from uncapped, idle wells in Texas

UNIVERSITY OF CINCINNATI

Research News

IMAGE: UC UNDERGRADUATE RESEARCH ASSISTANT JACOB HOSCHOUER TAKES SAMPLES FROM AN INACTIVE OIL WELL. view more 

CREDIT: UC GEOLOGY

Uncapped, idle oil wells could be leaking millions of kilograms of methane each year into the atmosphere and surface water, according to a study by the University of Cincinnati.

Amy Townsend-Small, an associate professor of geology and geography in UC's College of Arts and Sciences, studied 37 wells on private property in the Permian Basin of Texas, the largest oil production region on Earth. She found that seven had methane emissions of as much as 132 grams per hour. The average rate was 6.2 grams per hour.

"Some of them were leaking a lot. Most of them were leaking a little or not at all, which is a pattern that we have seen across the oil and gas supply chain," Townsend-Small said. "A few sources are responsible for most of the leaks."

The study, published in the journal Environmental Research Letters, is the first of its kind on methane emissions from inactive oil wells in Texas.

"Nobody has ever gotten access to these wells in Texas," Townsend-Small said. "In my previous studies, the wells were all on public land."

A 2016 study by Townsend-Small found a similar issue in inactive wells she tested in Colorado, Wyoming, Ohio and Utah. Spread across the estimated 3.1 million abandoned wells, the leaking methane is equivalent to burning more than 16 million barrels of oil, according to government estimates.

Five of the inactive wells Townsend-Small studied in Texas were leaking a brine solution onto the ground, in some cases creating large ponds. 

"I was horrified by that. I've never seen anything like that here in Ohio," Townsend-Small said. "One was gushing out so much water that people who lived there called it a lake, but it's toxic. It has dead trees all around it and smells like hydrogen sulfide."

Most of the wells had been inactive for three to five years, possibly because of fluctuations in market demand. Inactive wells could be a substantial source of methane emissions if they are not subject to leak detection and repair regulations, the UC study concluded.

The study was funded in part by a grant from the U.S. Department of the Interior.

Previous studies have found the basin generates 2.7 billion kilograms of methane per year or nearly 4% of the total gas extracted. That's 60% higher than the average methane emissions in oil and gas production regions nationally. This was attributed to high rates of venting and flaring due to a lack of natural gas pipelines and other gas production infrastructure.

Methane is a powerful greenhouse gas that scientists have linked to climate change. If the rate of methane leaks UC observed were consistent across all 102,000 idled wells in Texas, the 5.5 million kilograms of methane released would be equivalent to burning 150 million pounds of coal each year, according to an estimate by the magazine Grist and nonprofit news organization the Texas Observer.

Townsend-Small and her UC undergraduate research assistant Jacob Hoschouer, a study co-author, came to Texas at the suggestion of the media organizations, which wanted to explore the environmental impact of oil wells, particularly those that are inactive or abandoned. An expert on methane emissions, Townsend-Small has studied releases from oil and natural gas wells across the country.

The journalists arranged with the property owners for Townsend-Small to examine the wells. 

President Joe Biden's administration has pledged $16 billion in its infrastructure plan to cap abandoned oil and gas wells and mitigate abandoned mines. Hoschouer said it would be gratifying if their research could help regulators prioritize wells for capping.

In the meantime, regular inspections of inactive wells using infrared cameras to identify leaks could address the problem, the UC study suggested.

CAPTION

UC associate professor Amy Townsend-Small stands in front of ponding water from an inactive oil well.

CREDIT

UC Geology

Reducing blue light with a new type of LED that won't keep you up all night

AMERICAN CHEMICAL SOCIETY

Research News

 

IMAGE: THIS PROTOTYPE DEVICE CREATES A WARM WHITE LIGHT WITHOUT THE BLUE HUES THAT CAN CAUSE HEALTH PROBLEMS. view more 

CREDIT: JAKOAH BRGOCH

To be more energy efficient, many people have replaced their incandescent lights with light-emitting diode (LED) bulbs. However, those currently on the market emit a lot of blue light, which has been linked to eye troubles and sleep disturbances. Now, researchers reporting in ACS Applied Materials & Interfaces have developed a prototype LED that reduces -- instead of masks -- the blue component, while also making colors appear just as they do in natural sunlight.

LED light bulbs are popular because of their low energy consumption, long lifespan and ability to turn on and off quickly. Inside the bulb, an LED chip converts electrical current into high-energy light, including invisible ultraviolet (UV), violet or blue wavelengths. A cap that is placed on the chip contains multiple phosphors -- solid luminescent compounds that convert high-energy light into lower-energy visible wavelengths. Each phosphor emits a different color, and these colors combine to produce a broad-spectrum white light. Commercial LED bulbs use blue LEDs and yellow-emitting phosphors, which appear as a cold, bright white light similar to daylight. Continual exposure to these blue-tinted lights has been linked to cataract formation, and turning them on in the evening can disrupt the production of sleep-inducing hormones, such as melatonin, triggering insomnia and fatigue. To create a warmer white LED bulb for nighttime use, previous researchers added red-emitting phosphors, but this only masked the blue hue without getting rid of it. So, Jakoah Brgoch and Shruti Hariyani wanted to develop a phosphor that, when used in a violet LED device, would result in a warm white light while avoiding the problematic wavelength range.

As a proof of concept, the researchers identified and synthesized a new luminescent crystalline phosphor containing europium ((Na1.92Eu0.04)MgPO4F). In thermal stability tests, the phosphor's emission color was consistent between room temperature and the higher operating temperature (301 F) of commercial LED-based lighting. In long-term moisture experiments, the compound showed no change in the color or intensity of light produced. To see how the material might work in a light bulb, the researchers fabricated a prototype device with a violet-light LED covered by a silicone cap containing their luminescent blue compound blended with red-emitting and green-emitting phosphors. It produced the desired bright warm white light while minimizing the intensity across blue wavelengths, unlike commercial LED light bulbs. The prototype's optical properties revealed the color of objects almost as well as natural sunlight, fulfilling the needs of indoor lighting, the researchers say, though they add that more work needs to be done before it is ready for everyday use.

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The authors acknowledge funding from the U.S. National Science Foundation and the Welch Foundation.

The abstract that accompanies this paper is available here.

The American Chemical Society (ACS) is a nonprofit organization chartered by the U.S. Congress. ACS' mission is to advance the broader chemistry enterprise and its practitioners for the benefit of Earth and all its people. The Society is a global leader in promoting excellence in science education and providing access to chemistry-related information and research through its multiple research solutions, peer-reviewed journals, scientific conferences, eBooks and weekly news periodical Chemical & Engineering News. ACS journals are among the most cited, most trusted and most read within the scientific literature; however, ACS itself does not conduct chemical research. As a leader in scientific information solutions, its CAS division partners with global innovators to accelerate breakthroughs by curating, connecting and analyzing the world's scientific knowledge. ACS' main offices are in Washington, D.C., and Columbus, Ohio.

To automatically receive news releases from the American Chemical Society, contact newsroom@acs.org.  

The science of picky shoppers

New research defines what it means to be a picky shopper -- and what it means for businesses

PENN STATE

Research News

 

UNIVERSITY PARK, Pa. -- There are hard-to-please customers in almost every industry, with certain people being picky about which clothes, houses and even romantic partners they will consider.

A new series of studies has found that shopper pickiness can go beyond shopping for the "best" option. The researchers define what it means to be "picky" and also developed a scale for measuring shopper pickiness.

Margaret Meloy, department chair and professor of marketing at Penn State, said the findings could help companies devise the best strategies for satisfying their pickier customers.

"If a company knows they have a lot of picky customers, they may need to change the way they reward salespeople or dedicate specific salespeople to their pickiest customers, because picky shoppers have very narrow preferences and they see perceived flaws in products others wouldn't notice," Meloy said. "Alternatively, a company may allow picky shoppers to customize their products to satisfy their idiosyncratic preferences. It's not just about offering the best products, but offering the products that are best for the picky customers."

Meloy added that even the most robust promotional strategies, like offering a free gift with purchase, may fail with picky customers.

Previous research has found that about 40% of people have family or friends they would consider "picky," suggesting the trait is common. The researchers said it might be helpful for retailers to have a better understanding of what being "picky" means for their customer base, and what those customers may need from a product or shopping experience.

Meloy said that while pickiness affects a customer's shopping habits and therefore affects a company's business, there hasn't been much research done on defining pickiness or investigating how it influences a customer's behavior.

"In marketing, we call customers who want the absolute best version of a product 'maximizers,'" Meloy said. "But with picky customers, the best is more idiosyncratic. For them, it might not be about getting the best quality, but getting the precise version of a product they have in their head -- a shirt in a very precise shade of black, for example. We wanted to explore this a bit more."

For the paper -- recently published in the Journal of Consumer Psychology -- the researchers performed a series of studies to create a scale for measuring shopper pickiness and to identify the consequences of that pickiness on customer behavior.

The first series of studies focused on developing the scale. The researchers said they created a series of questions that would help uncover the psychological dimensions of pickiness while also avoiding using the word "picky," since the word tends to have negative connotations. Once the researchers were confident the scale accurately measured pickiness, they conducted additional studies to examine the possible consequences of pickiness.

The researchers found that people who scored higher on the picky shopper scale tend to have a small window of what they consider acceptable, which the researchers described as having a small latitude of acceptance and a wide latitude for rejection. These shoppers were more likely to reject a free gift when offered as a thank you for participating in a survey.

"This may seem irrational to some people who may not understand why a person would reject things that come at no cost," said Andong Cheng, an assistant professor of marketing at the University of Delaware who earned her doctorate at Penn State. "We speculate that it could be psychologically costly for picky shoppers to take free items that they don't like because possessing these items is a source of irritation for these individuals."

Additionally, the researchers found that picky people didn't change their opinions based on a product's popularity. When they were informed that their top choice of a product was less popular than other options, people who scored high on the picky scale weren't swayed by that information. They stuck with their original selection.

Meloy said the results support the theory that being picky is a general personality trait that isn't just present in one situation or area of a person's life.

"We looked at a range of contexts to see whether being picky in one domain meant you were likely to be picky in others," Meloy said. "Sure enough, individuals who were picky in one domain were picky in other domains. For example, if you tend to be picky while shopping for groceries, you'll probably be picky shopping for clothes, as well."

Meloy said the findings also illustrate the importance of a company understanding and tailoring their business practices to their customer base.

"If you know you have a lot of picky customers, you might not want to bother with offering free products or promoting products by saying how popular they are with other people," Meloy said. "It's just not going to work as well with picky customers. These companies will need to come up with strategies that give customers more control to better align their idiosyncratic preferences with the company's offerings."

Hans Baumgartner, Smeal Chair Professor of Marketing at Penn State, also participated in this work.

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Study finds green spaces linked to lower racial disparity in COVID infection rates

A new study is the first to examine the relationship between the supply of green spaces and reduced disparity in infectious disease rates.

UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN, NEWS BUREAU

Research News

 

IMAGE: FROM LEFT, RESEARCHERS BIN JIANG, YI LU AND WILLIAM SULLIVAN FOUND THAT MORE GREEN SPACES IN AN AREA IS ASSOCIATED WITH A LOWER RACIAL DISPARITY IN CORONAVIRUS INFECTION RATES. THEIR... view more 

CREDIT: PHOTOS COURTESY BIN JIANG, YI LU AND WILLIAM SULLIVAN

CHAMPAIGN, Ill. -- A higher ratio of green spaces at the county level is associated with a lower racial disparity in coronavirus infection rates, according to a new study. It is the first study to report the significant relationship between the supply of green spaces and reduced disparity in infectious disease rates.

The research team included William Sullivan, a landscape architecture professor at the University of Illinois Urbana-Champaign, and was led by Bin Jiang, a landscape architecture professor at The University of Hong Kong who received his Ph.D. at Illinois, and Yi Lu, an architecture professor at City University of Hong Kong. They reported their findings in the journal Environment International.

Previous studies by Sullivan, Jiang and Lu have shown that green spaces have positive effects on health. Access to green spaces is associated with improved cognitive performance, reduced mental fatigue and stress, reduced impulsiveness and aggressiveness, increased sense of safety, reduced crime rate, increased physical activity and increased social cohesion.

Prior studies also provide strong evidence that green spaces may mitigate racial disparities in health outcomes. However, none have looked at the effect on disparities in infectious diseases. Most studies examining the racial disparity in coronavirus infections have focused on its association with socio-economic status or pre-existing chronic disease factors.

For this study, the researchers identified 135 of the most urbanized counties in the U.S., with a total population of 132,350,027, representing 40.3% of the U.S. population. They collected infection data from county health departments from late January to July 10, 2020, and used it to calculate the infection rates for Black and white residents of the counties, while controlling for differences in income, pre-existing chronic diseases and urban density.

The data showed that the average infection rate for Black residents was more than twice that of white residents - 497 per 100,000 people for white individuals versus 988 per 100,000 people for Black individuals.

The researchers compared the infection rates of each population within each county, rather than across all the counties studied. The county-level comparison Is critical because it can minimize the bias caused by differences of socioeconomic, transportation, climate and policy conditions among counties, they said.

Sullivan, Jiang and Lu said several factors could account for the findings. They proposed that a greater proportion of green spaces in a county makes it more likely that Black and white individuals have more equal access to the green spaces and the accompanying health benefits.

"In many, many counties, Black folks have less access to green space than white folks do. In counties with more green space, that disparity may be less, and it may help account for some of the positive benefits we're seeing," Sullivan said.

The coronavirus is spread through aerosol particles, and the spread is heightened in indoor settings without adequate ventilation. Having access to green spaces attracts people outdoors, where air movement and the ease of social distancing can reduce the spread of the virus.

More access to green spaces is likely to promote physical activity, which may enhance the immune system. Green spaces enhance mental health and reduce stress, which also promotes immune system health. They strengthen social ties, which is an important predictor of health and well-being, the researchers said. Green spaces also may decrease infection risk by improving air quality and decreasing exposure to air pollutants in dense urban areas.

"We did not measure these things, but we know from previous research that all these things are tied to green spaces and have implications for health and well-being," Sullivan said.

Jiang described green space as preventive medicine, encouraging outdoor physical activity and social ties with neighbors that will boost the immune system and promote social trust and cooperation to reduce risk of infections.

While the study looked at infection rates in the U.S., "we also think the racial disparity issue is not just an American issue. It's an international issue," Jiang said.

The research shows the importance for local and regional governments to invest in the development of green spaces, Sullivan said.

"One of the things the pandemic has helped us understand is that the built environment has real implications for the spread of disease and for our health. The design of landscape in cities, in neighborhoods, in communities also has really important ways it can contribute to or detract from health and well-being," he said. "There is a lot of competition for investment of public dollars. Lots of times, investments in parks and green spaces are prioritized lower. People think it makes a place look pretty and it's a place to go for walks. What we're finding is these kinds of investments have implications for health and well-being."