Wednesday, September 10, 2025

 

Why teens defy—and how parents can help




New research shows that teens heed warnings about risky behavior more when parents model their own values and show understanding.




University of Rochester




Adolescence is a period when some teenagers begin experimenting with risky or rule-breaking behaviors such as skipping school, drinking, lying, or staying out past their curfew. When parents find out, their natural response is often to warn their child: Continue with the behavior and you’ll incur stricter rules, less freedom, and the loss of privileges.

On the surface, this response seems a reasonable attempt to deter further misbehaving. But how do teens actually experience these warnings—and why do some comply while others become even more defiant?

A team of US and Israeli researchers—among them University of Rochester psychologist Judith Smetana—set out to find answers. The resulting study, published in the Journal of Youth and Adolescence, concludes that the way teenagers receive their parents’ warnings depends less on the message itself and more on whether they see their parents as genuinely living up their own purported values.

If parents model their values consistently in everyday life and appear satisfied and vital while acting on their values, their warnings are more likely to be perceived by their teenagers as caring guidance. If not, teens often experience the warnings as an attempt to control them, which can spark defiance. But the researchers also discovered that while authentic parental values reduced defiance, they did not, by themselves, lead teens to stop their risky behaviors. The warnings proved most effective when parents took the time to understand their teens’ perspectives.

“Parents really have to ‘walk the walk’ and act on their values if they want their teens to behave responsibly,” says Smetana, an expert on adolescent-parent relationships.

The science behind motivation

The study, Smetana points out, builds directly on a famous Rochester construct—the highly influential, evidence-based framework for motivation, called self-determination theory (SDT), which was formulated in the 1970s and 1980s by Rochester psychologists Edward Deci and Richard Ryan.

According to SDT, people have three basic, intrinsic psychological needs:

  • Autonomy—the need to feel free from control so one can realize one’s authentic preferences
  • Competence—the need to feel capable
  • Relatedness—the need to feel connected and respected by others

When parenting actively supports these needs, adolescents feel motivated and understood. But when parents’ behaviors hinder these needs—what Deci and Ryan call “need thwarting” (where a person’s basic psychological needs for autonomy, competence, and relatedness are actively undermined)—teens may feel pressured, powerless, or disconnected, which can trigger resistance and rebellion.

“The idea of ‘need thwarting’ leading to defiance is drawn directly from self-determination theory, as is the very important notion of autonomy-supportive parenting, which is widely used in studies of parenting,” says Smetana.

Modeling values while parenting

Smetana and her team focused specifically on one parental factor called “inherent value demonstration” that can influence how warnings are received. For example, a parent who stresses the importance of kindness, volunteers regularly, and treats others respectfully—and appears satisfied and energetic while doing so—would be seen as high in value demonstration. In contrast, parents whose actions don’t match their words would be perceived as low in value demonstration.

The team surveyed 105 Israeli adolescents, average age 15, who had engaged in at least one problem behavior in the previous month. Each teen reported the most serious behavior their parents had discovered and then rated how their parents reacted—whether through warnings or by trying to understand their child’s perspective. The teens also shared how these reactions made them feel: Did they experience the reactions as supportive or as controlling? Did they feel motivated to stop, or did they feel defiant? Finally, they rated how much their parents generally demonstrated their values in daily life.

The findings were clear: When parents were perceived as low in value demonstration, their teens were much more likely to experience their warnings as “need thwarting.” But when parents were perceived as high in value demonstration, their warnings were more likely to be seen as protective and the teens experienced the warnings as “need supporting.” Teenagers in these families were less defiant and felt more supported, even if the warnings included unpleasant consequences, such as the loss of privileges.

Stopping teens’ risky behaviors

The researchers discovered that while authentic parental values reduced defiance, they did not, by themselves, lead teens to stop their risky behaviors.

“We were surprised to learn that even children who perceived their parents as demonstrating their values in their everyday behavior experienced their parents’ warnings as frustrating and insensitive to their basic psychological needs,” says lead coauthor Avi Assor at Israel-based Ben-Gurion University of the Negev. “We thought that because parents’ warnings referred to potentially harmful problem behaviors, children who appreciate their parents as good models of virtuous behavior may not experience these warnings as insensitive to their needs.”

Instead, the team found that the only parenting reaction linked to actually stopping the problem behavior was “perspective taking”—when parents tried to understand their child’s feelings and reasons. This empathic approach seemed to prompt reflection, making it more likely that teens reconsidered and stopped their risky actions.

In short: Putting yourself in your teenager’s shoes may be your best bet in trying to keep your child safe.

The researchers for this study came from Ben-Gurion University, Achva Academic College, Clark University, University of Rochester, and the University of Haifa.

 

 

AI model helps boost pandemic preparedness



Scripps Research breakthrough reduces antibody discovery time from weeks to hours, potentially revolutionizing pandemic response and therapeutic development.




Scripps Research Institute

AI model helps boost pandemic preparedness 

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Scripps Research scientists used a graphical neural network-based structure building tool, ModelAngelo, to discover monoclonal antibodies (bottom) from polyclonal antibody responses produced after mouse vaccination (top).

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Credit: Scripps Research





LA JOLLA, CA—Scientists at Scripps Research have developed a novel method that uses artificial intelligence (AI) and advanced imaging techniques to more accurately and efficiently identify therapeutic antibodies to treat infectious diseases.

The breakthrough method, published in Science Advances on August 15, 2025, reduces the time needed to identify protective antibodies from weeks to under a day—while offering a scalable approach that minimizes data bottlenecks and accelerates research. This advancement could transform how researchers develop treatments for influenza, HIV and other infectious diseases, particularly during health emergencies where rapid response is critical.

“This represents a paradigm shift in how we discover antibodies,” says study senior author Andrew Ward, professor in the Department of Integrative Structural and Computational Biology at Scripps Research. “By harnessing AI to analyze the structural details of immune responses, we can now identify the most promising therapeutic candidates in mere hours, with better success rates than traditional methods. This could be game-changing for pandemic preparedness and therapeutic development.”

Finding the needle in a haystack

Antibodies play a critical role in the immune system because of their ability to latch onto and neutralize bacteria, viruses and other pathogens. These large, Y-shaped proteins are naturally produced by the immune system, but can be engineered as treatments for cancer, autoimmune disease and infections. They’re among medicine’s most important therapeutic tools, comprising more than 200 approved drugs worldwide due to their safety and effectiveness in treating diverse diseases.

However, traditional antibody discovery methods are labor-intensive and time-consuming, requiring researchers to screen thousands of candidates individually to find those that bind to the right targets and still provide enough protection. This is because when the body encounters a threat like a virus, it produces a huge, diverse array of antibodies—but only a select few are able to target vulnerable spots that can neutralize the pathogen or provide therapeutic benefit. Sorting through this complexity has historically been a major bottleneck in drug and vaccine development.

AI meets advanced microscopy

Researchers have recently developed a potential solution to this problem by combining two powerful technologies: cryo-electron microscopy (cryoEM), which uses an electron beam to capture images of antibodies binding to their targets at near-atomic resolution, and ModelAngelo, an AI tool that builds molecular models from the cryoEM images and predicts which antibodies could provide protection. Leveraging these two technologies, Ward and his laboratory analyzed the structural patterns of antibody responses, and then used ModelAngelo to identify the most compatible antibodies from its database. This method, known as Structure-to-Sequence (STS), builds on previous findings from Ward’s lab that leveraged cryoEM to rapidly map all of the antibodies elicited by an infection in a matter of days.

“What’s exciting about this method is that it removes much of the guesswork from antibody discovery,” says first author of the study James Ferguson, a staff scientist in the Ward lab. “Instead of randomly screening thousands of antibodies, we can look directly at the immune-response structure and identify the ones that are binding to functionally important sites. ModelAngelo then helps us find these antibodies in genetic databases with remarkable precision.”

To demonstrate real-world therapeutic potential, the team tested the antibodies identified by ModelAngelo in animal models to see how well they protected against influenza. The researchers found that the antibodies identified with the ModelAngelo-powered STS pipeline showed significant protection from the virus—indicating that this method could be a powerful tool to identify the most protective antibodies against disease.

Preparing for the next pandemic

The implications extend far beyond influenza. The method’s speed and accuracy make it particularly valuable for responding to emerging infectious diseases, where rapid development of treatments can save lives.

“The integration of AI with immune response analysis not only accelerates vaccine development but also enhances our ability to respond swiftly to emerging pathogens,” Ward noted. “By streamlining the discovery of protective antibodies, this pipeline paves the way for faster, more targeted therapeutics in the face of future global health threats.”

To build upon their work, the research team has initiated collaborations with labs across Scripps Research to continue studying how ModelAngelo could revolutionize therapeutic antibody development. Ward and his lab envision a future where their method is able to support evolving health challenges, ultimately bringing life-saving treatments to patients faster than ever before.

In addition to Ward and Ferguson, authors of the study, “Functional and epitope specific monoclonal antibody discovery directly from immune sera using cryoEM,” are Sai Sundar Rajan Raghavan of Scripps Research; Garazi Peña Alzua of the Icahn School of Medicine at Mount Sinai; Disha Bhavsar of the Icahn School of Medicine at Mount Sinai; Jiachen Huang of Scripps Research; Alesandra J. Rodriguez of Scripps Research; Jonathan Torres of Scripps Research; Maria Bottermann of MIT and Harvard; Julianna Han of Scripps Research; Florian Krammer of the Icahn School of Medicine at Mount Sinai and the Medical University of Vienna; and Facundo D. Batista of MIT and Harvard.

This study was supported by the Centers of Excellence for Influenza Research and Response (CEIRR) contract # 75N93021C00014), Icahn School of Medicine at Mount Sinai institutional funds (F.K.), and by the National Institute Of Allergy And Infectious Diseases of the National Institutes of Health Award Number P01 AI136621 (A.B.W.).

About Scripps Research

Scripps Research is an independent, nonprofit biomedical research institute ranked one of the most influential in the world for its impact on innovation by Nature Index. We are advancing human health through profound discoveries that address pressing medical concerns around the globe. Our drug discovery and development division, Calibr-Skaggs, works hand-in-hand with scientists across disciplines to bring new medicines to patients as quickly and efficiently as possible, while teams at Scripps Research Translational Institute harness genomics, digital medicine and cutting-edge informatics to understand individual health and render more effective healthcare. Scripps Research also trains the next generation of leading scientists at our Skaggs Graduate School, consistently named among the top 10 US programs for chemistry and biological sciences. Learn more at www.scripps.edu.

 

As farm jobs decline, food industry work holds steady



Cornell University

ITHACA, N.Y. – A new Cornell University study covering nearly three decades and 189 countries finds that while traditional farm jobs decline as nations grow wealthier, employment in the broader food industry – from processing plants to restaurants – remains surprisingly steady, offering better wages but also deepening gender pay gaps.

The research challenges the classic economic story that development means a simple shift of workers from farms to factories. Instead, researchers found much of the movement occurs within the food system itself, reshaping which workers earn more and which earn less. The paper published Sept. 10 in Nature Food.

These shifts are driven more by consumer demand than by improvements in agricultural productivity, according to corresponding author Chris Barrett, professor of applied economics and management.

“As incomes rise, people demand more convenience, safety and diversity in their diets,” Barrett said. “That creates a huge pull for workers into food processing, retail, restaurants and transportation – not just into manufacturing.”

Among the study’s most striking results, jobs in food services and retail now rival or surpass farm employment in wealthier countries. Workers who leave farming typically find higher pay in midstream and downstream jobs like food manufacturing and distribution. That’s good news – but not necessarily for women, because this shift reinforces gender pay inequality.

“In low-income agrarian economies, men and women are largely doing the same work,” Barrett said. “People leaving farming find safer jobs and better pay. But it’s not equally good for men and women.”

While women do earn more after leaving farm work, they tend to move into service-sector jobs – in restaurants and retail – that are consistently lower paid than the midstream jobs in manufacturing, logistics, processing, wholesale trade and transport, where men predominate.

Over time, the difference adds up. The study found that as economies transition from poor to rich, the ratio of women’s to men’s average earnings in the food system falls from near parity to about 94 cents on the dollar. And because the analysis could not account for pay gaps within the same industry, much less the same occupation, the true divide is surely larger.

The findings underscore a tension facing policymakers. Calls to bring more young people “back to the farm” in some countries may be at odds with economic realities. The real job growth isn’t on the farm, according to Barrett. It’s in the industries that process, move and serve food – but those jobs are unequally distributed between men and women.

For additional information, see this Cornell Chronicle story.

Cornell University has dedicated television and audio studios available for media interviews.

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Kennesaw State researcher aiming to move AI beyond the cloud


Assistant professor of computer science Bobin Deng is researching how AI tools could function without an internet connection



Kennesaw State University

Bobin Deng 

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Bobin Deng

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Credit: Darnell Wilburn / Kennesaw State University





Artificial intelligence (AI) is often linked to supercomputers and massive data centers, but Kennesaw State University researcher Bobin Deng is aiming for something a bit more accessible through a new National Science Foundation (NSF) grant.

An assistant professor in Kennesaw State’s College of Computing and Software Engineering, Deng said the goal is to move AI beyond the cloud and into the hands of people where it can have the most impact – their personal devices. The research could allow AI tools to function without an internet connection, something that is uncommon with many current systems. 

“Most of today’s AI runs on large, expensive servers,” Deng said. “But many applications don’t need that level of computing power. “If we can run AI directly on a mobile phone, a drone, or other smaller systems, then we remove the reliance on costly supercomputers and make AI easier and faster access in more situations.” 

At the heart of his project is a technique that uses activation sparsity, a process where only a portion of neurons in an AI model are active while most remain inactive. Instead of loading all the data into memory, the system accurately predicts in advance which pieces it may need and loads only those, reducing memory usage, speeding up processes, and lowering energy demands. 

“Other methods shrink models by reducing the precision of data or pruning less important parameters,” Deng said. “Our approach is different. We predict which values will be activated. That allows us to combine our method with existing techniques like pruning or quantization to make models even more efficient.” 

The project will test tiny machine- learning models as predictors to support larger systems. This balance makes AI more feasible for devices like smartphones, drones, and industrial sensors. 

The open-source simulator Deng’s team is building will allow other researchers and students to explore and refine the technology.  

“This grant supports fundamental research that can benefit students in our new Master of Science in Artificial Intelligence program, as well as industry partners,” he said. “From monitoring factory robots to predicting equipment failures, embedding AI in smaller devices has the potential to transform many industries.” 

Deng conducts his research in the Sustainable Smart System Lab on KSU’s Marietta Campus. He discussed how the university has played a vital role in supporting his work, from lab space to grant administration.  

“The leadership here has been very supportive,” he said. “Whenever I have needed resources or assistance, from graduate assistants to proposal submissions, the university has been there to help.” 

CCSE Interim Dean Yiming Ji commended Deng’s efforts as a reflection of the college’s mission to advance innovation and prepare students for the future of technology.  

“Dr. Deng’s research represents the kind of forward-looking work that positions KSU as a leader in AI,” Ji said. “His approach not only addresses technical challenges but also creates real-world opportunities for students, industry partners, and the community.” 

 

Treating opioid addiction in jails improves treatment engagement, reduces overdose deaths and reincarceration



NIH-funded study demonstrates life-saving potential of providing medications for opioid use disorder in carceral settings



NIH/Office of the Director

 




A study supported by the National Institutes of Health (NIH) finds that individuals who received medication for opioid use disorder (MOUD) while incarcerated were significantly more likely to continue treatment six months after release than those who did not receive MOUD. The study also found that receiving MOUD in jail was associated with a 52% lower risk of fatal opioid overdose, a 24% lower risk of non-fatal opioid overdose, a 56% lower risk of death from any cause, and a 12% lower risk of reincarceration after release. These outcomes underscore the importance of providing MOUD treatment during incarceration. 

 

Published in The New England Journal of Medicine, the study analyzed data from 6,400 people with probable opioid use disorder who were incarcerated in seven Massachusetts county jails between September 2019 and December 2020. Of these, 42% received MOUD while in jail, while 58% did not. Researchers monitored treatment engagement, opioid overdose, reincarceration, and mortality for all participants for up to six months after release.  

 

“These findings demonstrate the importance of providing medications to treat opioid use disorder in correctional settings,” said Nora D. Volkow, M.D., Director of NIDA. “Offering effective opioid treatment to people in jail is a critical step toward addressing the opioid crisis, promoting recovery, saving lives and reducing reincarceration. It’s a win-win for public health.” 

 

The opioid epidemic remains a devastating public health challenge in the United States, contributing to more than 80,000 deaths in 2024 alone. People with opioid use disorder are overrepresented in jails compared to the general population. Despite their effectiveness, MOUD is available in only about 13% of U.S. jails and is often restricted to specific groups, such as pregnant women. This limited access contributes to forced withdrawal, increasing the risk of relapse and overdose post-release.  

 

Massachusetts has been especially impacted by the overdose epidemic, with fatal opioid-related overdoses quadrupling over the past two decades. In response, a 2018 state law mandated a four-year pilot program to provide all U.S. Food and Drug Administration-approved MOUD—buprenorphine, methadone, and naltrexone—in five county jails, with two additional jails voluntarily joining the program. The law requires that individuals already receiving treatment for opioid use disorder continue it during detention, begin treatment before release when appropriate, and be connected to community care after release.  

 

To evaluate the impact of the pilot program, the Massachusetts Department of Public Health partnered with the Massachusetts Justice Community Opioid Innovation Network (MassJCOIN) and participating jails to conduct a comprehensive study tracking post-release outcomes. Researchers collected data directly from incarcerated individuals and extracted information from jail administrative and clinical records. These data were integrated with the Massachusetts Public Health Data Warehouse, which links over 35 state databases to track treatment for substance use disorders, incarceration, mortality, and other public health indicators. This linkage enabled a robust analysis of the program’s impact on key post-release outcomes.   

 

Treatment in jail was strongly associated with better outcomes after release. Within the first 30 days, 60.2% of those who received MOUD in jail, initiated treatment in the community, compared to only 17.6% of individuals who weren’t treated. Half of the group treated in jail stayed on medication for at least 75% of the first 90 days after release, while only 12.3% of the untreated group did the same. Six months after release, 57.5% of those who received treatment in jail continued receiving MOUD, compared to just 22.8% of those who did not. Most people treated in jail received buprenorphine (67.9%) followed by methadone (25.7%) and naltrexone (6.5%). 

 

“The Massachusetts initiative represents a model for how jails can play a vital role in addressing the opioid epidemic in the community,” said Peter D. Friedmann, M.D., M.P.H., lead author and addiction medicine physician at the University of Massachusetts Chan Medical School. Senior author Elizabeth A. Evans, PhD, a public health professor from University of Massachusetts-Amherst added, “Establishing these types of programs in local jails is a powerful and effective strategy for engaging and retaining people in treatment and reducing overdose deaths after release.” 

 

Future research should explore the generalizability of these findings to other correctional systems, as well as how outcomes differ across population subgroups and by the type of medication received. Research to examine which strategies for implementing MOUD in jails are most effective in supporting recovery after release are also needed.  

 

This research was supported by the Justice Community Opioid Innovation Network (JCOIN), a nationwide research program that tests strategies to expand effective treatment, recovery, and related services for individuals with opioid use disorder involved in the criminal justice system. JCOIN is funded by the NIH’s National Institute on Drug Abuse as part of the NIH Helping to End Addiction Long-term ® (NIH HEAL Initiative®).  

 

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For more information on substance and mental health treatment programs in your area, call the free and confidential National Helpline 1-800-662-HELP (4357) or visit FindTreatment.gov. Anyone who needs assistance with the first steps in pursuing help can find guidance at FindSupport.gov. 

 

Reference: PD Friedmann, et al. Medications for Opioid Use Disorder in County Jails: Outcomes After ReleaseNew England Journal of Medicine. DOI: 10.1056/NEJMsa2415987 (2025). 

 

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About the National Institute on Drug Abuse (NIDA): NIDA is a component of the National Institutes of Health, U.S. Department of Health and Human Services. NIDA supports most of the world’s research on the health aspects of drug use and addiction. The Institute carries out a large variety of programs to inform policy, improve practice, and advance addiction science. For more information about NIDA and its programs, visit www.nida.nih.gov
 
About the National Institutes of Health (NIH): NIH, the nation’s medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov. 

 

 

NIH…Turning Discovery Into Health® 

 

Warming rivers in Alaska threaten Chinook salmon populations and Indigenous food security





University of Colorado at Boulder

Rivers in Alaska are changing rapidly 

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Rivers in Alaska are changing rapidly. 

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Credit: Peyton Thomas/CU Boulder






For millennia, Indigenous people living in Alaska and Canada’s Yukon territory have relied on Chinook salmon. The large, fatty fish provide essential nutrients for Arctic living and have influenced traditions and languages across generations.

But over the past three decades, many communities have been unable to fish Chinook amid a sharp salmon population decline.

The situation could worsen as climate change warms rivers in the Arctic, stunting salmon growth, according to a study published August 6 in Scientific Reports led by the University of Colorado Boulder.  

“The fish are really important for maintaining the culture and language of Indigenous communities,” said Peyton Thomas, a research associate at the Institute of Arctic and Alpine Research. 

In collaboration with locals on the ground, the team is now working to help communities prepare for the changes ahead.

Over the past 50 years, the Arctic has warmed nearly four times faster than the global average. Climate change has melted sea ice, thawed frozen ground and eroded coastlines, reshaping the Arctic landscapes Indigenous peoples have called home for generations.

Prior research has suggested that increased river temperatures can affect fish species adapted to cooler environments. Chinook salmon in the Arctic are a prime example. One study estimated that Chinook salmon populations in the Yukon River, Alaska’s largest, plummeted by more than 57% between 2003 and 2010. 

Working closely with Indigenous communities in Alaska, Thomas and her team set out to better predict how climate change would affect fish populations in the seven river basins spanning watersheds in Alaska and Yukon. 

After talking to tribal members, the team focused on two species important for subsistence, Chinook salmon and Dolly Varden, a type of trout.  

Using computer models, the team simulated how the region’s climate and rivers might change by mid-century. They found that summer river temperatures could rise by 1.26 °C (2.27 °F) by mid-century compared to the average between 1990 and 2021. 

When they combined these data with a fish growth model, they found that in the warmest future years, four out of seven river basins would experience water temperatures surging above what juvenile Chinook salmon can tolerate. 

On the other hand, Dolly Varden thrive in slightly warmer water than Chinook salmon. The simulations suggested that these fish might nearly double their growth in many rivers.

“It is good news that not all species are going to decline under warming,” Thomas said. “But communities have different preferences about fishing Dolly Varden. We’re trying to show that maybe in warm years, Dolly Varden could be an alternative.”   

This study comes just a year after Alaska and Canadian authorities agreed to pause Chinook salmon fishing, both commercial and subsistence, for seven years in a bid to allow their populations to recover. 

“The coolest part of this work is just being able to see how we're all trying to connect with each other,” Thomas said. “We learned so much from history and people's daily lived experiences in these places. Everyone should be a part of all of this work, because we can't do it just by modeling.”