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Tuesday, June 23, 2026

Can use of popular weight loss medications reduce behaviors linked to violent crime?

Wiley

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely prescribed for diabetes and obesity, but studies have found evidence that the medications may also influence behavior, such as supporting impulse control and reducing substance use and alcohol consumption by potentially interacting with the brain’s reward and stress systems. New research in Criminology adds to this growing evidence.

When investigators analyzed data from a 2025 nationally representative US survey involving 821 adults who had ever used GLP-1 medications, they found that while impulsivity and alcohol use were strongly associated with committing violent crime, these associations were significantly weaker among current GLP-1 RA users compared with former users. So even when a GLP-1 RA user drinks or acts impulsively, the situation is less likely to escalate into engaging in violent criminality. More thorough analyses showed that this finding was especially consistent related to impulsivity, but less so with alcohol use.

The findings suggest that GLP-1 RAs may lessen the extent to which certain established risk factors translate into violent behavior.

“As GLP-1 medications become increasingly widespread, understanding their broader behavioral effects becomes an important public health and criminological question that requires careful study,” said corresponding author Daniel C. Semenza, PhD, of Rutgers University.

URL upon publication: https://onlinelibrary.wiley.com/doi/10.1111/1745-9125.70058

Additional Information
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About the Journal
Criminology is devoted to the study of crime and deviant behavior. Interdisciplinary in scope, the journal publishes articles that advance the theoretical and research agenda of criminology and criminal justice.

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Journal

Criminology

DOI

10.1111/1745-9125.70058

Article Title

GLP-1 receptor agonist use and violent crime among US adults

Article Publication Date

17-Jun-2026

Researchers link use of GLP-1 medications to lower risk of violence

A Rutgers study finds that treatments such as Ozempic and Wegovy may diminish the link between impulsivity and violent behavior

Rutgers University

The use of GLP-1 medications commonly prescribed for weight loss or managing diabetes may have effects that extend beyond metabolic health, including on behaviors linked to violence, according to Rutgers researchers.

Their study, published in Criminology, examined whether the use of GLP-1 receptor agonist medications, such as Ozempic and Wegovy, influences violent criminal behavior among adults by moderating the effects of impulsivity and alcohol intake.

Researchers analyzed data from a 2025 survey of 7,521 U.S. adults and focused their primary analyses on 821 individuals who had ever used a GLP-1 medication. The study compared current GLP-1 users with former users and examined whether medication use changed the relationship between violent behavior, impulsivity and alcohol use. Violent behavior was measured using a validated self-reported offending scale assessing behaviors such as fighting, assault and robbery.

“The strongest finding in the study was that the well-established link between impulsivity and violent behavior was substantially weaker among current GLP-1 users compared to former users,” said Daniel Semenza, the lead author of the study as well as the director of research at the New Jersey Gun Violence Research Center at the Rutgers School of Public Health and an associate professor with the Rutgers School of Public Health. “As GLP-1 drugs become increasingly widespread, it is important to understand all of their potential behavioral effects, including those relevant to public safety,” Semenza said.

Researchers found that higher impulsivity and alcohol use were strongly associated with violent behavior overall, but those relationships were significantly weaker among current GLP-1 users. The association between impulsivity and violent behavior was about 62% weaker among current users compared with former users. The relationship between alcohol use and violent behavior was about 52% weaker among current users, although those findings were less consistent across sensitivity analyses.

“Our findings are consistent with these medications working like cognitive behavioral therapy, weakening the path from impulse to action rather than eliminating impulsivity itself,” said Christopher Thomas, an assistant professor at Rutgers University-Camden and the coauthor of the study.

The study was observational and cross-sectional, meaning causal conclusions cannot be drawn, the researchers said. They emphasized the need for future longitudinal and experimental studies to determine whether GLP-1 medications reduce violence risk and to better understand the mechanisms involved.

Journal

Criminology

Method of Research

Survey

Subject of Research

People

Article Title

GLP-1 receptor agonist use and violent crime among US adults

Article Publication Date

17-Jun-2026

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Friday, April 11, 2025

Junk Science and Bad Policing: The Homicide Prediction Project

by Binoy Kampmark / April 10th, 2025

The law enforcement breed can be a pretty dark lot. To be paid to think suspiciously leaves its mark, fostering an incentive to identify crimes and misdemeanours with instinctive compulsion. Historically, this saw the emergence of quackery and bogus attempts to identify criminal tendencies. Craniometry and skull size was, for a time, an attractive pursuit for the aspiring crime hunter and lunatic sleuth. The crime fit the skull.

With the onset of facial recognition technologies, we are seeing the same old habits appear, with their human creators struggling to identify the best means of eliminating compromising biases. A paper published by IBM researchers in April 2019 titled “Diversity in Faces” shows that doing so ends up returning to old grounds of quackery, including the use of “craniofacial distances, areas and ratios, facial symmetry and contrast, skin color, age and gender predictions, subjective annotations, and pose and resolution.”

The emergence of artificial intelligence (AI) tools in identifying a form of predictive criminality perpetuates similar sins. Police, to that end, have consistently shown themselves unable to resist the attractions supposedly offered by data programs and algorithmic orderings, however sophisticated. These can take such crude forms as those advanced by Pasco County Sheriff Chris Nocco, a devotee of that oxymoronic pursuit “intelligence-led policing,” stacked with its snake oil properties. A 2020 Tampa Bay Times piece on the exploits of that Florida county’s sheriff’s office made it clear that Nocco was keen on creating “a cutting-edge intelligence program that could stop crime before it happened.”

The counter to this was impressive in its savagery. Such forms of law enforcement featured, in the view of criminologist David Kennedy of the John Jay College of Criminal Justice, “One of the worst manifestations of the intersection of junk science and bad policing”, in addition to its utter lack of “common sense and humanity”.

The trend towards data heavy systems that supposedly offer insight into inherent, potential criminality has captured police departments in numerous countries. A recommendation paper from the European Crime Prevention Network notes the use of “AI tools in hopes of rendering law enforcement more effective and cost-efficient” across the European Union. Predictive policing is singled out as particularly attractive, notably as a response to smaller budgets and fewer staff.

In the United Kingdom, the government’s Ministry of Justice has taken to AI with gusto through the Homicide Prediction Project, a pilot program that hoovers up data from police and government data sets to generate profiles and assess the risk of a person committing murder. The program, commissioned by the Prime Minister’s Office in 2023 and involving the MoJ, the Home Office, Greater Manchester Police (GMP) and the Metropolitan Police in London, only came to light because of a Freedom of Information request by the charity Statewatch.

According to the Data and Analysis unit within the MoJ the data science program explores “the power of MOJ datasets in relation to assessment of homicide risk”, the “additional power of the Police National Computer dataset” in doing the same, and “the additional power of local police data”. It also seeks to review the characteristics of offenders that increase such a risk, exploring “alternative and innovative data science techniques to risk assessment and homicide.”

What stands out in the program is the type of data shared between the agencies. These include types of criminal convictions, the age a person first appeared as a victim (this includes domestic violence), and the age a person had their first encounter with the police. But also included are such matters as “health markers which are expected to have predictive power”, be they on mental health, addiction issues, suicide, self-harm and disability.

The use of predictive models is far from new for the wonks at the MoJ. Those used in the Offender Assessment System (OASys) have been previously found to profile people differently in accordance with their ethnicities. The National Offender Management service noted in a 2015 compendium of research and analysis of the system between 2009 and 2013, “Relative predictive validity was greater for female than male offenders, for White offenders than offenders of Asian, Black and Mixed ethnicity, and for older than younger offenders.”

Statewatch researcher Sofia Lyall has little to recommend the program, renamed for evidently more palatable consumption the Sharing Data to Improve Risk Assessment program. “Time and again, research shows that algorithmic systems for ‘predicting’ crime are inherently flawed.” The Homicide Prediction Project was “chilling and dystopian”, profiling individuals “as criminals before they have done anything.” She is also convinced that the system will, as with others, “code in bias towards racialized and low-income communities” while posing grave threats to privacy.

The unit claims that the work is only intended for dry research purposes, with “no direct operational or policy changes” arising because of it, or any individual application to a “person’s journey through the justice system.” This is a nonsensical assertion, given the sheer temptations open to officials to implement a program that uses hefty data sets in order to ease the task of rigorous policing. The representatives of law enforcement crave results, even those poorly arrived at, and algorithmic expediency and actuarial fantasy is there to aid them. The “precrime” dystopia portrayed in Philip K. Dick’s The Minority Report (1956) is well on its way to being realised.

Binoy Kampmark was a Commonwealth Scholar at Selwyn College, Cambridge. He lectures at RMIT University, Melbourne. Email: bkampmark@gmail.com. Read other articles by Binoy.

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Friday, November 01, 2024

WashU researchers use genetics to find psychopathology risks

GREAT CESARE LOMBROSO'S GHOST

A multitude of genetic, behavioral and environmental factors come together to create mental health problems in teens, study finds.

Washington University in St. Louis

When trying to understand how genetic influences factor into youth behavior, researchers at Washington University in St. Louis have taken the “big trawl” approach, casting their net wide to pull in all the measured traits, behaviors and environments that make up who we are and examine associations with the genetic building blocks comprising risk for mental health problems.

This cutting-edge methodology has turned up valuable new insights into factors related to psychopathological genetic risk, such as stressful life events and screen time. Although the results, published in Nature Mental Health, are unable to say if one causes the other, the findings provide promising leads to understand the nature of psychiatric disorders emerging during adolescence.

“We’re catching all the little fish here,” said Nicole Karcher, assistant professor of psychiatry at WashU Medicine, likening their genetic screening tools to trawling the ocean.

“But now we get to wade through the fish that we caught, and future steps include understanding the extent to which these are meaningful in terms of their ability to reduce risk for mental health concerns.”

An innovative approach to “catching” risk factors

Much of what we know about links between the genome and behavior come from Genome-wide Associations Studies (GWAS), which identify links between specific genetic variants across the genome and a feature of interest, also known as a phenotype. Phenotypes can range from physical characteristics to psychiatric disorders (e.g., depression, anxiety).

Many behavioral disorders are correlated at the genetic level. Results from a GWAS scanning for genetic links to depression, therefore, may also reflect genetic associations with frequently co-occurring conditions such as anxiety.

“We know that one behavioral variable is not going to be the only association with genetic risk, so we were interested in taking a more agnostic, data-driven approach to the wealth of information that is available in large datasets,” said Karcher.

Doing so would hopefully identify not only expected associations between genetic risk and psychiatric symptoms, but also potential novel associations that could improve insight into how psychiatric disorder risk may unfold.

So senior author Karcher and first author Sarah Paul, a graduate student in Ryan Bogdan's Behavioral Research and Imaging Neurogenetics Laboratory at Art & Sciences, ran what’s called a phenome-wide association study (PheWAS) that inverts the GWAS.

Rather than starting with the psychiatric condition and looking for associated genetic variants, their PheWAS started with genetic variants known to be linked with mental health disorders and examined their relationship to hundreds of measured variables reflecting behavior, symptoms, environments, health problems and other phenotypes. They included approximately 1,300 to 1,700 phenotypes in total from the Adolescent Brain Cognitive Development (ABCD) Study.

“We took a pretty broad approach,” said Paul, describing different phenotypes as “anything from impulse control problems and problematic behavior or psychotic-like experiences to screen time, to how much caffeine they consumed.”

Think of it as fishing with a big net.

That means they want to identify associations between genetic predisposition and potentially modifiable risk factors that can be potentially addressed before the onset of psychopathology, Bogdan, the Dean’s Distinguished Professor of Psychological & Brain Sciences in Arts & Sciences, said.

What they caught

The results of the PheWAS show some surprises and confirm some of what they already know about genetic risks and behaviors that are associated with mental health disorders in youth.

The WashU researchers took 11 GWAS and created four broad genetic risk factors, or polygenic scores: neurodevelopmental, internalizing (e.g., depression, anxiety), compulsive and psychotic. Below are some of the associations they found in those categories:

*Genetic risk for neurodevelopmental psychopathology (predominantly ADHD and Autism Spectrum Disorder, as well as Major Depressive Disorder and problematic alcohol use) was associated with some 190 phenotypes including inattention and impulsivity issues, as well as total screen time, sleep problems and psychotic-like experiences. Even environmental conditions like neighborhood crime rates and lower parental monitoring are associated with neurodevelopmental genetic risk.

*Genetic risk for internalizing behavior (Major Depressive Disorder, Generalized Anxiety Disorder, PTSD, as well as problematic alcohol use) were broadly associated with some 120 phenotypes such as depression, stressful life events, psychotic-like experiences and screen time.

*Psychotic risk (predominantly Schizophrenia and Bipolar Disorder) had few phenotype associations aside from lower school involvement and more consumption of energy drinks.

Karcher said it was somewhat surprising that “genetic liability” for mental health concerns may manifest through potentially modifiable behaviors in childhood and early adolescence.

The research sorted hundreds and hundreds of variables potentially associated with genetic risk, and the results highlighted several associations, including the association between neurodevelopmental genetic risk and screentime, she added.

“The PheWAS was able to point out these pockets of associations that may not have been found otherwise,” she said.

One such pocket was the association between psychotic disorder genetic risk and energy drink consumption. These studies are looking at correlation, not causation, so they cannot conclude that energy drink consumption causes psychotic disorders. It could be that there are genetic components that make these individuals more at risk for psychotic disorders and those same components might make these individuals more likely to consume caffeinated beverages.

A similar phenomenon could be a play with the strong association between screen time and neurodevelopmental risk.

The point of the PheWAS is not to sort those details of causation but get pointed in the right direction with “a 20,000-foot view of the associations,” Karcher said.

Time will tell as the ABCD kids get older and genomic databases get more diverse.

“Following these youth into early adulthood will help better inform how genetic risk is associated with things like screen time, psychopathology, symptoms, and sleep over the course of adolescence into early adulthood,” Paul said. “That will help paint a clearer picture of how these links between your overall genetic risk and your behavior and traits change or don’t change over time.”

Overall, the present work illustrates how the PheWAS technique can be used to identify potential targets for future prevention and early intervention strategies, with this study identifying several potentially modifiable targets, such as screen time and caffeinated beverage consumption, that could represent early “catches” for reducing risk for developing mental health concerns.

Previous genome-wide studies of psychiatric diagnoses/phenotypes make use of data from individuals most genetically similar to European reference populations, with limited well-powered GWAS available for other populations in the world. So, one major limitation of this study was that because the GWAS predominantly used data from European reference populations, only ABCD data from individuals with European ancestry could be used in the PheWAS.

“That really limits the generalizability of these findings,” Paul said, “but as more GWAS become available in individuals genetically similar to other reference populations, and as more sophisticated polygenic score approaches are developed, we should be able to expand the study population to be more inclusive.”

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Paul SE, Colbert SMC, Gorelik AJ, Hansen IS, Nagella I, Blaydon L, Hornstein A, Johnson EC, Hatoum AS, Baranger DAA, Elsayed NM, Barch DM, Bogdan R, Karcher NR. Phenome-wide Investigation of Behavioral, Environmental, and Neural Associations with Cross-Disorder Genetic Liability in Youth of European Ancestry. Nat. Mental Health (2024). https://doi.org/10.1038/s44220-024-00313-2

Data for this study were provided by the Adolescent Brain Cognitive Development (ABCD) study , which was funded by awards U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, and U24DA041147 from the NIH and additional federal partners (https://abcdstudy.org/federal-partners.html). This study was supported by R01 DA054750. Authors received funding support from NIH: SEP was supported by F31AA029934. NRK was supported by K23MH12179201. AJG was supported by NSF DGE-213989. ECJ was supported by K01DA051759. ASH was supported by K01AA030083. DMB (R01-MH113883; R01-MH066031; U01-MH109589; U01-A005020803; R01-MH090786), RB (R01-DA054750, R01-AG045231, R01-AG061162, R21-AA027827, R01-DA046224, U01-DA055367). NME was supported by NSF DGE-1745038.

Journal

Nature Mental Health

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Tuesday, June 23, 2026

Can use of popular weight loss medications reduce behaviors linked to violent crime?

Journal

DOI

Article Title

Article Publication Date

Researchers link use of GLP-1 medications to lower risk of violence

Journal

Method of Research

Subject of Research

Article Title

Article Publication Date

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Friday, November 01, 2024

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