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(https://www.psypost.org/virtual-reality-cognitive-training-shows-potential-for-treating-adolescents-with-depression/) Virtual reality cognitive training shows potential for treating adolescents with depression
Jan 19th 2025, 08:00

A study examining the effects of virtual reality cognitive training on Chinese adolescents with mild to moderate depression found that participants’ cognitive performance improved after treatment, and depressive symptoms decreased as well. The research was published in (https://doi.org/10.1016/j.psychres.2024.116144) Psychiatry Research.
Individuals with depression often experience cognitive impairments in addition to other symptoms of the condition, which further exacerbates their disease burden. Cognitive impairment in adolescents with depression often affects areas such as attention, memory, executive function, and processing speed, interfering with academic performance and daily activities. Depressed adolescents may struggle with concentration, leading to difficulties in completing tasks or retaining information.
These impairments are thought to stem from disruptions in brain regions like the prefrontal cortex and hippocampus, as well as imbalances in neurotransmitters such as serotonin and dopamine. Cognitive deficits in depression can persist even during periods of remission, potentially impacting long-term development and quality of life.
Study author Sihui Lyu and her colleagues conducted research to explore the effectiveness of virtual reality cognitive training in improving the cognitive functioning of adolescents with mild to moderate depressive episodes. They hypothesized that this training strategy would both improve participants’ cognitive performance and reduce depressive symptoms.
The study included 93 adolescents with depression and 44 healthy adolescents. Healthy participants were recruited from the community and through online media advertisements, while adolescents with depression were recruited from the First Affiliated Hospital of Jinan University in Guangzhou, China. Participants were between the ages of 12 and 17.
At the start of the study, adolescents with depression were randomly assigned to either undergo a virtual reality cognitive training program or be part of the waitlist control group (a group not receiving treatment during the study but informed they would undergo treatment afterward). Healthy adolescents only completed clinical assessments at the beginning and end of the study.
Participants completed a clinical interview to assess depression symptoms and a cognitive assessment evaluating four cognitive processes: planning, attention, simultaneous processing, and successive processing. These assessments were conducted at the start and end of the study.
The virtual reality cognitive training program required participants to wear virtual reality equipment and complete two training modules. One module aimed to improve attention, while the other targeted working memory. Each module consisted of five training tasks. The training was delivered in 20 sessions, each lasting 30 minutes, over the course of seven weeks. In each session, participants completed three randomly chosen tasks. By the end of the training, all participants had completed all tasks, with each task being repeated four to eight times. During this period, participants in the waitlist group received standard treatment for depression.
Results showed that depressed adolescents performed worse on cognitive tasks at the start of the study compared to healthy adolescents. There was no initial difference in cognitive performance between the two groups of depressed participants. However, after the treatment, the group that underwent virtual reality cognitive training demonstrated significant improvement in all four types of cognitive processes compared to both the waitlist group and their own baseline results. The improvements ranged from moderate to large in magnitude.
At the start of the study, the average severity of depressive symptoms was similar in the two groups of depressed adolescents. After the treatment, depressive symptoms in the cognitive training group improved substantially.
“Our intervention results suggest that the VRCT [virtual reality cognitive training] program may improve cognitive functions and alleviate emotional symptoms in adolescents with mild to moderate depressive episodes. Tailoring intervention strategies that integrate technology to target cognitive impairments could offer valuable additions to existing treatment options, promoting full recovery and fostering positive developmental trajectories in this group,” the study authors concluded.
The study provides preliminary evidence for the effectiveness of a novel method for potentially treating adolescents with depression. However, it is important to note that all assessments were either based on self-reports or highly dependent on participants’ motivation. Additionally, training group participants were fully aware of researchers’ expectations and the purpose of the intervention, making it likely that the observed effects were at least partly influenced by the Hawthorne effect—where participants alter their behavior to align with perceived expectations.
The paper, “(https://doi.org/10.1016/j.psychres.2024.116144) Effects of virtual reality-based cognitive training for adolescents with depressive episodes: A pilot randomized controlled study,” was authored by Sihui Lyu, Shuming Zhong, Yange Luo, Shuya Yan, Hanglin Ran, Manying Duan, Kailin Song, Kaiwei Ye, Haofei Miao, Yilei Hu, Zijin Song, Shunkai Lai, Yiliang Zhang, Jiali He, Yunxia Zhu, and Yanbin Jia.

(https://www.psypost.org/scientists-just-found-a-novel-way-to-uncover-ai-biases-and-the-results-are-unexpected/) Scientists just found a novel way to uncover AI biases — and the results are unexpected
Jan 19th 2025, 06:00

Humor is emerging as a revealing lens for understanding bias within artificial intelligence systems. A new study published in (https://www.nature.com/articles/s41598-024-83384-6) Scientific Reports found that when tools like ChatGPT and DALL-E were prompted to make images “funnier,” the resulting shifts in representation highlighted underlying patterns of bias. Stereotypical portrayals of age, body weight, and visual impairments became more prominent, while depictions of racial and gender minorities decreased.
Generative artificial intelligence tools, such as OpenAI’s ChatGPT and DALL-E, have garnered attention for their ability to create content across a variety of fields. ChatGPT, a large language model, processes and generates human-like text based on vast datasets it was trained on. It understands context, predicts responses, and produces coherent and meaningful text. Similarly, DALL-E is a text-to-image generator that creates visual content based on detailed prompts.
Humor is a complex human skill that combines elements of surprise, timing, and intent. Studies have shown that artificial intelligence can not only produce humor (https://www.psypost.org/ai-outshines-humans-in-humor-study-finds-chatgpt-is-as-funny-as-the-onion/) but sometimes outperform human creators. For example, a study in PLOS ONE found that AI-generated jokes were rated as equally or even more humorous than those created by human participants, including professional satirists. This suggests that AI’s ability to detect patterns and generate content extends to crafting jokes that resonate broadly, even without the emotional or experiential depth humans bring to humor.
The current study sought to build on this foundation by examining how humor influences bias in AI-generated images. Researchers were intrigued by an observation: when they asked ChatGPT to modify images to make them “funnier,” it often introduced exaggerated or stereotypical traits. This pattern raised concerns about whether humor in AI systems could reinforce stereotypes, particularly against groups that have historically been targets of prejudice.
“I am very interested in studying how consumers interact with new and emerging technologies such as generative AI. At one point, my co-authors and I noticed that when we instructed ChatGPT to make images ‘funnier,’ it would often introduce odd and stereotypical shifts, such as changing a white man driving a car into an obese man wearing oversized glasses,” said study author (https://marketing.wharton.upenn.edu/profile/saumure/) Roger Saumure, a PhD student at the University of Pennsylvania’s Wharton School.
“This struck us as more than a simple glitch and suggested that there might be systematic biases that arise when large language models interact with text-to-image generators. Given a large body of research in psychology and sociology that shows that humor can exacerbate stereotypes, we felt it was both theoretically and practically important to empirically test whether the interaction between AI models could reinforce stereotypes.”
The research involved a systematic audit of AI-generated images. Two research assistants (blind to the study’s hypothesis) inputted 150 prompts describing human activities into a popular generative AI system. These prompts generated 150 initial images. To create a second set of images, the assistants instructed the AI to make each image “funnier.” The process was repeated, resulting in 600 images across two conditions (original and funnier versions).
The team then analyzed both the visual features of the images and the textual descriptors used by the AI to generate them. Each image was coded for five dimensions of representation: race, gender, age, body weight, and visual impairment. The researchers noted whether traits in the “funnier” images deviated from those in the original images and whether these deviations reflected stereotypical portrayals.
The researchers found that stereotypical portrayals of older individuals, those with high body weight, and visually impaired people became more prevalent in the “funnier” images. Meanwhile, representations of racial and gender minorities—groups that are often at the center of discussions about bias—decreased.
“What was most striking to us is that the pattern of bias we observed was in the opposite direction of what the literature predicted,” Saumure told PsyPost. “Initially, we expected to replicate known patterns of racial and gender bias through the lens of humor, while elucidating whether the bias stemmed from the text or image models.”
“Yet we ended up finding that, if anything, the generative AI showed less bias for these categories while being biased against less politically sensitive groups. That is, when we asked the AI to make images ‘funnier,’ politically sensitive groups (racial and gender minorities) were less likely to appear, while groups like older adults, visually impaired individuals, or those with high body weight were more frequently depicted.”
Humor prompts often exaggerated traits associated with non-politically sensitive groups, such as making older individuals appear frail or depicting people with high body weight in an unflattering, exaggerated manner. For instance, a neutral depiction of a person reading a book might transform into a caricature of an older adult with thick glasses and exaggerated physical features.
Interestingly, the bias appeared to originate primarily from the text-to-image generator rather than the language model. While ChatGPT produced detailed textual descriptions to guide the image generation process, the changes in representation seemed to stem from how DALL-E interpreted these prompts to create visuals.
“A primary takeaway from this study is that contemporary AI systems may overcorrect for bias against politically salient groups (e.g., gender and race) while under-correcting for bias against less politically salient groups (e.g., higher body weight, older age, visual impairment),” Saumure said. “Thus, even though companies like OpenAI have made considerable efforts in reducing biases, these have likely mostly been toward keeping consumers and the media satisfied, rather than to reduce global bias overall. We believe this underscores the need for businesses and policymakers to take a more global and inclusive approach to auditing all forms of AI bias.”
“A second takeaway from our work is that it is particularly challenging to eliminate bias from certain modalities (i.e., image as opposed to text). A third takeaway is that humor can serve as a very useful lens for uncovering sometimes subtle biases in various types of AI output—including text, images, audio, and other modalities.”
The researchers also noted that underrepresentation of certain groups was apparent even before the humor prompts were introduced. “For instance, in our initial set of images, only about 9.80% featured female individuals and 0% featured individuals with high body weight—a severe underestimation of the national averages of 73.60% and 50.50%,” Saumure explained. “This result suggests that AI models may be reflecting default cultural assumptions of ‘thin, male, and White’ as the norm. Going forward, it will be important for companies to address and correct these omissions in order to create more inclusive and equitable AI systems.”
However, it is important to note that the research focused on a single generative AI system, leaving open the question of whether similar patterns occur in other models. Cultural context is another variable: AI systems trained in different regions may exhibit biases that reflect local sensitivities and social dynamics.
“Our theoretical perspective also predicts that the patterns of bias should look in different cultures, depending on which particular groups are viewed as politically sensitive,” Saumure said. “For instance, we should expect LLMs that generate images based on Hindi prompts to be more likely to correct for biases against Muslims, given the more salient tension in that culture between Hindus and Muslims.”
“I look forward to continuing my research on how consumers interact with generative AI. I am currently investigating the persuasive power of these technologies—how they can persuade consumers to communicate specific messages or reframe our interpretations of information. Ultimately, my goal is to better understand how such tools shape consumer behavior and wellbeing.”
The study, “(https://doi.org/10.1038/s41598-024-83384-6) Humor as a window into generative AI bias,” was authored by Roger Saumure, Julian De Freitas, and Stefano Puntoni.

(https://www.psypost.org/brief-exercise-sessions-linked-to-small-but-consistent-boosts-in-brain-performance/) Brief exercise sessions linked to small but consistent boosts in brain performance
Jan 18th 2025, 14:00

An analysis of decades of research into the cognitive effects of exercise suggests that even a single workout session can positively influence mental performance. The study, conducted by researchers at UC Santa Barbara and published in (https://doi.org/10.1038/s44271-024-00124-2) Communications Psychology, found that brief bouts of exercise have small but measurable impacts on cognitive tasks, particularly those requiring quick reactions and mental flexibility. However, these effects vary depending on the type, intensity, and timing of the exercise, as well as the cognitive task being performed.
While it is well-established that regular exercise enhances physical health and long-term brain function, the effects of single exercise sessions remain less clear. The researchers sought to address discrepancies in previous findings, which alternately suggested that single workouts improve, hinder, or have no effect on cognitive performance. They aimed to identify consistent patterns in the relationship between acute exercise and mental processes, with a particular focus on cognitive domains like attention, memory, and executive function.
“Human cognitive neuroscience is a field dedicated to understanding the neural mechanism of cognitive function and how they relate to behavior. The field is based on laboratory experiments in which participants engage in tasks that we can tightly control and measure performance. Sometimes we also do measurements of brain activity using a variety of neuroimaging methods,” said study author Barry Giesbrecht, a professor and head of (https://attentionlab.psych.ucsb.edu/) the Attention Lab at UC Santa Barbara.
“In my lab, we are very interested in how exercise and other changes in physiological state influence these processes. One of the most consistent findings in the literature is that exercise interventions (e.g., something like a program that you would engage in ~3 times a week over months) improve cognition and can even promote neurogenesis. Studies looking at the effects of single, acute bouts of exercise are much more mixed, largely due to variability in the cognitive tasks and exercise protocol. Here, what we tried to do is get a sense of what the most consistent patterns were in the literature.”
To assess the cognitive effects of acute exercise, the researchers conducted a meta-analysis of studies published between 1995 and 2023. They included experimental studies that tested individuals aged 18 to 45, focusing on non-clinical, healthy participants. Eligible studies had to compare cognitive performance before and after exercise or between exercise and control conditions. Cognitive domains assessed ranged from executive function and attention to memory and motor skills.
The researchers conducted a meta-analysis, synthesizing data from 113 studies (with 4,390 participants in total) published between 1995 and 2023 to evaluate the effects of a single bout of exercise on cognitive performance. The studies included in the analysis were selected based on specific criteria: they had to involve experimental designs where participants performed cognitive tasks either during or after an acute exercise session. Eligible studies focused on healthy adults aged 18 to 45.
To ensure a broad perspective, the meta-analysis included various exercise types, such as cycling, running, high-intensity interval training (HIIT), resistance training, and sport-based activities. The intensity of exercise ranged from light to vigorous, and durations varied across studies. Cognitive tasks tested participants’ performance in domains such as memory, attention, executive function, motor skills, and decision-making. Reaction times and task accuracy were measured as primary indicators of cognitive performance.
The researchers employed Bayesian statistical methods to analyze the data. This approach allowed for a more nuanced understanding of the evidence, incorporating probabilities and variability between studies. Unlike traditional statistical methods, Bayesian analysis estimates the likelihood of certain outcomes given the observed data, making it particularly well-suited for assessing the heterogeneous effects of exercise on cognition. Moderators such as exercise type, intensity, duration, and timing relative to cognitive testing were included in the analysis to explore their influence on the results.
The meta-analysis revealed that a single bout of exercise had a small but significant positive effect on overall cognitive performance. Tasks targeting executive functions, such as inhibition and cognitive flexibility, were linked to the most consistent improvements. Attention and tasks requiring rapid reaction times also showed measurable enhancements. However, outcomes for memory and other cognitive domains were less consistent.
The researchers also identified significant moderators. For instance, the type of exercise played a critical role, with cycling and high-intensity interval training (HIIT) showing the most substantial cognitive benefits, particularly for executive functions such as inhibition and planning.
“With this particular finding, we have to be a bit careful because there are many fewer HIIT studies in the literature, so with more studies this may change,” Giesbrecht said.
The intensity of exercise also emerged as an important factor. Vigorous-intensity workouts produced the strongest cognitive enhancements, while moderate-intensity exercise yielded smaller but still noticeable benefits. These findings suggest that the physiological and neurochemical changes induced by higher-intensity exercise might underlie its superior impact on cognitive performance.
“We all know that consistent exercise has positive effects on emotional and cognitive function, in addition to the general improvements in health,” Giesbrecht told PsyPost. “Here we show that even a single acute bout of exercise can have positive effects on cognition, especially executive functioning.”
The researchers also observed substantial variability between studies, emphasizing the importance of context in interpreting the effects of exercise on cognition. Factors such as the design of cognitive tasks, participant demographics, and experimental protocols all contributed to differences in outcomes. For instance, simpler cognitive tasks may have reached ceiling effects, limiting the ability to detect exercise-induced improvements. Additionally, variations in how exercise intensity and duration were reported across studies introduced further complexity.
“While consistent, the overall effect of a single bout of exercise was generally on the small side,” Giesbrecht noted. “We think that an intriguing hypothesis that could explain this finding, besides the variability in the exercise protocols themselves, is that most studies have people engage in a cognitive task while exercising or shortly after exercise. This is very different than the real-world, which typically requires us to integrate the actions of our body and cognitive systems when doing daily activities. We are about to engage in a series of studies that will systematically test this idea using a combination of lab tasks and real-world activities.”
The paper, “(https://doi.org/10.1038/s44271-024-00124-2) A systematic review and Bayesian meta-analysis provide evidence for an effect of acute physical activity on cognition in young adults,” was authored by Jordan Garrett, Carly Chak, Tom Bullock, and Barry Giesbrecht.

(https://www.psypost.org/individuals-with-thicker-insula-brain-region-take-more-cocaine-when-given-a-chance-study-finds/) Individuals with thicker insula brain region take more cocaine when given a chance, study finds
Jan 18th 2025, 12:00

A study of individuals with cocaine use disorder found that, when given the option, those with a thicker insula region in the brain administered more cocaine infusions to themselves. Women generally self-administered more cocaine infusions than men. The research was published in the (https://doi.org/10.1080/00952990.2024.2318585) American Journal of Drug and Alcohol Abuse.
Cocaine is a powerful stimulant drug derived from the coca plant, known for its ability to increase alertness, energy, and feelings of euphoria. It works by interfering with the brain’s dopamine system, causing a buildup of the neurotransmitter dopamine that amplifies pleasure and reward sensations. Cocaine is highly addictive, and its use can lead to serious health problems, including heart attacks, strokes, and mental health disorders such as anxiety and paranoia. It is commonly consumed as a white powder (snorted) or in its crystalline form (smoked as “crack cocaine”) but can also be administered via infusions.
Prolonged cocaine use can result in severe physical, psychological, and social consequences, leading to a condition known as cocaine use disorder. Cocaine use disorder is characterized by compulsive cocaine use despite negative consequences, such as health problems, strained relationships, or legal issues. It involves both physical dependence, marked by withdrawal symptoms, and psychological dependence, which includes intense cravings and loss of control over usage. It is often accompanied by severe mental health issues, including anxiety, paranoia, and depression.
Study author Robert J. Kohler and his colleagues sought to investigate associations between cocaine self-administration behavior and characteristics of subcortical and cortical brain regions. They hypothesized that the number of cocaine self-infusions a person chooses would be associated with gray matter volume in the striatum, amygdala, and hippocampus regions of the brain. To explore this, they conducted a neuroimaging study.
The study involved 33 adults with cocaine use disorder who were recruited from the community. These participants were not seeking treatment for their disorder and were otherwise medically healthy. Of the participants, 10 were women. All reported using cocaine either through smoking or infusions for at least one year. The researchers confirmed recent cocaine use by analyzing the participants’ urine samples. The average age of the participants was 44 years.
Participants were brought to an inpatient clinic for the experiment. There, they were provided with an analgesia pump they could use to inject intravenous cocaine hydrochloride into their veins. They were assigned appropriate doses based on their body weight and were given one hour to administer cocaine infusions. During this time, they could self-administer up to 12 cocaine infusions, with a mandatory 5-minute lockout period between infusions.
The researchers tracked the number of infusions each participant administered during the hour. Participants also underwent magnetic resonance imaging (MRI), which the researchers used to examine the morphometric characteristics of their brains.
On average, participants administered seven cocaine infusions to themselves during the 60-minute session, with an average interval of 10 minutes between infusions. Participants with higher gray matter volume in the caudate region of the brain and lower gray matter volume in the putamen region tended to administer more infusions. Individuals with a thicker insula region also gave themselves more infusions. Additionally, women self-administered cocaine more frequently than men.
Gray matter in the brain consists of neuronal cell bodies, dendrites, and synapses, playing a crucial role in processing information, muscle control, and sensory perception. The caudate and putamen regions are involved in motor control, learning, and reward processing, while the insula plays a key role in emotional regulation, sensory integration, and perception of internal body states.
“In sum, the present study identified brain structural measures associated with cocaine self-administration in people with CUD [cocaine use disorder]. The results suggest potential relationships between behavioral phenotypes (e.g., impulsivity and compulsive reward-seeking) and brain structural features that may underlie cocaine use, and these possibilities warrant direct examination in future studies,” the study authors concluded.
The study contributes to the scientific understanding of the neural underpinnings of drug-related behaviors. However, the sample size was very small, and the association between the listed brain characteristics and cocaine use behavior was relatively weak. Additionally, studies examining the relationship between brain structures and behavior are known for producing inconsistent results. Research with larger or more diverse samples may yield different findings.
The paper, “(https://doi.org/10.1080/00952990.2024.2318585) Cocaine self-administration behavior is associated with subcortical and cortical morphometry measures in individuals with cocaine use disorder,” was authored by Robert J. Kohler, Simon Zhornitsky, Marc N. Potenza, Sarah W. Yip, Patrick Worhunsky, and Gustavo A. Angarita.

(https://www.psypost.org/semaglutide-and-liraglutide-linked-to-lower-alcohol-related-hospitalization-risk/) Semaglutide and liraglutide linked to lower alcohol-related hospitalization risk
Jan 18th 2025, 10:00

A recent study published in (https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2825650) JAMA Psychiatry has uncovered promising evidence suggesting that glucagon-like peptide-1 (GLP-1) receptor agonists, particularly semaglutide and liraglutide, may be effective treatments for alcohol use disorder. These medications, originally developed to treat type 2 diabetes and obesity, were associated with reduced risks of hospitalization due to alcohol use disorder among individuals who also had comorbid obesity or diabetes. Strikingly, the reduction in risk was greater than that observed with officially approved medications for alcohol use disorder, highlighting the need for further research to confirm these findings.
Alcohol use disorder is a chronic condition characterized by the inability to control alcohol consumption despite negative consequences on one’s health, relationships, and daily life. It is a complex disorder influenced by genetic, psychological, and environmental factors.
Globally, alcohol use disorder is a leading cause of disability and death, contributing to liver disease, mental health issues, accidents, and various chronic conditions. Treatment typically involves a combination of psychosocial therapies, such as counseling or support groups, and pharmacological interventions. While medications like naltrexone, disulfiram, and acamprosate are approved for treating alcohol use disorder, they are often underprescribed and may not work for everyone, leaving a significant gap in effective treatment options.
GLP-1 agonists, on the other hand, are medications originally developed for managing type 2 diabetes and obesity. These drugs mimic the effects of a hormone called glucagon-like peptide-1, which regulates blood sugar levels and appetite. In addition to their metabolic benefits, research has suggested that GLP-1 agonists may influence the brain’s reward pathways, which play a central role in addictive behaviors. Preclinical studies in animals and anecdotal human observations have hinted at their ability to reduce alcohol cravings and consumption.
“I’ve been working as an addiction specialist and started to get feedback both from patients and colleagues that for some reason individuals treated with GLP-1 agonists (especially semaglutide) seem to lose interest in using alcohol (some even develop an aversion),” said study author Markku Lähteenvuo, a docent in forensic psychiatry at the University of Eastern Finland and the Niuvanniemi Hospital.
“We have some great medications to treat alcohol use disorder, but they are not suitable or effective for every individual, so we thought it would be really great to get additional medication to the toolbox. If this could be attained by repurposing (using existing approved medications for new indications, it would be even better, as this is often faster than starting a development project from scratch.”
The researchers analyzed data from nationwide Swedish electronic registries, which allowed them to study a cohort of over 227,000 individuals diagnosed with alcohol use disorder between 2006 and 2021. These individuals were followed for up to 15 years, providing a robust dataset for examining the relationship between medication use and health outcomes.
To identify medication use, the researchers employed a sophisticated method to reconstruct periods when participants were actively prescribed certain drugs. The primary focus was on GLP-1 agonists, including semaglutide and liraglutide, while a secondary focus was placed on officially approved alcohol use disorder medications, such as naltrexone, disulfiram, and acamprosate. The study primarily examined the risk of hospitalization due to alcohol use disorder as the outcome of interest. Secondary outcomes included hospitalization for other substance use disorders, physical illnesses, and suicide attempts.
A unique feature of the study was its within-individual design, which compared periods of medication use to periods of non-use within the same individuals. This approach reduced the potential for confounding factors that could bias the results, such as differences in individual health status or baseline risk.
The study found that the use of semaglutide and liraglutide was associated with a reduced risk of hospitalization due to alcohol use disorder. Semaglutide use was linked to a 36% reduction in risk, while liraglutide was associated with a 28% reduction. These reductions were markedly greater than those observed with approved medications for alcohol use disorder. For example, naltrexone, the most effective among the approved options, was associated with a 14% risk reduction.
“It was a surprise that the hazard ratios for the GLP-1 agonists were on par (and even better) with those of actual alcohol use disorder medications, like naltrexone, although we didn’t do any straight head-to-head comparisons between these medications,” Lähteenvuo told PsyPost.
Beyond alcohol use disorder, the medications also reduced the risk of hospitalization for any substance use disorder and physical illnesses. Semaglutide was associated with a 32% reduction in hospitalizations for substance use disorders and a 22% reduction in hospitalizations for physical illnesses. Similar patterns were observed for liraglutide, albeit with slightly smaller effects.
Interestingly, the study did not find a statistically significant association between GLP-1 agonist use and hospitalization due to suicide attempts. This finding contrasts with the increased risk of suicide attempts observed with some approved medications for alcohol use disorder.
“Our study is register based, so any results need to be taken with a grain of salt and we shouldn’t talk about causality,” Lähteenvuo explained. “However, I think our study is another in a line of already quite a few that seem to indicate that GLP-1 agonists might be helpful in the treatment of alcohol use disorder. There are some mechanistic studies, animal studies, register studies and now I hear the first randomized controlled trial is also coming out, which all seem to indicate we might be onto something here.”
“So, I think our study results should be treated as a preliminary indication that GLP-1 agonists might be usable for alcohol use disorder, but this needs to be verified in clinical studies before patients get prescribed these medications. However, as these medications do have approved indications, maybe they could be helpful for patients with diabetes (an official indication) who are also looking for help with alcohol abuse, especially in a situation where the doctor is contemplating between two equally effective alternatives diabetes wise.
“We also didn’t detect any increased signal for suicidal behavior,” Lähteenvuo continued, “which was a concern a few years ago for GLP-1 agonists, and this is in line with the recent very large inquiry made by the European Medicines Agency, which also (https://www.statnews.com/2024/04/12/europe-obesity-drugs-suicidal-thoughts/) did not find any evidence for an increase in suicidal behavior.”
But the study has important limitations. As an observational study, it cannot establish causality, only associations. The within-individual design helps mitigate some biases, but residual confounding cannot be entirely ruled out. Additionally, the study relied on registry data, which may not capture all relevant variables, such as alcohol consumption patterns or adherence to prescribed medications.
The researchers emphasize the need for randomized clinical trials to confirm the effectiveness and safety of glucagon-like peptide-1 receptor agonists in treating alcohol use disorder. These trials would provide more definitive evidence by directly comparing the medications to placebo and approved treatments in controlled settings.
“As our study was a register study there can always remain some sources of bias that we weren’t able to detect or control for,” Lähteenvuo noted. “We did do quite a few additional analyses to do our best to remove bias, but it is always possible some may remain, which is why it is always important to have other groups confirm our findings in their own cohorts and in randomized controlled trials. Also, register studies can never speak for causality, as mentioned above, only associations.”
“Our research group (lead by Professor Jari Tiihonen) has done medical epidemiology for decades. We are hoping to continue on that line and make interesting discoveries using the registry data, both to look at comparative effectiveness of approved medications, but also to look at possible repurposing aspects, such as in this study.”
“I cannot stress enough that no one should be prescribed GLP-1 agonists for alcohol use disorder based on our results alone,” Lähteenvuo added. “We still need confirmatory randomized controlled trials.”
The study, “(https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2825650) Repurposing Semaglutide and Liraglutide for Alcohol Use Disorder,” was authored by Markku Lähteenvuo, Jari Tiihonen, Anssi Solismaa, Antti Tanskanen, Ellenor Mittendorfer-Rutz, and Heidi Taipale.

Forwarded by:
Michael Reeder LCPC
Baltimore, MD

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