Video Game Addiction and Kids: Understanding Internet Gaming Disorder 

Every night, getting her 16-year-old son Ben to go to bed was a battle Karla would dread. He played video games online in the evening for hours, chatting with friends on his headset. As the time got late and she reminded him it was bedtime, inevitably he’d be in the middle of some campaign and wouldn’t stop. All his friends were still playing together, Ben would argue, and he would miss out.  

It’s a classic disagreement in families: Parents are worried that their kids have a video game addiction — they’re unable to limit their time spent playing — and kids think their parents are overreacting. Who’s right?  

The jury is still out. While researchers and clinicians acknowledge that gaming has addictive qualities, what constitutes a disorder and how to recognize the signs are still up for debate.  

Why parents worry about video game addiction 

“There are lots of reasons why parents don’t like video games,” says Dave Anderson, PhD, a clinical psychologist who treats teens at the Child Mind Institute. “They’ll say kids spend too much time playing, and they’re not spending enough time on schoolwork. The video games are violent and contain sexualized content. They’re playing the game online with their friends, and in the chat, they seem to be saying inappropriate things.” 

For many kids, video games are a place for entertainment and social connection — it’s fun and something to do with friends. Problems arise when parents need them to stop. “A lot of parents will say it leads to major conflicts when we’re asking them to stop playing video games,” Dr. Anderson says. “But that does not necessarily mean the kid has a gaming disorder.”  

What is internet gaming disorder? 

While parents might call it “video game addiction,” it’s called “internet gaming disorder” in the official Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Internet gaming disorder is not a fully recognized disorder in the most recent edition of the DSM-5. Since 2013, it has been provisional, categorized as a condition for further study, underscoring the lack of clear consensus on whether it should be a standalone disorder, even as concerns mount about the mental health effects of video games and internet use generally. 

The DSM-5 proposes that someone could have internet gaming disorder if they experience at least five of the following over a 12-month period: 

  • Preoccupation with video games where it becomes the dominant activity in daily life 
  • Withdrawal symptoms such as irritability, anxiety, or sadness when games are taken away  
  • Needing to spend increasing amounts of time playing video games 
  • Has made unsuccessful attempts to control how much time they spend playing games  
  • Loss of interest in other hobbies  
  • Has continued game-playing despite being aware that it’s causing problems in their life 
  • Has lied to others about how much they are playing video games 
  • Uses gaming to escape or relieve a negative mood 
  • Has jeopardized or lost a significant relationship, job, or educational opportunity because of gaming 

While gaming disorder hasn’t yet been accepted as an official disorder in the United States, the World Health Organization (WHO) adopted it in their standard classification in 2019, and it went into effect in 2022. The criteria are simpler in what’s called the International Classification of Diseases (ICD-11). By the ICD-11 definition, someone has a gaming disorder if they fit at least two of the following over a 12-month period:  

  • Impaired control over gaming (e.g., onset, frequency, intensity) 
  • Increased priority given to gaming so that it takes precedence over other life interests and daily activities 
  • Continuation or escalation of gaming despite negative consequences 

Some researchers argue that the simpler ICD-11 definition, with its focus on how gaming negatively affects other aspects of life, is better at capturing when gaming is truly a problem. Kids who use gaming as an escape when they are unhappy might get labeled with internet gaming disorder according to the DSM-5, for example, so clinicians are concerned about risks of overdiagnosis. While there is growing recognition that excessive gaming can be harmful, experts are still studying whether it is an addictive disorder.  

Internet gaming disorder and other diagnoses 

Dr. Anderson notes that gaming disorder rarely occurs without other disorders, such as ADHD, depression, or social anxiety. “Most of the time we see problematic gaming, it is co-occurring with something else, like ADHD,” he says. “Or they might be on the autism spectrum, and having a hard time making friends, so gaming becomes a kind of retreat. Or they’re depressed, and they feel like other activities aren’t necessarily going to be that rewarding. So they turn to gaming.” 

But that doesn’t mean that it isn’t important to take it seriously. Douglas Gentile, PhD, a professor of psychology at Iowa State University who researches the effects of video games and media, notes that several disorders occurring together isn’t unusual. “In fact comorbidity is the norm, not the exception, in mental health,” he says. And he adds that his own research has found evidence that problematic gaming can lead to or exacerbate depression. 

“Let’s say there’s a kid who’s not doing well in school, doesn’t have a lot of friends and gets depressed,” he hypothesizes. “So he goes home and he plays games as a way of relieving the stress of that. And that, of course, doesn’t help him make new friends, and it doesn’t help his grades. So he doesn’t get better at those. So he gets more depressed, so he plays more games, so he gets more depressed, right? At some point, the gaming can become a problem on its own.” 

Dr. Gentile stresses that it’s valuable for pediatricians, clinicians, and counselors to ask about gaming habits along with other mental health concerns. That’s why he hopes gaming disorder will be recognized as a full disorder in the next edition of the DSM: “We will start remembering, oh, we should ask about this, too, because it often does co-occur with ADHD, depression, anxiety, social phobia, poor school performance, aggression.” 

How to tell when gaming is a problem 

When a family is concerned about excessive time spent playing video games, Dr. Anderson will ask families for information:  

  • How much time does your child spend gaming?   
  • How does it impair their functioning and academic performance? 
  • How does it affect their sleep? 
  • How does it lead to conflict?  
  • What other diagnoses do they have? 

Dr. Anderson is cautious about making the diagnosis of gaming disorder if he thinks there’s an underlying condition, because treating that underlying condition might mean the problematic gaming will resolve as well.  

“If I think a kid’s depressed and they’re also gaming too much, I am going to make sure that I emphasize the treatment for depression,” Dr. Anderson says. “Because treatment for depression involves behavioral activation — getting the kid involved in certain activities in life, boosting their mood with that kind of that involvement and social support — which is antithetical to the gaming. So that would treat the downstream problem of gaming.” 

Treatment for internet gaming disorder 

Treatment for internet gaming disorder usually involves cognitive behavioral therapy (CBT), including emotion regulation training skills, which can help people face their problems in life if they’ve been using gaming as an escape. Clinicians also may use motivational interviewing and family-based therapy.   

Dr. Gentile has seen programs where family involvement seems to make a difference. One theory, he says, is that kids play video games because it satisfies the deep human need for autonomy, belonging, and competence: They are in control, play with friends, and are good at it.  

“If you’re not getting these needs met in real life but you’re getting them met by playing games, you’re more motivated to keep doing the games,” Dr. Gentile says. So the program works with families to get those needs filled with real-life activities, like learning to fish or joining a sports team. Parents also sit down and learn to play video games alongside their child, so they better understand why the kid likes it so much — and that creates a bridge to help improve communication.  

Setting boundaries on gaming 

While some parents want kids to stop gaming entirely, Dr. Anderson advises against that in most cases. “There are a lot of kids who see themselves as gamers — it’s a part of their identity,” he says. Instead, he encourages parents to place reasonable boundaries on gaming so that their child is investing enough time in four main areas: academics, extracurricular activities, face-to-face time with friends, and sleep.  

“This is the thing we’re trying to collaboratively problem solve for,” Dr. Anderson says. “How do we get it so that you complete your homework, you have at least one activity you’re invested in — whether you play an instrument or a sport, or you’re in the school play. You’re spending time with friends in person, and you’re getting enough sleep.” When those are in place, then families can test out having the child engage in a moderate amount of gaming. “Time spent on games is a want, not a need. It’s earned,” he says. 

Kids will push back on restrictions, of course. “That just means that we might need more of a behavioral approach — how they earn video game playing time, or think more about the consequences if they, for example, break the controller when they come off of it,” Dr. Anderson says.    

“The complaints we hear from kids are, ‘My friends are on at different times. You’re making it so I can’t connect to my friends,’” he says. “And we’ll say, ‘Look, we’re willing to make a reasonable accommodation to try to figure out how you can be on with your friends at the right time. We need these other things that are best for your development. We can then negotiate about when gaming happens.’” 

Tips to limit video games 

To enforce limits on gaming, Dr. Anderson coaches parents on how to make sure games aren’t available except during the designated times. With younger kids, games are usually played on devices like an iPad that can be taken away. The difficulty in setting boundaries, he says, “usually involves an ‘extinction burst,’ which is the idea that if you’ve got a kid who throws tantrums, their tantrums are going to get worse before they get better when we set boundaries.” He helps parents make a plan to maintain everyone’s safety to get past these behaviors, and he works with the child to learn emotion regulation skills to use when they have to stop doing an activity they enjoy.  

But older kids need computers to do schoolwork, so limiting access to games is more difficult. To control cellphone use, he suggests setting screen time limits or blocking apps by using a device like Brick. To control access to video game consoles or computers, parents can remove the power cord.  

With kids of all ages, families work on reducing conflict by making access to games something that is predictable and available as long as their other essential developmental needs are fulfilled. 

“I want parents to realize that all of those symptoms in youth don’t happen in isolation,” Dr. Anderson says. “Even if you think your child has internet gaming disorder, frequently what we want is a comprehensive diagnostic evaluation to be sure there’s not something else treatable that’s underlying this behavior. Then we can then restore a bit of balance to life and make it so that gaming is not the major activity this kid’s engaging in.” 

Frequently Asked Questions

What is internet gaming disorder?

Internet gaming disorder is a term used for playing video games so much that it’s difficult to control and starts interfering with important parts of life. It’s included in the DSM-5 as a condition for further study, meaning experts are still debating exactly how it should be defined.

Is video game addiction a real addiction?

Experts agree that excessive gaming can become problematic for some kids and adults, but there is still debate about whether it should be categorized as an addiction disorder.

What are the symptoms of gaming addiction?

Warning signs include being unable to cut back on gaming, losing interest in other activities, becoming upset when gaming is restricted, and continuing to play despite negative consequences. Gaming can also start affecting sleep, school performance, friendships, or family relationships.

How is internet gaming disorder diagnosed?

Clinicians look at whether gaming has become hard to control and whether it is causing significant problems in daily life over an extended period of time. They also consider factors like sleep, school performance, family conflict, and whether conditions such as ADHD, anxiety, or depression may be contributing to the behavior.

The post Video Game Addiction and Kids: Understanding Internet Gaming Disorder  appeared first on Child Mind Institute.

Exploring Real-World Use of AI Chatbots for Mental Health Support: Cross-Sectional Survey Study

<strong>Background:</strong> In recent years, innovations in generative AI, in particular large language models (LLMs) in the form of AI chatbots, have found their way to the general public. First studies indicate a growing prevalence of individuals talking to AI chatbots about mental health–related topics; yet, knowledge of how, why, and which individuals are using these AI chatbots for their mental health is limited. <strong>Objective:</strong> This study aimed to provide insights into the use of AI chatbot–delivered mental health support. <strong>Methods:</strong> To do so, an online survey in 2 Belgian samples was conducted. A student sample was collected, and individuals who used AI chatbots for mental health support were included (approximately 40% of the student sample were eligible users). Second, a recruitment call for users of AI chatbots for mental health support was launched in the general public. Data from 349 participants, 276 members of the general public, and 73 students were included in the analyses. <strong>Results:</strong> Descriptive analyses were used to report the use of AI chatbot–delivered mental health support. Most respondents in the present samples were women and indicated having received or receiving professional mental health support. The most common conversation topics across both samples focused on personal and interpersonal issues. Freely accessible AI chatbots, mainly ChatGPT, were the predominant choice in both samples and were mainly chosen for their constant availability and accessibility. Respondents in the student sample also preferred their anonymity, and those in the general sample also used them because they felt supported by them. The preliminary associations found between digital working alliance and engagement factors in the student sample and in the general sample suggest that relational factors might play a role in sustained AI chatbot use but warrant further investigation. <strong>Conclusions:</strong> To conclude, this study confirms that general-purpose AI chatbots that are not designed or regulated for mental health support, specifically ChatGPT, are being used to obtain social and emotional support, often by individuals already familiar with professional mental health support.

Large Language Model–Based Behavioral Activation Chatbot for Young People With Depression Using Artificial Users and Clinical Experts: Mixed Methods Evaluation

Background: Mental health chatbots are increasingly used to support people with depressive symptoms, and large language models make these systems more flexible than rule-based chatbots. However, it remains unclear how well large language model–based chatbots deliver structured psychological interventions. Objective: This study examined how well a GPT-4o–based chatbot delivered a behavioral activation intervention for young people with depression using sessions with artificial users and clinical expert assessment. It also identified limitations and potential refinements. Methods: We implemented a GPT-4o (gpt-4o-2024-08-06; OpenAI)–based chatbot using a structured system prompt to deliver a single-session behavioral activation intervention for people with depression aged 14 to 29 years. We generated 48 sessions with GPT-4o–based artificial users derived from clinical vignettes varying across 7 characteristics. Ten clinical experts, either licensed psychotherapists or advanced psychotherapy trainees, independently assessed the sessions using the 14-item Quality of Behavioral Activation Scale (Q-BAS), rated from 0 to 6, supplemented by rating therapeutic capabilities, artificial user authenticity and difficulty, and qualitative feedback. Results: The chatbot completed all 7 intervention phases in every session. The mean holistic session quality rating was 3.94 (SD 1.23), and the mean Q-BAS rating was 4.03 (SD 1.18). Thirteen of 14 Q-BAS components exceeded the satisfactory threshold of 3. Ratings were highest for mood assessment (mean 5.42, SD 1.09) and activity planning (mean 4.98, SD 1.41) and lowest for explaining positive reinforcement (mean 2.92, SD 2.30) and supporting activity-mood monitoring (mean 3.02, SD 2.04). Therapeutic capability ratings were highest for message safety (mean 5.90, SD 0.37), message clarity (mean 5.56, SD 0.77), and objective, nonjudgmental communication (mean 5.17, SD 1.04) and lowest for therapeutic rapport (mean 4.12, SD 1.45) and natural conversation flow (mean 4.25, SD 1.42). Artificial users were rated below the scale midpoint for authenticity (mean 2.75, SD 1.41) and difficulty (mean 1.23, SD 1.46). Clinical experts described the chatbot as structured, clear, and safe but identified insufficient clinical reasoning as the main limitation, particularly in evaluating the therapeutic suitability and feasibility of activities, barriers, solution strategies, and rewards. Artificial users were often highly compliant, especially when identifying positive activities. Conclusions: In expert-rated sessions with artificial users, the chatbot delivered the behavioral activation intervention as intended and performed strongest on procedural components. It performed less well on positive reinforcement and activity-mood monitoring, indicating refinement needs in clinical reasoning, follow-up questioning, and evaluating whether proposed activities, plans, barriers, solution strategies, and rewards are therapeutically appropriate and feasible. The findings identify targets for improvement before testing with human users, while the artificial user design and expert ratings limit conclusions about real therapeutic interactions.
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Young Researchers Honored During the 2026 Youth Mental Health Academy Capstone Awards

Now in its fourth year, the Youth Mental Health Academy (YMHA) at the Child Mind Institute welcomed more than 400 high school students this summer. For five weeks, they engaged in hands-on learning, career exploration, mentorship, and professional development.

Created in partnership with the state of California, YMHA is designed to expand access to mental health career pathways — with a focus on young people from communities historically underrepresented in the mental health workforce. Since launching in 2023, the program has served more than 3,000 students.

Students in the 2026–2027 cohort developed capstone projects focused on mental health topics that matter to them and their communities. From the impact of social media and screen time to the relationship between identity, economic background, and mental health outcomes, they brought their own questions, perspectives, and experiences to their research.

On the final day of the program, students presented their capstone projects to an audience of their peers, mentors, and program staff. Following the presentations, students and their projects were selected for special recognition in six categories: community impact, research excellence, innovation, communication, collaboration, and leadership.

Meet the 2026 YMHA Capstone Award Winners

Community Impact Award

Growing Up Too Soon: The Impact of Parentification on Relationship and Emotional Well-Being

Zamya Slack, Daniela Velazquez, Brenda Ramirez, Amy Marroquin, and Brandon Mares Lopez

YMHA Site: Compton College

Research Excellence Award

Alzheimer’s Disease: How Does Neuroinflammation Accelerate Alzheimer’s Disease Progression, and What Other Factors May Accomplish the Same Effect?

Siobhan Walsh, Samian Syed, Sinthia Salcedo, Sn’cer Wannamaker, and Sophia Park

YMHA Site: Virtual

Online Mental Health Resources and Underserved Communities

Carl Aragones, Chloe Tan, Arturo Perez, and Natalia Martinez

YMHA Site: Virtual

Innovation Award

The No-Sleep Club: How Does Lack of Sleep Affect the Youth in Low-Income Communities

Ivery Norman, Jaide Hood, Jocelyn Segovia, and Jackson McGhee

YMHA Site: California State University, Dominguez Hills

Excellence in Communication Award

More Than a Game: Investigating the Effects of High School Sports Team Bonding on Teen Mental Health

Jayden Tcheyacnou, Mattox Williams, Landen Cassel, and Joseph Malana

YMHA Site: California State University, Dominguez Hills

Collaboration Award

Positive vs. Negative Peer Pressure: How It Affects Teen Mental Health

Erica Mandujano, Samaria Ramirez, Prevailer Umejesi, and Zhiyah White

YMHA Site: California State University, Dominguez Hills

Student Leadership Awards

Devin Bennett

YMHA Site: California State University, Dominguez Hills

Mercy Quezada

YMHA Site: Compton College

Julian Sanchez

YMHA Site: Virtual

Explore award-winning capstone projects from previous YMHA cohorts.

While the Summer Academy has come to an end, the YMHA journey continues for these students. Throughout the school year, they will participate in mentorship, workshops, networking opportunities, and other programming designed to build on their summer experience as well as support their academic and career development.

The mental health field needs diverse voices and professionals who understand the communities they serve. YMHA gives young people the opportunity to explore their interests, build meaningful connections, and begin to see themselves as part of the field.

Learn more about the Youth Mental Health Academy.

The post Young Researchers Honored During the 2026 Youth Mental Health Academy Capstone Awards appeared first on Child Mind Institute.

Experiences and Perceptions of Crisis Text Services: Interview Study Among Young Adults With Suicidal Ideation

Background: Suicide remains a leading cause of death among young adults aged 18 to 25 years. Young adults experiencing suicidal ideation (SI) are increasingly using crisis text services (CTSs), a free and accessible option for crisis intervention. Little is known about CTSs from the young adult perspective. Objective: This study aimed to characterize young adults’ experiences with and perceptions of CTSs for SI. Methods: We conducted in-depth interviews, by phone, Zoom, or text, with young adults (n=39) in the United States who had a lifetime history of SI. Participants included those who had or had not engaged with CTSs for SI. Semistructured interviews were conducted from January to July 2024. The data were analyzed using a modified grounded theory approach. Results: We constructed 5 key themes to characterize young adults’ perceptions of and experiences with CTSs for SI. Young adults perceived CTSs as a unique component of their mental health crisis management. They appreciated CTSs’ technological features, particularly the privacy they provided and the ability to reflect on and edit responses. However, they expressed dissatisfaction with the nonspecific nature of many CTS interactions. The perceived anonymity of CTSs served multiple functions, both as a motivator for CTS use and as a potential point of vulnerability, should it be lost during a CTS interaction. Participants’ perceptions of CTSs’ impact varied; some viewed them as beneficial, whereas others reported neutral or inconsistent effects over time. Conclusions: Among young adults with SI, CTSs are a key yet imperfect resource. Quality improvement and evaluation efforts may be needed to understand how responders can better tailor responses to improve conversational quality and consistency for young adult texters.
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Understanding Sensory Phenomena in OCD

By Goi Khia Eng, PhD

This article describes the results of a 2022 Michael Jenike Young Investigator Award, an IOCDF-funded research project.

Obsessive compulsive disorder (OCD) is a chronic condition with diverse symptom presentations. OCD is often thought of as driven by fears, such as fear of germs leading to washing, or worries about safety driving checking. However, many people with OCD also experience sensory phenomena, which are uncomfortable and aversive sensory experiences, including sensory-based physical urges. Consider someone who experiences a compelling need to tap both sides of the body the same number of times until it feels “even”, not out of fear that something bad might happen if they do not, but because of an intense urge like a persistent itch demanding relief. Sensory phenomena affect as many as 60% of individuals with OCD (Miguel et al., 2000; Shavitt et al., 2014) and can drive compulsive behaviors such as touching, tapping, repeating, evening-up or arranging objects that are performed until they feel “just right” (Ferrão et al., 2012; Katz et al., 2022).

The Science Behind Sensory Urges

Sensory-based urges in OCD (and the urges before tics in Tourette disorder) are similar to everyday urges-for-action, such as the urge to blink or scratch an itch, both in how they feel and in the brain processes involved. Like everyday urges, sensory urges are internally generated and tend to intensify when they are suppressed or delayed (Berman et al., 2012; Neuner et al., 2014). Brain imaging studies in people without mental health diagnoses show that everyday urges-for-action activate a network of brain areas involved in movement preparation, as well as physical sensations and sensations arising from within the body. This brain network involves the insula and sensorimotor regions (including the postcentral gyrus, precentral gyrus, supplementary motor area, and cingulate cortex) (Jackson et al., 2011; Zouki et al., 2024). Most work examining brain regions related to pathological urges has been conducted in Tourette disorder, where studies found increased activation in a similar network of brain regions a few seconds prior to the onset of tics (Bohlhalter et al., 2006; Neuner et al., 2014). Our previous work examining the urge to blink in people with OCD also found activation in similar regions when participants were told to suppress blinking (Stern et al., 2020).

Current Treatments for Sensory Phenomena Are Lacking

Although they are common and distressing, sensory phenomena are not well addressed by first-line OCD treatments, behavioral therapies like cognitive behavioral therapy (CBT) and exposure and response prevention (ERP), and serotonin reuptake inhibitor (SRI) medication (Abramowitz et al., 2003; Stein et al., 2007). Although these treatments help many people with OCD, symptoms like sensory phenomena without a fear component may be more challenging to treat, as behavioral therapies may not be as readily applicable and medications may be less effective (Foa et al., 1999; Stein et al., 2007). Even when sensory phenomena do respond to these treatments, only about half of patients achieve full recovery, underscoring the need to develop new approaches to targeting sensory symptoms in OCD.

Transcranial Magnetic Stimulation (TMS)

TMS is a non-invasive neuromodulation technique that involves placing a specialized coil against the scalp, which generates a magnetic field that induces small electrical currents in the brain (Hallett, 2007). Depending on the stimulation parameters, TMS can either increase or reduce brain activity in the targeted region.

TMS offers several research and clinical advantages. It requires no surgical intervention, no needles, and no substances entering the body beyond the magnetic field itself. Individuals remain seated while the coil is positioned against the scalp using anatomical landmarks or a neuronavigation system. Aside from clicking sounds and mild scalp sensations, TMS is generally well-tolerated with minimal side effects. TMS received FDA approval for treatment-resistant depression in 2008 and for OCD in 2018; it is typically delivered in multiple sessions over several days or weeks, and has an established safety profile across multiple psychiatric applications (Cotovio et al., 2023; Rossi et al., 2021).

From Eyeblinks to Clinically Relevant Sensory Urges

Our research began by studying eyeblink suppression as a model for investigating sensory-based urges (Bragdon et al., 2023; Eng et al., 2024; Stern et al., 2020). People with OCD failed to suppress eyeblinks more than control participants when instructed to do so (Stern et al., 2020). These failures were associated with more severe sensory phenomena (Eng et al., 2024), measured using the gold-standard University of São Paulo-Sensory Phenomena Scale (USP-SPS) (Rosario et al., 2009). Importantly, greater activation in several brain regions, including the postcentral gyrus (involved in processing sensory information), was associated with both eyeblink suppression failures and more severe sensory phenomena in OCD (Eng et al., 2025).

Building on these findings, we tested whether reducing activity in the postcentral gyrus could modulate sensory urges and brain activation. In an initial pilot sample of four participants with OCD, we delivered single-session inhibitory TMS to an individualized target in the postcentral gyrus on one day (active TMS) and sham (inactive) TMS on another (Eng et al., 2025). Active TMS, compared to sham, was generally associated with reduced activity in this brain region during eyeblink suppression and lower self-reported urge to perform compulsions.

Through funding from the Michael Jenike Young Investigator Award, we expanded data collection to include 12 additional participants, for a total sample of 16. Each participant completed i) one baseline brain-imaging session, during which they performed the eyeblink suppression task while their brains were scanned using magnetic resonance imaging (MRI), and ii) two single-session TMS visits on different days, at least 5 days apart. Of these two TMS visits, one visit delivered active inhibitory TMS to an individualized target in the postcentral gyrus, and the other delivered sham TMS, which followed the same procedures but without actual brain stimulation. Participants were not told which condition they received. Immediately before and after each TMS session, participants rated the strength of their urge to perform compulsions using visual analogue scales (VAS). Changes in this rating served as the primary outcome, reflecting acute changes of clinically relevant OCD urges. Immediately after TMS and completing the VAS ratings, participants performed the eyeblink suppression task in the MRI scanner.

The Innovation

To our knowledge, this is the first study to use neuromodulation to specifically target sensory-based urges and the postcentral gyrus in individuals with OCD. Our selection of the postcentral gyrus as a target region is novel and supported by evidence linking higher activation there to more eyeblink suppression failures and more severe sensory phenomena. To tailor stimulation for each participant, we did not target the exact same brain location in everyone. Instead, we used each participant’s own brain scan to identify the specific “hotspot” within the postcentral gyrus that was most active during eyeblink suppression. To lessen discomfort, we delivered TMS in quick bursts rather than using traditional repetitive protocols, so that stimulation can be completed in under a minute. Neuronavigation technology, which is essentially a GPS system for the brain, was used throughout the session to track the TMS coil’s position in real time relative to the participant’s brain to ensure precise and consistent targeting. These approaches acknowledge individual differences in brain anatomy and apply principles of personalized medicine to neuromodulation.

Study Findings

Our study results, while preliminary given the small sample size, showed encouraging patterns across multiple measures. Most importantly from a clinical perspective, participants reported greater reductions in the strength of their urge to perform OCD-related compulsions following active TMS compared to sham, suggesting that modulating activity in the postcentral gyrus may have clinical relevance. In terms of brain activation, regions of the urge network including the postcentral gyrus, precentral gyrus, and insula showed less activation during eyeblink suppression following active TMS compared to sham.

Notably, there was individual variability in response. Some participants showed substantial decreases in the strength of their urge to perform compulsions following active TMS compared to sham, while others showed smaller decreases or minimal change. We found that participants who reported greater reduction in their urge to perform compulsions after active TMS (compared to sham) showed greater decreases in brain activity in regions associated with urges-for-action (including the postcentral gyrus, precentral gyrus, supplementary motor area, and insula), as well as regions involved in cognition and emotional processing, and reduced connectivity between the postcentral gyrus TMS target and these regions.

Conclusion and study implications

This proof-of-concept investigation represents an important step toward addressing a significant unmet clinical need. By demonstrating that modulating activity in the postcentral gyrus was associated with changes in both the urge to perform compulsions and underlying brain circuitry (with notable individual variability), we established a foundation for developing targeted neuromodulation approaches for sensory-based urges in OCD. These findings are promising and worthy of replication in a larger sample.

Although this study examined only short-term effects, these mechanistic findings will inform future clinical trials employing repeated (multi-week) sessions of individualized TMS to achieve longer-term modulation of sensory phenomena in OCD. Beyond TMS, the insights gained from this work are also guiding our exploration of other cutting-edge non-invasive brain stimulation techniques, such as low-intensity focused ultrasound, which can reach deeper brain structures and may ultimately expand treatment options for individuals with sensory phenomena.


About the Author

Goi Khia Eng, PhD, is a Research Scientist at Nathan Kline Institute for Psychiatric Research. Her current research involves understanding the neural underpinnings of sensory phenomena in OCD and she aims to utilize non-invasive stimulation methods to elucidate the pathophysiology of these processes.


References

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Berman, B. D., Horovitz, S. G., Morel, B., & Hallett, M. (2012). Neural correlates of blink suppression and the buildup of a natural bodily urge. Neuroimage, 59(2), 1441-1450. https://doi.org/10.1016/j.neuroimage.2011.08.050

Bohlhalter, S., Goldfine, A., Matteson, S., Garraux, G., Hanakawa, T., Kansaku, K., Wurzman, R., & Hallett, M. (2006). Neural correlates of tic generation in Tourette syndrome: An event-related functional MRI study. Brain : a journal of neurology, 129, 2029-2037. https://doi.org/10.1093/brain/awl050

Bragdon, L. B., Nota, J. A., Eng, G. K., Recchia, N., Kravets, P., Collins, K. A., & Stern, E. R. (2023). Failures of Urge Suppression in Obsessive-Compulsive Disorder: Behavioral Modeling Using a Blink Suppression Task. Journal of Obsessive-Compulsive and Related Disorders, 38, 100824. https://doi.org/10.1016/j.jocrd.2023.100824

Cotovio, G., Ventura, F., Rodrigues da Silva, D., Pereira, P., & Oliveira-Maia, A. J. (2023). Regulatory clearance and approval of therapeutic protocols of transcranial magnetic stimulation for psychiatric disorders. Brain Sciences, 13(7), 1029.

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Comparison of subject-to-template registration schemes using CT and MR radiotherapy images with brain lesions

IntroductionVoxel-based analyses have been used more widely in radiotherapy in recent years. The purpose of this study is to compare eight different methods of registering images on to a template space for such analyses. A novel way, using both CT and MR data, is proposed.MethodsCT and MR brain images from 85 participants in the CoDe-B-Rad study (NCT06466720) were registered on an age-specific template. The registration schemes used included sCT-Template (linear and non-linear); MR-Template (linear, non-linear, masked, and enantiomorphic); and Dual-Template (linear and non-linear). The registrations were compared qualitatively and quantitatively against the template MR images with scores ranging from 1 (lowest) to 5 (highest) and quantitatively (via Jaccard, ASD, and HD95).ResultsQualitatively, the best registration scheme was the Dual-Template-non-linear registration, with 60 participants scoring above 4. The second best was the MR-Template-enantiomorphic, with 53 participants scoring above 4. Quantitatively, the Dual-Template-non-linear method outperformed on the mean (±SD) for the ASD and HD95, with 0.918 (±0.1774) and 2.965 (±0.5392) respectively. For ASD the difference compared to other methods was significant (p = 0.03). The MR-Template-masked outperformed on the Jaccard mean (±SD), median (IQR), and ASD, achieving values of 0.567 (±0.0557), 0.555 (0.055), and 0.808 (0.162) respectively. The Dual-Template-non-linear and MR-Template-masked and non-linear had the same result for the median HD95: 2.639. The performance of all linear schemes was inadequate both quantitatively and qualitatively. All non-linear registration schemes had issues with distortions of tissue and landmarks, however, for the Dual-Template scheme these were minimal.ConclusionThe Dual-Template-non-linear registration scheme is a new way of registering lesioned brain images for use with voxel-wise techniques in radiotherapy, which utilises both CT and MR image data. The scheme provides fidelity of the underlying soft tissue as well as the surrounding skull, minimising anatomical and dosimetric distortions.

RutiSafeNet: a behavioral risk and nursing workload monitoring tool for open-door acute inpatient mental health units

IntroductionOpen-door policies for acute inpatient mental health units (AIMHU) have shown promising results in reducing coercive measures, but concerns remain among patients and staff regarding increased workload, constant surveillance, and potential safety risks associated with these policies. This study aims to develop a monitoring tool to facilitate safety management in AIMHUs by monitoring behavioral risks and nursing workload.MethodsThis study employed a qualitative approach using the content analysis method. Data were collected through three in-depth interviews and two focus groups involving staff (n=19) from the AIMHU of the hospital.Results34 items were identified to define behavioral risks related to self-harm and suicide, aggressiveness, and absconding, alongside factors affecting nursing workload. These items were categorized into three levels of risk: low, moderate, and high.DiscussionRutiSafeNet is a preliminary, observation-based monitoring prototype intended to support, rather than to predict, structured risk and workload monitoring in acute inpatient mental health units. As a qualitatively developed instrument, it requires psychometric validation, including inter-rater reliability, construct and criterion validity, predictive value, and clinical feasibility, before it can be implemented as a validated scale in clinical practice.

Path and Bayesian network analyses in the complex design of a well-being survey via New Zealand’s Integrated Data Infrastructure

IntroductionIn mental health research involved with sensitive features and privacy issues, using integrated data offers an efficient alternative to traditional approaches such as interviews or in−person data collection. These conventional methods frequently face logistical barriers, including low response rates among study populations. Using integrated data from multiple existing administrative and survey sources provides protection for participants and economic savings for researchers, despite being constrained by the limitations of the original data sources. Our research questions were: 1) Can we conduct path and network analyses of school absenteeism, psychosocial factors, and mental health outcomes using the integrated survey data from New Zealand’s Integrated Data Infrastructure (IDI)? and 2) How can we account for the complex design of the General Social Survey (GSS) to ensure representative inference?Materials and methodsThe study population was New Zealand youth enrolled in school, aged 15 years and older in 2018, who participated in the 2018 GSS. The study analyzed the Ministry of Education data integrated with the 2018 GSS survey data from New Zealand’s IDI. To explore the relationship between outcomes of including the WHO-5, “perceived life worthwhileness”, “perceived general health”, and predictors including school absenteeism, psychosocial factors, and family factors, quantile mixed−effects regression, path analysis, and Bayesian network (BN) analysis were used. The complex survey design was calibrated using replicated weights from the GSS, a design-based method for complex sampling, in path and regression analyses, and bootstrap resampling, in BN analysis.ResultsIn descending order from the weighted path model, overall life satisfaction (standardized path coefficient: 0.36), perceived health condition (0.34), ease in accepting cultural identity (0.12), and trust in the education system (0.07) were all significantly (positively) related to students’ mental health well-being (WHO-5). Perceived life worthwhileness correlated with the WHO-5 but was only connected to overall life satisfaction. Similar factors were identified for perceived health, with additional attributing factors, such as fear of crime in the area and the family’s overall well-being.ConclusionThe integration of Bayesian networks and path analysis offers rigorous methods for detecting complex interrelationships among integrated mental health outcomes from population data and variables from a complex survey design.

The relationship between trait mindfulness and psychotic-like experiences in a brief AI-generated music listening context: the roles of presence, perceived interactivity, and emotional arousal

Background and objectiveWithin the interdisciplinary field of cyberpsychology and mental health, trait mindfulness has been associated with lower levels of subclinical anomalous symptoms, such as Psychotic-Like Experiences (PLEs), has gained increasing attention. However, in the context of daily digital human-computer interactions (e.g., listening to AI-generated music), the specific pathways through which Mindfulness operates (the involvement with Presence and Perceived Interactivity) and the boundary conditions of physiological arousal, remain to be clarified. This study aims to explore the direct predictive relationship between mindfulness and individuals’ PLEs, and to investigate the multipath effect of brief AI-generated music listening context (with Presence and Perceived Interactivity), along with the moderating effect of Arousal.MethodsWith a cross-sectional survey design, self-reported multimodal data were collected from 527 Chinese participants. Structural equation modeling (SEM) was conducted using Mplus 8.3 to empirically test the main effects (path coefficients) of the theoretical hypotheses and the moderation model.ResultsBoth the measurement and structural models demonstrated good fit. The path analysis results indicated that: (1) trait trait mindfulness was significantly and negatively associated with PLEs (p < 0.001); (2) regarding the main effect paths of brief AI-generated music listening context, mindfulness significantly and positively predict individuals’ Presence and Perceived Interactivity, while both significantly and negatively predict PLEs; (3) Arousal played a significant moderating role in the relationship between mindfulness and brief AI-generated music listening context, exhibiting a synergistic enhancement effect. Higher levels of Arousal significantly amplified the positive prediction of Mindfulness on both Presence and Perceived Interactivity (p < 0.01).ConclusionsWith the help the SEM, this study maps out the underlying multipath network through which mindfulness is associated with lower PLEs within a brief AI-generated music listening context. The observed associations suggest that presence and perceived interactivity may function as pivotal correlational nodes relevant to mental health correlates, while these results also nuance classic cognitive load assumptions by indicating a potential synergistic association between trait mindfulness and emotional arousal. These results provide a solid empirical foundation and prospective insights, for the mental health-oriented design of AI music products, such as the immersive acoustic environment construction and dynamic, arousal-based interaction recommendations.