Radically different
In traditional human psychotherapy, the therapeutic alliance (TA) is regarded as a fundamental factor that describes the client-therapist relationship, mainly due to strong evidence demonstrating its impact on treatment outcomes regardless of theoretical orientation. More recently, advances in artificial intelligence (AI) and other technologies have led to the emergence of the concept of digital TA, used to characterize the relationship between clients and AI-based therapeutic systems. This approach replicates human dynamics but overlooks key differences between human therapists and digital agents. Prematurely translating the concept of TA into the digital context fails to address issues such as the sycophantic tendencies of current systems and the inherent limitations of algorithmic interaction. We propose the digital therapeutic nexus, a framework that recognizes these differences and provides a set of structured criteria for categorizing digital interactions into 3 progressive levels. This Viewpoint argues that only at the highest level can parallels be drawn to the human TA and stratifies the main risks associated with each nexus level. Transitioning from the concept of alliance to that of a nexus offers a more precise conceptual basis for describing and evaluating digital therapeutic relationships, with implications for research, design, and the ethical development of AI-based mental health interventions.
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Background: Depression in older adults is often underdiagnosed due to atypical symptom presentation and generational stigma, leading to delayed intervention. Early identification of individuals at risk of developing elevated depressive symptoms is therefore critical, but traditional approaches show limited predictive accuracy. To date, no study has applied machine learning (ML) models to predict clinically significant depressive symptoms at 2-year follow-up in older adults in the United Kingdom using data from the English Longitudinal Study of Ageing (ELSA). Moreover, the impact of encoding strategies for categorical health care variables has not been examined. Objective: This study aimed to develop and evaluate ML models to predict the clinically significant depressive symptoms at 2-year follow-up in older adults using ELSA data. We further compared ordinal and one-hot encoding strategies across different ML architectures and identified key predictors of depressive symptoms at follow-up. Methods: Data were drawn from 4 consecutive waves of ELSA, including participants aged ≥50 years without significant depressive symptoms at the baseline wave (waves 6‐9). Clinically significant depressive symptoms were defined as 8-item Center for Epidemiologic Studies Depression Scale (CES-D 8) scores of ≥4 at the subsequent wave (waves 7‐10). Over 120 features spanning sociodemographic, psychological, and health-related domains were analyzed. Eight ML models were applied, including tree-based ensembles, deep learning architectures for tabular data, distance-based methods, probabilistic methods, and linear methods. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and -score. Model interpretability was examined using Shapley additive explanations (SHAP). Sensitivity analyses assessed the robustness of results across alternative CES-D 8 thresholds (≥3, ≥4, and ≥5) and encoding strategies. Results: Across waves, the best-performing models achieved mean AUROC scores of 0.72‐0.73, with a peak of 0.75 in the highest-performing wave. Ordinal encoding consistently outperformed one-hot encoding across all ML models, yielding improvements in AUROCs and -scores, with the greatest increase in tree-based methods. SHAP consistently identified loneliness, sleep disturbances, and low social engagement as strong predictors of elevated depressive symptoms at follow-up. Sensitivity analyses across CES-D 8 thresholds demonstrated robust feature importance, with AUROCs ranging from 0.67 to 0.82. Traditional ML models (random forest, extreme gradient boosting, and support vector machines) generally achieved higher performance than the deep learning models for this task. Conclusions: Our findings demonstrate the feasibility of predicting clinically significant depressive symptoms at 2-year follow-up in UK older adults, with moderate accuracy. Ordinal encoding demonstrates superior performance for health care datasets with inherently ordered categorical features. The identification of consistent risk factors highlights opportunities for developing targeted clinical screening tools and preventive interventions. This study provides new evidence on depressive symptom prediction in the UK context, leveraging longitudinal data from ELSA, and contributes to advancing digital mental health research for aging populations.
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In early June, SXSW London returned for its second year, gathering thousands of creatives, enthusiasts, entrepreneurs, and investors into the city to celebrate film, music, tech, and culture. As part of this year’s festival, the Child Mind Institute, in partnership with Wellcome, proudly presented the inaugural Youth Mental Health Hub – a week of programming dedicated to advancing solutions to one of the defining challenges of our time: the global youth mental health crisis. Through six thought-provoking sessions, leaders in clinical care, science, technology, policy, and media came together to explore how to strengthen prevention, improve early identification, reduce stigma, and build systems that meet young people where they are.
Here’s a look back at the inspiring conversations that took place throughout the week.
As artificial intelligence rapidly transforms the experience of childhood, experts explored how AI can both support and challenge young people’s mental health. The panelists discussed when and under what conditions young people may be most vulnerable as well as what systems we need to support them.
Moderator
Gary Wilson, Director of Research, Huo Family Foundation
Speakers
Catherine Sebastian, PhD, Head of Evidence for Mental Health, Wellcome
John Pickavance, PhD, Principal Data Scientist, Born in Bradford
Georgia Turner, Postdoctoral Research Associate, University of Cambridge
Michael Milham, MD, PhD, Chief Science Officer, Child Mind Institute
Youth are experiencing the impacts of AI earlier and more intensely than any previous generation has. This session explored the role of public leadership in anticipating harm before it becomes systemic — establishing guardrails, fostering digital resilience, and ensuring that innovation advances hand in hand with youth mental health and well-being.
Moderator
Sarah Aguiar-Borges, PhD, University of Cambridge
Speakers
Julia Gillard, former Prime Minister of Australia; Chair, Wellcome
Kanishka Narayan, UK Minister for AI and Online Safety
Giovanni Salum, MD, PhD, SVP, Global Programs, Child Mind Institute.
Experts shared insights on the unique mental health challenges facing children affected by war, displacement, and humanitarian crises. This session explored how societies can implement youth-centered systems grounded in prevention and use early identification to position youth mental health as a cornerstone of long-term recovery and resilience.
Moderator
Krupa Padhy, BBC Radio 4
Speakers
Dr. Mark Jordans, professor, Centre for Global Mental Health, King’s College London; Director of Research & Development, War Child
Emma Ferguson, mental health policy and advocacy specialist, UNICEF
Mohamed Ali, Director, Iftin Global
In a timely discussion, experts explored how dyslexia is currently understood in society, challenging current language and misperceptions that can impact a child’s confidence and mental health. Through a blend of personal experience and clinical expertise, the conversation focused on the need for evidence-based support and strengths-based approaches to help children and their families thrive.
Moderator
Kate Griggs, Founder, Made By Dyslexia
Speakers
Maggie Aderin, PhD, space scientist & educator; dyslexia advocate
Harold S. Koplewicz, MD, President and Medical Director, Child Mind Institute
Suicide is one of the leading causes of death among young people globally. This session gathered community, clinical, and digital leaders to explore what a more connected system of support looks like in practice. The panelists also discussed the important of recognizing warning signs, expanding access to evidence-based care, and prioritizing early intervention to help prevent youth suicide.
Moderator
Krupa Padhy, BBC Radio 4
Speakers
Victoria Hornby, CEO, Mental Health Innovations
Dean Perryman, Empty Chairs
Michael Milham, MD, PhD, Chief Science Officer, Child Mind Institute
With technology evolving faster than the science designed to understand it, experts examined how research, philanthropy, and clinical leaders can work together to build the evidence, safeguards, and infrastructure needed to protect children’s mental health in the digital age.
Moderator
Chelsea Clinton, Vice Chair, Clinton Global Initiative
Speakers
Miranda Wolpert, Director of Mental Health, Wellcome
Margaret Laws, President & CEO, HopeLab
Daria Bukhman, Co-Founder and Chair, Bukhman Philanthropies
Harold S. Koplewicz, MD, President & Medical Director, Child Mind Institute
The post A Recap of the Inaugural Youth Mental Health Hub at SXSW London appeared first on Child Mind Institute.
By now, you’ve probably heard of the term looksmaxxing. Think pieces about the trend have popped up all over the internet. And in a recent episode of Saturday Night Live, comedians poked fun at lookmaxxing influencers obsessed with having the perfect male physique.
While this new social media craze may seem silly, it’s impacting more boys than you might think. In a study conducted last year that surveyed over 3,000 young men (ages 16–25) from the United States, United Kingdom, and Australia, nearly two-thirds of participants were regularly engaging with masculinity influencers.
Teen boys are being encouraged to change the way they look in order to fit a certain standard of attraction. The growing amount of looksmaxxing content they see online can have real effects on their self-esteem and mental health.
Looksmaxxing originated nearly a decade ago in incel forums where men blamed their lack of romantic partners on the belief that female sexual selection is primarily based on physical qualities. So men who aren’t born with traits desirable to women are doomed to fail romantically. While traditional incels wallow in this fate, looksmaxxers seek to enhance their appearance to become more attractive. Their community claims that there is a universal standard for what the ideal man (and woman) should look like.
This is determined by a rating system called the PSL scale — the name being an amalgamation of three prominent misogynistic incel forums of the 2010s. There are many factors that go into the scaling, such as eye shape, jaw size, nose angle, and body fat percentage. Along this scale, you can land in four categories: subhuman, normie, Chadlite, and Chad (the ultimate catch).
During the pandemic, looksmaxxing went mainstream, merging with “manosphere” content on social media platforms like TikTok and Instagram. The trend became less about the ability to attract women and more of a competition among boys and men as they engaged in mog-offs — online contests where people have their faces analyzed and compared by facial recognition software to determine who’s better looking.
Self-improvement practices have gained popularity among boys. Some are considered to be softmaxxing, like developing skincare routines or eating high-protein diets, and others to be hardmaxxing, like using growth hormones or getting cosmetic surgery.
Prominent young influencers like Clavicular represent the extreme side of looksmaxxing. He practices bonesmashing (using a hammer on facial bones to try to form more angular features), injects himself with testosterone, and takes meth to maintain a low body fat percentage while still having a muscular physique.
The rise of looksmaxxing seems to have a caused a ripple effect among teen boys. While the ideal look has centered on big muscles and washboard abs for decades, there’s now an added pressure on facial beauty that’s typically been reserved for girls.
“With some of the teen boys I work with, most of whom already have self-esteem issues, I think there is a lot more concern about how they look,” observes Alnardo Martinez, LMHC, director of the Pediatric OCD Intensive Program and a mental health counselor at the Child Mind Institute. “They want to have the strong jaw, really big muscles, clear skin, and a perfect haircut.”
However, Martinez notes that it sometimes take a while for boys to admit that they feel this pressure. They may insist that they don’t really care about that stuff. “But then, maybe a few months later, it comes out that there is a lot of comparison. They’re spending a lot of time in front of the mirror or in the bathroom trying to create this perfect image,” he observes.
We talked to young men who were critical of Clavicular and the impact looksmaxxing can have on teens but were positive about engaging in some form of physical self-improvement.
Wyatt, now 19, remembers comparing his jawline to his peers’ when he was in 7th grade. “I just felt like they had really sharp jawlines. And I was just like, ‘Oh, I want to get closer to that.’” He would also come across TikToks advertising rubber chewing blocks and chin exercises meant to strengthen the jawline.
And so, Wyatt began to do jaw exercises he’d found online, reciting the alphabet while stretching out the muscles. “I would go through my Zoom classes throughout the day and then after that was done, I’d just go into the bathroom and go through the whole exercise. It would take like an hour sometimes,” he recalls. “It turned into more like a self-care, self-improvement session. I would do that every day after my classes. I didn’t feel like I was done with school until I finished my jawline routine.” He took photos to document his progress.
Wyatt feels like the routine had a positive effect, because he was able to see an improvement. “I felt more satisfied with myself, a little more confident.”
Lev, now 19, remembers wanting to have some control over his body when going through puberty in high school. “Puberty is not a straightforward process. It’s not all peaches and cream. Your body changes, and it can be uncomfortable,” he explains. “But with lifting and strength training, it was very exciting to see this, you know, man energy that came out of it. I wanted to harness that and really take it by the reins. Have some agency as a man.”
And while he rejects the extreme parts of looksmaxxing, Lev does regularly practice self-improvement through weight lifting, skin care routines, and taking GLP-1 weight loss medication.
Since looksmaxxing places such a strong emphasis on achieving a very specific look, clinicians are concerned about its influence on teens. “Self-esteem is pretty fragile during puberty,” Martinez says. “There’s already a ton of comparison and perceived flaws that teens don’t love about themselves.”
These insecurities can be exacerbated by the type of content teens engage with online, Martinez explains. Along with ChatGPT bots specifically designed to judge aesthetics, Reddit threads such as r/Mewing and websites like Looksmaxxing Forum encourage boys to post pictures of their faces and bodies to get rated by their peers. Boys as young as 13 visit these forums, posting pictures and asking for tips on how to improve their looks.
“These are generally places where people are already pretty harsh and critical. These boys are receiving a lot more ‘confirmation’ around the perceived things that are wrong with them or that they need to change,” Martinez says. “And it just feeds into the already present negative self-image and self-talk.”
He explains that this type of social media engagement can also compound underlying mental health issues like depression and social anxiety. “They might be less likely to go out and talk to people because they’re thinking, ‘Everyone is going to see this one thing that everyone else has told me is wrong with me. So now I can’t go out,’”he says.
Martinez is also concerned that online content can negatively affect teens with body dysmorphic disorder (BDD). “If they think they have a big nose, for example, they might go on these Reddits and ask, ‘What does my nose look like? Is it too big?’ There are trolls out there. Someone is going to say yes and then that’s going to make the BDD symptoms even worse.”
In some ways, teen boys taking part in more self-improvement practices could be seen as a good thing. They’re exercising, taking care of their skin, and eating more balanced diets. The issues begin when these types of practices turn into obsession. And given the underlying ideology of looksmaxxing and the nature of social media, things can become unhealthy.
According to Martinez, there are some changes in behavior to look out for that indicate you might want to step in.
One clear change, he says, is a noticeable shift in the amount of time they’re spending on grooming themselves. “Maybe they were someone who would typically just get up and run out the door without washing their face,” he says. “But now they’re spending a lot more time in the bathroom and asking a lot of questions about how they look.”
Another warning sign can be a big change in personality. “Irritability is a big one that we’ll see a lot,” he says. “They’re unhappy with how they look, so this increases a general level of irritation.”
These behaviors paired with an unusual uptick in time spent on social media, Martinez explains, can be a sign that something’s wrong and support is needed.
If you’re worried that your child might be engaging in looksmaxxing-related behaviors to an unhealthy degree, says Martinez, there are a few things you can do:
A lot of parenting comes down to open communication around what your kids are seeing and what they’re feeling. We all have things about our bodies that we might not like and wish we could change, says Martinez, and it can help to normalize those feelings. “And then you can discuss how they can make changes in healthy ways,” he suggests. “Go over what’s a realistic change and what’s a dangerous change.”
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