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Are teenage girls really unhappier than boys?

The lockdown generation. Credit: Getty

The lockdown generation. Credit: Getty

1 September 2025 - 1:10pm

Teenage girls, according to a new survey, are more miserable than teenage boys. More In Common polled over 1,000 16- and 17-year-olds, and revealed that more than half of both sexes reported suffering some kind of mental health condition. But there’s a marked sex difference: 34% of girls report suffering from anxiety, compared to 14% of boys.

Why, then, are girls so much more unhappy than boys? The short answer: I’m not sure they are.

It should surprise no one if today’s adolescents feel under pressure. Born roughly concurrently with the global financial crash, this group has never known a Britain that wasn’t roiled by one crisis or another. Where their parents would have reached adolescence amid the widespread optimism after the fall of the Berlin Wall, theirs happened among the divisive Brexit referendum and, shortly thereafter, the Covid pandemic.

And this in particular was uniformly catastrophic for children. Those now aged 16 and 17 were locked down right at the formative moment of beginning secondary school, a transition that represents a socially and psychologically significant caesura in the lives of almost every child growing up in Britain. Now, imagine that this momentous change arrives — but you spend the usually socially formative first year sitting at home doomscrolling. No wonder some are not bouncing back: Government figures published earlier this year indicated that the number of young people receiving Personal Independence Payment (PIP) — the main welfare benefit issued for disability — has skyrocketed since the pandemic from 2,967 to 7,857 a month, with much of this increase due to reported mental health conditions.

So when More in Common show girls self-reporting much higher levels of mental illness than boys, you might expect this to show up in statistics on welfare claims in this age group. But when I looked at current Government figures on PIP claims since 2019, I found that the opposite is true. While the overall figures do skew female, this only holds in older age brackets. Among young people, the sex disparity runs the other way, with 116,000 claims among boys aged 16-19 and 78,000 for girls in the same age bracket.

These figures don’t specify the nature of the claim, but the marked difference in numbers suggests a gap between what’s reported to pollsters, and what’s experienced acutely enough to prompt a welfare application. So what gives? One hypothesis is that unhappiness is prevalent across both sexes, but shows up differently between them. This would be consistent with extant psychological research, which suggests boys are more likely to “externalise” unhappiness via confrontational, disruptive, or risk-taking behaviour, while girls are more likely to “internalise” their distress. For girls this often means anxiety and depression, conditions linked to the “Big Five” traits of conscientiousness and neuroticism where psychological research also shows women generally score more highly than men.

So, even leaving aside extraordinary experiences such as lockdown, you’d expect unhappiness to show up differently in polls depending on sex. But it doesn’t follow from this that boys aren’t suffering. The teenager who told More In Common about social difficulties after lockdown was a boy. Jake, 17, said: “When we went back [to school], I felt very out of place … I struggled a lot with social interaction.” And if girls are reporting high anxiety, a teenage girl quoted recently by columnist Caitlin Moran points to one way in which the unhappy boys may be externalising: by tormenting the girls. The girl asked Moran pointedly: “Who do you think they’re taking out their unhappiness on? It’s us.”

Nothing is ever monocausal. The poll also points to pornography and phone overuse as factors. But taken all together, Government PIP figures plus this new poll all point to the way an existing negative trend in youth mental health has been exacerbated by the disastrous psychological impact of lockdowns. And while it’s easy to take self-reports at face value, and focus concern on girls, reading the figures sideways suggests this would be an error. Really, distress is equally distributed, but the sexes’ divergent responses to this distress are amplifying one another, in unhappily asymmetrical ways.


Mary Harrington is a contributing editor at UnHerd.

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China is threatening America in the AI race

Reports sugget Zhipu AI  has released a new model that can rival leading US systems. Credit: Getty

Reports sugget Zhipu AI has released a new model that can rival leading US systems. Credit: Getty

1 July 2026 - 10:18am

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.


Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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