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Why is loneliness hitting teen girls hardest?

Being a teenage girl has always been a fraught, challenging time. Credit: Getty

Being a teenage girl has always been a fraught, challenging time. Credit: Getty

1 July 2025 - 4:15pm

Rob Thomas, the American screenwriter, said that he created the character of Veronica Mars — 17 years old, fiercely intelligent, unafraid to speak her mind — to help teenage girls, who are “the most self-conscious people on the planet”.

It turns out that teenage girls are not just self-conscious, but profoundly lonely. A new study by the World Health Organization has found that almost a quarter of teenage girls say they are lonely, the highest of any group.

Being a teenage girl has always been a fraught, challenging time. Adolescence means suddenly having to navigate a world of raging hormones and complex social dynamics and hierarchies. Girls, in particular, find that they are now defined by how they look rather than what they do, and will inevitably be sexualised, whether they are ready for it or not.

Yet these relatively timeless struggles do not explain why we are going through a more recent “happiness recession”. A quarter of British 15-year-olds now report having poor life satisfaction, the highest in Europe, while between 2015 and 2022 happiness levels among girls in the UK also declined more sharply than the European average.

Physical inactivity may play a significant role: only one in 10 15-year-olds get 60 minutes of physical activity a day, with girls far more likely to do no exercise at all. Yet the fact that this decline accelerates around 2015 suggests that, once again, screen time and social media are to blame.

It’s well established that girls spend more time on their phones. One Swedish study found that 60% of teenage girls reported excessive smartphone use, compared to only 35% of boys. Research also shows that boys are more likely to use their screen time gaming (which has a more social element), whereas girls consume more social media, which, ironically, is anything but social.

Social media algorithms, too, are known to push very different content depending on your sex. Girls, in particular, are more likely to be shown information related to self-harm, eating disorders, and body image; even briefly engaging with fitness-related images can lead them down a rabbit hole of weight-loss content.

However, it is not just the more extreme types of content that are spreading this epidemic of loneliness and depression among teenage girls. The stereotyping, self-limiting nature of social media algorithms is also an important catalyst. For example, one study found that 68% of teenage girls said that their social media interests were limited to beauty, fashion and reality television. None of these are “dangerous” per se, but they are far more likely to negatively affect their self-esteem than the boys’ reported interests: sport, technology, politics and business.

Of course some girls will be actively seeking out this kind of content, but how can we tell what is intentional and what is imposed by an algorithm assuming this is “what girls like”? Anecdotally, when I speak to my students it seems that teenage boys primarily engage with content because it is funny: they enjoy watching pranks and stunts, witty interviews, comedians doing stand-up. For girls, the content is much more emotionally loaded: make-up tutorials, outfit “hauls”, gym workouts, vlogs of sun-kissed influencers “living their best life”. Again, it may not be dangerous, but it certainly changes one’s perception of what life ought to look like. Since most people’s lives do not resemble online perfection, it’s no wonder young girls become disillusioned with the real world. Disconnection and loneliness, then, are never far behind.


Kristina Murkett is a freelance writer and English teacher.

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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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