The decline in teenage mental well-being has been fuelled by disruption to their routines, uncertainty, reduced contact with friends and a fear of catching the virus.
This has prompted an 80 per cent increase in their social media and smartphone use, which is thought to have further contributed to their anxiety.
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The pandemic has also had a profound effect on sleep patterns, the study found. The average teenager slept 60 per cent longer during school closures as they got up later in the morning, according to the preliminary findings from a major study of 5,000, 16 to 18 year olds that will be published shortly.
Professor Mireille Toledano, the Imperial College London scientist leading the study, is concerned that the mental health issues her work has highlighted could be storing up major mental health problems for the future.
Adolescence is a critical period in a person’s development that can have a bearing on their mental health and quality of life for decades to come, she said.
She said: “We’ve all been touched by the lockdown but children and their parents, in particular from school closures, have really been affected.”
“These might be short term effects but if they persist this could be very worrying. Early life through to adolescence is a really critical period for lifelong health – half of adult mental health illness manifests by age 14 and by age 24 that figure is already 75 per cent,” she said.
Minister for Mental Health, Nadine Dorries, added:
“These initial findings illuminate how incredibly difficult this pandemic has been for many, especially children and young people, and I remain absolutely committed to supporting the mental wellbeing of everyone.
The study found that the proportion of teenagers who are clinically depressed more than doubled from 14 to 35 per cent during the first nine months of the pandemic. Meanwhile anxiety orders have jumped from 13 per cent to 29 per cent.
The study also found that the mental health of teenage girls has been affected more than boys during the pandemic, while those from the most deprived sections of society are twice as likely to have reached the ‘anxiety clinical threshold threshold’ compared to the most affluent.
The research is the latest in a series of studies to highlight the way Covid-19 is widening inequality in society.
A report from the Institute for Fiscal Studies in February warned that “the long-run costs of the pandemic will fall disproportionately on today’s children”.
It estimated the disruption will lead to a potential £40,000 loss in income across a lifetime, with the effects largely concentrated on those from disadvantaged backgrounds.
The Imperial study also showed the effects of Covid disruptions are felt quite differently between various minority ethnic groups.
Prof Toledano said: “Chinese ethnic groups are by far the worst affected by depression and anxiety, followed by Indians, followed by white children. Black communities have actually fared very well and didn’t show any increases in depression and anxiety.”
“I think a lot of it probably comes down to fear and cultural fears around things. Certain Bame groups have not shown this fear about Covid in the same ways that other groups have. Some groups are just very scared. Some are taking up the vaccine with full force and others are really not interested to take up the vaccine,” she said.
Public health experts said they were very worried by the report.
Shaun Friel, the head of Childline, said: “These findings are incredibly concerning and there is no doubt the pandemic has had a huge impact on young people.
“Many children have contacted Childline because they are struggling with the closure of schools, social isolation and concern for family and friends. Mental health is the top reason they’ve got in touch with us in the last 12 months.”
“When it comes to mental health, it’s essential young people get the right support at the right time to prevent issues from becoming far more problematic later on. The Government needs to invest in an ambitious plan for children that goes beyond catching up on lessons and helps them recover from an incredibly challenging year. This must include more mental health support in both the classroom and the community,” Mr Friel said.
David Stephenson, senior policy and campaigns officer at the Mind mental health charity, added: “As we come out of the pandemic and economic recession, we are beginning to see the scale of poor mental health across the nation, with young people among those worst affected.”
“That’s why we urgently need to see a focus on young people in the UK Government’s recovery plan. There is still a lot more work to be done to make sure every young person gets the support they need and deserve for their mental health,” he said.
Ms Dorries added: “Early intervention and treatment is vital, and we are providing an extra £2.3 billion a year to mental health services, this will help an additional 345,000 children and young people access NHS-funded services or school and college-based support by 2023/24.”
“Our cross-government Mental Health Recovery Action plan, backed by an additional £500 million, specifically targets those that have been most impacted by the pandemic including those with severe mental illness, young people, and frontline staff.”
Personalised mental health treatments are on the horizon
Personalised mental health treatments could one day become available on the NHS as scientists look to harness the power of artificial intelligence to analyse vast reams of data on patients suffering from depression and anxiety.
Professor Mireille Toledano, of Imperial College London, is leading the move to offer patients more ‘tailored’ mental health treatments. She is gathering and analysing huge amounts of data from thousands of teenagers covering a wide range of factors such as age, ethnicity and genetics.
She says that most of the focus on the fledgling area of personalised medicine so far has been on physical treatments, but argues that tailored mental health care is at least as important as it depends on a wide range of inter-related factors that are only now starting to become understood.
Scientists are already working towards the first tailored mental health treatment plans. These would initially be in the form of a handful of general templates, taking in factors such as person’s gender, ethnicity or socio-economic group.
But in the longer term, Prof Toledano hopes treatments for depression, anxiety and other mental health problems can be targeted much more precisely.
“The most important thing is that we can get to a point with all medicine where we can do a personalised approach. At the moment it’s more of a theoretical concept that hasn’t really taken off. But ideally you would want the same thing for mental health because one approach won’t work for all people. It will even help when you start splitting by gender and ethnicity but at the end of the day it is a very personal thing,” she said.
“We need to get further down and to do that you need real interrogation of the data with machine learning to really unpick and explore the data in ways which traditional statistics don’t do. And through that you can really pick up the individual patterns and understand,” she said.
Although genes and family background clearly play a large role in a person’s mental state there are other factors involved that are key – and there is a need to learn much more about them and the way they interact, according to Prof Toledano.
She is working to find out more about them with a view to tailoring increasingly sophisticated treatment programmes.
Although it’s far too early to say how these might look, they might potentially entail a plan guiding factors such as diet, exercise and lifestyle.
“What you end up doing is not necessarily individualising to the actual individual but you can find profiles of people who have similar patterns and then advise them. Those groupings of people would not be not based on traditional things like gender, deprivation and ethnicity which might be very crude groups that don’t really work for mental health,” she said.
“Just lumping all black people or all white people together is really quite ridiculous. So you can then go much further into really understanding the nuances if you can start unpicking with artificial intelligence the underlying patterns in the data sets that the computer technology can pick up that a normal human undertaking statistical models in the normal ways don’t pick up. Because we are hypothesis testing and what they do is much more exploratory. It’s basically what we call fishing in the data – it’s a completely different way of using the data sets,” she said.