It’s one of the most pervasive messages about technology and sleep. We’re told bright, blue light from screens prevents us falling asleep easily. We’re told to avoid scrolling on our phones before bedtime or while in bed. We’re sold glasses to help filter out blue light. We put our phones on “night mode” to minimise exposure to blue light.

But what does the science actually tell us about the impact of bright, blue light and sleep? When our group of sleep experts from Sweden, Australia and Israel compared scientific studies that directly tested this, we found the overall impact was close to meaningless. Sleep was disrupted, on average, by less than three minutes.

We showed the message that blue light from screens stops you from falling asleep is essentially a myth, albeit a very convincing one.

Instead, we found a more nuanced picture about technology and sleep.

What we did

We gathered evidence from 73 independent studies with a total of 113,370 participants of all ages examining various factors that connect technology use and sleep.

We did indeed find a link between technology use and sleep, but not necessarily what you’d think.

We found that sometimes technology use can lead to poor sleep and sometimes poor sleep can lead to more technology use. In other words, the relationship between technology and sleep is complex and can go both ways.

How is technology supposed to harm sleep?

Technology is proposed to harm our sleep in a number of ways. But here’s what we found when we looked at the evidence:

• bright screen light – across 11 experimental studies, people who used a bright screen emitting blue light before bedtime fell asleep an average of only 2.7 minutes later. In some studies, people slept better after using a bright screen. When we were invited to write about this evidence further, we showed there is still no meaningful impact of bright screen light on other sleep characteristics including the total amount or quality of sleep
• arousal is a measure of whether people become more alert depending on what they’re doing on their device. Across seven studies, people who engaged in more alerting or “exciting” content (for example, video games) lost an average of only about 3.5 minutes of sleep compared to those who engaged in something less exciting (for example, TV). This tells us the content of technology alone doesn’t affect sleep as much as we think
• we found sleep disruption at night (for example, being awoken by text messages) and sleep displacement (using technology past the time that we could be sleeping) can lead to sleep loss. So while technology use was linked to less sleep in these instances, this was unrelated to being exposed to bright, blue light from screens before bedtime.

Which factors encourage more technology use?

Research we reviewed suggests people tend to use more technology at bedtime for two main reasons:

• to “fill the time” when they’re not yet sleepy. This is common for teenagers, who have a biological shift in their sleep patterns that leads to later sleep times, independent of technology use.
• to calm down negative emotions and thoughts at bedtime, for apparent stress reduction and to provide comfort.

There are also a few things that might make people more vulnerable to using technology late into the night and losing sleep.

We found people who are risk-takers or who lose track of time easily may turn off devices later and sacrifice sleep. Fear of missing out and social pressures can also encourage young people in particular to stay up later on technology.

What helps us use technology sensibly?

Last of all, we looked at protective factors, ones that can help people use technology more sensibly before bed.

The two main things we found that helped were self-control, which helps resist the short-term rewards of clicking and scrolling, and having a parent or loved one to help set bedtimes.

Why do we blame blue light?

The blue light theory involves melatonin, a hormone that regulates sleep. During the day, we are exposed to bright, natural light that contains a high amount of blue light. This bright, blue light activates certain cells at the back of our eyes, which send signals to our brain that it’s time to be alert. But as light decreases at night, our brain starts to produce melatonin, making us feel sleepy.

It’s logical to think that artificial light from devices could interfere with the production of melatonin and so affect our sleep. But studies show it would require light levels of about 1,000-2,000 lux (a measure of the intensity of light) to have a significant impact.

Device screens emit only about 80-100 lux. At the other end of the scale, natural sunlight on a sunny day provides about 100,000 lux.

What’s the take-home message?

We know that bright light does affect sleep and alertness. However our research indicates the light from devices such as smartphones and laptops is nowhere near bright or blue enough to disrupt sleep.

There are many factors that can affect sleep, and bright, blue screen light likely isn’t one of them.

The take-home message is to understand your own sleep needs and how technology affects you. Maybe reading an e-book or scrolling on socials is fine for you, or maybe you’re too often putting the phone down way too late. Listen to your body and when you feel sleepy, turn off your device.

Chelsea Reynolds, Casual Academic/Clinical Educator and Clinical Psychologist, College of Education, Psychology and Social Work, Flinders University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Ovarian cancers are often found when they are already advanced and hard to treat.

Researchers have long believed this was because women first experienced symptoms when ovarian cancer was already well-established. Symptoms can also be hard to identify as they’re vague and similar to other conditions.

But a new study shows promising signs ovarian cancer can be detected in its early stages. The study targeted women with four specific symptoms – bloating, abdominal pain, needing to pee frequently, and feeling full quickly – and put them on a fast track to see a specialist.

As a result, even the most aggressive forms of ovarian cancer could be detected in their early stages.

So what did the study find? And what could it mean for detecting – and treating – ovarian cancer more quickly?

Why is ovarian cancer hard to detect early?

Ovarian cancer cannot be detected via cervical cancer screening (which used to be called a pap smear) and pelvic exams aren’t useful as a screening test.

Current Australian guidelines recommend women get tested for ovarian cancer if they have symptoms for more than a month. But many of the symptoms – such as tiredness, constipation and changes in menstruation – are vague and overlap with other common illnesses.

This makes early detection a challenge. But it is crucial – a woman’s chances of surviving ovarian cancer are associated with how advanced the cancer is when she is diagnosed.

If the cancer is still confined to the original site with no spread, the five-year survival rate is 92%. But over half of women diagnosed with ovarian cancer first present when the cancer has already metastatised, meaning it has spread to other parts of the body.

If the cancer has spread to nearby lymph nodes, the survival rate is reduced to 72%. If the cancer has already metastasised and spread to distant sites at the time of diagnosis, the rate is only 31%.

There are mixed findings on whether detecting ovarian cancer earlier leads to better survival rates. For example, a trial in the UK that screened more than 200,000 women failed to reduce deaths.

That study screened the general public, rather than relying on self-reported symptoms. The new study suggests asking women to look for specific symptoms can lead to earlier diagnosis, meaning treatment can start more quickly.

What did the new study look at?

Between June 2015 and July 2022, the researchers recruited 2,596 women aged between 16 and 90 from 24 hospitals across the UK.

They were asked to monitor for these four symptoms:

• persistent abdominal distension (women often refer to this as bloating)
• feeling full shortly after starting to eat and/or loss of appetite
• pelvic or abdominal pain (which can feel like indigestion)
• needing to urinate urgently or more often.

Women who reported at least one of four symptoms persistently or frequently were put on a fast-track pathway. That means they were sent to see a gynaecologist within two weeks. The fast track pathway has been used in the UK since 2011, but is not specifically part of Australia’s guidelines.

Some 1,741 participants were put on this fast track. First, they did a blood test that measured the cancer antigen 125 (CA125). If a woman’s CA125 level was abnormal, she was sent to do a internal vaginal ultrasound.

What did they find?

The study indicates this process is better at detecting ovarian cancer than general screening of people who don’t have symptoms. Some 12% of women on the fast-track pathway were diagnosed with some kind of ovarian cancer.

A total of 6.8% of fast-tracked patients were diagnosed with high-grade serous ovarian cancer. It is the most aggressive form of cancer and responsible for 90% of ovarian cancer deaths.

Out of those women with the most aggressive form, one in four were diagnosed when the cancer was still in its early stages. That is important because it allowed treatment of the most lethal cancer before it had spread significantly through the body.

There were some promising signs in treating those with this aggressive form. The majority (95%) had surgery and three quarters (77%) had chemotherapy. Complete cytoreduction – meaning all of the cancer appears to have been removed – was achieved in six women out of ten (61%).

It’s a promising sign that there may be ways to “catch” and target ovarian cancer before it is well-established in the body.

What does this mean for detection?

The study’s findings suggest this method of early testing and referral for the symptoms leads to earlier detection of ovarian cancer. This may also improve outcomes, although the study did not track survival rates.

It also points to the importance of public awareness about symptoms.

Clinicians should be able to recognise all of the ways ovarian cancer can present, including vague symptoms like general fatigue.

But empowering members of the general public to recognise a narrower set of four symptoms can help trigger testing, detection and treatment of ovarian cancer earlier than we thought.

This could also save GPs advising every woman who has general tiredness or constipation to undergo an ovarian cancer test, making testing and treatment more targeted and efficient.

Many women remain unaware of the symptoms of ovarian cancer. This study shows recognising them may help early detection and treatment.

Jenny Doust, Clinical Professorial Research Fellow, Australian Women and Girls’ Health Research Centre, The University of Queensland

This article is republished from The Conversation under a Creative Commons license. Read the original article.