Gathering Data on Circadian Rhythms, Sleep in Adolescents Poses Challenges in Lab and Home Testing

The session held at SLEEP 2024 focused on the challenges of collecting data on sleep and circadian rhythms in adolescents, as well as the difference between home and lab measurements.

The challenges of collecting data on sleep and circadian rhythms in adolescents were discussed during a session held during the SLEEP 2024 Annual Meeting, held in Houston, Texas, between June 1 and June 5, 2024. The panel also focused on differences in the way both sleep and circadian phases are measured from the patient’s home to the lab.

Experts Reut Gruber, PhD, of McGill University; Helen Burgess, PhD, from the University of Michigan; and Merrill S. Wise, MD, a pediatric neurologist with Mid-South Pulmonary & Sleep Specialists, led the discussion of the unique challenges in collecting data for adolescents about their sleep cycles. The reason, said Gruber, to collect data on adolescent sleep is because there are a lot of changes occurring in adolescents during this time that can affect how much sleep they are receiving.

Teenager sleeping | Image credit: -

Teenager sleeping | Image credit: -

“What we know about adolescent sleep is that sleep is really a moving target in this age that really changes significantly relative to a younger age and it’s going to be different than what comes later, when we determine somebody is no longer a teenager,” said Gruber.

These changes can include a delay of sleep by about 2 hours without a change in their school start time, which can lead to sleep deprivation and circadian misalignment in regularly developing adolescents. Sleep pressure is also prevalent in adolescents, with sleep slowly building up in the child throughout the day. Slow wave sleep decreases while stage 2 deep nonrapid eye movement (NREM) sleep increases.

“We know that sleep is extremely significant as it relates to [adolescents’] physical health, to their emotional functioning, [and] to their cognitive functioning,” said Gruber. “Of course, it’s always important but maybe even more so during adolescence.”

Determining what parts of an adolescent’s sleep patterns is normal or abnormal can be tough, as different aspects of their sleep need to be measured by different types of measurements. For example, sleep duration as well as sleep quality can be measured with actigraphy, in-lab polysomnography (PSG), or a home-based electroencephalogram (EEG) test whereas circadian timing has to be measured using dim light melatonin onset (DLMO) timing testing. Gruber noted that self-reported measures were also used but less reliable, as adolescents may not be as diligent about noting their sleeping patterns.

Wrist actigraphy is a method that researchers use to measure sleep, as it only requires the participant to wear the wristwatch for the specified amount of time. In her experience as a researcher, Burgess noted that she has preferred FitBit over the ActiGraph device, as the FitBit is more affordable and has the best validation against PSG. However, she noted, the FitBit does have some downsides, notably in the way that it tracks activity.

“We want to look at sleep, but we’re also curious about other activities across the 24 hours,” said Burgess. “We realized we just got used to that and then we switched to FitBit and realized that you don’t get that. You get steps instead of activity and steps are nowhere near as sensitive.”

Burgess noted that a study conducted in 2021 found that better sleep detection was tracked with activity and heart rate when compared with PSG but noted that there’s hidden complexities in these devices, even if they outwardly look to be easy to use.

“In our lab, we have people text in just before they’re turning off the light to go to bed and then once they’re up for the day they text as well. And that’s been very valuable data, because the FitBit will sometimes say that someone fell asleep when they’re actually in bed just scrolling on their phone,” said Burgess.

EEGs that can be performed at home have their own pros and cons according to Wise. He said that the demand, stress, and impact on the patient or their family can be very different between EEGs done at the lab vs at home.

“Coming to the sleep lab is challenging for some families [between] transportation issues, getting off work, things of that type,” said Wise. “So there really can be a significant advantage, just from the family impact standpoint, of monitoring at home.”

Another challenge he noted was signal quality, where EEGs often give less signal quality when compared with in-lab PSGs and adolescents can place it on themselves incorrectly. Sleep-wake scoring is also very variable in adolescents who test at home, with differences coming due to the subject, the equipment or the algorithm. Wise also said that there are challenges with home EEG due to the interface from wake to sleep and sleep back to wake.

However, he said that at-home EEGs could be better at capturing how the patient actually lives. “In terms of capturing sleep patterns that are truly representative of the way the patient lives and sleeps at home, it’s obvious that in-laboratory [PSG] is very lacking,” said Wise. “We’re doing in-lab [PSG] in a very structured fashion in a bed that is not the patient’s home environment.”

Wise mentioned that “first night effect” often gives inaccurate readings for how a patient might sleep normally. EEG monitoring at home could help fix this issue by having the patient sleep in their own bed but hasn’t been thoroughly documented yet.

The last challenge he mentioned was finances, with insurance not covering PSGs the same way for everyone. This could lead to co-pays, deductibles, and other expenses piling up in a way that makes PSG not feasible. EEGs are less expensive by and large, which could allow for longer monitoring in these patients.

Gruber also noted the challenges that researchers face in participants using the PSGs. “We have had such challenges in terms of just getting participants,” she said. “To get them to actually sleep in a lab for research purposes, it’s not exactly what they’re dying to do.”

This can also be affected by capturing sleep in the summer, which does not always represent a participant’s normal sleep schedule during the school year, when they have to go to school at a certain time. However, she also noted that EEGs, while they are easier to take home for people, can have some drawbacks, as an adolescent in her research woke up with the device off of his head due to movement while sleeping.

Burgess noted that testing for dim light melatonin onset (DLMO), a gold standard in testing circadian phases, has both a lab and home version. The home version is likely easier for the participant and is less expensive, but the likelihood of data loss is higher in the home version. However, she recommended that, due to the time intensive nature of testing for DLMO, other methods, such as a timestamp sleep diary, can be implemented first to evaluate sleep timing and night to night variability.

The challenges of evaluating sleep cycles and circadian phases is documented but approaching each participant of a clinical trial or patient in a clinician’s office individually to discuss the best option for them could be a way to continue to best treat the patient and collect the best data for research. New developments in mobile technology, sleep testing, and circadian rhythm tracking could provide more effective and reliable ways to test in the future.

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