Why optimising your sleep might be making it worse
Most people who struggle to sleep aren't doing anything wrong. They're doing too much. There's a clinical name for what happens when the pursuit of perfect sleep starts to produce the very sleeplessness you're trying to fix, and it's more common than you'd think.
It's 10:52pm. You put your phone on the nightstand, turn the light off, and find yourself thinking about a number you haven't been assigned yet.
You know roughly what you need to do, wind down, breathe, let the day go. But somewhere in the background, there's a calculation running. You had two glasses of wine at dinner. You went to bed later than usual. The room might be too warm. Any of these could hurt the score. You find yourself reviewing your choices like an athlete who had a bad training session, already preparing a post-mortem for something that hasn't happened yet.
At some point, you fall asleep. In the morning, before coffee, before conversation, before you've even decided how you feel, you check.
If you recognise any version of this, you're in good company. There's actually a clinical name for it: orthosomnia. Coined in 2017 and now formally measured by a validated psychometric scale developed in 2025 (the Bergen Orthosomnia Scale, published in Frontiers in Sleep), it describes the obsessive pursuit of perfect sleep driven by tracker data and the way that pursuit ends up producing the very sleeplessness you were trying to fix.
A 2024 cross-sectional study of over 500 adults found that somewhere between 3 and 14 percent of people meet criteria for orthosomnia, depending on how strictly it's defined. Separately, nearly one in five sleep app users reported that the app made them more worried about their sleep, not less.
None of this means the trackers are evil or that you should throw yours in a drawer. The interesting question is why this happens, and who it tends to happen to.
Sleep is probably the only performance domain where trying harder makes you measurably worse.
When you're working on something difficult, a decision, a presentation, a difficult conversation , effort helps. You can bring your prefrontal cortex to bear on the problem, monitor your progress, course-correct. But sleep doesn't work that way. Sleep onset requires the prefrontal cortex to effectively disengage. The monitoring, planning, and problem-solving circuitry that's useful for most of your day has to stand down. And what activates that circuitry most reliably is exactly what tracker culture encourages: attention, intention, and effort directed at sleep itself.
Research by Dressle (2023, Journal of Sleep Research) identified pre-sleep cognitive arousal, the mental monitoring and anticipatory thinking you do around sleep, as the most important symptom in the insomnia-hyperarousal network. It's not just correlated with bad sleep; it's mechanistically involved in producing it. When you lie in bed reviewing tonight's conditions, checking whether you feel sleepy enough, or planning how to optimise tomorrow's score, you're activating the exact system that sleep needs you to switch off.
There's also a separate problem: the data you're anxious about may not even be accurate.
Consumer sleep trackers are useful devices, but what they measure is an estimate. A 2023 multicentre study validating eleven consumer wearables against polysomnography (the clinical gold standard) found that while some devices perform reasonably well for total sleep time, sleep stage data, like deep sleep and REM, remains inconsistent across all of them. A 2025 validation study of six wearables reached a similar conclusion. The number on your app in the morning is a sophisticated approximation. When you treat it as a medical verdict and let it define how your day starts, you're ceding a lot of internal authority to something that was never designed to carry that weight.
One researcher decided to test this directly. She wore an Oura Ring for a month alongside keeping a daily diary and body maps of how she felt, comparing the app's data against her actual experience. One morning the app reported a sleep score of 76 and "enough restorative sleep." She felt stressed, unrested, and physically depleted. Her paper (Eccles & Pitt, 2024, Frontiers in Computer Science) is titled exactly that: "The sleep data looks way better than I feel." The gap she documented wasn't unusual.
The profile of who orthosomnia tends to affect is worth sitting with for a moment.
The Bergen Orthosomnia Scale study found that both factors of orthosomnia, interference with daily life and rigidity about what "good sleep" must look like, correlate positively with perfectionism, health anxiety, high sleep effort, and dysfunctional beliefs about sleep. In other words, the people most likely to develop a problematic relationship with their tracker are the people who were already anxious about performance, already prone to self-monitoring, and already inclined to treat health as something to be optimised rather than attended to.
The tracker doesn't create something new. It gives something that already existed a very specific, very measurable new home.
For a lot of people who come to this kind of work, the sleep issue and the perfectionism issue turn out to be the same issue wearing different clothes.
If this resonates, a few things that tend to be useful are:
Note: Take this into consideration, not as sleep hygiene prescriptions, but as ways of reorienting your relationship to data and to your own body.
The morning check. Before you look at any score tomorrow morning, take thirty seconds and write down one sentence about how you feel. Not an evaluation, just a description. Then look at the score. Notice whether the number changes your felt sense. Notice how much authority you give it.
The verdict question. When the score is low, ask yourself: is this data, or is this a verdict? Data is something you factor in. A verdict is something you accept as true and act on immediately. These are different things, and your tracker was designed for the first.
The untracked week. Take your tracker off for seven days. Not forever, just seven days. Pay attention to what changes, and what you notice about yourself when the feedback loop is removed. What do you use instead to know how you slept?
The body's version. Think back to the last time you woke up and just knew you'd slept well, without checking anything. What did that feel like? Where did you feel it? Write that down. That's information too, arguably better calibrated to you than any algorithm.
Sleep is not a performance metric. It's a biological process, and for most of human history, people managed to do it without a score.
The data can be useful. But there's a difference between information that helps you notice patterns and a system you've handed authority over to. When the device designed to help you sleep becomes the thing keeping you awake, that's worth looking at, not as a problem with the technology, but as something the technology has made visible about how you relate to your own internal experience. That, more than any sleep score, is usually where the real work begins.
If you're noticing patterns around performance, recovery, or how you relate to your body's signals, and you'd like to explore what's behind them, I offer an initial 15-minute consultation. You can find out more and book through the contact page.
References:
Kolla, B.P. et al. (2023). The Tale of Orthosomnia: I Am so Good at Sleeping that I Can Do It with My Eyes Closed and My Fitness Tracker on Me. Nature and Science of Sleep. https://pmc.ncbi.nlm.nih.gov/articles/PMC9875581/
Pallesen, S. et al. (2025). Development of a scale for measuring orthosomnia: the Bergen Orthosomnia Scale (BOS). Frontiers in Sleep. https://www.frontiersin.org/journals/sleep/articles/10.3389/frsle.2025.1640355/full
Suh, S. et al. (2024). Prevalence of Orthosomnia in a General Population Sample: A Cross-Sectional Study. Brain Sciences. https://pmc.ncbi.nlm.nih.gov/articles/PMC11592250/
Eccles, A. & Pitt, A. (2024). "The sleep data looks way better than I feel." Frontiers in Computer Science. https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2024.1258289/full
Dressle, R.J. (2023). Hyperarousal in insomnia disorder: Current evidence and potential mechanisms. Journal of Sleep Research. https://onlinelibrary.wiley.com/doi/10.1111/jsr.13928
Chinoy, E.D. et al. (2023). Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study. JMIR mHealth and uHealth. https://mhealth.jmir.org/2023/1/e50983
Menghini, L. et al. (2025). A performance validation of six commercial wrist-worn wearable sleep-tracking devices compared to polysomnography. SLEEP Advances. https://academic.oup.com/sleepadvances/article/6/2/zpaf021/8090472