Track Everything About Your Sleep? Keep Only the Wake Time

A 27-year-old woman’s Fitbit told her she slept at 60% efficiency; her overnight sleep study found no sleep-disordered breathing and normal arousals, and she still asked why the Fitbit said she slept poorly. Cases like hers gave orthosomnia its name, the term clinicians use for a preoccupation with perfecting wearable sleep data. The worry is that chasing a good score may lead people to spend more time in bed, fret at night, or distrust how rested they feel. The popular advice to track everything about your sleep in order to improve it rests on the assumption that more numbers mean more control. For most of the numbers, that assumption fails.

This post is a counter-take, so a disclosure: the author’s company, DontSnooze, makes an alarm app where friends can see whether you woke up, which is a bet on the one number argued for below. Read the argument with that in mind.

What the original orthosomnia paper actually described

Kelly Glazer Baron, Sabra Abbott, Nancy Jao, Natalie Manalo and Rebecca Mullen coined the word in the Journal of Clinical Sleep Medicine in 2017 (volume 13, issue 2, pages 351 to 354). They built it from “ortho” (straight, correct) and “somnia”, on the model of orthorexia, the unhealthy fixation on eating healthily. The paper is a case series of three patients, not a prevalence study, and it should be read that way. There is a longer overview of the orthosomnia pattern elsewhere on this site; the narrower point here is what the three cases share.

All three patients spent more time in bed trying to raise the tracker’s sleep total, which the authors suggested may have worsened their insomnia. The woman above was one of them. The authors report that educating patients about tracker validity did not change their beliefs, even with polysomnography data in hand. Their own caveat matters: two of the three devices were gifts, and no one knows how these patients slept before tracking began.

What the validation data say about the numbers

The strongest counter to “the data is just wrong” is that part of it is fine. Chinoy and colleagues (Sleep, 2021) put seven consumer devices against polysomnography in 34 healthy adults aged 28.1 on average. Every device had sensitivity of at least 0.93 for sleep. Wake detection was the weak side: specificity ran from 0.18 (Garmin Fenix 5S) to 0.54 (Fitbit Alta HR). Total sleep time errors ranged from -0.3 minutes (ResMed S+) to +46.8 minutes (Garmin Vivosmart 3). All six devices that reported stages differed from polysomnography on light sleep.

So a single night’s duration may be off by most of an hour, and the stage labels, which the study found inconsistent against polysomnography, deserve less trust than the headline total. The participants were healthy young adults in a lab, and the authors caution that results may not carry over to clinical populations or home use. The AASM’s 2018 position statement (Khosla et al., J Clin Sleep Med) is blunter about the consumer side: these devices cannot be used to diagnose or treat sleep disorders at this time.

The claim: wake time is the only number worth acting on

Of everything a tracker reports, wake time is the only value that is both observable without the device and something a person can change on purpose. Total sleep, efficiency, stages and readiness scores are outputs you cannot set directly; trying to move them is how the patients in that case series ended up lingering in bed. Wake time is an input: you decide it, an alarm enforces it, and the rest of the night adjusts around it.

Clinical practice points the same way. Standard CBT-I fixes the rise time and computes everything else from it, a logic laid out in three jobs a fixed wake time does. And timing consistency has its own research line, including a 2024 analysis covered in the sleep regularity versus duration comparison.

The rest should be treated as weather: worth a glance, useless as a goal. A “readiness 61” is something that happened to you overnight, not an assignment.

What would change this view

Three things, in order of how much they would move me. First, a randomized trial in which people without insomnia who received nightly stage and score feedback slept better or functioned better than controls with the tracker hidden. Second, validation showing that devices time the final awakening accurately at home. The numbers above are epoch-by-epoch agreement in a lab, not final wake time, so “the tracker gets wake time right” is not something this post can claim. The argument is that wake time does not need the tracker: a clock and a bed-exit event will do. Third, evidence that people who open their score every morning are not more anxious than people who do not. The Baron paper cannot answer that, since it describes three people who sought treatment.

There is also a fair objection from the other side. Trackers sometimes surface real problems, and the AASM statement itself says the data may enhance the patient-clinician interaction. Someone whose tracker repeatedly flags snoring or very short nights has a reason to see a clinician. That is a use of the data as a prompt, not as a daily scoreboard.

A practical test for the ring on your finger

Pick a fixed wake time and keep it for two weeks, weekends included. Wear the tracker or do not. If you wear it, do not open the app until after you have rated how rested you feel on paper. Compare. The authors of the orthosomnia paper proposed a similar experiment for clinic patients: contrast subjective sleep quality and daytime function with and without the tracker. If your own ratings and your score disagree, the score is the number to doubt, because it is the one a wrist sensor inferred from movement and heart rate.