Your smartwatch knows your health data. But does it know how you feel?

Wearable trackers promise insight. As an occupational therapist, I want to talk about what the research actually says — and why your score might be working against you.

Wearables are everywhere. One in three Americans now tracks their sleep with a device. Clients come to my practice with screenshots of their sleep stages, heart rate scores, and recovery percentages — and often, they're more anxious about those numbers than they are about the sleep itself.

That's not coincidence. It's a pattern that has a name in sleep medicine now — and it's worth understanding before you strap on a device and expect it to fix things.

The case for tracking

Let's be fair: passive data collection is genuinely useful. You don't have to remember to log anything. Sleep duration trends, resting heart rate, step counts — these accumulate automatically over weeks and can reveal patterns you'd never notice from memory alone. For people rebuilding their health after burnout, having some objective signal alongside subjective reporting is valuable.

Wearables also work well as habit anchors. Research from Michigan State University found that long-term wearable users were successful because they started with small behavioral goals and gradually increased them, using consistent contextual cues to build routines. The device becomes part of the ritual.

That's reassuring news for anyone who's skipped a day and felt like they'd derailed everything.

Where the research gets complicated

Here's what the device manufacturers won't tell you: consumer wearables are reasonably good at detecting total sleep time, but poor at staging accuracy. They regularly misclassify light versus deep sleep. The score on your wrist is an estimate — and a rough one at that.

This mismatch matters because it can pull clients in two wrong directions: some believe they're sleeping fine because the app says so, despite feeling exhausted; others spiral into anxiety because their score dipped, even if they slept perfectly well.

Meet orthosomnia

In 2017, clinical psychologist Kelly Baron and her colleagues at Rush University Medical Center invented a term for what was showing up in sleep clinics: orthosomnia — an unhealthy preoccupation with achieving perfect sleep, driven by wearable data.

Dr. Sabra Abbott at Northwestern described it well: patients were coming in who didn't meet classical insomnia criteria, but were still being kept awake. They had become so dependent on their devices that they were destroying their sleep by not measuring up to what the tracker considered "good." They were even spending excessive time in bed trying to improve their scores — which, as anyone who's done CBT-I knows, is exactly the wrong move.

The most important thing sleep research tells us

Here's the clinical truth that gets lost in all the biometric noise: how rested you feel is the signal, not the score.

Sleep is fundamentally a subjective experience. Your brain's assessment of restoration is the outcome that matters. A study by Draganich and Erdal (2014) demonstrated this in a striking way — participants who were simply told they'd had poor sleep performed worse on cognitive tasks, even when their sleep was objectively normal. The belief created the impairment.

The score is a proxy. Your subjective sense of restoration is the outcome. When clients start chasing the score rather than feeling their way through recovery, I know the device has become part of the problem.

What about compulsive checking and habit loops?

The addiction risk with wearables isn't physiological — it's behavioral. Smartwatches operate on the same variable-reward loops as social media. The gamification layer (rings, streaks, recovery scores) is designed to create engagement. For most people that's benign. For someone already prone to health anxiety or optimization fixation, it can tip into compulsive checking — monitoring heart rate every few minutes, convinced a minor spike signals something serious.

On the flip side, wearable sensors are actively being used in addiction medicine research: Alinia et al. (2021), found that real-time stress measurement via wristbands could be used to develop new intervention techniques for relapse prevention in alcohol dependency. The same data stream that can fuel anxiety can also serve as an early-warning system in the right hands.

My clinical guidance as an OT

Closing remarks

A smartwatch is a context, not a cure. It amplifies whatever relationship you already have with data and performance. Used passively, with good data literacy and clear limits, it can genuinely support habit formation and health awareness. Used reactively — first thing in the morning, every hour, with notifications on — it adds a layer of vigilance that works against the nervous system regulation you're trying to rebuild. The goal is always to feel well, not to score well.

References

• Alinia, P., Sah, R. K., McDonell, M., Pendry, P., Parent, S., Ghasemzadeh, H., & Cleveland, M. J. (2021). Associations between physiological signals captured using wearable sensors and self-reported outcomes among adults in alcohol use disorder recovery: Development and usability study. JMIR Formative Research, 5(7), e27891. https://doi.org/10.2196/27891

• Baron, K. G., Abbott, S., Jao, N., Manalo, N., & Mullen, R. (2017). Orthosomnia: Are some patients taking the quantified self too far? Journal of Clinical Sleep Medicine, 13(2), 351–354. https://doi.org/10.5664/jcsm.6472

• Tsilivigkos, C., et al. (2024). Prevalence of orthosomnia in a general population sample: A cross-sectional study. Brain Sciences, 14(11), 1123. https://doi.org/10.3390/brainsci14111123

• Robbins, R., et al. (2025). Using consumer sleep trackers in clinical practice. CHEST Physician. https://www.chestphysician.org/consumer-sleep-trackers-in-clinical-practice/

• Draganich, C., & Erdal, K. (2014). Placebo sleep affects cognitive functioning. Journal of Experimental Psychology: General, 143(5), 2284–2290. https://doi.org/10.1037/a0037512

• Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Habit formation in wearable activity tracker use among older adults: Qualitative study. JMIR mHealth and uHealth, 9(1), e22488. https://doi.org/10.2196/22488

• Thomas, J. G., & Bond, D. S. (2019). Evaluating motivational interviewing and habit formation to enhance the effect of activity trackers on healthy adults' activity levels: Randomized intervention. JMIR mHealth and uHealth, 7(2), e10988. https://doi.org/10.2196/10988