For a few months now, I’ve been playing around with a sleep app to get a better idea of how easy they are to use, what data I could collect, and whether I’d remember to input my sleep data every day. When I first started using it, I was mainly interested in my sleep duration and sleep timing. Recently though, I’ve noticed the developers for my particular app have been adding more and more bells and whistles. There was always the option to indicate lights on and off times for your sleep period, with additional options to limit phone functions, such as receiving calls and emails overnight. However, my app now claims that it can use the accelerometer in my smartphone to accurately detect movement overnight, and interpret movement as sleep stages.
Many apps now include this feature, and provide users with a range of outputs from basic sleep structure to specific recommendations about how to improve sleep alongside their behaviour and sleep patterns. What is concerning though, is that some of these recommendations are not scientifically-based or in line with best practise. Most of these apps also claim to be extraordinarily accurate in their movement detection and sleep stage interpretation. These claims are somewhat surprising given that sleep researchers themselves have been using movement as a surrogate for sleep and wake for some time, and not one of us thinks we can accurately interpret sleep stages from that data. (Believe me, if it was possible, we would use it in a second.)
Activity monitors (actigraphs) are fairly reliable at detecting total sleep time (sleep duration). Although not quite as accurate, they also provide an acceptable measure of sleep onset latency (the time from lights out to falling asleep) and sleep fragmentation (broken sleep). Actigraphs are less reliable in clinical populations than in healthy adults. It is not known whether this reduced accuracy extends to those with sub-clinical sleep difficulties.
Actigraphs cannot reliably measure different sleep stages, and I think this is highly evident in the graphical representations of sleep that many of these apps produce. Often their sample diagrams show vastly abnormal sleep structure, and slow wave sleep shortly before waking. If you’re getting a healthy amount of sleep each night, slow wave sleep just prior to waking is extremely unlikely.
Many sleep apps now include a feature to optimise our time of waking, so that we wake from light sleep. This is purported to reduce sleep inertia, which is a sensation of grogginess, confusion and decreased functioning, experienced immediately on waking. Waking from slow wave sleep is thought to contribute to sleep inertia; however, sleep structure, sleep routine and time of day are also likely to be involved. However, if we are to assume that sleep stage detection was reliable and given that regularly waking from slow wave sleep would suggest restricted sleep duration, and/or poor sleep routine or timing, I wonder if the focus should be on improving overall sleep health, rather than fixation on alarm clock times.
That said, a few apps provide great advice on healthy sleep, with sensible advice on how to achieve it. Additionally, many people report benefit from using these apps (for example, waking feeling more refreshed) but I’m inclined to think that this results from a focus on achieving better sleep, and perhaps the effect of receiving personalised feedback on your own sleep, than the performance of the app itself.