The NIH investigation shows sleep delays circadian rhythm and reduces sleep times. The 2017 Nobel Prize for Biology Winning Theme “Controlling the molecular mechanisms for circadian rhythm”, pointed out that irregular sleep patterns may increase the risk of psychiatric and medical illnesses. For academia and clinicians, there is difficulty in long-term (months or years) naturalistic and objective recording of daily sleep patterns. The NIH Health Sciences Research Team led by Dr. Lin, has developed a smartphone-based automatic sleep recording system – “rhythm” which successfully solves this barrier to research. Using this system, we have found that smartphone use before bed affects circadian rhythm and sleep time.
Dr. Lin’s research discovered, that one hour of smartphone use during the day delays circadian rhythm by 3.5 minutes and decreases total sleep time by 5.5 minutes. Smartphone use before bedtime was only around 14.3% of total use, but had around 44% of the impact on sleep. Previous literature shows light exposure significantly impacts circadian rhythm. Dr. Lin’s research team demonstrated that use before bed time significantly affects circadian rhythm. The research results have recently been published in the March 2019 issue of the Journal of Psychiatric Research
The research team was comprised of researchers from National Taiwan University Hospital, Mackay Memorial Hospital, Chiao Tung University, and Dan Jiang University, with expertise in the fields of psychiatry, psychology, and statistics. The investigation utilized the “Rhythm” app and continuously collected smartphone use data for 14 days along with a questionnaire. A significant amount of data was collected and analyzed for use patterns and sleep times.
The method in which the “Rhythm” App collects sleep and use data is based on the times of the screen turning on and off. Most importantly, our research is the first that uses “proactive use” (turning on the smartphone, making phone calls, using applications) and “passive use” (receiving calls, receiving notifications) in our analytical algorithm to predict sleep times and to precisely calculate the impact of smartphone use on sleep times. Statistical analysis shows our methodology has 84% correlation to results from the user questionnaire.
Dr. Lin notes that most apps currently on the market must be manually set and have devices be worn or placed bedside in order to monitor and record behavior. If a user forgets to set, worn, or properly placed, the data collection is interrupted. The “Rhythm” App is completely automatic and collects data from continuously and calculates sleep times from this data. The App is also power efficient.
Dr. Lin also notes that the “Rhythm App” having the ability to continuously and automatically record use patterns and sleep times over long periods, will have utility in sleep and health monitoring. The “Rhythm” App will also have the ability to precisely calculate smartphone use and its impact on sleep. It is more objective then a user description or questionnaire, and is a breakthrough in research methodology. It will have great potential in the fields of sleep medicine and psychiatry.