Medication is an important part of treatment for many patients with major depressive disorder, but the transition to antidepressants isn’t always smooth.
It can take six weeks for a person to respond to depression medications, but researchers at the University of Michigan who specialize in both psychiatry and sleep medicine found a potential way to help. A precise sleep schedule could affect antidepressant remission rates and response time, researchers found. But not in the way they thought.
In the new U-M study published in the Journal of Clinical Psychiatry, 68 adults were assigned to spend either six or eight hours in bed each night during their first two weeks on the antidepressant fluoxetine.
It’s the first study to assess the mood effects of a modest time-in-bed restriction on outpatients. Sleep and mood were measured daily for the first two weeks, and mood measurement continued weekly for six more weeks after the patients returned to their preferred sleep schedules and continued fluoxetine.
Surprisingly, the group who spent the full eight hours in bed each night showed greater improvements on all fronts. The subjects were almost twice as likely to achieve symptom remission after the full eight weeks of antidepressant treatment–63 percent compared with 33 percent in the six-hour group. They also experienced a faster response to treatment.
“This is the first study to demonstrate that adequate sleep might accelerate and augment antidepressant treatment response,” said J. Todd Arnedt, Ph.D., principal investigator and U-M associate professor in psychiatry and neurology.
Arnedt said more study is needed, but this is a good step toward understanding how sleep and antidepressants can work together.
Because this study was designed to primarily evaluate the effects of restricting time in bed on antidepressant treatment response, the next step, Arnedt says, is to directly assess whether optimizing or extending sleep time while initiating antidepressant therapy improves response. Optimization of the sleep schedule would involve considering not only how much people are sleeping but also individual factors such as a subject’s preferred sleep and wake times and sleep quality.