This study investigated whether inter-episode sleep/circadian variables are associated with illness course and concurrent symptoms in bipolar disorder. Our hypothesis that greater inter-episode sleep disturbance would correlate with a more chronic and severe illness course was partially supported. Specifically, having experienced a greater number of depressive episodes was associated with poorer and more variable sleep efficiency and with more variable TWT. Additionally, although the correlation was not statistically significant, a greater number of depressive episodes was also associated with more variability in bedtime. These findings raise the possibility that an unstable sleeping pattern, particularly as indicated by poor and variable sleep efficiency and TWT, may be a correlate of or contributor to a depressive bipolar disorder illness course. It may be the case that experiencing a greater number of depressive episodes, which are marked by disturbed sleep, leads to spending more time in bed than is spent sleeping, possibly as the bed comes to be associated with poor sleep and depression. Alternately, spending excessive time awake in bed may have detrimental effects on mood. Indeed, in recent discussions of hypersomnia, we have suggested that excessive time in bed (i.e., poor sleep efficiency) may contribute to depression through associated interpersonal, occupational, and self-esteem problems (Kaplan & Harvey, in press
). Perhaps an escalating vicious cycle may develop between a tendency toward experiencing depression and an inconsistent and disturbed sleep pattern.
One finding partially supported our second hypothesis that greater inter-episode sleep disturbance would be associated with more concurrent manic and depressive symptoms. Specifically, variability in falling asleep time was positively correlated with concurrent depressive symptoms. The potential conclusions we can draw from this correlation are tentative given that this was the only significant correlation to support our hypothesis. However, this finding is consistent with the idea discussed above that a tendency toward experiencing depressive symptoms may be associated with more unstable sleep patterns. Additionally, in contrast to our hypothesis, we also found a higher level of manic symptoms to be associated with increased sleep efficiency. This is surprising because sleep efficiency is typically considered to be a sign of good sleep; the higher the sleep efficiency, the larger the portion of the time spent in bed is spent sleeping. Additionally, although not statistically significant, we found a negative correlation of medium size between TWT and manic symptoms other than sleep disturbance (total YMRS score excluding the item assessing sleep disturbance), suggesting that those individuals who were experiencing more manic symptoms also spent less time awake at night trying to sleep. These findings raise the possibility that experiencing more manic symptoms may be associated with a greater likelihood of leaving the bed during awakenings in the night or getting up earlier in the morning and starting the day rather than attempting to return to sleep. It is possible that this behavior may be related to the excessive goal-directed activity that has been observed in inter-episode bipolar disorder (Johnson, Ruggero, & Carver, 2005
). This possible link between sleep efficiency and manic symptoms during the inter-episode period warrants further investigation.
Our third hypothesis was that tendency toward delayed phase would be associated with a more severe and chronic illness course and with more concurrent symptoms. This hypothesis was not supported. It is possible that the fairly low percentage of participants (20%) reporting a bedtime or falling asleep time that was later than 1 AM likely resulted in a reduced range in the data set, limiting the possibility of significant correlations emerging. On the one hand, this is a potential limitation. On the other hand, perhaps the low number of individuals with late bedtimes may indicate that a tendency toward delayed phase may be less prevalent in, and central to, bipolar disorder than has been theorized. If the latter turns out to be true, these findings would be in contrast to the recent emphasis on delayed phase as a core deficit in bipolar disorder (Staton, 2008
) and to questionnaire data from adults with bipolar disorder (Mansour et al., 2005
). Future studies using questionnaire data to assess tendency toward a delayed phase may benefit from considering bedtime, falling asleep time, and midsleep time, particularly on days when individuals’ sleep schedules are not constrained by their work schedule. Data identifying hich of the days the diary was kept were such unconstrained days was not available in the present study. We emphasize that the gold standard method for assessing circadian phase is the direct measurement of the circadian clock (i.e., through melatonin) in a forced desynchronization protocol (Dijk & Cajochen, 1997
). Given the involved nature of this method, it might be considered unethical to ask an individual with bipolar disorder to participate, and anyone who could successfully complete the protocol may well not be representative of most bipolar individuals. Thus, although neither questionnaire nor diary data are the gold standards for assessing tendency toward delayed phase, they are reasonable proxies. Importantly, the mixed data obtained with these methods warrants further investigation of the hypothesis that a delayed phase contributes to the onset and maintenance of bipolar disorder.
Several researchers have suggested that cognitive behavioral approaches for insomnia be applied to bipolar disorder while including calls for an empirical approach to adapting existing interventions and developing new interventions (Harvey, 2008
; Plante & Winkelman, 2008
). As one step in this direction, we found that sleep efficiency and TWT and their variability were significantly associated with lifetime history of depressive episodes and with concurrent symptoms. Given the chronic and treatment-resistant nature of bipolar depression (Sachs et al., 2007
), it is important to target variables such as sleep disturbance that are potential contributors to depressive illness course in bipolar disorder. Sleep efficiency and variability in sleep may be particularly noteworthy variables to consider given that the goal of two empirically supported treatments for insomnia, stimulus control and sleep restriction, is to increase sleep efficiency and regularize the sleep-wake cycle (Morin et al., 2006
). Stimulus control and sleep restriction are the most thoroughly empirically tested and supported treatments for insomnia (Morin et al., 2006
). They are thought to target conditioned night-time anxiety and arousal. Rather than staying in bed when having trouble falling asleep at the beginning of the night or after an awakening in the middle of the night, patients treated with stimulus control and sleep restriction are encouraged to leave the bed and bedroom when they cannot sleep, attempting to initiate or resume sleep only when they feel that sleep is imminent. Additionally, patients set a regular waking time for the morning regardless of the time they actually fall asleep. If this approach were trialed in patients with bipolar disorder, manic symptoms would need to be carefully monitored as both stimulus control and sleep restriction may involve a mild form of short-term sleep deprivation, which could place individuals with bipolar disorder at risk for increased manic symptoms (Harvey, 2008
). This is particularly important given the present findings linking increased manic symptoms with increased sleep efficiency.
A number of potential limitations must be noted. First, we recognize that our discussion needs to be tempered because of the relatively small sample (n = 21). However, we emphasize that our chosen participant group can be difficult to recruit and retain, and that a strength of our approach was its inclusion of a detailed characterization of sleep, including many of the “gold standard” measures (Buysee et al., 2006). Given the sample size, we carefully considered our approach to multiple statistical comparisons. On the one hand, not correcting for multiple comparisons increases the risk of Type I error. On the other hand, applying a correction for multiple comparisons increases the risk of Type II error. On balance, we elected not to correct for multiple comparisons as we were more concerned with decreasing the risk of Type II error because links between variables considered in this study have not previously been investigated (Nakagawa, 2004
). Given our goal of identifying potential treatment targets for interventions designed to address sleep disturbance in bipolar disorder, we believe it was important to investigate associations between a variety of sleep variables and clinical factors. We hope these findings will allow future investigations to take a more targeted approach enabling fewer statistical tests. Second, we relied on self-report for assessing sleep disturbance. Future studies should try to replicate these findings with objective naturalistic sleep measures such as actigraphy. Third, we assessed sleep over the course of one week. It is possible that a longer duration of sleep assessment (2 weeks or longer) would have yielded a more accurate impression of participants’ sleep. Fourth, although the NIMH-LCMr is a well-validated measure of bipolar illness course, it is retrospective and is potentially subject to recall bias. It may be the case that those individuals who were experiencing more disturbed sleep and were more prone to mood disturbance were more likely to recall negative past experiences. Supplementing such a measure with data collected from medical records would be useful in future research. Fifth, our sample was primarily recruited via advertisements. It is possible that the socioeconomic or clinical characteristics of individuals responding to research advertisements may differ from the larger population of bipolar individuals. Thus, future investigations of bipolar disorder should utilize multiple recruitment strategies. Sixth, there are potentially confounding effects of psychotropic medications on sleep. However, given that no medication taken by our participants is consistently associated with sedating/activating effects, any possible effects of medications on sleep are likely to have been randomly distributed in the sample. In addition, side effects often wear off or diminish as individuals continue on a medication course (Talbot et al., 2009
). In spite of these limitations, we believe that our findings support the theory that sleep disturbance may be a potential trait marker of bipolar disorder, and they extend previous research by raising the importance of SE and sleep variability as critical sleep parameters in bipolar disorder.