A rapidly expanding scientific literature supports the frequent co-occurrence of sleep and circadian disturbances following mild traumatic brain injury (mTBI). Although many questions remain unanswered, the preponderance of evidence suggests that sleep and circadian disorders can result from mTBI. Among those with mTBI, sleep disturbances and clinical sleep and circadian disorders contribute to the morbidity and long-term sequelae across domains of functional outcomes and quality of life. Specifically, along with deterioration of neurocognitive performance, insufficient and disturbed sleep can precede, exacerbate, or perpetuate many of the other common sequelae of mTBI, including depression, post-traumatic stress disorder, and chronic pain. Further, sleep and mTBI share neurophysiologic and neuroanatomic mechanisms that likely bear directly on success of rehabilitation following mTBI. For these reasons, focus on disturbed sleep as a modifiable treatment target has high likelihood of improving outcomes in mTBI. Here, we review relevant literature and present a research agenda to 1) advance understanding of the reciprocal relationships between sleep and circadian factors and mTBI sequelae and 2) advance rapidly the development of sleep-related treatments in this population.
Experimental sleep restriction and deprivation lead to risky decision-making. Further, in naturalistic settings, short sleep duration and poor sleep quality have been linked to real-world high-risk behaviors (HRB), such as reckless driving or substance use. Military populations, in general, tend to sleep less and have poorer sleep quality than non-military populations due to a number of occupational, cultural, and psychosocial factors (e.g., continuous operations, stress, trauma). Consequently, it is possible that insufficient sleep in this population is linked to HRB. To investigate this question, we combined data from four diverse United States Army samples and conducted a mega-analysis by aggregating raw, individual-level data (n = 2296, age 24.7 ± 5.3). A negative binomial regression and a logistic regression were used to determine whether subjective sleep quality (Pittsburgh Sleep Quality Index [PSQI], Insomnia Severity Index [ISI] and duration [hours]) predicted instances of military-specific HRB and the commission of any HRB (yes/no), respectively. Poor sleep quality slightly elevated the risk for committing HRBs (PSQI Exp(B): 1.12 and ISI Exp(B): 1.07), and longer duration reduced the risk for HRBs to a greater extent (Exp(B): 0.78), even when controlling for a number of relevant demographic factors. Longer sleep duration also predicted a decreased risk for commission of any HRB behaviors (Exp(B): 0.71). These findings demonstrate that sleep quality and duration (the latter factor, in particular) could be targets for reducing excessive HRB in military populations. These findings could therefore lead to unit-wide or even military-wide policy changes regarding sleep and HRB.
EMA is emerging as a novel modality of assessment in rehabilitation. Scientists and clinicians should consider incorporating this assessment approach as a rehabilitation tool that may more accurately assess the complex and dynamic nature of disability over the long-term through an objective and ecologically-valid data source. Implications for rehabilitation Ecological momentary assessment (EMA) has been underutilized in the rehabilitation field and should be considered by researchers and clinicians as a novel assessment method for capturing rich, ecologically-valid data. EMA methods provide a greater capability to assess complex or difficult to measure outcomes of interest when compared with more traditional approaches conducted during finite clinic hours due to data collection occurring, with or without any input from the user, through wearable technology, and without a needed clinician presence. EMA data can be integrated with other data sources (e.g., self-report or clinician observation) to assess a more comprehensive picture of outcomes of interest, including highlighting discordance and identifying the most efficient target areas for intervention.
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