Study Objectives A critical barrier to successful treatment of circadian misalignment in shift workers is determining circadian phase in a clinical or field setting. Light and movement data collected passively from wrist actigraphy can generate predictions of circadian phase via mathematical models; however, these models have largely been tested in non-shift working adults. This study tested the feasibility and accuracy of actigraphy in predicting dim light melatonin onset (DLMO) in fixed-night shift workers. Methods A sample of 45 night shift workers wore wrist actigraphs before completing DLMO in the laboratory (17.0 days ± 10.3 SD). DLMO was assessed via 24 hourly saliva samples in dim light (&10 lux). Data from actigraphy were provided as input to a mathematical model to generate predictions of circadian phase. Agreement was assessed and compared to average sleep timing on non-workdays as a proxy of DLMO. Model code and a prototype assessment tool are available open source. Results Model predictions of DLMO showed good concordance with in-lab DLMO, with a Lin’s concordance coefficient of 0.70, which was twice as high as agreement using average sleep timing as a proxy of DLMO. The absolute mean error of the predictions was 2.88 hours, with 76% and 91% of the predictions falling with 2 and 4 hours, respectively. Conclusion This study is the first to demonstrate the use of wrist actigraphy-based estimates of circadian phase as a clinically useful and valid alternative to in-lab measurement of DLMO in fixed night shift workers. Future research should explore how additional predictors may impact accuracy.

Study Objectives Racial and ethnic minorities are more likely to suffer from insomnia that is more severe; however, few studies have examined mechanisms by which racial disparities in severity of insomnia disorder may arise. One potential mechanism for disparities in insomnia severity is perceived discrimination. This study tested discrimination as a mediator in the relationship between race and insomnia. Methods Participants were recruited from communities in the Detroit metropolitan area and were diagnosed with insomnia disorder using the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition). The final sample included 1,458 individuals. Insomnia symptom severity was assessed via the Insomnia Severity Index and self-reported racial discrimination was evaluated using a single item. Racial discrimination was tested as a mediator in the relationship between race and insomnia symptom severity. Individuals were categroized as either White or a racial minority (i.e., non White individuals), with sensitivity analyses examining Black individuals and non-Black racial minority groups. Results Consistent with our hypothesis, racial discrimination was a significant mediator accounting for 57.3% of the relationship between race and insomnia symptom severity. Sensitivity analyses indicated that the indirect effect of racial discrimination was stronger in the non-Black racial minority group compared to Black individuals. Conclusions These results provide support that racial discrimination is likely an important mechanism by which racial and ethnic sleep disparities exist. Implications for prevention, intervention, and treatment of insomnia in racial minorities to reduce health disparities are discussed.

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Background While the negative consequences of insomnia are well-documented, a strengths-based understanding of how sleep can increase health promotion is still emerging and much-needed. Correlational evidence has connected sleep and insomnia to resilience; however, this relationship has not yet been experimentally tested. This study examined resilience as a mediator of treatment outcomes in a randomized clinical trial with insomnia patients. Methods Participants were randomized to either digital cognitive behavioral therapy for insomnia (dCBT-I; n = 358) or sleep education control (n = 300), and assessed at pre-treatment, post-treatment, and 1-year follow-up. A structural equation modeling framework was utilized to test resilience as a mediator of insomnia and depression. Risk for insomnia and depression was also tested in the model, operationalized as a latent factor with sleep reactivity, stress, and rumination as indicators (aligned with the 3-P model). Sensitivity analyses tested the impact of change in resilience on the insomnia relapse and incident depression at 1-year follow-up. Results dCBT-I resulted in greater improvements in resilience compared to the sleep education control. Furthermore, improved resilience following dCBT-I lowered latent risk, which was further associated with reduced insomnia and depression at 1-year follow-up. Sensitivity analyses indicated that each point improvement in resilience following treatment reduced the odds of insomnia relapse and incident depression 1 year later by 76% and 65%, respectively. Conclusions Improved resilience is likely a contributing mechanism to treatment gains following insomnia therapy, which may then reduce longer-term risk for insomnia relapse and depression.

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