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Published on: August 8, 2019
Identifying and characterizing longitudinal patterns of insomnia across the deployment cycle in active duty Army
Katherine E Miller1, Christine M Ramsey1,2, Elaine M Boland1,3
1Mental Illness Research, Education and Clinical Center, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA.
Study Objectives:
The present study characterized a sample of 4,667 Army soldiers based on their patterns of insomnia before, during, and after deployment, and explored pre-deployment factors predictive of these patterns.
Methods:
Data were analyzed from the Army Study to Assess Risk and Resilience in Service members (STARRS)-Pre/Post Deployment Study (PPDS), using surveys that captured data approximately 1-2 months pre-deployment, and 3- and 9-month post-deployment from soldiers deployed to Afghanistan. Patterns of insomnia across time were examined. Theoretically derived variables linked to sleep disturbance were examined as predictors of the insomnia patterns.
Results:
Five longitudinal patterns of insomnia characterized the majority of the sample: "No Insomnia" (no insomnia symptoms at any timepoint; 31%), "Deployment-related Insomnia" (no pre-deployment insomnia, developed insomnia symptoms during deployment and recovered; 40%), "Incident Insomnia" (development insomnia during or shortly after deployment that did not remit; 14%), "Chronic Insomnia" (insomnia both pre- and post-deployment; 11%), and "Other Insomnia" (reported insomnia at ≥1 timepoint, but no clear pattern across the deployment cycle; 4%). Several pre-deployment factors were predictive of insomnia trajectories, including lifetime major depressive episodes, traumatic brain injury history, posttraumatic stress disorder, and past year personal life stressors.
Conclusions:
Distinct longitudinal patterns of insomnia were identified, with more than half of the sample reporting insomnia at some point in the deployment cycle. Identifying mental health conditions that are associated with different insomnia patterns prior to deployment can inform targeted interventions to reduce long-term sleep difficulty.
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