OBJECTIVE : To present the seventh in a series of articles designed to deconstruct chronic low back pain (CLBP) in older adults. This article focuses on insomnia and presents a treatment algorithm for managing insomnia in older adults, along with a representative clinical case. METHODS : A modified Delphi process was used to develop the algorithm and supportive materials. A multidisciplinary expert panel representing expertise in health psychology and sleep medicine developed the algorithm and supporting documents that were subsequently refined through an iterative process of input from a primary care provider panel. RESULTS : We present an illustrative clinical case and an algorithm to help guide the care of older adults with insomnia, an important contributor to CLBP and disability. Multicomponent cognitive behavioral therapy for insomnia (CBTI) and similar treatments (e.g., brief behavioral treatment for insomnia [BBTI]) are the recommended first-line treatment. Medications should be considered only if BBTI/CBTI is suboptimal or not effective and should be prescribed at the lowest effective dose for short periods of time (< 90 days). CONCLUSIONS : Insomnia is commonly comorbid with CLBP in older adults and should be routinely evaluated and treated because it is an important contributor to pain and disability. The algorithm presented was structured to assist primary care providers in planning treatment for older adults with CLBP and insomnia.
Overall, the findings suggest that sedative-hypnotic medications were overwhelmingly the primary treatment recommendation despite evidence to support CBT-I as the recommended first-line treatment. However, key factors were identified that increased the likelihood of Veterans being referred for CBT-I. Suggestions for better identifying and understanding key factors that impact treatment recommendations are discussed.
This study extends the MPI literature by establishing the usefulness of the measure in determining those reports of MVC-related pain and emotional distress that are most likely to be associated with postcollision psychological disability. The current study supports the usefulness of MPI profile classifications in identifying MVC patients who are likely to require and benefit from intensive psychological and other rehabilitative interventions.
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