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SCIENTIFIC LITERATURE · PPR

The Effects of RBD Medications on Dream Content: A Critical Review of Evidence

· 2025-09-01

DOI: 10.31234/osf.io/5q92h_v1

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Research overview

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REM sleep behavior disorder, often an early marker of α-synucleinopathies, is characterized by the loss of REM-related muscle atonia and the occurrence of dream enactment behaviors. Dream reports in REM sleep behavior disorder are frequently described as more vivid, violent, and negative than typical dreams. However, evidence for this remains inconsistent, likely due to methodological variability and unaddressed confounds – most notably, the influence of pharmacological treatments. The extent to which medications affect REM sleep behavior disorder dream content remains poorly understood.This systematic review critically evaluates the literature on the effects of medications commonly used in REM sleep behavior disorder and Parkinson’s disease – including clonazepam, other benzodiazepines, melatonin, melatonin receptor agonists, levodopa, pramipexole, and other dopamine agonists - on dream content. We identified 27 relevant studies employing qualitative and/or quantitative methods.Our analysis revealed major methodological limitations across studies, including a lack of standardized protocols and definitions, frequent reliance on retrospective or anecdotal reports, and predominantly qualitative or semi-quantitative assessments. These limitations constrain the interpretability and comparability of findings. Available evidence offers only limited support for clonazepam, melatonin, and pramipexole in reducing disturbing dream content. More consistent, but still preliminary, evidence links levodopa to increases in vivid or disturbing dreams, including nightmares.This review highlights the need for rigorously controlled studies using standardized and reproducible methods to clarify the role of pharmacological treatments in shaping dream content in REM sleep behavior disorder. Future research should also integrate retrospective and prospective data-collection designs to account for potential recall biases.

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