Why measuring sleep matters beyond sleep-focused clinical trials
Even when it is not the primary focus of a clinical trial, sleep is an important component to track and measure. Poor or disrupted sleep can affect daily functioning and quality of life, overlap with symptoms such as fatigue, and potentially signal an unintended effect of treatment [1].
According to the National Institutes of Health, sleep disturbance can “skew efficacy data, mimic or mask adverse drug events, reduce participant compliance, and alter placebo responses” in a clinical trial. Sleep acts as a “confounding variable that impacts both subjective symptom reporting and objective physiological endpoints" [2]. Sleep can also overlap with other symptoms commonly measured in clinical trials, including fatigue and daytime functioning. Therefore, understanding sleep may provide important context for interpreting treatment benefits and the broader patient experience.
Sleep is not a single concept, however. Difficulty falling asleep, disrupted sleep, poor sleep quality and excessive daytime sleepiness are related but distinct experiences. Thus, selecting a fit-for-purpose Clinical Outcome Assessment (COA) starts with understanding which of these concepts is most relevant to the population, treatment, and study objectives.
What aspects of sleep may need to be measured?
Several patient-reported outcomes (PROs) are available to assess sleep, each one uniquely designed and validated to answer different questions.
The Pittsburgh Sleep Quality Index (PSQI), for example, assesses sleep quality and disturbances over a one-month period. Its 19 self-reported items contribute to seven component scores covering areas such as sleep duration, sleep latency, sleep efficiency, and sleep disturbances [3].
For studies specifically concerned with insomnia, the Insomnia Severity Index (ISI) is a seven-item instrument that measures the nature, severity, and impact of insomnia [4]. In fact, measuring insomnia can also be important in trials that aren’t focused on sleep. Research shows that insomnia and nighttime sleep difficulties are common in people suffering from chronic pain, cancer, cardiovascular and respiratory disease, and depression and anxiety, and can have a meaningful impact on daily functioning and quality of life [5].
Daytime sleepiness is another wholly distinct concept. The Epworth Sleepiness Scale (ESS) measures a person’s usual level of daytime sleepiness. Rather than asking patients about the quality of their nighttime sleep, the ESS asks about the likelihood that they may fall asleep during eight every-day situations such as sitting and reading, watching television, or sitting quietly after lunch. Even in trials for an entirely non-sleep related condition, the ESS can be critical in understanding whether a treatment is achieving its intended clinical effect. If patients experience daytime sleepiness that interferes with work, driving, social activities, or other aspects of daily life, it can have a meaningful impact on their quality of life and overall treatment experience.
Start with the concept, not the instrument
Sleep does not need to be the primary focus of a clinical trial for these concepts to matter. In fact, a treatment may achieve its intended clinical effect while patients continue, or start, to experience poor sleep, insomnia symptoms or daytime sleepiness that can affect how they feel and function. Measuring the relevant aspects of sleep can provide a fuller picture of treatment benefit and the patient’s experience during treatment.
There is no single “sleep COA” that is appropriate for every clinical trial. The appropriate, fit-for-purpose instrument depends on the specific population, context of use and concept of interest.
Researchers must first evaluate what role sleep can play in the condition or treatment being studied. Questions such as “could the disease itself affect sleep?”, “could the treatment improve or disrupt it?” and “could daytime sleepiness affect patients’ ability to function in their daily lives?” can serve as starting points for which concept is of interest. Including the patient voice by understanding the most salient and meaningful aspects of health is fundamental to a patient-focused endpoint strategy, and foundational in the determination of which concepts to pursue.
A well-defined concept makes it easier to then evaluate the available instruments and the evidence supporting their use. From there, study teams can determine the fit-for-purpose COA that has been validated to measure the concept of interest. Sleep quality, insomnia and daytime sleepiness are related, but each captures a different part of the patient experience.
Each of the three COAs mentioned in this article address different aspects of sleep and its impact on patients. The PSQI may be considered when the study needs to understand overall sleep quality and sleep patterns, the ISI when insomnia symptoms and their impact are of interest, and the ESS when daytime sleepiness is the concept the study needs to capture.
When considering sleep in a clinical trial, the first step is to identify which aspect of sleep could provide meaningful information about the treatment and the patient experience. Starting with that question can help study teams determine whether sleep should be measured and select a COA that is fit for purpose.
Explore sleep-related Clinical Outcome Assessments in ePROVIDE™ to review instrument characteristics, available translations, conditions of use and supporting measurement information.
References
[1] McCarthy M, Murphy P, Rosenberg R, Orford C. The overlooked vital sign: The importance of measuring sleep in drug development studies. Drug Discov Today. 2022 Mar;27(3):690-696. doi: 10.1016/j.drudis.2021.12.003. Epub 2021 Dec 9. PMID: 34896625.
[2] Koffel E, Kats AM, Kroenke K, Bair MJ, Gravely A, DeRonne B, Donaldson MT, Goldsmith ES, Noorbaloochi S, Krebs EE. Sleep Disturbance Predicts Less Improvement in Pain Outcomes: Secondary Analysis of the SPACE Randomized Clinical Trial. Pain Med. 2020 Jun 1;21(6):1162-1167. doi: 10.1093/pm/pnz221. PMID: 31529104; PMCID: PMC7069777.
[3] Carpi M. The Pittsburgh Sleep Quality Index: a brief review. Occup Med (Lond). 2025 Apr 4;75(1):14-15. doi: 10.1093/occmed/kqae121. Erratum in: Occup Med (Lond). 2025 Jul 14;75(3):214. doi: 10.1093/occmed/kqaf038. PMID: 40190123; PMCID: PMC11973415.
[4] Eric B. Larson, Sleep Disorders in Neurorehabilitation: Insomnia. Sleep Medicine Clinics, Volume 7, Issue 4, 2012, Pages 587-595. https://doi.org/10.1016/j.jsmc.2012.08.003.
[5] Van Straten A, Weinreich KJ, Fábián B, Reesen J, Grigori S, Luik AI, Harrer M, Lancee J. The Prevalence of Insomnia Disorder in the General Population: A Meta-Analysis. J Sleep Res. 2025 Oct;34(5):e70089. doi: 10.1111/jsr.70089. Epub 2025 May 14. PMID: 40369835; PMCID: PMC12426706.