Sleep state misperception in psychiatric patients

Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study

BACKGROUND

Sleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive.

OBJECTIVE

This study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders.

METHODS

We analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs.

RESULTS

The findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P<.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments.

CONCLUSIONS

Our study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.

The paradox of paradoxical insomnia: A theoretical review towards a unifying evidence-based definition

Paradoxical insomnia is one of the most intriguing yet challenging subtypes of insomnia. Despite being recognized for a long time by the international community, it is still unclear whether this entity really exists, which are its features and boundaries. Much of the debate is fuelled by the lack of a consensus on its precise definition. To help filling some of the existing gaps, a systematic review of the literature was conducted, through which 19 different quantitative definitions were obtained. These definitions were then applied to two distinct datasets. The first consisted of 200 chronic primary insomnia patients, diagnosed according to the DSM-IV-TR criteria. The second consisted of 200 age- and sex-matched healthy persons without insomnia. For each dataset, available data from the objective sleep parameters and their subjective estimation were imported and analysed in MATLAB. Depending on the definition used, the prevalence of paradoxical insomnia ranged from 8 to 66%, while agreement between different definitions ranged from -0.19 to 0.9 (using Cohen's kappa coefficient). Based on the results garnered, necessary features for a quantitative definition of paradoxical insomnia were identified. Several open questions remain, such as whether there is a minimum number of hours a patient should sleep to fulfill the criteria for a diagnosis of paradoxical insomnia, and whether sleep latency can be used in the definition along with total sleep time. We conclude by advocating continued study of paradoxical insomnia and sleep state misperception and by providing specific directions for future research. STATEMENT OF SIGNIFICANCE: The current understanding of paradoxical insomnia and, more broadly, of sleep state misperception, is greatly hampered by the lack of agreement on a quantitative and evidence-base measure of the discrepancy between subjective and objective sleep evaluation. The current study provides a critical analysis about the strength and the limitations of the available definitions, using both a data-driven and a theory-driven approach. The overarching goal is to motivate a rigorous discussion involving the main experts of the field, to build a consensus, and develop an evidence-based measure of sleep state misperception and/or of paradoxical insomnia.