Social Rhythm Disruption is Associated with Greater Depressive Symptoms in People with Mood Disorders: Findings from a Multinational Online Survey During COVID-19.

OBJECTIVES: Societal restrictions imposed to prevent transmission of COVID-19 may challenge circadian-driven lifestyle behaviours, particularly amongst those vulnerable to mood disorders. The overarching aim of the present study was to investigate the hypothesis that, in the routine-disrupted environment of the COVID-19, amongst a sample of people living with mood disorders, greater social rhythm disruption would be associated with more severe mood symptoms. METHODS: We conducted a two-wave, multinational survey of 997 participants (MAge=39.75±13.39,Female=81.6%) who self-reported a mood disorder diagnosis (i.e., major depressive disorder or bipolar disorder). Respondents completed questionnaires assessing demographics, social rhythmicity (The Brief Social Rhythm Scale), depression symptoms (Patient Health Questionnaire-9), sleep quality and diurnal preference (The Sleep, Circadian Rhythms and Mood questionnaire) and stressful life events during the COVID-19 pandemic (The Social Readjustment Rating Scale). RESULTS: The majority of participants indicated COVID-19-related social disruption had affected the regularity of their daily routines to at least some extent (n = 788, 79.1%). As hypothesised, lower social rhythmicity was associated with greater depressive symptoms when tested cross-sectionally (standardised ß = -.25, t = -7.94, P = 0.000) and when tested using a 2-level hierarchical linear model across two time points (b = -0.14, t = -3.46, df = 264, P ≤ 0.001). CONCLUSIONS: These results are consistent with the social zeitgeber hypothesis proposing that mood disorders are sensitive to life events that disrupt social rhythms.

Validity, potential clinical utility, and comparison of consumer and research-grade activity trackers in Insomnia Disorder I: In-lab validation against polysomnography.

Consumer activity trackers claiming to measure sleep/wake patterns are ubiquitous within clinical and consumer settings. However, validation of these devices in sleep disorder populations are lacking. We examined 1 night of sleep in 42 individuals with insomnia (mean = 49.14 ± 17.54 years) using polysomnography, a wrist actigraph (Actiwatch Spectrum Pro: AWS) and a consumer activity tracker (Fitbit Alta HR: FBA). Epoch-by-epoch analysis and Bland-Altman methods evaluated each device against polysomnography for sleep/wake detection, total sleep time, sleep efficiency, wake after sleep onset and sleep latency. FBA sleep stage classification of light sleep (N1 + N2), deep sleep (N3) and rapid eye movement was also compared with polysomnography. Compared with polysomnography, both activity trackers displayed high accuracy (81.12% versus 82.80%, AWS and FBA respectively; ns) and sensitivity (sleep detection; 96.66% versus 96.04%, respectively; ns) but low specificity (wake detection; 39.09% versus 44.76%, respectively; p = .037). Both trackers overestimated total sleep time and sleep efficiency, and underestimated sleep latency and wake after sleep onset. FBA demonstrated sleep stage sensitivity and specificity, respectively, of 79.39% and 58.77% (light), 49.04% and 95.54% (deep), 65.97% and 91.53% (rapid eye movement). Both devices were more accurate in detecting sleep than wake, with equivalent sensitivity, but statistically different specificity. FBA provided equivalent estimates as AWS for all traditional actigraphy sleep parameters. FBA also showed high specificity when identifying N3, and rapid eye movement, though sensitivity was modest. Thus, it underestimates these sleep stages and overestimates light sleep, demonstrating more shallow sleep than actually obtained. Whether FBA could serve as a low-cost substitute for actigraphy in insomnia requires further investigation.

Validity, potential clinical utility and comparison of a consumer activity tracker and a research-grade activity tracker in insomnia disorder II: Outside the laboratory.

Accurate assessment of sleep can be fundamental for monitoring, managing and evaluating treatment outcomes within diseases. A proliferation of consumer activity trackers gives easy access to objective sleep. We evaluated the performance of a commercial device (Fitbit Alta HR) relative to a research-grade actigraph (Actiwatch Spectrum Pro) in measuring sleep before and after a cognitive behavioural intervention in insomnia disorder. Twenty-five individuals with DSM-5 insomnia disorder (M = 50.6 ± 15.9 years) wore Fitbit and Actiwatch and completed a sleep diary during an in-laboratory polysomnogram, and for 1 week preceding and following seven weekly sessions of cognitive-behavioural intervention for insomnia. Device performance was compared for sleep outcomes (total sleep time, sleep latency, sleep efficiency and wake after sleep onset). The analyses assessed (a) agreement between devices across days and pre- to post-treatment, and (b) whether pre- to post-treatment changes in sleep assessed by devices correlated with clinical measures of change. Devices generally did not significantly differ from each other on sleep variable estimates, either night to night, in response to sleep manipulation (pre- to post-treatment) or in response to changes in environment (in the laboratory versus at home). Change in sleep measures across time from each device showed some correlation with common clinical measures of change in insomnia, but not insomnia diagnosis as a categorical variable. Overall, the Fitbit provides similar estimates of sleep outside the laboratory to a research grade actigraph. Despite the similarity between Fitbit and Actiwatch performance, the use of consumer technology is still in its infancy and caution should be taken in its interpretation.

Adrift in time: the subjective experience of circadian challenge during COVID-19 amongst people with mood disorders.

Social distancing/lockdown policies during the coronavirus (COVID-19) pandemic may alter social rhythms of people through imposition of restrictions on normal daily activities. This may in turn challenge circadian function, particularly in people with mood disorders. Although objective data describing the relationship between circadian disturbances and mood disorders exist, data regarding the subjective experience of circadian challenge is sparse, and its association with mood symptoms is unclear. The present qualitative study was one component of a mixed-methods multi-national project, which took advantage of widespread disruption to daily routines due to Government COVID-related lockdowns during 2020. The Behavior Emotion and Timing during COVID-19 (BEATCOVID) survey study included three open questions generating qualitative data on participants' subjective experience of social disruption due to social distancing/lockdown policies, two of which asked about the barriers and opportunities for stabilizing routines. Responses were coded and analyzed using Thematic Analysis. A total of N = 997 participants responded to at least one of the free-text questions. Four themes were identified: 1) loss of daily timed activities, 2) role of social interaction, 3) altered time perception and 4) disruption to motivation and associated psychological effects. Themes were organized into a provisional heuristic map, generating hypotheses for future research centered on the new concept of 'psychological drift.'