1098 Altered Actigraphic Behavioral Activity Rhythm In Depression

Abstract Introduction Disturbances in sleep and behavioral activity rhythms (BAR) are frequently observed in individuals with depression. However, it remains unclear how activity variability across the 24-hour period is specifically associated with this disorder. The present study aimed to examine actigraphy-measured sleep and BAR in depression. Methods As part of a larger study, fourteen patients with DSM-5 major depressive episode (27.8±7.7 years, 69.2% female) and 13 healthy controls (21.8±1.2 years, 76.5% female) were evaluated with 7-14 days of wrist-actigraphy. Actigraphy-derived sleep parameters included total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE). Minute-by-minute activity counts were aggregated into hour-by-hour bins; hourly mean activity levels were then generated to depict 24-hour activity patterns (i.e., BAR). Factorial (GroupxTime) mixed models were conducted to examine whether BAR differed between patients with MDD and controls. Generalized Additive Models (GAM), by fitting smoothed nonlinear curves to log-transformed aggregated activity, were performed as exploratory analyses to characterize onset (UP slope) and offset (DOWN slope) of BAR. Results Compared to healthy controls, patients with MDD exhibited greater actigraphic TST (p=.026); no other between-group differences were detected for the remaining sleep parameters. Significant between-group differences were observed for mean activity during wakefulness (p<.001). Mixed models assessing hour-by-hour daily activity revealed a significant GroupxTime interaction (p=.001) with significant main effects of group (p=.017) and time (p<.001); patients with MDD had lower activity from 6 to 9 pm (ps<.005). Exploratory GAMs results showed an attenuated DOWN slope in patients with MDD (p=.014), indicating a slower decrease in activity during the evening. Conclusion Altered BAR, characterized by an overall dampened activity pattern that was most prominent during the evening, was associated with depression. Furthermore, patients with MDD took longer to wind down in the evening. Future studies are needed to explore the potential benefits of adjunctive interventions addressing both BAR along with sleep in mitigating symptoms of depression. Support Research supported by National Institutes of Health R01 MH102392.

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1196 Machine Learning Derived-Interpretative Algorithm Better Differentiates Sleep and Wake Epochs and Estimates Sleep Parameters from Wrist Actigraphy Data

SLEEP ◽

10.1093/sleep/zsaa056.1190 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A457-A458 ◽

Cited By ~ 1

Author(s):

S Haghayegh ◽

S Khoshnevis ◽

M H Smolensky ◽

K R Diller ◽

R J Castriotta

Keyword(s):

Machine Learning ◽

Body Movement ◽

Sleep Onset ◽

Sleep Time ◽

Series Data ◽

Sleep Onset Latency ◽

Zero Crossing ◽

Wrist Actigraphy ◽

Sleep Parameters ◽

Kappa Agreement

Abstract Introduction Several different interpretive algorithms (IAs) are available for scoring actigraphy-obtained body movement data for sleep and wake epochs. Although most have high sensitivity in detecting sleep epochs, they identify wake epochs poorly. We derived a machine learning (ML) based IA that improves differentiation of sleep and wake epoch to better estimate sleep parameters. Methods Forty-one adults (18 females) 26.6±12.0 years old underwent at-home single-night sleep assessment. Motionlogger® Micro Watch Actigraph recorded in zero crossing mode body movement per 30s epoch, with automated sleep scoring by single-channel electroencephalography (EEG) device (Zmachine® Insight+) as reference. The popular Cole-Kripke IA was applied to score body movement time series data of the following combination of current 1, preceding 4, and following 2 minute long epochs. Data of 21 subjects were utilized to train/derive the ML IA (logistic regression), and data of the other 20 subjects were used to test performance of it and the Cole-Kripke IA. Results In reference to the EEG, the Cole-Kripke actigraphy IA showed sensitivity of 0.98±0.02, specificity of 0.48±0.19, and kappa agreement of 0.53±0.16 in detecting sleep epochs, while the ML-derived IA showed corresponding values of 0.90±0.06, 0.71±0.14, and 0.57±0.11. The Cole-Kripke IA, relative to EEG, method significantly (P<0.05) underestimated sleep onset latency (SOL) by 18.0 min and wake after sleep onset (WASO) by 35.1 min, and overestimated total sleep time (TST) by 53.1 min and sleep efficiency (SE) by 9.6%. The ML-derived IA, relative to EEG significantly underestimated SOL by 15.1 min, but comparably (P>0.05) estimated WASO, TST, and SE. Conclusion The ML-derived IA, in comparison to Cole-Kripke IA, when applied to sleep-time wrist actigraphy data significantly better differentiates wake from sleep epochs and better estimates sleep parameters. Support This work was supported by the Robert and Prudie Leibrock Professorship in Engineering at the University of Texas at Austin.

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Mindfulness and Behaviour Therapy for Insomnia: An Assessment of Treatment Effect in a Sleep Disorders Clinic Population with Insomnia

Behaviour Change ◽

10.1017/bec.2020.18 ◽

2020 ◽

pp. 1-15

Author(s):

Allie Peters ◽

John Reece ◽

Hailey Meaklim ◽

Moira Junge ◽

David Cunnington ◽

...

Keyword(s):

Sleep Disorders ◽

Treatment Effect ◽

Sleep Onset ◽

Sleep Efficiency ◽

Health Concern ◽

Sleep Diary ◽

Sleep Onset Latency ◽

Subjective Sleep ◽

Sleep Parameters

Abstract Insomnia is a common major health concern, which causes significant distress and disruption in a person's life. The objective of this paper was to evaluate a 6-week version of Mindfulness-Based Therapy for Insomnia (MBTI) in a sample of people attending a sleep disorders clinic with insomnia, including those with comorbidities. Thirty participants who met the DSM-IV-TR diagnosis of insomnia participated in a 6-week group intervention. Outcome measures were a daily sleep diary and actigraphy during pre-treatment and follow-up, along with subjective sleep outcomes collected at baseline, end-of-treatment, and 3-month follow-up. Trend analyses showed that MBTI was associated with a large decrease in insomnia severity (p < .001), with indications of maintenance of treatment effect. There were significant improvements in objective sleep parameters, including sleep onset latency (p = .005), sleep efficiency (p = .033), and wake after sleep onset (p = .018). Significant improvements in subjective sleep parameters were also observed for sleep efficiency (p = .005) and wake after sleep onset (p < .001). Overall, this study indicated that MBTI can be successfully delivered in a sleep disorders clinic environment, with evidence of treatment effect for both objective and subjective measures of sleep.

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778 Poor Sleep Quality is Associated with Reduced Myelination in Patients with Psychotic Disorders

SLEEP ◽

10.1093/sleep/zsab072.775 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A303-A303

Author(s):

Cagri Yuksel ◽

Xi Chen ◽

Lauren Watford ◽

Margaret Gardner ◽

Kathryn Lewandowski ◽

...

Keyword(s):

White Matter ◽

Sleep Quality ◽

Psychotic Disorders ◽

Sleep Onset ◽

Sleep Loss ◽

Magnetization Transfer Ratio ◽

Poor Sleep ◽

Sleep Onset Latency ◽

Healthy Controls ◽

Poor Sleep Quality

Abstract Introduction Recent studies show that sleep favors oligodendrocyte proliferation and myelination, and sleep loss is associated with alterations in white matter structure and decreased myelination. Psychotic disorders are characterized by disrupted white matter integrity, and abnormal axon and myelin structure. Despite common sleep disturbances in these disorders, little is known about the relationship between sleep quality and white matter findings. A novel in vivo neuroimaging technique that combines diffusion tensor spectroscopy (DTS) and magnetization transfer ratio (MTR) allows separately examining the axon structure and glial function, and myelin content, respectively. Using this method, we examined the association of sleep quality with white matter biology in a sample of patients with psychotic disorders and matched healthy controls. Methods Participants included patients diagnosed with bipolar disorder with psychotic features (euthymic or depressed, n=12) and schizophrenia spectrum disorders (n=9), and age and sex matched healthy controls (n=20). DTS and MTR data was collected from the right prefrontal white matter at 4T. DTS measures included apparent diffusion coefficients of water, NAA, creatine and choline. Sleep quality was measured using Pittsburgh Sleep Quality Index (PSQI). Results PSQI total score was significantly higher in patients. and patient sample included a higher percentage of poor sleepers (PSQI total score>5). In patients, total PSQI score and sleep onset latency were significantly and negatively associated with MTR (F=6.9, p=0.02 and F=9.7, p=0.007, respectively). There was no difference in any DTS measures between groups. Conclusion Our preliminary results show that poor sleep quality is associated with decreased myelin content in the frontal lobe, in patients with psychotic disorders. This finding suggests that sleep loss may be a mediator of white matter alterations in psychosis. Support (if any) This work is supported by National Institute of Mental Health K23MH119322 to Cagri Yuksel

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Characterizing Behavioral Activity Rhythms in Older Adults Using Actigraphy

Sensors ◽

10.3390/s20020549 ◽

2020 ◽

Vol 20 (2) ◽

pp. 549

Author(s):

Ariel B. Neikrug ◽

Ivy Y. Chen ◽

Jake R. Palmer ◽

Susan M. McCurry ◽

Michael Von Korff ◽

...

Keyword(s):

Older Adults ◽

Older Adult ◽

Activity Patterns ◽

Additive Models ◽

Behavioral Activity ◽

New Approach ◽

Activity Rhythms ◽

Activity Measurements ◽

Wrist Actigraphy

Wrist actigraphy has been used to assess sleep in older adult populations for nearly half a century. Over the years, the continuous raw activity data derived from actigraphy has been used for the characterization of factors beyond sleep/wake such as physical activity patterns and circadian rhythms. Behavioral activity rhythms (BAR) are useful to describe individual daily behavioral patterns beyond sleep and wake, which represent important and meaningful clinical outcomes. This paper reviews common rhythmometric approaches and summarizes the available data from the use of these different approaches in older adult populations. We further consider a new approach developed in our laboratory designed to provide graphical characterization of BAR for the observed behavioral phenomenon of activity patterns across time. We illustrate the application of this new approach using actigraphy data collected from a well-characterized sample of older adults (age 60+) with osteoarthritis (OA) pain and insomnia. Generalized additive models (GAM) were implemented to fit smoothed nonlinear curves to log-transformed aggregated actigraphy-derived activity measurements. This approach demonstrated an overall strong model fit (R2 = 0.82, SD = 0.09) and was able to provide meaningful outcome measures allowing for graphical and parameterized characterization of the observed activity patterns within this sample.

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Links between sleep and body mass index in bipolar disorders: An exploratory study

European Psychiatry ◽

10.1016/j.eurpsy.2014.04.006 ◽

2015 ◽

Vol 30 (1) ◽

pp. 89-93 ◽

Cited By ~ 20

Author(s):

C. Boudebesse ◽

P.-A. Geoffroy ◽

C. Henry ◽

A. Germain ◽

J. Scott ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Sleep Disturbances ◽

Sleep Onset ◽

Bipolar Disorders ◽

Sleep Time ◽

Sleep Efficiency ◽

Sleep Onset Latency ◽

Cross Sectional ◽

Sleep Parameters

AbstractStudy objectives:Obesity and excess bodyweight are highly prevalent in individuals with bipolar disorders (BD) and are associated with adverse consequences. Multiple factors may explain increased bodyweight in BD including side effects of psychotropic medications, and reduced physical activity. Research in the general population demonstrates that sleep disturbances may also contribute to metabolic burden. We present a cross-sectional study of the associations between body mass index (BMI) and sleep parameters in patients with BD as compared with healthy controls (HC).Methods:Twenty-six French outpatients with remitted BD and 29 HC with a similar BMI completed a 21-day study of sleep parameters using objective (actigraphy) and subjective (PSQI: Pittsburgh Sleep Quality Index) assessments.Results:In BD cases, but not in HC, higher BMI was significantly correlated with lower sleep efficiency (P = 0.009) and with several other sleep parameters: shorter total sleep time (P = 0.01), longer sleep onset latency (P = 0.05), higher fragmentation index (P = 0.008), higher inter-day variability (P = 0.05) and higher PSQI total score (P = 0.004).Conclusions:The findings suggest a link between a high BMI and several sleep disturbances in BD, including lower sleep efficiency. Physiological mechanisms in BD cases may include an exaggeration of phenomena observed in non-clinical populations. However, larger scale studies are required to clarify the links between metabolic and sleep-wake cycle disturbances in BD.

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The Relationship between Fatigue and Actigraphy-Derived Sleep and Rest-Activity Patterns in Cancer Survivors

10.31236/osf.io/yswn8 ◽

2019 ◽

Author(s):

Tristan Martin ◽

Rosemary Twomey ◽

Mary E Medysky ◽

John Temesi ◽

S. Nicole Culos-Reed ◽

...

Keyword(s):

Cancer Survivors ◽

Activity Patterns ◽

Sleep Onset ◽

Activity Cycle ◽

Objective Measures ◽

Sleep Onset Latency ◽

Cancer Related Fatigue ◽

Wrist Actigraphy ◽

Activity Cycles ◽

Rest Activity

Background: Cancer-related fatigue can continue long after curative cancer treatment. The aim of this study was to investigate sleep and rest-activity cycles in fatigued and non-fatigued cancer survivors. We hypothesized that sleep and rest-activity cycles would be more disturbed in people experiencing clinically-relevant fatigue, and that objective measures of sleep would be associated with the severity of fatigue in cancer survivors.Methods: Cancer survivors (n=87) completed a 14-day wrist actigraphy measurement for the estimation of sleep and rest-activity cycles. Fatigue was measured using the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F). Participants were dichotomised into two groups using a previously validated score (fatigued n=51 and non-fatigued n=36). Perception of sleep was measured using the Insomnia Severity Index (ISI).Results: FACIT-F score was correlated with wake after sleep onset (r =-0.28; p = 0.010), sleep efficiency (r=0.26; p=0.016), sleep onset latency (r=-0.31; p=0.044) and ISI score (r=-0.56; p <0.001). The relative amplitude of the rest-activity cycles was lower in the fatigued vs. non-fatigued group (p=0.017; d=0.58). Conclusions: After treatment for cancer, the severity of cancer-related fatigue is correlated with specific objective measures of sleep, and there is evidence of rest-activity cycle disruption in people experiencing clinically-relevant fatigue.

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Associations of Actigraphic Sleep Parameters With Fatigability in Older Adults

The Journals of Gerontology Series A ◽

10.1093/gerona/glaa137 ◽

2020 ◽

Vol 75 (9) ◽

pp. e95-e102 ◽

Cited By ~ 1

Author(s):

Alfonso J Alfini ◽

Jennifer A Schrack ◽

Jacek K Urbanek ◽

Amal A Wanigatunga ◽

Sarah K Wanigatunga ◽

...

Keyword(s):

Older Adults ◽

Perceived Exertion ◽

Sleep Onset ◽

Later Life ◽

Sleep Time ◽

Community Dwelling ◽

Rating Of Perceived Exertion ◽

Poor Sleep ◽

Wrist Actigraphy ◽

Sleep Parameters

Abstract Background Poor sleep may increase the likelihood of fatigue, and both are common in later life. However, prior studies of the sleep–fatigue relationship used subjective measures or were conducted in clinical populations; thus, the nature of this association in healthier community-dwelling older adults remains unclear. We studied the association of actigraphic sleep parameters with perceived fatigability—fatigue in response to a standardized task—and with conventional fatigue symptoms of low energy or tiredness. Methods We studied 382 cognitively normal participants in the Baltimore Longitudinal Study of Aging (aged 73.1 ± 10.3 years, 53.1% women) who completed 6.7 ± 0.9 days of wrist actigraphy and a perceived fatigability assessment, including rating of perceived exertion (RPE) after a 5-minute treadmill walk or the Pittsburgh Fatigability Scale (PFS). Participants also reported non-standardized symptoms of fatigue. Results After adjustment for age, sex, race, height, weight, comorbidity index, and depressive symptoms, shorter total sleep time (TST; <6.3 hours vs intermediate TST ≥6.3 to 7.2 hours) was associated with high RPE fatigability (odds ratio [OR] = 2.56, 95% confidence interval [CI] = 1.29, 5.06, p = .007), high PFS physical (OR = 1.88, 95% CI = 1.04, 3.38, p = .035), and high mental fatigability (OR = 2.15, 95% CI = 1.02, 4.50, p = .044), whereas longer TST was also associated with high mental fatigability (OR = 2.19, 95% CI = 1.02, 4.71, p = .043). Additionally, longer wake bout length was associated with high RPE fatigability (OR = 1.53, 95% CI = 1.14, 2.07, p = .005), and greater wake after sleep onset was associated with high mental fatigability (OR = 1.14, 95% CI = 1.01, 1.28, p = .036). Conclusion Among well-functioning older adults, abnormal sleep duration and sleep fragmentation are associated with greater perceived fatigability.

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Assessing sleep quality in older adults: A comparison of three measurement approaches

Innovation in Aging ◽

10.1093/geroni/igaa057.3256 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 882-882

Author(s):

Amy Berkley ◽

Patricia Carter

Keyword(s):

Older Adults ◽

Sleep Quality ◽

Assessment Tool ◽

Sleep Problems ◽

Adult Population ◽

Sleep Onset ◽

Self Report ◽

Sleep Onset Latency ◽

Wrist Actigraphy ◽

Sleep Assessment

Abstract Discrepancies between subjective and objective sleep measures have been reported for some time; however, it is critical to consider the implications of inaccurate or incomplete sleep assessment for frail older adults who are struggling to maintain independence. To compare sleep assessment methods, we collected objective sleep measurements (via wrist actigraphy), subjective measures via self-report sleep surveys (Pittsburgh Sleep Quality Index; Insomnia Severity Index, Sleep Hygiene Index), and qualitative data through semi-structured audio-recorded interviews, from 8 older adults who self-reported sleep problems while living in a retirement community in southwestern US. Participants’ objective sleep (Total Sleep Time, Sleep Onset Latency, Wake After Sleep Onset, and Sleep Efficiency) and qualitative narratives were congruent, but self-report measures failed to capture several unique sleep problems identified in the sample. Disordered sleep in older adults has been linked to increased incidence of falls, depression and anxiety, cognitive impairment, institutionalization, and mortality, but traditional sleep assessment instruments, designed for the general adult population, fail to capture many of the experiences and causes that are unique to older adults. functioning. A sleep assessment tool designed to measure older people’s sleep experiences could provide more accurate and sensitive data.

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Self-administered electroencephalography-based sleep assessment: compliance and perceived feasibility in children and adults

Sleep Science and Practice ◽

10.1186/s41606-021-00059-1 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Jesper Pedersen ◽

Martin Gillies Banke Rasmussen ◽

Line Grønholt Olesen ◽

Peter Lund Kristensen ◽

Anders Grøntved

Keyword(s):

A Priori ◽

Pilot Trial ◽

Sleep Onset ◽

Sleep Time ◽

Secondary Outcome ◽

Sleep Onset Latency ◽

Assessment Protocol ◽

Sleep Assessment ◽

Sleep Parameters

Abstract Background Sleep is a crucial part of our lives and insufficient sleep has been linked to several health disorders in both children and adults. However, most studies are based on single night laboratory polysomnography, actigraphy, or sleep diaries. The primary aim of this study was to evaluate compliance to and perceived feasibility of the Zmachine insight+ for assessment of habitual sleep parameters in a sample of children and adults for six nights. The secondary aim was to report sleep parameters derived from the Zmachine. Methods We analyzed data from 12 families who participated in the SCREENS pilot trial (2018–2019). Children (n=14) and adults (n=19) had to undergo three nights of EEG-based sleep assessment at baseline and follow-up. We assessed compliance to the sleep assessment protocol and summarized perceived feasibility in children and adults. Summary estimates were computed for total sleep time, sleep onset latency, wake after sleep onset, light sleep, deep sleep, and rapid eye movement sleep. Results Compliance to the sleep assessment protocol was high with 92.9 and 89.4% of children and adults meeting the a priori specified compliance goal of at least two out of three nights of complete sleep data at both baseline and follow-up. In general, the protocol was perceived as feasible, with low prevalence of sleep disruption and only minor issues, e.g. difficulties with removing sensors. Results on sleep parameters indicate large within group variation. Conclusions Our findings support the use of a self-administered EEG-based habitual sleep assessment protocol, including multiple days of measurement, in children and adults. Trial registration Cilinicaltrials.gov: NCT03788525 [Secondary outcome measures; Retrospectively registered; 27th December, 2018].

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Internet Addiction and Sleep Problems among Russian Adolescents: A Field School-Based Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph181910397 ◽

2021 ◽

Vol 18 (19) ◽

pp. 10397

Author(s):

Sergey Tereshchenko ◽

Edward Kasparov ◽

Marina Smolnikova ◽

Margarita Shubina ◽

Nina Gorbacheva ◽

...

Keyword(s):

Internet Addiction ◽

Daytime Sleepiness ◽

Sleep Problems ◽

Sleep Onset ◽

Russian Language ◽

Sleep Onset Latency ◽

Cross Sectional ◽

Sleep Parameters ◽

Nighttime Sleep

This study aims to establish a link between disturbances in the night sleep habitus, quality of sleep, and daytime sleepiness in adolescents with Internet addiction and different types of content consumed. Methods: This is a cross-sectional observational study of a school sample in three large cities in Central Siberia. 4615 schoolchildren of 12–18 years old were examined. The Russian-language versions of the Chen Internet Addiction Scale, the Game Addiction Scale for Adolescents, and the Social Media Disorder Scale were used to identify Internet addiction. Questions from the Pittsburgh Sleep Quality Index questionnaire were used to assess nighttime sleep. Daytime sleepiness was assessed using the Pediatric Daytime Sleepiness Scale questionnaire. Results: Adolescents with Internet addiction go to bed and wake up late; they are characterized by a decrease in the duration of nighttime sleep, an increase in sleep onset latency, and frequent nighttime awakenings, as well as more pronounced daytime sleepiness. Among the sleep parameters studied, the indicators of daytime sleepiness and night awakening scales have the highest effect size in Internet-addicted adolescents, regardless of the media consumed. Conclusion: Internet-addicted adolescents are characterized by significant disturbances in the quality of nighttime sleep and excessive daytime sleepiness, which requires appropriate psychological correction.

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