Real-time Mobile Monitoring of the Dynamic Associations Among Motor Activity, Energy, Mood, and Sleep in Adults With Bipolar Disorder

Merikangas, Kathleen R.; Swendsen, Joël; Hickie, Ian B.; Cui, Lihong; Shou, Haochang; Merikangas, Alison; Zhang, Jihui; Lamers, Femke; Crainiceanu, Ciprian M.; Volkow, Nora D.; Zipunnikov, Vadim

doi:10.1001/jamapsychiatry.2018.3546

Cited by 164 publications

(144 citation statements)

References 90 publications

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“…The centrality of symptoms related to activation (eg fatigue and motor hyperactivity) suggests that intervening specifically on these symptoms would also be effective and efficient in treating bipolar illness. Recent work has found that increased motor activity, but not mood, predicts circadian and sleep dysregulation within bipolar disorder, suggesting that intervening on motor activity and energy may be more efficacious for these symptoms than targeting mood . Preliminary findings suggest that behavioral interventions for the management of sleep and insomnia—which often address levels of daily or nightly activation—reduce rates of bipolar relapse and improve general functioning .…”

Section: Discussionmentioning

confidence: 96%

“…Recent work has found that increased motor activity, but not mood, predicts circadian and sleep dysregulation within bipolar disorder, suggesting that intervening on motor activity and energy may be more efficacious for these symptoms than targeting mood. 57 Preliminary findings suggest that behavioral interventions for the management of sleep and insomnia-which often address levels of daily or nightly activation-reduce rates of bipolar relapse and improve general functioning. 58,59 Behavioral activation has large effects on anhedonia and fatigue, in addition to depressed mood 60 ;…”

Section: Discussionmentioning

confidence: 98%

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Network analysis of mood symptoms in adolescents with or at high risk for bipolar disorder

2019

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Objectives Network analyses of psychopathology examine the relationships between individual symptoms in an attempt to establish the causal interactions between symptoms that may give rise to episodes of psychiatric disorders. We conducted a network analysis of mood symptoms in adolescents with or at risk for bipolar spectrum disorders. Methods The sample consisted of 272 treatment‐seeking adolescents with or at high risk for bipolar disorder who had at least subsyndromal depressive or (hypo)manic symptoms. Based on symptom scores assessed via semi‐structured interviews, we constructed the network of depressive and manic symptoms and identified the most central symptoms and symptom communities within the network. We used bootstrapping analyses to determine the reliability of network parameters. Results Symptoms within the depressive and manic mood poles were more related to each other than to symptoms of the opposing mood pole. Four communities were identified, including a depressive symptom community and three manic symptom communities. Fatigue and depressed mood were the strongest individual symptoms within the overall network (ie the most highly correlated with other symptoms), followed by motor hyperactivity. Mood lability and irritability were found to be “bridge” symptoms that connected the two mood poles. Conclusions Symptoms of activity/energy (ie fatigue and hyperactivity) and depressed mood are the most prominent mood symptoms among youth with bipolar spectrum disorders. Mood lability and irritability represent potential warning signs of emergent episodes of either polarity. Targeting these central and bridge symptoms would lead to more efficient assessments and therapeutic interventions for bipolar disorder.

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Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 98%

Network analysis of mood symptoms in adolescents with or at high risk for bipolar disorder

2019

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“…Recent developments in wearables technology make them suitable for healthcare purposes. Mobile health technology has been explored in different diseases and patient groups [6][7][8][9] and the use of wearables including smartphones and sensor-equipped devices in medical research is growing constantly. There is research activity in cancer patients using activity monitors, consisting mostly of a pedometer or accelerometer [10].…”

Section: Introductionmentioning

confidence: 99%

Feasibility and Usability Aspects of Continuous Remote Monitoring of Health Status in Palliative Cancer Patients Using Wearables

Pavic¹,

Theile²,

Kraft³

et al. 2019

Oncology

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Background: Mobile health is a promising strategy aiming to anticipate and prevent the deterioration of health status in palliative cancer patients. A prerequisite for successful implementation of this technology into clinical routine is a high level of usability and acceptance of devices. Objectives: We aimed to evaluate feasibility as well as patients' acceptance of remote monitoring using wearables in palliative cancer patients. Methods: In this prospective single-center observational feasibility study, 30 cancer patients treated with palliative intent in an inpatient setting with an estimated life expectancy of > 8 weeks and < 12 months were provided with a smartphone including a pre-installed "Activity Monitoring" app and a sensor-equipped bracelet and monitored over a period of 12 weeks starting at discharge from hospital. We report detailed feasibility and usability aspects and comment on patients' acceptance of the wearables. Results: Between February 2017 and May 2018 a total of 30 patients were included in the study. From these, 25 participants (83%) completed the whole study period. On average, the bracelet was worn on 53% and smartphone used on 85% of the study days. The completion rate of daily digital questionnaires for subjective ratings (pain and distress scale) was 73%, and 28 patients were able to handle the wearables and to operate the app without major problems. Use of the bracelet was low during the night hours, with a wearing time of 1.7% of all night hours (8 p.m. to 8 a.m.). Conclusions: Remote monitoring of health care status in palliative cancer patients with a limited life expectancy is feasible and patients are able to handle the smartphone and the sensor-equipped bracelet. Feedback towards use of this monitoring system was mostly positive.

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“…We used SOLAR to estimate heritability of traits by creating a pedigree structure of MZ and DZ twin families, and we considered three possible covariates, sex, age and body mass index (BMI), given their known influence on sleep/wake and circadian traits. [30][31][32][33] The SOLAR "polygenic" command performs a variance component analysis to determine broad sense heritability.…”

Section: Discussionmentioning

confidence: 99%

“…The SOLAR software package https://helix.nih.gov/Documentation/solar-6.6.2-doc/03.chapter.html provides extensive capabilities for analyzing heritability and has been widely used in family and twin studies. We used SOLAR to estimate heritability of traits by creating a pedigree structure of MZ and DZ twin families, and we considered three possible covariates, sex, age and body mass index (BMI), given their known influence on sleep/wake and circadian traits . The SOLAR “polygenic” command performs a variance component analysis to determine broad sense heritability.…”

Section: Methodsmentioning

confidence: 99%

Twin‐based heritability of actimetry traits

Gehrman

Ghorai

Goodman

et al. 2019

Genes Brain and Behavior

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There is a critical need for phenotypes with substantial heritability that can be used as endophenotypes in behavioral genetic studies. Activity monitoring, called actimetry, has potential as a means of assessing sleep and circadian rhythm traits that could serve as endophenotypes relevant to a range of psychopathologies. This study examined a range of actimetry traits for heritability using a classic twin design. The sample consisted of 195 subjects from 45 monozygotic (MZ) and 50 dizygotic (DZ) twin pairs aged 16‐40 years. Subjects wore both a research‐grade actimeter (GENEActiv) and a consumer‐oriented device (FitBit) for 2 weeks. Sleep and circadian traits were extracted from GENEActiv data using PennZzz and ChronoSapiens software programs. Sleep statistics for a limited number of FitBit‐collected traits were generated by its accompanying mobile app. Broad sense heritability was computed on a set of 33 MZ and 38 DZ twin pairs with complete data using both OpenMX and SOLAR software. These analyses yielded a large number of actimetry‐derived traits, 20 of which showed high heritability (h2 > 0.6), seven of which remain significant after Bonferroni correction. These results indicate that actimetry enables assessing a range of phenotypes with substantial heritability that may be useful as endophenotypes for genetic studies.

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Real-time Mobile Monitoring of the Dynamic Associations Among Motor Activity, Energy, Mood, and Sleep in Adults With Bipolar Disorder

Cited by 164 publications

References 90 publications

Network analysis of mood symptoms in adolescents with or at high risk for bipolar disorder

Network analysis of mood symptoms in adolescents with or at high risk for bipolar disorder

Feasibility and Usability Aspects of Continuous Remote Monitoring of Health Status in Palliative Cancer Patients Using Wearables

Twin‐based heritability of actimetry traits

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