Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: A scoping review

Sequeira, Lydia; Perrotta, Steve; LaGrassa, Jennifer; Merikangas, Kathleen R.; Kreindler, David; Kundur, Deepa; Courtney, Darren; Szatmári, Péter; Battaglia, Marco; Strauss, John S.

doi:10.1016/j.jad.2019.11.156

Cited by 62 publications

(44 citation statements)

References 70 publications

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“…Recently, researchers have proposed the use of mobile health (mHealth) technologies, such as wearable and smartphone devices, to passively index mental health in everyday life (Torous et al, 2016. Despite many review articles delineating the potential promise of these devices (Miller, 2012;Onnela & Rauch, 2016;Torous et al, 2016;Torous & Roberts, 2017) and some studies emerging on smartphone sensor data and mental health (Ben-Zeev et al, 2015;Jacobson & Chung, 2020;Pratap et al, 2019;Saeb et al, 2016), there is currently a dearth of research examining 1) how passively collected wearable biobehavioral features (e.g., heart rate, step count, sleep duration and their variability) are associated with mental health functioning, 2) with even fewer research studies conducted during adolescence (Sequeira et al, 2020), and 3) virtually no research conducted with traditional hypothesis testing as opposed to computational psychiatry approaches (i.e., machine learning) that are prevalent in the field. Note that while machine learning approaches are valuable and may increase predictive validity, traditional hypothesis testing is also needed to provide an explanation of associations among mHealth variables of interest and mental health.…”

Section: Introductionmentioning

confidence: 99%

Concurrent and Prospective Associations Between Fitbit Derived RDoC Arousal and Regulation Constructs and Adolescent Internalizing Symptoms

Nelson¹,

Flannery²,

Duell³

et al. 2021

Preprint

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Background: Adolescence is characterized by alterations in biobehavioral functioning, during which individuals are at heightened risk for first onset of psychopathology, particularly internalizing disorders (e.g., depression and anxiety). Recently, researchers have proposed the use of mobile Health (mHealth) technologies to passively index biobehavioral functioning in everyday life yet, there is a dearth of research examining how wearable metrics, which map onto NIMH Research Domain Criteria (RDoC) of Arousal and Regulation, are associated with concurrent and prospective changes in mental health.Methods: We preregistered secondary data analyses using the Adolescent Brain Cognitive Development (ABCD) Study dataset to determine whether wearable indices of resting heart rate (HR), step count, and sleep duration as well as variability in these measures were cross-sectionally associated with internalizing symptomatology in 5,686 adolescents. All models were also run controlling for age, sex, body mass index, socioeconomic status, and race. We also performed prospective analyses on a subset of this sample across 25 months that had Fitbit data available at Baseline and Follow Up (n = 143). Results: Cross-sectional analyses revealed that higher resting HR, lower step count and step count variability, and greater variability in sleep duration were associated with greater internalizing symptoms. Cross-lagged panel model analysis revealed that there were no prospective associations between wearable variables, but greater internalizing symptoms predicted lower step count 25 months later.Conclusions: Findings indicate that wearable indices concurrently, but not prospectively, associate with internalizing symptoms during early adolescence. Future research should capitalize on the temporal resolution provided by wearable devices to determine the intensive longitudinal relations between biobehavioral risk factors and acute changes in mental health.

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Section: Introductionmentioning

confidence: 99%

Concurrent and Prospective Associations Between Fitbit Derived RDoC Arousal and Regulation Constructs and Adolescent Internalizing Symptoms

Nelson¹,

Flannery²,

Duell³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…Wearable technology has the potential to feedback accurate data about a child’s health, or adherence to the intervention, without placing a burden on the parent or child to actively monitor behaviours. Wearable technology has been developed for a variety of paediatric conditions, including ADHD (Tavakoulnia et al, 2019), mood disorders (Sequeira et al, 2020), juvenile idiopathic arthritis (Heale et al, 2018), cerebral palsy (Bialocerkowski, 2011), asthma (Siering et al, 2019), and epilepsy (Bruno et al, 2018). Child-centred design principles could be incorporated, such as rewards and gamification (Brigden et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Chronic fatigue syndrome/myalgic encephalomyelitis in children aged 5 to 11 years: A qualitative study

Brigden

Shaw

Anderson

et al. 2020

Clin Child Psychol Psychiatry

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Treatments for paediatric chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) have not been designed or evaluated for younger children (5–11-years). The development of a complex intervention for this population requires an in-depth understanding of the perspectives and psychosocial context of children and families. Children with CFS/ME (5–11-years) and their families were recruited from a specialist CFS/ME service, and interviewed using semi-structured topic guides. Data were analysed thematically. Twenty-two participants were interviewed; eight parents, two children (aged nine and ten) and six parent-child dyads (aged 5–11-years). Theme 1: CFS/ME in younger children is complex and disabling. Theme 2: Children aged eight and over (in comparison to those under eight) were more able to describe their illness, engage in clinical consultation, understand diagnosis and self-manage. Theme 3: Parents of children under eight took full responsibility for their child’s treatment. As children got older, this increasingly became a joint effort between the parent and child. Parents felt unsupported in their caring role. Clinicians should consider different treatment approaches for children under eight, focusing on: parent-only clinical sessions, training parents to deliver treatment, and increasing support for parents. Children over eight may benefit from tools to help them understand diagnosis, treatment and aids for self-management.

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“…Furthermore, wearable technology can also be used to monitor mood. Sequeira et al [35] have demonstrated the feasibility of wearable tools in the prediction of depressive symptoms in children and adolescents. Health monitoring of pregnant women can be divided into 2 aspects [36].…”

Section: Health and Safety Monitoringmentioning

confidence: 99%

“…Through sensor technology, wearable health devices can collect all kinds of user information, such as health information, geographical location, and living habits [34]. The various formats, large scale, and numerous mobile links of these data may increase the risk of leakage and tampering [8,35,122,123].…”

Section: Security and Privacy Concernsmentioning

confidence: 99%

Wearable Health Devices in Health Care: Narrative Systematic Review (Preprint)

Lu¹,

Zhang²,

Xie³

et al. 2020

Preprint

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UNSTRUCTURED With the development of science and technology, wearable devices have been widely used in the field of health care. In this article, we summarize the characteristics, key technologies, and classification of wearable devices, as well as their application in health and safety monitoring, chronic disease management, diagnosis and treatment of diseases, and rehabilitation. We analyze the shortcomings of wearable devices to highlight development trends and provide a useful reference for the development of wearable devices by collecting data on the application and investigation of wearable devices in the medical field.

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Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: A scoping review

Cited by 62 publications

References 70 publications

Concurrent and Prospective Associations Between Fitbit Derived RDoC Arousal and Regulation Constructs and Adolescent Internalizing Symptoms

Concurrent and Prospective Associations Between Fitbit Derived RDoC Arousal and Regulation Constructs and Adolescent Internalizing Symptoms

Chronic fatigue syndrome/myalgic encephalomyelitis in children aged 5 to 11 years: A qualitative study

Wearable Health Devices in Health Care: Narrative Systematic Review (Preprint)

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