The Effectiveness of Therapeutic Exercise Interventions With Virtual Reality on Balance and Walking Among Persons With Chronic Stroke: Systematic Review, Meta-Analysis, and Meta-Regression of Randomized Controlled Trials.

Background: Well-targeted balance, walking, and weight-shift training can improve balance capabilities in the chronic phase of stroke. There is an urgent need for a long-term approach to rehabilitation that extends beyond the acute and subacute phases, supporting participation without increasing the demand for health care staff.

Objective: This study aims to evaluate the effectiveness of therapeutic exercise interventions with virtual reality (VR) training on balance and walking at the activity and participation levels in individuals with chronic stroke, compared with control groups receiving no treatment, conventional physical therapy, specific training, similar treatment, or identical treatment without VR.

The Effects of Virtual Reality Training on Cognition in Older Adults: A Systematic Review, Meta-Analysis, and Meta-Regression of Randomized Controlled Trials.

The aim of this systematic review, meta-analysis, and meta-regression was to examine the effects of virtual reality-based training on global cognition and executive function compared with conventional training or information-based treatment in older adults, regardless of cognitive level. A systematic literature search was conducted using four databases. A total of 31 randomized controlled trials were identified.

Previous radiotherapy improves treatment responses and causes a trend toward longer time to progression among patients with immune checkpoint inhibitor-related adverse events.

Background: Immune-related adverse events (irAEs) are frequently encountered by patients during immune checkpoint inhibitor (ICI) treatment and are associated with better treatment outcomes. The sequencing of radiotherapy (RT) and ICIs is widely used in current clinical practice, but its effect on survival has remained unclear.

Methods: In a real-world multicenter study including 521 patients who received ICI treatment for metastatic or locally advanced cancer, RT schedules and timing, irAEs, time to progression, overall survival, and treatment responses were retrospectively reviewed.

The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity.

Background: Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.

Methods: Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study.

Mobile health solutions: An opportunity for rehabilitation in low- and middle income countries?

Mobile health (mHealth) development has advanced rapidly, indicating promise as an effective patient intervention. mHealth has many potential benefits that could help the treatment of patients, and the development of rehabilitation in low- and middle-income countries (LMICs). mHealth is a low-cost option that does not need rapid access to healthcare clinics or employees.

Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis.

Background: Remote measurement technologies (RMTs) have the potential to revolutionize major depressive disorder (MDD) disease management by offering the ability to assess, monitor, and predict symptom changes. However, the promise of RMT data depends heavily on sustained user engagement over extended periods. In this paper, we report a longitudinal qualitative study of the subjective experience of people with MDD engaging with RMTs to provide insight into system usability and user experience and to provide the basis for future promotion of RMT use in research and clinical practice.

Biopsychosocial Response to the COVID-19 Lockdown in People with Major Depressive Disorder and Multiple Sclerosis.

Background: Changes in lifestyle, finances and work status during COVID-19 lockdowns may have led to biopsychosocial changes in people with pre-existing vulnerabilities such as Major Depressive Disorders (MDDs) and Multiple Sclerosis (MS).

Methods: Data were collected as a part of the RADAR-CNS (Remote Assessment of Disease and Relapse-Central Nervous System) program. We analyzed the following data from long-term participants in a decentralized multinational study: symptoms of depression, heart rate (HR) during the day and night; social activity; sedentary state, steps and physical activity of varying intensity.

The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions.

Background And Objectives: Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS.

Mobile health applications for improving physical function, physical activity, and quality of life in stroke survivors: a systematic review.

Purpose: To evaluate the effectiveness of mobile health applications (mHealth apps) containing a physical training component on physical function and physical activity in stroke rehabilitation.

Materials And Methods: A systematic literature search was conducted in three databases for studies published from inception to 12 July 2022. Clinical trials including mHealth apps with a physical training component were included using outcomes of physical function and physical activity.

Associations Between Depression Symptom Severity and Daily-Life Gait Characteristics Derived From Long-Term Acceleration Signals in Real-World Settings: Retrospective Analysis.

Background: Gait is an essential manifestation of depression. However, the gait characteristics of daily walking and their relationships with depression have yet to be fully explored.

Objective: The aim of this study was to explore associations between depression symptom severity and daily-life gait characteristics derived from acceleration signals in real-world settings.

Designing daily-life research combining experience sampling method with parallel data.

Background: Ambulatory monitoring is gaining popularity in mental and somatic health care to capture an individual's wellbeing or treatment course in daily-life. Experience sampling method collects subjective time-series data of patients' experiences, behavior, and context. At the same time, digital devices allow for less intrusive collection of more objective time-series data with higher sampling frequencies and for prolonged sampling periods.

mHealth Apps for Low Back Pain Self-management: Scoping Review.

Background: The role of self-management in health promotion, as well as prevention and rehabilitation, is increasing through the use of mobile health (mHealth) apps. Such mHealth apps are also increasingly being used for self-management of low back pain (LBP), but their effectiveness has not been sufficiently explored.

Objective: The aim of this scoping review was to provide an overview of the literature on self-management mHealth apps and their effects on the levels of pain and disability in people with LBP.

Using Telehealth to Guarantee the Continuity of Rehabilitation during the COVID-19 Pandemic: A Systematic Review.

COVID-19 has abruptly disrupted healthcare services; however, the continuity of rehabilitation could be guaranteed using mobile technologies. This review aims to analyze the feasibility and effectiveness of telehealth solutions proposed to guarantee the continuity of rehabilitation during the COVID-19 pandemic. The PubMed, Cochrane Library, Web of Science and PEDro databases were searched; the search was limited to randomized controlled trials, observational and explorative studies published up to 31 May 2022, assessing the feasibility and effectiveness of telerehabilitation during the COVID-19 pandemic.

The Effectiveness of Physical Activity-Promoting Web- and Mobile-Based Distance Weight Loss Interventions on Body Composition in Rehabilitation Settings: Systematic Review, Meta-analysis, and Meta-Regression Analysis.

Background: Overweight and obesity are major problems worldwide, and they lead to an increased risk for several diseases. The use of technology in the treatment of obesity is promising, but in the existing literature, there is considerable uncertainty regarding its efficacy. In this review, we included web- and mobile-based weight loss interventions that were implemented remotely in rehabilitation settings.

Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study.

Background: The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored.

Objective: We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time.

Methods: Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse-Major Depressive Disorder, which was conducted in 3 European countries.

Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study.

Background: Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected.

The association between self-reported stress and cardiovascular measures in daily life: A systematic review.

Background: Stress plays an important role in the development of mental illness, and an increasing number of studies is trying to detect moments of perceived stress in everyday life based on physiological data gathered using ambulatory devices. However, based on laboratory studies, there is only modest evidence for a relationship between self-reported stress and physiological ambulatory measures. This descriptive systematic review evaluates the evidence for studies investigating an association between self-reported stress and physiological measures under daily life conditions.

Predicting Depressive Symptom Severity Through Individuals' Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study.

Background: Research in mental health has found associations between depression and individuals' behaviors and statuses, such as social connections and interactions, working status, mobility, and social isolation and loneliness. These behaviors and statuses can be approximated by the nearby Bluetooth device count (NBDC) detected by Bluetooth sensors in mobile phones.

Objective: This study aimed to explore the value of the NBDC data in predicting depressive symptom severity as measured via the 8-item Patient Health Questionnaire (PHQ-8).

Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study.

Background: Sleep problems tend to vary according to the course of the disorder in individuals with mental health problems. Research in mental health has associated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography (PSG), is not suitable for long-term, continuous monitoring of daily sleep, and methods such as sleep diaries rely on subjective recall, which is qualitative and inaccurate.

Remote Assessment of Disease and Relapse in Epilepsy: Protocol for a Multicenter Prospective Cohort Study.

Background: In recent years, a growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. In clinical practice, seizure assessment typically relies on self-report, which is known to be highly unreliable. Moreover, most people with epilepsy self-identify factors that lead to increased seizure likelihood, including mood, behavior, sleep pattern, and cognitive alterations, all of which are amenable to measurement via multiparametric RMT.

Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19.

Background: In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed.

Objective: We aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)-base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19.

Momentary predictors of compliance in studies using the experience sampling method.

The influence of momentary experiences on compliance has not yet been studied extensively in diary methods such as the experience sampling method (ESM). This study investigated to what extent momentary experiences at the moment of responding (hereafter 'beep') can predict compliance in high frequency ESM protocols. Lagged-analyses were conducted using a pooled dataset of seven studies including 1,318 healthy volunteers and individuals with different mental health conditions.