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

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis

BACKGROUND

Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings.

OBJECTIVE

This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts.

METHODS

Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score.

RESULTS

Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (β=-93.61, P<.001), increased sleep variability (β=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: β=0.55, P=.001; sleep offset: β=1.12, P<.001; M10 onset: β=0.73, P=.003; HR acrophase: β=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (β of PHQ-8 × spring = -31.51, P=.002) and summer (β of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (β of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer.

CONCLUSIONS

Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation

BACKGROUND

Depression is often accompanied by changes in behavior, including dietary behaviors. The relationship between dietary behaviors and depression has been widely studied, yet previous research has relied on self-reported data which is subject to recall bias. Electronic device-based behavioral monitoring offers the potential for objective, real-time data collection of a large amount of continuous, long-term behavior data in naturalistic settings.

OBJECTIVE

The study aims to characterize digital dietary behaviors in depression, and to determine whether these behaviors could be used to detect depression.

METHODS

A total of 3310 students (2222 healthy controls [HCs], 916 with mild depression, and 172 with moderate-severe depression) were recruited for the study of their dietary behaviors via electronic records over a 1-month period, and depression severity was assessed in the middle of the month. The differences in dietary behaviors across the HCs, mild depression, and moderate-severe depression were determined by ANCOVA (analyses of covariance) with age, gender, BMI, and educational level as covariates. Multivariate logistic regression analyses were used to examine the association between dietary behaviors and depression severity. Support vector machine analysis was used to determine whether changes in dietary behaviors could detect mild and moderate-severe depression.

RESULTS

The study found that individuals with moderate-severe depression had more irregular eating patterns, more fluctuated feeding times, spent more money on dinner, less diverse food choices, as well as eating breakfast less frequently, and preferred to eat only lunch and dinner, compared with HCs. Moderate-severe depression was found to be negatively associated with the daily 3 regular meals pattern (breakfast-lunch-dinner pattern; OR 0.467, 95% CI 0.239-0.912), and mild depression was positively associated with daily lunch and dinner pattern (OR 1.460, 95% CI 1.016-2.100). These changes in digital dietary behaviors were able to detect mild and moderate-severe depression (accuracy=0.53, precision=0.60), with better accuracy for detecting moderate-severe depression (accuracy=0.67, precision=0.64).

CONCLUSIONS

This is the first study to develop a profile of changes in digital dietary behaviors in individuals with depression using real-world behavioral monitoring. The results suggest that digital markers may be a promising approach for detecting depression.

Risk Factors Associated with Acute Sarcopenia in Patients Hospitalized with COVID-19

Background

The COVID-19 pandemic is an extraordinary global emergency. The pandemic has changed profoundly people's lifestyles. This resulted in reductions in physical activity and changes in dietary intakes that have the potential to accelerate sarcopenia.

Objective

The aim of this study was to evaluate the risk factors associated with acute sarcopenia in patients hospitalized with COVID-19.

Methods

This was a cross-sectional study conducted from January/2021 to March/2022 in a private hospital in Cuiabá/MT, central region of Brazil. The main variable was the prevalence of acute sarcopenia among adults hospitalized with COVID19. Patients were assessed for acute sarcopenia using the SARC-F ≥4 questionnaire (strength, assistance with walking, rise from a chair, climb stairs, and falls), grip strength (<20 kg (female) and <35 kg (male)), and calf circumference (<33 cm (female) and <34 cm (male)).

Results

In all, 213 patients aged 57.4 ± 15.4 years, 63.8% male, were studied. Thirty-four (16.0%) patients were diagnosed with acute sarcopenia. Advanced age (older people) and the percentage of weight lost ≥3% before hospitalization were independent risk factors for acute sarcopenia in hospitalized patients with COVID-19.

Conclusion

Acute sarcopenia was present in 16% of patients. Advanced age and percentage of weight lost ≥3% were independent risk factors for acute sarcopenia in patients hospitalized with COVID-19.

The administration of the paper and electronic versions of the Manual Ability Measure-36 (MAM-36) and Fatigue Severity Scale (FSS) is equivalent in people with multiple sclerosis

BACKGROUND

The mobile device diffusion has increasingly highlighted the opportunity to collect patient-reported outcomes (PROs) through electronic patient-reported outcomes measurements (ePROMs) during the clinical routine. Despite the ePROMs promises and advantages, the equivalence when a PRO measure is moved from the original paper-and-pencil to the electronic version is still little investigated. This study aims at evaluating equivalence between PROMs and ePROMs self-administration in people with multiple sclerosis (PwMS); in addition, preference of self-administration type was evaluated.

METHODS

The Manual Ability Measure-36 (MAM-36) and Fatigue Severity Scale (FSS) were selected for the equivalence test. The app ABOUTCOME was developed through a user-centered design approach to administer the questionnaires on tablet. Both paper-and-pencil and electronic versions were randomly self-administered. Intrarater reliability between both versions was evaluated through the intraclass correlation coefficient (ICC, excellent for values ≥ 0.75).

RESULTS

Fifty PwMS (35 females) participated to the study (mean age: 54.7±11.0 years, disease course: 27 relapsing-remitting and 23 progressive; mean EDSS: 4.7±1.9; mean disease duration: 13.3±9.5 years). No statistically significant differences were found for the means total scores of MAM-36 (p = 0.61) and FSS (p = 0.78). The ICC value for MAM-36 and FSS was excellent (0.98 and 0.94, respectively). Most of participants preferred the tablet version (84%).

CONCLUSION

The results of the study provide evidence about the equivalence between the paper-and-pencil and electronic versions of PROs administration. In addition, PwMS prefer electronic methods rather than paper because the information can be provided more efficiently and accurately. The results could be easily extended to other MS PROs.

The Appropriateness of Medical Devices Is Strongly Influenced by Sex and Gender

Until now, research has been performed mainly in men, with a low recruitment of women; consequentially, biological, physiological, and physio-pathological mechanisms are less understood in women. Obviously, without data obtained on women, it is impossible to apply the results of research appropriately to women. This issue also applies to medical devices (MDs), and numerous problems linked to scarce pre-market research and clinical trials on MDs were evidenced after their introduction to the market. Globally, some MDs are less efficient in women than in men and sometimes MDs are less safe for women than men, although recently there has been a small but significant decrease in the sex and gender gap. As an example, cardiac resynchronization defibrillators seem to produce more beneficial effects in women than in men. It is also important to remember that MDs can impact the health of healthcare providers and this could occur in a sex- and gender-dependent manner. Recently, MDs' complexity is rising, and to ensure their appropriate use they must have a sex-gender-sensitive approach. Unfortunately, the majority of physicians, healthcare providers, and developers of MDs still believe that the human population is only constituted by men. Therefore, to overcome the gender gap, a real collaboration between the inventors of MDs, health researchers, and health providers should be established to test MDs in female and male tissues, animals, and women.

Cognitive dispersion is related to subtle objective daily functioning changes in older adults with and without cognitive impairment

Early detection of cognitive and functional decline is difficult given that current tools are insensitive to subtle changes. The present study evaluated whether cognitive dispersion on neuropsychological testing improved prediction of objectively assessed daily functioning using unobtrusive monitoring technologies. Hierarchical linear regression was used to evaluate whether cognitive dispersion added incremental information beyond mean neuropsychological performance in the prediction of objectively assessed IADLs (i.e., computer use, pillbox use, driving) in a sample of 104 community-dwelling older adults without dementia (Mage = 74.59, 38.5% Female, 90.4% White). Adjusting for age, sex, education, and mean global cognitive performance, cognitive dispersion improved prediction of average daily computer use duration (R2 Δ = 0.100, F Change, p = 0.005), computer use duration variability (R2 Δ = 0.089, F Change p = 0.009), and average daily duration of nighttime driving (R2 Δ = 0.072, F Change p = 0.013). These results suggest cognitive dispersion may improve prediction of objectively assessed functional changes in older adults without dementia.

Evaluating a Remote Monitoring Program for Respiratory Diseases: Prospective Observational Study

BACKGROUND

Patients with chronic respiratory diseases and those in the postdischarge period following hospitalization because of COVID-19 are particularly vulnerable, and little is known about the changes in their symptoms and physiological parameters. Continuous remote monitoring of physiological parameters and symptom changes offers the potential for timely intervention, improved patient outcomes, and reduced health care costs.

OBJECTIVE

This study investigated whether a real-time multimodal program using commercially available wearable technology, home-based Bluetooth-enabled spirometers, finger pulse oximeters, and smartphone apps is feasible and acceptable for patients with chronic respiratory diseases, as well as the value of low-burden, long-term passive data collection.

METHODS

In a 3-arm prospective observational cohort feasibility study, we recruited 60 patients from the Royal Free Hospital and University College Hospital. These patients had been diagnosed with interstitial lung disease, chronic obstructive pulmonary disease, or post-COVID-19 condition (n=20 per group) and were followed for 180 days. This study used a comprehensive remote monitoring system designed to provide real-time and relevant data for both patients and clinicians. Data were collected using REDCap (Research Electronic Data Capture; Vanderbilt University) periodic surveys, Remote Assessment of Disease and Relapses-base active app questionnaires, wearables, finger pulse oximeters, smartphone apps, and Bluetooth home-based spirometry. The feasibility of remote monitoring was measured through adherence to the protocol, engagement during the follow-up period, retention rate, acceptability, and data integrity.

RESULTS

Lowest-burden passive data collection methods, via wearables, demonstrated superior adherence, engagement, and retention compared with active data collection methods, with an average wearable use of 18.66 (SD 4.69) hours daily (77.8% of the day), 123.91 (SD 33.73) hours weekly (72.6% of the week), and 463.82 (SD 156.70) hours monthly (64.4% of the month). Highest-burden spirometry tasks and high-burden active app tasks had the lowest adherence, engagement, and retention, followed by low-burden questionnaires. Spirometry and active questionnaires had the lowest retention at 0.5 survival probability, indicating that they were the most burdensome. Adherence to and quality of home spirometry were analyzed; of the 7200 sessions requested, 4248 (59%) were performed. Of these, 90.3% (3836/4248) were of acceptable quality according to American Thoracic Society grading. Inclusion of protocol holidays improved retention measures. The technologies used were generally well received.

CONCLUSIONS

Our findings provide evidence supporting the feasibility and acceptability of remote monitoring for capturing both subjective and objective data from various sources for respiratory diseases. The high engagement level observed with passively collected data suggests the potential of wearables for long-term, user-friendly remote monitoring in respiratory disease management. The unique piloting of certain features such as protocol holidays, alert notifications for missing data, and flexible support from the study team provides a reference for future studies in this field.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/28873.

The impact of the COVID-19 pandemic on daily rhythms

OBJECTIVE

The COVID-19 pandemic has significantly impacted daily activity rhythms and life routines with people adjusting to new work schedules, exercise routines, and other everyday life activities. This study examines temporal changes in daily activity rhythms and routines during the COVID-19 pandemic, emphasizing disproportionate changes among working adult subgroups.

MATERIALS AND METHODS

In June 2021, we conducted a year-long study to collect high-resolution fitness tracker data and questionnaire responses from 128 working adults. Questionnaire data were analyzed to explore changes in exercise and work routines during the pandemic. We build temporal distributions of daily step counts to quantify their daily movement rhythms, then measure their consistency over time using the inverse of the Earth mover's distance. Linear mixed-effects models were employed to compare movement rhythm variability among subpopulations.

RESULTS

During the pandemic, our cohort exhibited a shift in exercise routines, with a decrease in nonwalking physical exercises, while walking remained unchanged. Migrants and those living alone had less consistent daily movement rhythms compared to others. Those preferring on-site work maintained more consistent daily movement rhythms. Men and migrants returned to work more quickly after pandemic restriction measures were eased.

DISCUSSION

Our findings quantitatively show the pandemic's unequal impact on different subpopulations. This study opens new research avenues to explore why certain groups return to on-site work, exercise levels, or daily movement rhythms more slowly compared to prepandemic times.

CONCLUSIONS

Considering the pandemic's unequal impact on subpopulations, organizations and policymakers should address diverse needs and offer tailored support during future crises.

Use of wearables for monitoring cardiometabolic health: A systematic review

INTRODUCTION

Cardiometabolic disorders (CMD) such as hyperglycemia, obesity, hypertension, and dyslipidemia are the leading causes of mortality and significant public health concerns worldwide. With the advances in wireless technology, wearables have become popular for health promotion, but its impact on cardiometabolic health is not well understood.

PURPOSE

A systematic literature review aimed to describe the features of wearables used for monitoring cardiometabolic health and identify the impact of using wearables on those cardiometabolic health indicators.

METHODS

A systematic search of PubMed, CINAHL, Academic Search Complete, and Science and Technology Collection databases was performed using keywords related to CMD risk indicators and wearables. The wearables were limited to sensors for blood pressure (BP), heart rate (HR), electrocardiogram (ECG), glucose, and cholesterol.

INCLUDED STUDIES

1) were published from 2016 to March 2021 in English, 2) focused on wearables external to the body, and 3) examined wearable use by individuals in daily life (not by health care providers). Protocol, technical, and non-empirical studies were excluded.

RESULTS

Out of 53 studies, the types of wearables used were smartwatches (45.3%), patches (34.0%), chest straps (22.6%), wristbands (13.2%), and others (9.4%). HR (58.5%), glucose (28.3%), and ECG (26.4%) were the predominant indicators. No studies tracked BP or cholesterol. Additional features of wearables included physical activity, respiration, sleep, diet, and symptom monitoring. Twenty-two studies primarily focused on the use of wearables and reported direct impacts on cardiometabolic indicators; seven studies used wearables as part of a multi-modality approach and presented outcomes affected by a primary intervention but measured through CMD-sensor wearables; and 24 validated the precision and usability of CMD-sensor wearables.

CONCLUSION

The impact of wearables on cardiometabolic indicators varied across the studies, indicating the need for further research. However, this body of literature highlights the potential of wearables to promote cardiometabolic health.

A scoping review of 'Pacing' for management of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): lessons learned for the long COVID pandemic

BACKGROUND

Controversy over treatment for people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a barrier to appropriate treatment. Energy management or pacing is a prominent coping strategy for people with ME/CFS. Whilst a definitive definition of pacing is not unanimous within the literature or healthcare providers, it typically comprises regulating activity to avoid post exertional malaise (PEM), the worsening of symptoms after an activity. Until now, characteristics of pacing, and the effects on patients' symptoms had not been systematically reviewed. This is problematic as the most common approach to pacing, pacing prescription, and the pooled efficacy of pacing was unknown. Collating evidence may help advise those suffering with similar symptoms, including long COVID, as practitioners would be better informed on methodological approaches to adopt, pacing implementation, and expected outcomes.

OBJECTIVES

In this scoping review of the literature, we aggregated type of, and outcomes of, pacing in people with ME/CFS.

ELIGIBILITY CRITERIA

Original investigations concerning pacing were considered in participants with ME/CFS.

SOURCES OF EVIDENCE

Six electronic databases (PubMed, Scholar, ScienceDirect, Scopus, Web of Science and the Cochrane Central Register of Controlled Trials [CENTRAL]) were searched; and websites MEPedia, Action for ME, and ME Action were also searched for grey literature, to fully capture patient surveys not published in academic journals.

METHODS

A scoping review was conducted. Review selection and characterisation was performed by two independent reviewers using pretested forms.

RESULTS

Authors reviewed 177 titles and abstracts, resulting in 17 included studies: three randomised control trials (RCTs); one uncontrolled trial; one interventional case series; one retrospective observational study; two prospective observational studies; four cross-sectional observational studies; and five cross-sectional analytical studies. Studies included variable designs, durations, and outcome measures. In terms of pacing administration, studies used educational sessions and diaries for activity monitoring. Eleven studies reported benefits of pacing, four studies reported no effect, and two studies reported a detrimental effect in comparison to the control group.

CONCLUSIONS

Highly variable study designs and outcome measures, allied to poor to fair methodological quality resulted in heterogenous findings and highlights the requirement for more research examining pacing. Looking to the long COVID pandemic, our results suggest future studies should be RCTs utilising objectively quantified digitised pacing, over a longer duration of examination (i.e. longitudinal studies), using the core outcome set for patient reported outcome measures. Until these are completed, the literature base is insufficient to inform treatment practises for people with ME/CFS and long COVID.

Pathophysiologic Basis of Connected Health Systems

Since the start of the COVID-19 pandemic, there has been a rapid transition to telehealth across the United States, primarily involving virtual clinic visits. Additionally, the proliferation of consumer technologies related to health reveals that for many people health and care in the contemporary world extends beyond the boundaries of a clinical interaction and includes sensors and devices that facilitate health in personal environments. The ideal connected environment is networked and intelligent, personalized to promote health and prevent disease. The combination of sensors, devices, and intelligence constitutes a connected health system around an individual that is optimized to improve and maintain health, deliver care, and predict and reduce risk of illness. Just as modern medicine uses the pathophysiology of disease as a framework for the basis of pharmacologic therapy, a similar clinically reasoned approach can be taken to organize and architect technological elements into therapeutic systems. In this work, we introduce a systematic methodology for the design of connected health systems grounded in the pathophysiologic basis of disease. As the digital landscape expands with the ubiquity of health devices, it is pivotal to enable technology-agnostic clinical reasoning to guide the integration of technological innovations into systems of health and care delivery that extend beyond the boundaries of a clinical interaction. Applying clinical reasoning in a repeatable and systematic way to organizing technology into therapeutic systems can yield potential benefits including expanding the study of digital therapeutics from individual devices to networked technologies as therapeutic interventions; empowering physicians who are not technological experts to still play a significant role in using clinical reasoning for architecting therapeutic networks of sensors and devices; and developing platforms to catalog and share combinations of technologies that can form therapeutic networks and connected health systems.

Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis

BACKGROUND

Major depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data; distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features.

OBJECTIVE

We aimed to address these 3 challenges to inform future work in stratified analyses.

METHODS

Using smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the individual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model.

RESULTS

We demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression.

CONCLUSIONS

This work contributes to our understanding of how these mobile health-derived features are associated with depression symptom severity to inform future work in stratified analyses.

Beyond the bowel - chaos caused by leaky barriers

The current issue of the Biomedical Journal includes a study presenting a possible agent against gut aging, a review of recent results in the field of breath biomarkers, as well as the investigation of the relationship between kidney disease and leptospirosis. Furthermore, the advantages of 3D imaging in dental medicine are elucidated, the influence of afterhyperpolarization in regulating the circadian clock is discussed, and the effectiveness of apremilast against ARDS is demonstrated. A controversial factor involved in the complex process of bone homeostasis is reviewed, and prevalent non-SARS human coronavirus types in Taiwan are looked at in detail. Lastly, the impact family history has on type 2 diabetes for the identification of high risk groups is addressed, the link between postoperative delirium risk and frailty in elderly patients is examined, and elements involved in recovering walking ability after stroke are analyzed.

The effects of social interactions on momentary stress and mood during COVID-19 lockdowns

OBJECTIVE

Social interactions are vital for our well-being, particularly during times of stress. However, previous studies linking social interactions to psychological outcomes during the COVID-19 pandemic have largely been retrospective and/or cross-sectional. Thus, we tested four preregistered hypotheses (H1-H4) concerning the real-time effect of social interactions on momentary changes in stress and mood during two COVID-19 lockdowns.

DESIGN

We used an ecological momentary assessment approach in 732 participants in spring 2020 (burst 1) and in a subsample of these participants (n = 281) during a further lockdown in autumn/winter 2020 (burst 2).

METHODS

Participants reported their stress and mood in a smartphone app five times per day for 7 days and indicated the nature and frequency of their recent social interactions.

RESULTS

Social interactions (H1) and their frequency (H2) improved momentary affect (e.g., social interactions increased mood valence: estimate = 2.605, p < .001 for burst 1). This was particularly the case for face-to-face interactions which, compared with other types of interactions, reduced momentary stress (e.g., estimate = -2.285, p < .001 for burst 1) and boosted mood (e.g., estimate = 1.759, p < .001 for burst 1) across both lockdowns, even when controlling for the pleasantness of the interaction and the closeness of the interaction partner (H3). We also show that individual differences in people's responsiveness to different social rewards modulated the impact of social interactions on momentary mood (H4).

CONCLUSIONS

This study extends findings from cross-sectional and retrospective studies by highlighting the real-time affective benefits of social interactions during COVID-19 lockdown. The results have important implications for the (self-) management of stress and mood during psychologically demanding periods.

mCrutch: A Novel m-Health Approach Supporting Continuity of Care

This paper reports the architecture of a low-cost smart crutches system for mobile health applications. The prototype is based on a set of sensorized crutches connected to a custom Android application. Crutches were instrumented with a 6-axis inertial measurement unit, a uniaxial load cell, WiFi connectivity, and a microcontroller for data collection and processing. Crutch orientation and applied force were calibrated with a motion capture system and a force platform. Data are processed and visualized in real-time on the Android smartphone and are stored on the local memory for further offline analysis. The prototype's architecture is reported along with the post-calibration accuracy for estimating crutch orientation (5° RMSE in dynamic conditions) and applied force (10 N RMSE). The system is a mobile-health platform enabling the design and development of real-time biofeedback applications and continuity of care scenarios, such as telemonitoring and telerehabilitation.

Real-time sensing of war's effects on wellbeing with smartphones and smartwatches

BACKGROUND

Modern wars have a catastrophic effect on the wellbeing of civilians. However, the nature of this effect remains unclear, with most insights gleaned from subjective, retrospective studies.

METHODS

We prospectively monitored 954 Israelis (>40 years) from two weeks before the May 2021 Israel-Gaza war until four weeks after the ceasefire using smartwatches and a dedicated mobile application with daily questionnaires on wellbeing. This war severely affected civilians on both sides, where over 4300 rockets and missiles were launched towards Israeli cities, and 1500 aerial, land, and sea strikes were launched towards 16,500 targets in the Gaza Strip.

RESULTS

We identify considerable changes in all the examined wellbeing indicators during missile attacks and throughout the war, including spikes in heart rate levels, excessive screen-on time, and a reduction in sleep duration and quality. These changes, however, fade shortly after the war, with all affected measures returning to baseline in nearly all the participants. Greater changes are observed in individuals living closer to the battlefield, women, and younger individuals.

CONCLUSIONS

The demonstrated ability to monitor objective and subjective wellbeing indicators during crises in real-time is pivotal for the early detection of and prompt assistance to populations in need.

AwarNS: A framework for developing context-aware reactive mobile applications for health and mental health

In recent years, interest and investment in health and mental health smartphone apps have grown significantly. However, this growth has not been followed by an increase in quality and the incorporation of more advanced features in such applications. This can be explained by an expanding fragmentation of existing mobile platforms along with more restrictive privacy and battery consumption policies, with a consequent higher complexity of developing such smartphone applications. To help overcome these barriers, there is a need for robust, well-designed software development frameworks which are designed to be reliable, power-efficient and ethical with respect to data collection practices, and which support the sense-analyse-act paradigm typically employed in reactive mHealth applications. In this article, we present the AwarNS Framework, a context-aware modular software development framework for Android smartphones, which facilitates transparent, reliable, passive and active data sampling running in the background (sense), on-device and server-side data analysis (analyse), and context-aware just-in-time offline and online intervention capabilities (act). It is based on the principles of versatility, reliability, privacy, reusability, and testability. It offers built-in modules for capturing smartphone and associated wearable sensor data (e.g. IMU sensors, geolocation, Wi-Fi and Bluetooth scans, physical activity, battery level, heart rate), analysis modules for data transformation, selection and filtering, performing geofencing analysis and machine learning regression and classification, and act modules for persistence and various notification deliveries. We describe the framework's design principles and architecture design, explain its capabilities and implementation, and demonstrate its use at the hand of real-life case studies implementing various mobile interventions for different mental disorders used in clinical practice.

The Impact of COVID-19 Lockdown on Adults with Major Depressive Disorder from Catalonia: A Decentralized Longitudinal Study

The present study analyzes the effects of each containment phase of the first COVID-19 wave on depression levels in a cohort of 121 adults with a history of major depressive disorder (MDD) from Catalonia recruited from 1 November 2019, to 16 October 2020. This analysis is part of the Remote Assessment of Disease and Relapse-MDD (RADAR-MDD) study. Depression was evaluated with the Patient Health Questionnaire-8 (PHQ-8), and anxiety was evaluated with the Generalized Anxiety Disorder-7 (GAD-7). Depression's levels were explored across the phases (pre-lockdown, lockdown, and four post-lockdown phases) according to the restrictions of Spanish/Catalan governments. Then, a mixed model was fitted to estimate how depression varied over the phases. A significant rise in depression severity was found during the lockdown and phase 0 (early post-lockdown), compared with the pre-lockdown. Those with low pre-lockdown depression experienced an increase in depression severity during the "new normality", while those with high pre-lockdown depression decreased compared with the pre-lockdown. These findings suggest that COVID-19 restrictions affected the depression level depending on their pre-lockdown depression severity. Individuals with low levels of depression are more reactive to external stimuli than those with more severe depression, so the lockdown may have worse detrimental effects on them.

Mobile applications in the Philippines during the COVID-19 pandemic: systematic search, use case mapping, and quality assessment using the Mobile App Rating Scale (MARS)

Background

In the Philippines, various mobile health apps were implemented during the COVID-19 pandemic with very little knowledge in terms of their quality. The aims of this paper were 1) to systemically search for mobile apps with COVID-19 pandemic use case that are implemented in the Philippines; 2) to assess the apps using Mobile App Rating Scale (MARS); and 3) to identify the critical points for future improvements of these apps.

Methods

To identify existing mobile applications with COVID-19 pandemic use case employed in the Philippines, Google Play and Apple App Stores were systematically searched. Further search was conducted using the Google Search. Data were extracted from the app web store profile and apps were categorized according to use cases. Mobile apps that met the inclusion criteria were independently assessed and scored by two researchers using the MARS-a 23-item, expert-based rating scale for assessing the quality of mHealth applications.

Results

A total of 27 apps were identified and assessed using MARS. The majority of the apps are designed for managing exposure to COVID-19 and for promoting health monitoring. The overall MARS score of all the apps is 3.62 points (SD 0.7), with a maximum score of 4.7 for an app used for telehealth and a minimum of 2.3 for a COVID-19 health declaration app. The majority (n = 19, 70%) of the apps are equal to or exceeded the minimum "acceptable" MARS score of 3.0. Looking at the categories, the apps for raising awareness received the highest MARS score of 4.58 (SD 0.03) while those designed for managing exposure to COVID-19 received the lowest mean score of 3.06 (SD 0.6).

Conclusions

There is a heterogenous quality of mHealth apps implemented during the COVID-19 pandemic in the Philippines. The study also identified areas to better improve the tools. Considering that mHealth is expected to be an integral part of the healthcare system post-pandemic, the results warrant better policies and guidance in the development and implementation to ensure quality across the board and as a result, positively impact health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44247-023-00007-2.

Tele-Physical Activity Promotion Program among College Students during the COVID-19 Pandemic

Background and Objectives: During the COVID-19 pandemic, lockdown and distance learning affected physical activity (PA) levels among college students. The aims were to assess the effectiveness of a tele-health PA promotion program for 6 weeks, among junior college students, on PA level and on the proportion of physically active students during the pandemic. Materials and Methods: A pre-post study design was conducted on 46 students aged 19 (±0.9) years old in Saudi Arabia. The study consisted of online introductory and educational PA classes, followed by a 6-week course during which students received daily online PA promotive messages. Wilcoxon signed-rank and McNemar's tests were used to measure the mean differences in PA level and the changes in proportion of physically active students before and after the program, respectively. Results: The proportion of students who perform walking increased significantly from 47.4% to 68.4% (p = 0.02), while the number of students who perform moderate PA in their leisure time increased significantly from 38.9% to 69.4% (p = 0.02). No significant differences were detected between other PA levels. Conclusions: This program is effective in encouraging more college students to be physically active, but not in improving PA levels. Larger scale studies using PA objective measurement tools are needed.

Exercise, diet, and sleep habits of nurses working full-time during the COVID-19 pandemic: An observational study

BACKGROUND

Healthy diet, exercise, and sleep practices may mitigate stress and prevent illness. However, lifestyle behaviors of acute care nurses working during stressful COVID-19 surges are unclear.

PURPOSE

To quantify sleep, diet, and exercise practices of 12-hour acute care nurses working day or night shift during COVID-19-related surges.

METHODS

Nurses across 10 hospitals in the United States wore wrist actigraphs and pedometers to quantify sleep and steps and completed electronic diaries documenting diet over 7-days.

FINDINGS

Participant average sleep quantity did not meet national recommendations; night shift nurses (n = 23) slept significantly less before on-duty days when compared to day shift nurses (n = 34). Proportionally more night shift nurses did not meet daily step recommendations. Diet quality was low on average among participants.

DISCUSSION

Nurses, especially those on night shift, may require resources to support healthy sleep hygiene, physical activity practices, and diet quality to mitigate stressful work environments.

Randomized Controlled Trial Evaluating the Benefit of a Novel Clinical Decision Support System for the Management of COVID-19 Patients in Home Quarantine: A Study Protocol

(1) Background: We present the protocol of a randomized controlled trial designed to evaluate the benefit of a novel clinical decision support system for the management of patients with COVID-19. (2) Methods: The study will recruit up to 500 participants (250 cases and 250 controls). Both groups will receive the conventional telephone follow-up protocol by primary care and will also be provided with access to a mobile application, in which they will be able to report their symptoms three times a day. In addition, patients in the active group will receive a wearable smartwatch and a pulse oximeter at home for real-time monitoring. The measured data will be visualized by primary care and emergency health service professionals, allowing them to detect in real time the progression and complications of the disease in order to promote early therapeutic interventions based on their clinical judgement. (3) Results: Ethical approval for this study was obtained from the Drug Research Ethics Committee of the Valladolid East Health Area (CASVE-NM-21-516). The results obtained from this study will form part of the thesis of two PhD students and will be disseminated through publication in a peer-reviewed journal. (4) Conclusions: The implementation of this telemonitoring system can be extrapolated to patients with other similar diseases, such as chronic diseases, with a high prevalence and need for close monitoring.

The impact of pandemic-related social distancing regulations on exercise performance-Objective data and training recommendations to mitigate losses in physical fitness

Introduction

In the context of the COVID-19 pandemic in Germany, governmental restrictions led to the closure of sports facilities for several months. To date, only subjective and fitness-tracking related data on physical activity during the pandemic are available. Using data of a chip-controlled fitness circuit, training data as a measure of physical performance before and after the lockdown during the first wave of the COVID-19 pandemic will show the impact of the training interruption on exercise performance in middle-aged and older adults. The re-training data are analyzed, to extract practical recommendations.

Methods

Objective training data of 17,450 participants [11,097 middle-aged (45-64 yrs), 6,353 older (≥65 yrs)] were exported from chip-controlled milon^® fitness circuit systems before and after the first COVID-19 related lockdown in Germany. The change in the product of training weight (sum of lifting and lowering the training weight) and repetitions on the leg extension resistance exercise device (leg score) between the last three training sessions before the lockdown and the first ten training sessions after individual training resumption as well as the last training session before the second lockdown in October 2020 was analyzed.

Results

Participants who trained with high intensity before the lockdown, experienced deleterious effects of the training interruption (middle-aged group: -218 kg, older group: ~-230.8 kg; p < 0.001 for change in leg score from to post-lockdown) with no age effect. Participants training with a leg score of more than 3,000 kg did not resume their leg score until the second lockdown.

Conclusion

The interruption of training in a fitness circuit with combined resistance and endurance training due to the lockdown affected mainly those participants who trained at high intensity. Apparently, high-intensity training could not be compensated by home-based training or outdoor activities. Concepts for high-intensity resistance training during closure of sports facilities are needed to be prepared for future periods of high incidence rates of infectious diseases, while especially vulnerable people feel uncomfortable to visit sports facilities.

Trial registration

Identifier, DRKS00022433.

COVID-BEHAVE dataset: measuring human behaviour during the COVID-19 pandemic

Aiming to illuminate the effects of enforced confinements on people's lives, this paper presents a novel dataset that measures human behaviour holistically and longitudinally during the COVID-19 outbreak. In particular, we conducted a study during the first wave of the lockdown, where 21 healthy subjects from the Netherlands and Greece participated, collecting multimodal raw and processed data from smartphone sensors, activity trackers, and users' responses to digital questionnaires. The study lasted more than two months, although the duration of the data collection varies per participant. The data are publicly available and can be used to model human behaviour in a broad sense as the dataset explores physical, social, emotional, and cognitive domains. The dataset offers an exemplary perspective on a given group of people that could be considered to build new models for investigating behaviour changes as a consequence of the lockdown. Importantly, to our knowledge, this is the first dataset combining passive sensing, experience sampling, and virtual assistants to study human behaviour dynamics in a prolonged lockdown situation.

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. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients' activity profiles has the potential to assess the level of MS-induced disability in free-living conditions.

METHODS

In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months' duration. We combined these features with participants' demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS).

RESULTS

The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT.

CONCLUSIONS

This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance.

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. Linear mixed-effects regression analyses with repeated measures were fitted to assess the changes among three time periods (pre, during and post-lockdown) across the groups, adjusting for depression severity before the pandemic and gender.

RESULTS

Participants with MDDs (N = 255) and MS (N = 214) were included in the analyses. Overall, depressive symptoms remained stable across the three periods in both groups. A lower mean HR and HR variation were observed between pre and during lockdown during the day for MDDs and during the night for MS. HR variation during rest periods also decreased between pre- and post-lockdown in both clinical conditions. We observed a reduction in physical activity for MDDs and MS upon the introduction of lockdowns. The group with MDDs exhibited a net increase in social interaction via social network apps over the three periods.

CONCLUSIONS

Behavioral responses to the lockdown measured by social activity, physical activity and HR may reflect changes in stress in people with MDDs and MS. Remote technology monitoring might promptly activate an early warning of physical and social alterations in these stressful situations. Future studies must explore how stress does or does not impact depression severity.

Anti-COVID-19 measures threaten our healthy body weight: Changes in sleep and external synchronizers of circadian clocks during confinement

BACKGROUND & AIMS

Emergency measures in the face of the recent COVID-19 pandemic have been different among countries, although most have opted for confinement and restrictions on social contact. These measures have generated lifestyle changes with potential effects on individuals' health. The disturbances in daily routines due to confinement and remote work have impacted circadian rhythms and energy balance; however, the consequences of these disruptions have not been studied in depth. The objective was to evaluate the impact of 12-week confinement on body weight, considering changes in several external synchronizers of the biological clock.

METHODS

The participants, 521 university students (16-35 years), responded to 52 questions oriented to determine light exposure, sleep patterns, sedentary lifestyle, and eating times.

RESULTS

We found a reduction in sunlight exposure and sleep duration, an increment in sedentarism and screen exposure, and a delay in the timing of the main meals and sleep in the whole cohort. These behavioral changes were associated with a twofold increase in obesity. Subjects who increased their sedentary hours and shortened their sleep to a higher degree were those who gained more bodyweight. The most influential factors in body weight variation during confinement were sleep duration, physical activity (sedentarism), and light (timing of screen exposure). The mediation model explained 6% of the total body weight variation.

CONCLUSIONS

Results support a significant impact of confinement on several external synchronizers of the biological clock and on body weight. Health-related recommendations during the pandemic must include behavioral recommendations to mitigate the adverse effects on the biological clock.

The Use of a Health Compliance Monitoring System During the COVID-19 Pandemic in Indonesia: Evaluation Study

BACKGROUND

COVID-19 cases are soaring in Asia. Indonesia, Southeast Asia's most populous country, is now ranked second in the number of cases and deaths in Asia, after India. The compliance toward mask wearing, social distancing, and hand washing needs to be monitored to assess public behavioral changes that can reduce transmission.

OBJECTIVE

This study aimed to evaluate this compliance in Indonesia between October 2020 and May 2021 and demonstrate the use of the Bersatu Lawan COVID-19 (BLC) mobile app in monitoring this compliance.

METHODS

Data were collected in real time by the BLC app from reports submitted by personnel of military services, police officers, and behavioral change ambassadors. Subsequently, the data were analyzed automatically by the system managed by the Indonesia National Task Force for the Acceleration of COVID-19 Mitigation.

RESULTS

Between October 1, 2020, and May 2, 2021, the BLC app generated more than 165 million reports, with 469 million people monitored and 124,315,568 locations under observation in 514 districts/cities in 34 provinces in Indonesia. This paper grouped them into 4 colored zones, based on the degree of compliance, and analyzed variations among regions and locations.

CONCLUSIONS

Compliance rates vary among the 34 provinces and among the districts and cities of those provinces. However, compliance to mask wearing seems slightly higher than social distancing. This finding suggests that policy makers need to promote higher compliance in other measures, including social distancing and hand washing, whose efficacies have been proven to break the chain of transmission when combined with masks wearing.

Changes of sarcopenia case finding by different Asian Working Group for Sarcopenia in community indwelling middle-aged and old people

Sarcopenia is an emerging issue, but there is no universal consensus regarding its screening and diagnosis, especially regarding the influence of the Asian Working Group for Sarcopenia (AWGS) 2019 new definition on the prevalence of community-dwelling adults. To compare the prevalence of sarcopenia between the 2019 and 2014 definitions, a cross-sectional study including 606 normal nutritional status subjects (203 men/403 women; mean age 63.3 ± 10.0 years) was performed. Sarcopenic parameters, including calf circumference, grip strength, 6-m gait speed, and bioelectrical-impedance-analysis-derived skeletal mass index (SMI), were evaluated. According to the 2019 AWGS definition, the prevalence of possible sarcopenia and sarcopenia among community-dwelling adults was 7.4 and 2.8%, respectively. There were highly consistent findings regarding sarcopenia between the 2019 and 2014 AWGS definitions according to Cohen's kappa coefficient (0.668). However, the prevalence of possible sarcopenia according to 2014 and 2019 AWGS in males increased 7.9%; in contrast, sarcopenia decreased from 7.4 to 3.7% in females (p < 0.001). In conclusion, the AWGS 2019 definition is more convenient for sarcopenia case screening and remains considerably consistent in sarcopenia identification in community-dwelling adults in Taiwan. The discordance of possible sarcopenia and sarcopenia by sex is a concern.

The role of mobile health technologies in promoting COVID-19 prevention: A narrative review of intervention effectiveness and adoption

Background

Researchers have found innovative ways of using mobile health (mHealth) technologies to prevent the spread of coronavirus disease 2019 (COVID-19). However, fewer studies have been done to determine their adoption and effectiveness.

Objective

This review summarises the published evidence on the effect of mHealth technologies on the adoption of COVID-19 preventive measures, prevention knowledge acquisition and risk perception as well as technology adoption features for COVID-19 prevention.

Methods

PubMed, IEEE and Google Scholar databases were searched for peer-reviewed literature from 1 January 2020 to 31 March 2022 for studies that evaluated the effect of mHealth technologies on COVID-19 preventive measures adoption, prevention knowledge acquisition and risk perception. Thirteen studies met the inclusion criteria and were included in this review. All the included studies were checked for quality using the mHealth evidence reporting and assessment (mERA) checklist.

Results

The review found out that the utilisation of mHealth interventions such as alert text messages, tracing apps and social media platforms was associated with adherence behaviour such as wearing masks, washing hands and using sanitisers, maintaining social distance and avoiding crowded places. The use of contact tracing was linked to low-risk perception as users considered themselves well informed about their status and less likely to pose transmission risks compared to non-users. Privacy and security issues, message personalisation and frequency, technical issues and trust concerns were identified as technology adoption features that influence the use of mHealth technologies for promoting COVID-19 prevention.

Conclusion

Utilisation of mHealth may be a feasible and effective way to prevent the spread of COVID-19. However, the small study samples and short study periods prevent generalisation of the findings and calls for larger, longitudinal studies that encompass diverse study settings.

Impact of Covid-19 emergency on rehabilitation services for Multiple Sclerosis: An international RIMS survey

Background

Covid-19 pandemic greatly impacted on the healthcare systems worldwide with negative consequences on several aspects of clinical populations. For neurological chronic conditions such as Multiple Sclerosis (MS), rehabilitation activities have been suspended or postponed during the pandemic. Rehabilitation is crucial for people with MS (PwMS) because it promotes recovery from relapses and maximizes opportunities for social participation. To better understand the impact of Covid-19 emergency on rehabilitation services for MS, the European network for rehabilitation in MS (RIMS) disseminated a survey to healthcare professionals (HPs) and representatives of the MS rehabilitation services (RSs), to explore the two different perspectives on the delivery of rehabilitation in usual circumstances and during the Covid-19 emergency.

Methods

The online survey was distributed from July 9th to September 20th, 2020. Besides general information on the responders (e.g. location of center, and memebership to RIMS), information was collected on usual service delivery (e.g. settings, specialities, and types of treatment), the impact of Covid-19 circumstances (e.g. restrictions, use of personal protective equipment, and impact on work), and the use of technologiesin rehabilitation.

Results

Twenty-two representatives of MS rehabilitation services (RSs)and 143 health care professionals (HPs) responded. Most of RSs and HPs worked in services specialized for MS including a mixture of all usual rehabilitation settings (i.e. inpatient, outpatient and community setting). The majority of services adopted a multidisciplinary framework, including physical therapy, occupational therapy, social service, speech and language therapy, psychological support, dietary interventions, medical management, vocational rehabilitation and cognitive rehabilitaton. Overall, most of responders indicated they did not use technologies in their practice (e.g. for treatment or assessment). However, depending on the type of technology a low-to-medium percentage of responders declared to use some technologies before Covid-19 crisis (5-55% for RSs and 12-53% for HPs) and a low percentage planned the use after pandemic (0-14% for RSs and 1-10% for HPs). Moreover, for the responders the most feasible interventions deliverable through tele-rehabilitation were psychological support and dietary interventions, with psychological support considered the most necessary intervention to be remotely implemented. Moderate feasibility (30-60%) was reported for hands-off interventions (e.g. aerobic exercise and cognitive rehabilitation) whereas low feasibility (<30%) was reported for hands-on interventions. Feasibility was especially low when tools were used that are not adaptable at-home (e.g. hyperbaric oxygen therapy).

Conclusion

The Covid-19 pandemic has stimulated the MS healthcare professionals to find new solutions to deliver alternative interventions to PwMS. In this context, the role of telemedicine is crucial to continue rehabilitation services at home, and limit exposure to infection. However, most of healthcare professionals have not incorporated the use of technologies. Therefore, the implementation of digital health solutions in the clinical practice needs more attention towards education on the potentials of technologies for rehabilitation and simplification of the national healthcare system reimbursement procedures for the rehabilitation technologies use.

Impact of Daycare Service Interruption during COVID-19 Pandemic on Physical and Mental Functions and Nutrition in Older People with Dementia

This study evaluated changes of cognitive, physical, and nutritional status before and after the interruption and resumption of daycare services during the COVID-19 pandemic in older dementia people in a daycare center. Comprehensive geriatric assessment data were analyzed before and after the lockdown of daycare center services, including mini-mental state examination, activities of daily living (ADL) scores, mini-nutritional assessment-short forms (MNA-SF), and timed up-and-go (TUG) tests. Among 19 dementia people participating in daycare services, 17 participants were enrolled in the study with, finally, two excluded because of incomplete follow-ups. They had a median age of 81 years; their MNA-SF scores and TUG values deteriorated significantly after a 3-month closure of daycare services (p < 0.05), and after resumption of daycare services the MNA-SF scores and TUG values recovered to near the pre-lockdown levels (p < 0.05). Besides, baseline ADL scores predicted a decline and recovery of TUG and MNA-SF values. Our findings suggest that planning continuous support for older dementia adults is important for daycare facilities during COVID-19 pandemic confinement.

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

BACKGROUND

The COVID-19 pandemic has broad negative impact on the physical and mental health of people with chronic neurological disorders such as multiple sclerosis (MS).

OBJECTIVE

We presented a machine learning approach leveraging passive sensor data from smartphones and fitness trackers of people with MS to predict their health outcomes in a natural experiment during a state-mandated stay-at-home period due to a global pandemic.

METHODS

First, we extracted features that capture behavior changes due to the stay-at-home order. Then, we adapted and applied an existing algorithm to these behavior-change features to predict the presence of depression, high global MS symptom burden, severe fatigue, and poor sleep quality during the stay-at-home period.

RESULTS

Using data collected between November 2019 and May 2020, the algorithm detected depression with an accuracy of 82.5% (65% improvement over baseline; F₁-score: 0.84), high global MS symptom burden with an accuracy of 90% (39% improvement over baseline; F₁-score: 0.93), severe fatigue with an accuracy of 75.5% (22% improvement over baseline; F₁-score: 0.80), and poor sleep quality with an accuracy of 84% (28% improvement over baseline; F₁-score: 0.84).

CONCLUSIONS

Our approach could help clinicians better triage patients with MS and potentially other chronic neurological disorders for interventions and aid patient self-monitoring in their own environment, particularly during extraordinarily stressful circumstances such as pandemics, which would cause drastic behavior changes.

Association of visceral fat area with pre-frailty in Japanese community-dwelling older adults: a cross-sectional study

Background

Screening and intervention in pre-frailty can help prevent or delay frailty among older adults. Being overweight has shown associated with pre-frailty, and overweight is highly prevalent among community-dwelling older adults during COVID-19. However, the impact of visceral fat accumulation remains unclear. This study aimed to explore the association between visceral fat area and pre-frailty in community-dwelling older adults.

Methods

The participants of this study included community-dwelling older adults from three elderly welfare centers. The frailty phenotype was assessed using the frailty screening index. The body composition was measured using bioelectrical impedance analysis.

Results

A total of 214 community-dwelling older adults completed the questionnaire and measurements. After excluding 16 frail participants, 149 (75.3%) were pre-frailty. The mean age of participants was 75.4 ± 5.4 years, and 69.7% (138) of participants were women. There were 54 (27.3%) participants with high visceral fat area. The multivariable model showed that participants with high visceral fat area were at increased risk for pre-frailty (adjusted OR, 3.15; 95% CI, 1.26 − 7.87; P = 0.014), even after adjusted for age, sex, health status, and impact of COVID-19 pandemic.

Conclusions

This study suggests that the association between visceral fat accumulation and pre-frailty may help to identify a new target for prevention. Further longitudinal studies are needed to determine their mechanisms in older adults.

Recruitment & Retention in Remote Research: Learnings from a Large Decentralized Real-World Study (Preprint)

BACKGROUND

Smartphones are increasingly used in health research. They provide a continuous connection between participants and researchers to monitor long-term health trajectories of large populations at a fraction of the cost of traditional research studies. However, despite the potential of using smartphones in remote research, there is an urgent need to develop effective strategies to reach, recruit, and retain the target populations in a representative and equitable manner.

OBJECTIVE

We aimed to investigate the impact of combining different recruitment and incentive distribution approaches used in remote research on cohort characteristics and long-term retention. The real-world factors significantly impacting active and passive data collection were also evaluated.

METHODS

We conducted a secondary data analysis of participant recruitment and retention using data from a large remote observation study aimed at understanding real-world factors linked to cold, influenza, and the impact of traumatic brain injury on daily functioning. We conducted recruitment in 2 phases between March 15, 2020, and January 4, 2022. Over 10,000 smartphone owners in the United States were recruited to provide 12 weeks of daily surveys and smartphone-based passive-sensing data. Using multivariate statistics, we investigated the potential impact of different recruitment and incentive distribution approaches on cohort characteristics. Survival analysis was used to assess the effects of sociodemographic characteristics on participant retention across the 2 recruitment phases. Associations between passive data-sharing patterns and demographic characteristics of the cohort were evaluated using logistic regression.

RESULTS

We analyzed over 330,000 days of engagement data collected from 10,000 participants. Our key findings are as follows: first, the overall characteristics of participants recruited using digital advertisements on social media and news media differed significantly from those of participants recruited using crowdsourcing platforms (Prolific and Amazon Mechanical Turk; P<.001). Second, participant retention in the study varied significantly across study phases, recruitment sources, and socioeconomic and demographic factors (P<.001). Third, notable differences in passive data collection were associated with device type (Android vs iOS) and participants' sociodemographic characteristics. Black or African American participants were significantly less likely to share passive sensor data streams than non-Hispanic White participants (odds ratio 0.44-0.49, 95% CI 0.35-0.61; P<.001). Fourth, participants were more likely to adhere to baseline surveys if the surveys were administered immediately after enrollment. Fifth, technical glitches could significantly impact real-world data collection in remote settings, which can severely impact generation of reliable evidence.

CONCLUSIONS

Our findings highlight several factors, such as recruitment platforms, incentive distribution frequency, the timing of baseline surveys, device heterogeneity, and technical glitches in data collection infrastructure, that could impact remote long-term data collection. Combined together, these empirical findings could help inform best practices for monitoring anomalies during real-world data collection and for recruiting and retaining target populations in a representative and equitable manner.

A systematic review of engagement reporting in remote measurement studies for health symptom tracking

Remote Measurement Technologies (RMTs) could revolutionise management of chronic health conditions by providing real-time symptom tracking. However, the promise of RMTs relies on user engagement, which at present is variably reported in the field. This review aimed to synthesise the RMT literature to identify how and to what extent engagement is defined, measured, and reported, and to present recommendations for the standardisation of future work. Seven databases (Embase, MEDLINE and PsycINFO (via Ovid), PubMed, IEEE Xplore, Web of Science, and Cochrane Central Register of Controlled Trials) were searched in July 2020 for papers using RMT apps for symptom monitoring in adults with a health condition, prompting users to track at least three times during the study period. Data were synthesised using critical interpretive synthesis. A total of 76 papers met the inclusion criteria. Sixty five percent of papers did not include a definition of engagement. Thirty five percent included both a definition and measurement of engagement. Four synthetic constructs were developed for measuring engagement: (i) engagement with the research protocol, (ii) objective RMT engagement, (iii) subjective RMT engagement, and (iv) interactions between objective and subjective RMT engagement. The field is currently impeded by incoherent measures and a lack of consideration for engagement definitions. A process for implementing the reporting of engagement in study design is presented, alongside a framework for definition and measurement options available. Future work should consider engagement with RMTs as distinct from the wider eHealth literature, and measure objective versus subjective RMT engagement.Registration: This review has been registered on PROSPERO [CRD42020192652].

Fitness Apps, Live Streaming Workout Classes, and Virtual Reality Fitness for Physical Activity During the COVID-19 Lockdown: An Empirical Study

Background

Physical activity is an essential need of the human body that helps improve the physical fitness of an individual and creates a positive impact on overall wellbeing. Smartphone applications play an essential role in providing several benefits to consumers by offering various capabilities in terms of health and fitness.COVID-19 preventive measures shut down public places, and people cannot go to the gym and parks for physical activity. Smart applications for physical activity are an effective way to keep active while staying at home.

Objective

The objective of the present study was to assess the mediating role of the e-platforms physical activity among the Chinese people in China during the COVID-19 lockdown.

Method

The participants in this study were Chinese citizens living in home isolation during the early stages of the epidemic in China. The primary data was collected via an online survey using a convenience sample strategy in accordance with the study purpose. The collected data were cleaned by using the SPSS-25 statistical software. SmartPLS 3.0 software was used to investigate the suggested study framework utilizing the structural equation modeling technique.

Results

Descriptive statistics shows that the ratio of gender includes 49% (n = 2,626) male and 51% females in the entire sample. SEM results show that all hypotheses (H1: β = 0.497, T = 43.068, P = <0.001; H2: β = 0.498, T = 41.078, P = <0.001; H3: β = 0.498, T = 41.078, P = <0.001; H4: β = 0.471, T = 39.103, P = <0.001; H5: β = 0.468, T = 42.633, P = <0.001; H6: β = 0.251, T = 11.212, P = <0.001; H7: β = 0.367, T = 16.032, P = <0.001; H8: β = 0.170, T = 13.750, P = <0.001; H9: β = 0.125, T = 10.604, P = <0.001; H10: β = 0.173, T = 14.842, P = <0.001) were statistically confirmed.

Conclusion

In COVID-19, when there are limited physical activity resources, smart applications play an essential role as an alternative to gyms and change people's perspective regarding the adoption of health and fitness. Smart applications have made exercise and physical activity accessible and convenient to adopt.

Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences

Background

Behavioral science researchers are increasingly collecting detailed location data such as second-by-second GPS tracking on participants due to increased ease and affordability. While intraindividual variability has been discussed in the travel literature for decades, traditional methods designed for studying individual differences in central tendencies limit the extent to which novel questions about variability in lived experiences can be answered. Thus, new methods of quantifying behavior that focus on intraindividual variability are needed to address the context in which the behavior occurs and the location tracking data from which behavior is derived.

Methods

We propose deviations from typical paths as a data processing technique to separate individual-level typical travel behavior from a location tracking data set in order to highlight atypical travel behavior as an outcome measure.

Results

A simulated data example shows how the method works to produce deviation measures from a location dataset. Analysis of these deviations offers additional insights compared to traditional measures of maximum daily distance from home.

Conclusions

This process can be integrated into larger research questions to explore predictors of atypical behavior and potential mechanisms of behavior change.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00305-4.

Epilepsy and COVID 2021

Coronavirus 19 (COVID-19) has infected over 400 million people worldwide. Although COVID-19 causes predominantly respiratory symptoms, it can affect other organs including the brain, producing neurological symptoms. People with epilepsy (PWE) have been particularly impacted during the pandemic with decreased access to care, increased stress, and worsening seizures in up to 22% of them probably due to multiple factors. COVID-19 vaccines were produced in a record short time and have yielded outstanding protection with very rare serious side effects. Studies have found that COVID-19 vaccination does not increase seizures in the majority of PWE. COVID-19 does not produce a pathognomonic EEG or seizure phenotype, but rather 1 that can be seen in other types of encephalopathy. COVID-19 infection and its complications can lead to seizures, status epilepticus and post-COVID inflammatory syndrome with potential multi-organ damage in people without pre-existing epilepsy. The lack of access to care during the pandemic has forced patients and doctors to rapidly implement telemedicine. The use of phone videos and smart telemedicine are helping to treat patients during this pandemic and are becoming standard of care. Investment in infrastructure is important to make sure patients can have access to care even during a pandemic.

Research on Digital Technology Use in Cardiology: Bibliometric Analysis

Background

Digital technology uses in cardiology have become a popular research focus in recent years. However, there has been no published bibliometric report that analyzed the corresponding academic literature in order to derive key publishing trends and characteristics of this scientific area.

Objective

We used a bibliometric approach to identify and analyze the academic literature on digital technology uses in cardiology, and to unveil popular research topics, key authors, institutions, countries, and journals. We further captured the cardiovascular conditions and diagnostic tools most commonly investigated within this field.

Methods

The Web of Science electronic database was queried to identify relevant papers on digital technology uses in cardiology. Publication and citation data were acquired directly from the database. Complete bibliographic data were exported to VOSviewer, a dedicated bibliometric software package, and related to the semantic content of titles, abstracts, and keywords. A term map was constructed for findings visualization.

Results

The analysis was based on data from 12,529 papers. Of the top 5 most productive institutions, 4 were based in the United States. The United States was the most productive country (4224/12,529, 33.7%), followed by United Kingdom (1136/12,529, 9.1%), Germany (1067/12,529, 8.5%), China (682/12,529, 5.4%), and Italy (622/12,529, 5.0%). Cardiovascular diseases that had been frequently investigated included hypertension (152/12,529, 1.2%), atrial fibrillation (122/12,529, 1.0%), atherosclerosis (116/12,529, 0.9%), heart failure (106/12,529, 0.8%), and arterial stiffness (80/12,529, 0.6%). Recurring modalities were electrocardiography (170/12,529, 1.4%), angiography (127/12,529, 1.0%), echocardiography (127/12,529, 1.0%), digital subtraction angiography (111/12,529, 0.9%), and photoplethysmography (80/12,529, 0.6%). For a literature subset on smartphone apps and wearable devices, the Journal of Medical Internet Research (20/632, 3.2%) and other JMIR portfolio journals (51/632, 8.0%) were the major publishing venues.

Conclusions

Digital technology uses in cardiology target physicians, patients, and the general public. Their functions range from assisting diagnosis, recording cardiovascular parameters, and patient education, to teaching laypersons about cardiopulmonary resuscitation. This field already has had a great impact in health care, and we anticipate continued growth.

Impact of COVID-19 on physical activity: A rapid review

Background

Physical activity is a commonly prescribed medicine for people with conditions such as obesity and diabetes who are also at increased risk of being hospitalized or severely ill from COVID-19. However, many people are reporting challenges in engaging in a healthy dose of physical activity amid the pandemic.

Objective

This rapid review synthesizes the current empirical evidence about the impacts of COVID-19 on people’s outdoor physical activity and sedentary behavior while highlighting the role of community environments in promoting or hindering physical activity during the pandemic.

Methods

Literature searches were conducted using keywords related to COVID-19: physical activity, mobility, and lifestyle behaviors. Eligibility criteria were peer-reviewed empirical and quantitative studies published in English, addressing COVID-19 and using physical activity and/or sedentary behavior as the study outcomes.

Results

Out of 61 eligible studies, the majority (78.3%) were conducted in Asian and European countries, with only four (6.7%) being US studies. The results showed that COVID-19 was linked with significant decreases in mobility, walking, and physical activity, and increases in sedentary activity. A few studies also reported contradicting results including increased uses of parks/trails and increased recreational activity among certain groups of population.

Conclusions

Evidence suggests an overall negative impact of COVID-19 on physical activity, with differential effects across different sub-populations. Significant knowledge gaps are also found in the roles of social and physical attributes that can promote physical activity during pandemics with reduced safety risks.

Changes in objectively measured lifestyle factors during the COVID-19 pandemic in community-dwelling older adults

Background

In this manuscript, we investigate whether objectively measured lifestyle factors, including walking steps, sedentary time, amount of unforced physical activity, level of slight and energetic physical activity, conversation time, and sleep parameters, were altered before and during the COVID-19 pandemic among community-dwelling older adults.

Methods

Data were obtained from a prospective cohort study conducted from 2015 to 2019 and a subsequent dementia prevention study undertaken in September 2020. Community-dwelling adults aged ≥ 65 years wore wearable sensors before and during the pandemic.

Results

A total of 56 adults were enrolled in this study. The mean age was 74.2 ± 3.9 years, and 58.9% (n = 33) of the participants were female. Moderate and vigorous physical activity time significantly decreased, and sedentary time significantly increased during the pandemic.

Conclusions

This is the first study to demonstrate differences in objectively assessed lifestyle factors before and during the COVID-19 pandemic among community-dwelling older adults. The findings show that the pandemic has adversely affected physical activity among older adults living on their own in Japan.

Impact of COVID-19 lockdown restrictions on cardiac rehabilitation participation and behaviours in the United Kingdom

BACKGROUND

COVID-19 lockdown measures led to the suspension of centre-based cardiac rehabilitation (CR). We aimed to describe the impact of lockdown on CR behaviours and perceptions of efficacy in a sample of CR participants.

METHODS

An online survey was conducted amongst CR participants from May to October 2020, COVID-19-related lockdown restrictions. Anthropometric data, participant-determined levels of motivation and self-perceived efficacy, CR practices etc., pre- and post-lockdown, were collected.

RESULTS

The probability of practicing CR in public gyms and hospitals decreased 15-fold (47.2% pre-, 5.6% post-lockdown; OR[95% CI] 0.065[0.013; 0.318], p < 0.001), and 34-fold (47.2% pre, 2.8% post; OR[95% CI] 0.029[0.004; 0.223], p < 0.001), respectively. Amongst participants, 79.5% indicated that their CR goals had changed and were 78% less likely to engage in CR for socialization after lockdown (47.2% pre, 16.7% post; OR[95% CI] 0.220[0.087; 0.555]; p = 0.002). The probability of receiving in-person supervision decreased by 90% (94.4% pre, 16.7% post; OR[95% CI] 0.011[0.002; 0.056]), while participants were almost 7 times more likely to use online supervision (11.1% pre, 44.4% post; OR[95% CI] 6.824[2.450; 19.002]) (both p < 0.001). Fifty percent indicated that their enjoyment of CR was lower than before lockdown and 27.8% reported they would be less likely to continue with CR in the newer format.

CONCLUSIONS

Lockdown was associated with considerable changes in how CR was practiced, motivation levels and willingness to continue with CR. Further research is warranted to develop and improve strategies to implement in times when individuals cannot attend CR in person and not only during pandemics.

Time to Sleep?-A Review of the Impact of the COVID-19 Pandemic on Sleep and Mental Health

Sleep is intrinsically tied to mental and overall health. Short sleep duration accompanies the modern lifestyle, possibly reaching epidemic proportions. The pandemic and subsequent lockdowns determined a fundamental shift in the modern lifestyle and had profound effects on sleep and mental health. This paper aims to provide an overview of the relationship between sleep, mental health and COVID-19. Contrasting outcomes on sleep health have been highlighted by most reports during the pandemic in the general population. Consequently, while longer sleep durations have been reported, this change was accompanied by decreases in sleep quality and altered sleep timing. Furthermore, an increased impact of sleep deficiencies and mental health burden was generally reported in health care workers as compared with the adult general population. Although not among the most frequent symptoms during the acute or persistent phase, an increased prevalence of sleep deficiencies has been reported in patients with acute and long COVID. The importance of sleep in immune regulation is well known. Consequently, sleep deficiencies may influence multiple aspects of COVID-19, such as the risk, severity, and prognosis of the infection and even vaccine response.

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. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants' location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility.

RESULTS

This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=-0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=-0.07, P<.001) the subsequent periodicity of mobility.

CONCLUSIONS

Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.

Comparing SF-36 Scores Collected Through Web-Based Questionnaire Self-completions and Telephone Interviews: An Ancillary Study of the SENTIPAT Multicenter Randomized Controlled Trial

Background

The 36-Item Short Form Health Survey (SF-36) is a popular questionnaire for measuring the self-perception of quality of life in a given population of interest. Processing the answers of a participant comprises the calculation of 10 scores corresponding to 8 scales measuring several aspects of perceived health and 2 summary components (physical and mental). Surprisingly, no study has compared score values issued from a telephone interview versus those from an internet-based questionnaire self-completion.

Objective

This study aims to compare the SF-36 score values issued from a telephone interview versus those from an internet-based questionnaire self-completion.

Methods

Patients with an internet connection and returning home after hospital discharge were enrolled in the SENTIPAT multicenter randomized trial on the day of discharge. They were randomized to either self-completing a set of questionnaires using a dedicated website (internet group) or providing answers to the same questionnaires administered during a telephone interview (telephone group). This ancillary study of the trial compared SF-36 data related to the posthospitalization period in these 2 groups. To anticipate the potential unbalanced characteristics of the responders in the 2 groups, the impact of the mode of administration of the questionnaire on score differences was investigated using a matched sample of individuals originating from the internet and telephone groups (1:1 ratio), in which the matching procedure was based on a propensity score approach. SF-36 scores observed in the internet and telephone groups were compared using the Wilcoxon-Mann-Whitney test, and the score differences between the 2 groups were also examined according to Cohen effect size.

Results

Overall, 29.2% (245/840) and 75% (630/840) of SF-36 questionnaires were completed in the internet and telephone groups, respectively (P<.001). Globally, the score differences between groups before matching were similar to those observed in the matched sample. Mean scores observed in the telephone group were all above the corresponding values observed in the internet group. After matching, score differences in 6 out of the 8 SF-36 scales were statistically significant, with a mean difference greater than 5 for 4 scales and an associated mild effect size ranging from 0.22 to 0.29, and with a mean difference near this threshold for 2 other scales (4.57 and 4.56) and a low corresponding effect size (0.18 and 0.16, respectively).

Conclusions

The telephone mode of administration of SF-36 involved an interviewer effect, increasing SF-36 scores. Questionnaire self-completion via the internet should be preferred, and surveys combining various administration methods should be avoided.

Trial Registration

ClinicalTrials.gov NCT01769261; https://www.clinicaltrials.gov/ct2/show/record/NCT01769261

Review on people's trust on home use medical devices during Covid-19 pandemic in India

With the rapid development of the medical device against COVID-19 is an excellent achievement. There are numerous obstacles effectively facing the worldwide population, from manufacture to distribution, deployment and, acceptance. Many manufacturers have entered the market rivalry as people's knowledge and demand for home-use medical equipment has increased. India represents a compelling market opportunity for global medical device manufacturers. Substantial growth for the Indian medical device industry is expected to be driven by the current low per-person spending rate for medical devices. The growth of the medical devices industry in India raises competition law issues (anti-trust) and therefore maintaining public trust in home-use medical devices during COVID-19 will be as essential. The review article aims to create awareness among people about commonly used medical devices during the COVID-19 pandemic and to survey people’s trust in home usable medical devices in India. In a worldwide pandemic, manufacturers of medical devices face insufficient storage and the impossibility of meeting the requirements of the health centre. The sale of some of the most significant medical devices has increased, making it more difficult for the medical device industry to satisfy demand with high-quality goods since the quality of COVID-19 items plays a vital part in the present scenario. Despite the difficulty in providing enough medical equipment during a pandemic, they are striving to adapt to the circumstance. After recognizing the need to promote awareness and grasp the selling, and production, handling of medical instruments during COVID-19 at home was conducted. In addition, medical equipment manufacturers and distributors look at this scenario as an opportunity to profit more. This review article would enable researchers during COVID-19 to build more knowledge and widespread trust in medical technologies respectively.

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. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data.

METHODS

Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months.

RESULTS

Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types.

CONCLUSIONS

RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.