An alternative to the ‘light touch’ digital health remote study: The Stress and Recovery in Frontline COVID-19 Healthcare Workers Study (Preprint)

2021 ◽  
Author(s):  
Sarah Margaret Goodday ◽  
Emma Karlin ◽  
Alexandria Alfarano ◽  
Alexa Brooks ◽  
Carol Chapman ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Acute Stress ◽  
Digital Health ◽  
Wearable Sensors ◽  
Health Study ◽  
Smartphone App ◽  
Light Touch ◽  
Subjective Data ◽  
Study Duration ◽  
Passive Data

BACKGROUND Background: Several app-based studies share similar characteristics of a ‘light touch’ approach that recruit, enroll, and onboard via a smartphone app and attempt to minimize burden through low-friction active study tasks, while emphasizing the collection of passive data with minimal human contact. However, engagement is a common challenge across these studies reporting low retention and adherence. OBJECTIVE To describe an alternative to a ‘light touch’ digital health study that involved a participant centric design including high friction app-based assessments, semi-continuous passive data from wearable sensors and a digital engagement strategy centered on providing knowledge and support to participants. METHODS The Stress and Recovery in Frontline COVID-19 Healthcare Workers Study included US frontline healthcare workers followed between May-November 2020. The study comprised 3 main components: 1) active and passive assessments of stress and symptoms from a smartphone app; 2) objective measured assessments of acute stress from wearable sensors; and 3) a participant co-driven engagement strategy that centered on providing knowledge and support to participants. The daily participant time commitment was an average of 10-15 minutes. Retention and adherence are described both quantitatively and qualitatively. RESULTS Results: 365 participants enrolled and started the study and 81.0% (297/365) of them completed the study for a total study duration of 4 months. Average wearable sensor usage was 90.6% days of total study duration. App-based daily, weekly, and every other week surveys were completed on average 69.18%, 68.37%, 72.86% of the time, respectively. CONCLUSIONS Conclusions: This study found evidence for feasibility and acceptability of a participant centric digital health study approach that involved building trust and respect with participants and providing support through regular phone check-ins. In addition to high retention and adherence, the collection of large volumes of objective measured data alongside contextual self-reported subjective data was able to be collected that is often missing from ‘light touch’ digital health studies. CLINICALTRIAL Clinicaltrials.Gov (NCT04713111)

scholarly journals An alternative to the ‘light touch’ digital health remote study: The Stress and Recovery in Frontline COVID-19 Healthcare Workers Study (Preprint)

10.2196/32165 ◽  
2021 ◽  
Author(s):  
Sarah Margaret Goodday ◽  
Emma Karlin ◽  
Alexandria Alfarano ◽  
Alexa Brooks ◽  
Carol Chapman ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Digital Health ◽  
Light Touch

Collecting patient reported outcomes to facilitate prescription opioid management: Development and testing of the Opioid Management App (OM-App) (Preprint)

2020 ◽  
Author(s):  
Jessica Robinson-Papp ◽  
Gabriela Cedillo ◽  
Richa Deshpande ◽  
Mary Catherine George ◽  
Qiuchen Yang ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Pain Intensity ◽  
Risk Behaviors ◽  
Digital Health ◽  
Monitoring Program ◽  
Prescription Opioid ◽  
Research Database ◽  
Cross Sectional ◽  
Study Duration ◽  
Patient Reported

BACKGROUND Collecting patient-reported data needed by clinicians to adhere to opioid prescribing guidelines represents a significant time burden. OBJECTIVE We developed and tested an opioid management app (OM-App) to collect these data directly from patients. METHODS OM-App used a pre-existing digital health platform to deliver daily questions to patients via text-message and organize responses into a dashboard. We pilot tested OM-App over 9 months in 40 diverse participants with HIV who were prescribed opioids for chronic pain. Feasibility outcomes included: ability to export/integrate OM-App data with other research data; patient-reported barriers and adherence to OM-App use; capture of opioid-related harms, risk behaviors and pain intensity/interference; comparison of OM-App data to urine drug testing, prescription drug monitoring program data, and validated questionnaires. RESULTS OM-App data was exported/integrated into the research database after minor modifications. Thirty-nine of 40 participants were able to use OM-App, and over the study duration 70% of all OM-App questions were answered. Although the cross-sectional prevalence of opioid-related harms and risk behaviors reported via OM-App was low, some of these were not obtained via the other measures, and over the study duration all queried harms/risks were reported at least once via OM-App. Clinically meaningful changes in pain intensity/interference were captured. CONCLUSIONS OM-App was used by our diverse patient population to produce clinically relevant opioid- and pain-related data, which was successfully exported and integrated into a research database. These findings suggest that OM-App may be a useful tool for remote monitoring of patients prescribed opioids for chronic pain. CLINICALTRIAL NCT03669939 INTERNATIONAL REGISTERED REPORT RR2-doi:10.1016/j.conctc.2019.100468

scholarly journals Opportunities and Challenges Surrounding the Use of Data From Wearable Sensor Devices in Health Care: Qualitative Interview Study (Preprint)

2020 ◽  
Author(s):  
Ijeoma Azodo ◽  
Robin Williams ◽  
Aziz Sheikh ◽  
Kathrin Cresswell
Keyword(s):  
Health Care ◽  
Digital Health ◽  
Wearable Sensors ◽  
Unintended Consequences ◽  
Wearable Sensor ◽  
Use Of Data ◽  
Qualitative Interview Study ◽  
Sensor Devices ◽  
Care Technology ◽  
International Experts

BACKGROUND Wearable sensors connected via networked devices have the potential to generate data that may help to automate processes of care, engage patients, and increase health care efficiency. The evidence of effectiveness of such technologies is, however, nascent and little is known about unintended consequences. OBJECTIVE Our objective was to explore the opportunities and challenges surrounding the use of data from wearable sensor devices in health care. METHODS We conducted a qualitative, theoretically informed, interview-based study to purposefully sample international experts in health care, technology, business, innovation, and social sciences, drawing on sociotechnical systems theory. We used in-depth interviews to capture perspectives on development, design, and use of data from wearable sensor devices in health care, and employed thematic analysis of interview transcripts with NVivo to facilitate coding. RESULTS We interviewed 16 experts. Although the use of data from wearable sensor devices in health and care has significant potential in improving patient engagement, there are a number of issues that stakeholders need to negotiate to realize these benefits. These issues include the current gap between data created and meaningful interpretation in health and care contexts, integration of data into health care professional decision making, negotiation of blurring lines between consumer and medical care, and pervasive monitoring of health across previously disconnected contexts. CONCLUSIONS Stakeholders need to actively negotiate existing challenges to realize the integration of data from wearable sensor devices into electronic health records. Viewing wearables as active parts of a connected digital health and care infrastructure, in which various business, personal, professional, and health system interests align, may help to achieve this.

scholarly journals An Evaluation of Digital Health Tools for Diabetes Self-Management in Hispanic Adults: Exploratory Study (Preprint)

2018 ◽  
Author(s):  
Leah Yingling ◽  
Nancy A Allen ◽  
Michelle L Litchman ◽  
Vanessa Colicchio ◽  
Bryan S Gibson
Keyword(s):  
Blood Glucose ◽  
Low Income ◽  
Digital Health ◽  
Wearable Sensors ◽  
Self Management ◽  
Food Diary ◽  
Self Monitoring ◽  
Hispanic Adults ◽  
Monitoring Technologies ◽  
Potential Integration

BACKGROUND Although multiple self-monitoring technologies for type 2 diabetes mellitus (T2DM) show promise for improving T2DM self-care behaviors and clinical outcomes, they have been understudied in Hispanic adult populations who suffer disproportionately from T2DM. OBJECTIVE The objective of this study was to evaluate the acceptability, feasibility, and potential integration of wearable sensors for diabetes self-monitoring among Hispanic adults with self-reported T2DM. METHODS We conducted a pilot study of T2DM self-monitoring technologies among Hispanic adults with self-reported T2DM. Participants (n=21) received a real-time continuous glucose monitor (RT-CGM), a wrist-worn physical activity (PA) tracker, and a tablet-based digital food diary to self-monitor blood glucose, PA, and food intake, respectively, for 1 week. The RT-CGM captured viewable blood glucose concentration (mg/dL) and PA trackers collected accelerometer-based data, viewable on the device or an associated tablet app. After 1 week of use, we conducted a semistructured interview with each participant to understand experiences and thoughts on integration of the data from the devices into a technology-facilitated T2DM self-management intervention. We also conducted a brief written questionnaire to understand participants’ self-reported T2DM history and past experience using digital health tools for T2DM self-management. Feasibility was measured by device utilization and objective RT-CGM, PA tracker, and diet logging data. Acceptability and potential integration were evaluated through thematic analysis of verbatim interview transcripts. RESULTS Participants (n=21, 76% female, 50.4 [SD 11] years) had a mean self-reported hemoglobin A1c of 7.4 [SD 1.8] mg/dL and had been diagnosed with T2DM for 7.4 [SD 5.2] years (range: 1-16 years). Most (89%) were treated with oral medications, whereas the others self-managed through diet and exercise. Nearly all participants (n=20) used both the RT-CGM and PA tracker, and 52% (11/21) logged at least one meal, with 33% (7/21) logging meals for 4 or more days. Of the 8 possible days, PA data were recorded for 7.1 [SD 1.8] days (range: 2-8), and participants averaged 7822 [SD 3984] steps per day. Interview transcripts revealed that participants felt most positive about the RT-CGM as it unveiled previously unknown relationships between lifestyle and health and contributed to changes in T2DM-related thoughts and behaviors. Participants felt generally positive about incorporating the wearable sensors and mobile apps into a future intervention if support were provided by a health coach or health care provider, device training were provided, apps were tailored to their language and culture, and content were both actionable and delivered on a single platform. CONCLUSIONS Sensor-based tools for facilitating T2DM self-monitoring appear to be a feasible and acceptable technology among low-income Hispanic adults. We identified barriers to acceptability and highlighted preferences for wearable sensor integration in a community-based intervention. These findings have implications for the design of T2DM interventions targeting Hispanic adults.

Abstract P070: Longer Sleep Duration Is Associated With Less Myosteatosis In African Caribbean Adults

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Adrianna I Acevedo-Fontanez ◽  
Ryan Cvejkus ◽  
Allison L Kuipers ◽  
Joseph Zmuda ◽  
Victor Wheeler ◽  
...  
Keyword(s):  
Physical Activity ◽  
Skeletal Muscle ◽  
Sleep Duration ◽  
Vigorous Physical Activity ◽  
Health Study ◽  
Muscle Area ◽  
Subjective Data ◽  
Muscle Density ◽  
Intermuscular Adipose Tissue ◽  
African Caribbean

Introduction: Skeletal muscle is the largest organ in the human body and vital to maintaining metabolic homeostasis. Increased skeletal muscle fat infiltration (i.e. myosteatosis) is now recognized as a major risk factor for cardio-metabolic diseases, independent of general obesity. Modifications in lifestyle, such as sleep, to reduce myosteatosis would be of great public health importance. However, studies of this relationship often use subjective data and are lacking in minority populations. The aim of this study was to examine the relation between objectively measured sleep duration and myosteatosis at the calf among African Caribbeans. Methods: Data were collected on men (n=393) and women (n=438) from the Tobago Health Study. Sleep duration and physical activity was collected using a SenseWear Pro Armband (BodyMedia, Inc.). Participants were instructed to wear the armband at all times, except in water, for 4-7 days. Measures of muscle density, intermuscular adipose tissue (IMAT), and area were obtained by peripheral QCT scans of the calf (Stratec XCT-2000). Model covariates included age, sex, BMI, diabetes, alcohol intake, smoking, and moderate to vigorous physical activity (MVPA). Linear regression was used to assess the relationship of sleep duration on skeletal muscle. Results: Mean sleep duration was 5.5 hours/day (Min 2.2, Max 11.6). Overall, participants were aged 58.7 years, had a BMI of 30.2 kg/m 2 , spent an average of 42 min/day in MVPA, and 18% were diabetic. In fully adjusted models, longer sleep duration was associated with smaller muscle area, but greater muscle density and less IMAT (all P<0.03). There was no interaction of sleep and sex on muscle density, area and IMAT (p-value=0.5184; 0.2730; 0.0954). Conclusions: In African Caribbean men and women, longer sleep duration was associated with less myosteatosis, as well as, less muscle area at the calf. Further research is warranted to understand this relationship longitudinally in order to determine how it may inform lifestyle guidelines in the Caribbean.

scholarly journals The Digital Health Revolution and People with Disabilities: Perspective from the United States

2020 ◽  
Vol 17 (2) ◽  
pp. 381 ◽  
Author(s):  
Mike Jones ◽  
Frank DeRuyter ◽  
John Morris
Keyword(s):  
United States ◽  
Mobile Health ◽  
Chronic Conditions ◽  
Digital Health ◽  
Wearable Sensors ◽  
Healthcare Delivery ◽  
People With Disabilities ◽  
The United States ◽  
Models Of Care ◽  
Health Technologies

This article serves as the introduction to this special issue on Mobile Health and Mobile Rehabilitation for People with Disabilities. Social, technological and policy trends are reviewed. Needs, opportunities and challenges for the emerging fields of mobile health (mHealth, aka eHealth) and mobile rehabilitation (mRehab) are discussed. Healthcare in the United States (U.S.) is at a critical juncture characterized by: (1) a growing need for healthcare and rehabilitation services; (2) maturing technological capabilities to support more effective and efficient health services; (3) evolving public policies designed, by turns, to contain cost and support new models of care; and (4) a growing need to ensure acceptance and usability of new health technologies by people with disabilities and chronic conditions, clinicians and health delivery systems. Discussion of demographic and population health data, healthcare service delivery and a public policy primarily focuses on the U.S. However, trends identified (aging populations, growing prevalence of chronic conditions and disability, labor shortages in healthcare) apply to most countries with advanced economies and others. Furthermore, technologies that enable mRehab (wearable sensors, in-home environmental monitors, cloud computing, artificial intelligence) transcend national boundaries. Remote and mobile healthcare delivery is needed and inevitable. Proactive engagement is critical to ensure acceptance and effectiveness for all stakeholders.

The mental health burden of COVID-19 on cardiac healthcare workers and their patients

2020 ◽  
Vol 15 (10) ◽  
pp. 1-8
Author(s):  
Barbara M Murphy ◽  
Rosemary O Higgins ◽  
Alun C Jackson
Keyword(s):  
Mental Health ◽  
Health Professionals ◽  
Healthcare Workers ◽  
Acute Stress ◽  
Cardiac Patients ◽  
Post Traumatic Stress ◽  
Early Recovery ◽  
Stress Symptoms ◽  
Post Traumatic ◽  
Mental Health Effects

The COVID-19 pandemic is taking a toll on the healthcare workforce across the world and, with many health professionals experiencing high levels of exposure to the coronavirus, the rate of infection among healthcare workers is high. Documented mental health effects on these workers are also concerning, with higher-than-usual levels of acute stress, post-traumatic stress symptoms, anxiety, depression and sleep disorders, particularly insomnia. Cardiac patients are particularly vulnerable, and health professionals caring for this group face additional stresses. This article provides an overview of the mental health impacts of the pandemic on healthcare workers, with an emphasis on those working in hospital settings and in cardiac care, as well as on the patients for whom they care. The specific impacts of COVID-19 are also discussed, as well as associated social restrictions on cardiac patients, both during hospitalisation and early recovery, and in terms of long-term risks. Strategies are proposed that healthcare workers can adopt to help preserve and improve their coping and enhance their resilience as they work through this unprecedented and unpredictable pandemic.

scholarly journals Designing an integrated, nurse-driven and home-based digital intervention to improve insulin management in under-resourced settings

2021 ◽  
Vol 12 ◽  
pp. 204201882110546
Author(s):  
Patrick Ngassa Piotie ◽  
Paola Wood ◽  
Elizabeth M. Webb ◽  
Johannes F.M. Hugo ◽  
Paul Rheeder
Keyword(s):  
South Africa ◽  
Type 2 Diabetes ◽  
Primary Care ◽  
Healthcare Workers ◽  
Digital Health ◽  
Complex Interventions ◽  
Community Healthcare ◽  
Community Healthcare Workers ◽  
Project Intervention

Background: In South Africa, initiating insulin for people with type 2 diabetes and subsequent titration is a major challenge for the resource-constrained healthcare system. Inadequate support systems in primary care, including not being able to access blood glucose monitors and test strips for self-monitoring of blood glucose, results in patients with type 2 diabetes being referred to higher levels of care. In primary care, initiation of insulin may be delayed due to a shortage of healthcare workers. The delayed initiation of insulin is also exacerbated by the reported resistance of both healthcare providers and people with type 2 diabetes to start insulin. In South Africa, telehealth provides an opportunity to overcome these challenges and manage insulin therapy in primary care. Methods: We describe the development of a digital health intervention including the framework used, the theoretical approach and subsequent implementation strategies. Results: This intervention is an innovative, nurse-driven and app-enabled intervention called ‘the Tshwane Insulin Project intervention’. The Tshwane Insulin Project intervention was designed and evaluated using the framework recommended by the Medical Research Council for complex interventions. The Tshwane Insulin Project intervention was developed in four sequential phases: planning, design, implementation and evaluation. The Tshwane Insulin Project intervention followed the Integrated Chronic Disease Management framework to facilitate implementation and acceptability. The Tshwane Insulin Project comprises a facility-level intervention, where nurses evaluate patients and initiate insulin, an individual-level intervention where community healthcare workers visit patients at their homes to follow-up and provide educational information, while using telehealth to enable physician-directed insulin titration if needed, and a community-level intervention aimed at empowering community healthcare workers to support people living with diabetes and raise awareness of diabetes. Conclusion: The technological advancements in digital health and telemedicine present an opportunity to improve diabetes care in resource-limited countries. This work can inform those intending to develop and implement complex interventions in primary healthcare in developing countries.

scholarly journals Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study (Preprint)

2020 ◽  
Author(s):  
Abhishek Pratap ◽  
Daniel Grant ◽  
Ashok Vegesna ◽  
Meghasyam Tummalacherla ◽  
Stanley Cohan ◽  
...  
Keyword(s):  
Real World ◽  
Test Performance ◽  
Digital Health ◽  
Finger Tapping ◽  
Health Study ◽  
Functional Tests ◽  
Lower Extremity Function ◽  
The Real ◽  
Extremity Function ◽  
The Impact

BACKGROUND Multiple sclerosis (MS) is a chronic neurodegenerative disease. Current monitoring practices predominantly rely on brief and infrequent assessments, which may not be representative of the real-world patient experience. Smartphone technology provides an opportunity to assess people’s daily-lived experience of MS on a frequent, regular basis outside of episodic clinical evaluations. OBJECTIVE The objectives of this study were to evaluate the feasibility and utility of capturing real-world MS-related health data remotely using a smartphone app, “elevateMS,” to investigate the associations between self-reported MS severity and sensor-based active functional tests measurements, and the impact of local weather conditions on disease burden. METHODS This was a 12-week, observational, digital health study involving 3 cohorts: self-referred participants who reported an MS diagnosis, clinic-referred participants with neurologist-confirmed MS, and participants without MS (controls). Participants downloaded the elevateMS app and completed baseline assessments, including self-reported physical ability (Patient-Determined Disease Steps [PDDS]), as well as longitudinal assessments of quality of life (Quality of Life in Neurological Disorders [Neuro-QoL] Cognitive, Upper Extremity, and Lower Extremity Function) and daily health (MS symptoms, triggers, health, mobility, pain). Participants also completed functional tests (finger-tapping, walk and balance, voice-based Digit Symbol Substitution Test [DSST], and finger-to-nose) as an independent assessment of MS-related cognition and motor activity. Local weather data were collected each time participants completed an active task. Associations between self-reported baseline/longitudinal assessments, functional tests, and weather were evaluated using linear (for cross-sectional data) and mixed-effects (for longitudinal data) regression models. RESULTS A total of 660 individuals enrolled in the study; 31 withdrew, 495 had MS (n=359 self-referred, n=136 clinic-referred), and 134 were controls. Participation was highest in clinic-referred versus self-referred participants (median retention: 25.5 vs 7.0 days). The top 5 most common MS symptoms, reported at least once by participants with MS, were fatigue (310/495, 62.6%), weakness (222/495, 44.8%), memory/attention issues (209/495, 42.2%), and difficulty walking (205/495, 41.4%), and the most common triggers were high ambient temperature (259/495, 52.3%), stress (250/495, 50.5%), and late bedtime (221/495, 44.6%). Baseline PDDS was significantly associated with functional test performance in participants with MS (mixed model–based estimate of most significant feature across functional tests [β]: finger-tapping: β=–43.64, <i>P</i>&lt;.001; DSST: β=–5.47, <i>P</i>=.005; walk and balance: β=–.39, <i>P</i>=.001; finger-to-nose: β=.01, <i>P</i>=.01). Longitudinal Neuro-QoL scores were also significantly associated with functional tests (finger-tapping with Upper Extremity Function: β=.40, <i>P</i>&lt;.001; walk and balance with Lower Extremity Function: β=–99.18, <i>P</i>=.02; DSST with Cognitive Function: β=1.60, <i>P</i>=.03). Finally, local temperature was significantly associated with participants’ test performance (finger-tapping: β=–.14, <i>P</i>&lt;.001; DSST: β=–.06, <i>P</i>=.009; finger-to-nose: β=–53.88, <i>P</i>&lt;.001). CONCLUSIONS The elevateMS study app captured the real-world experience of MS, characterized some MS symptoms, and assessed the impact of environmental factors on symptom severity. Our study provides further evidence that supports smartphone app use to monitor MS with both active assessments and patient-reported measures of disease burden. App-based tracking may provide unique and timely real-world data for clinicians and patients, resulting in improved disease insights and management.

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