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Mobile Health and Mobile Rehabilitation for People with Disabilities

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Disabilities".

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 43056

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Special Issue Editors

Dr. Michael L. Jones

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Virginia C. Crawford Research Institute, Shepherd Center, Atlanta, GA 30309, USA
Interests: design and management of environments, programs, and services that promote independent living and full inclusion of people with disabilities; applications of universal design, information and communication technology; behavior management strategies; independent living philosophy to promote health, wellness, and community participation
Special Issues, Collections and Topics in MDPI journals

Dr. Frank Deruyter

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Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
Interests: innovative assistive; information and communication technologies to enable persons with disabilities to optimize accessibility and usability of those technologies to access the world; emerging mainstream technologies; outcomes/performance monitoring, and program development
Special Issues, Collections and Topics in MDPI journals

Dr. John T. Morris

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Virginia C. Crawford Research Institute, Shepherd Center, Atlanta, GA 30309, USA
Interests: research and development of assistive and rehabilitation technology for people with all types of disability; research on user needs and usability of technology products and services; development of mobile software applications and clinical interventions leveraging mainstream consumer technology platforms.
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mobile healthcare—the delivery of health and wellness services via mobile communication technologies—is witnessing prolific growth. Mobile health (mHealth) and mobile rehabilitation (mRehab) have been touted as important new approaches for the management of chronic health conditions, including those affecting people with disabilities.

Concerns have been raised that the proliferation of mHealth could increase health disparities if it disproportionately benefits advantaged populations and leaves vulnerable populations behind, including people with disabilities. mRehab—the use of mobile communications to support remote delivery of rehabilitation programs to patients at home or in the community—is less mature than mHealth and must also confront critical challenges of utility, efficacy, acceptance by patients and providers, integration into hospitals’ health information systems, and reimbursement.

In this Special Issue, we hope to summarize the current state-of-the-art in mHealth and mRehab service delivery, elucidate the challenges and barriers to adoption of mHealth/mRehab, and lay out an agenda for future research and development efforts in this area.

We encourage your submission of papers presenting original research findings, innovative mHealth/mRehab service delivery approaches, or review of critical barriers to adoption.

Dr. Michael L. Jones
Dr. Frank Deruyter
Dr. John Morris
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

mHealth
mRehab
information and communication technologies
disability
chronic disease
self-management of health and wellness

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Related Special Issue

Mobile Health and Mobile Rehabilitation for People with Disabilities: 2nd Edition in International Journal of Environmental Research and Public Health (7 articles)

Published Papers (10 papers)

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Research

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18 pages, 1722 KiB

Open AccessArticle

A Pilot Study of a Sensor Enhanced Activity Management System for Promoting Home Rehabilitation Exercise Performed during the COVID-19 Pandemic: Therapist Experience, Reimbursement, and Recommendations for Implementation

by Veronica A. Swanson, Vicky Chan, Betsaida Cruz-Coble, Celeste M. Alcantara, Douglas Scott, Mike Jones, Daniel K. Zondervan, Naveen Khan, Jan Ichimura and David J. Reinkensmeyer

Int. J. Environ. Res. Public Health 2021, 18(19), 10186; https://doi.org/10.3390/ijerph181910186 - 28 Sep 2021

Cited by 7 | Viewed by 2937

Abstract

Adherence to home exercise programs (HEPs) during physical rehabilitation is usually unmonitored and is thought to be low from self-reports. This article describes exploratory implementation of a Sensor Enhanced Activity Management (SEAM) system that combines HEP management software with a movement sensor for monitoring and motivating HEP adherence. The article also presents results from attempting to gain reimbursement for home use of the system with therapist oversight using Remote Physiologic Monitoring (RPM) codes. Four therapists used the system in their regular practice during the first six months of the COVID-19 pandemic. Therapists filled out surveys, kept notes, and participated in interviews. Billing and reimbursement data were obtained from the treatment facility. Exercise data from the SEAM system were used to understand HEP adherence. Patients were active for a mean of 40% (26% SD) of prescribed days and completed a mean of 25% (25% SD) of prescribed exercises. The therapists billed 23 RPM codes (USD 2353), and payers reimbursed eight of those instances (USD 649.21). The therapists reported that remote monitoring and the use of a physical movement sensor was motivating to their patients and increased adherence. Sustained technical support for therapists will likely improve implementation of new remote monitoring and treatment systems. RPM codes may enable reimbursement for review and program management activities, but, despite COVID-19 CMS waivers, organizations may have more success if these services are billed under supervision of a physician. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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14 pages, 879 KiB

Open AccessArticle

A Pilot Evaluation of mHealth App Accessibility for Three Top-Rated Weight Management Apps by People with Disabilities

by Erin Radcliffe, Ben Lippincott, Raeda Anderson and Mike Jones

Int. J. Environ. Res. Public Health 2021, 18(7), 3669; https://doi.org/10.3390/ijerph18073669 - 1 Apr 2021

Cited by 18 | Viewed by 4191

Abstract

Growing evidence demonstrates that people with disabilities face more challenges in accessing healthcare and wellness resources, compared to non-disabled populations. As mobile applications focused on health and wellness (mHealth apps) become prevalent, it is important that people with disabilities can access and use mHealth apps. At present, there is no source of unified information about the accessibility and usability of mHealth apps for people with disabilities. We set out to create such a source, establishing a systematic approach for evaluating app accessibility. Our goal was to develop a simple, replicable app evaluation process to generate useful information for people with disabilities (to aid suitable app selection) and app developers (to improve app accessibility and usability). We collected data using two existing assessment instruments to test three top-rated weight management apps with nine users representing three disability groups: vision, dexterity, and cognitive impairment. Participants with visual impairments reported the lowest accessibility ratings, most challenges, and least tolerance for issues. Participants with dexterity impairments experienced significant accessibility-related difficulties. Participants with cognitive impairments experienced mild difficulties and higher tolerances for issues. Our pilot protocol will be applied to test mHealth apps and populate a “curation” website to assist consumers in selecting mHealth apps. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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8 pages, 2853 KiB

Open AccessArticle

Adaptive Health Coaching Technology for Tailored Interventions

by Holly Jimison, Michael Shapiro and Misha Pavel

Int. J. Environ. Res. Public Health 2021, 18(5), 2761; https://doi.org/10.3390/ijerph18052761 - 9 Mar 2021

Cited by 3 | Viewed by 2588

Abstract

Recent advances in sensor and communications technology have enabled scalable methods for providing continuity of care to the home for patients with chronic conditions and older adults wanting to age in place. In this article we describe our framework for a health coaching platform with a dynamic user model that enables tailored health coaching messages. We have shown that this can improve coach efficiency without a loss of message quality. We also discovered many lessons for coaching technology, most demonstrating the need for more coach input on sample message content, perhaps even requiring that individual coaches be able to modify the message database directly. Overall, coaches felt that the structure of the automated message generation was useful in remembering what to say, easy to edit if necessary and especially helpful for training new health coaches. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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17 pages, 1382 KiB

Open AccessArticle

Mobile-Health Technologies for a Child Neuropsychiatry Service: Development and Usability of the Assioma Digital Platform

by Elisa Fucà, Floriana Costanzo, Dimitri Bonutto, Annarita Moretti, Andrea Fini, Alberto Ferraiuolo, Stefano Vicari and Alberto Eugenio Tozzi

Int. J. Environ. Res. Public Health 2021, 18(5), 2758; https://doi.org/10.3390/ijerph18052758 - 9 Mar 2021

Cited by 3 | Viewed by 3073

Abstract

We developed an m-Health platform to support clinical pathways in a child and adolescent neuropsychiatry unit. The Assioma platform was created for tablets, smartphones and PCs, to support data collection and clinical workflow, to promote constant communication between patients, caregivers and clinicians, and to promote active family involvement in day hospital (DH) procedures. Through the Assioma application for tablets, caregivers filled out an anamnestic questionnaire and explored contents on the DH procedures and neurodevelopmental conditions. The application for smartphones included an agenda function for the DH pathways. Through the application for desktops, clinicians could export anamnestic information in text and Excel formats, send real-time notifications, and push relative contents to families’ account. We tested the usability and satisfaction of the Assioma platform in a group of children, caregivers (N = 24) and clinicians (N = 6). Both families and clinicians gave high scores to almost all usability items. The overall satisfaction reached the highest levels at 50% satisfied for families and at 33% for clinicians. Our results indicate that the Assioma platform has the potential to optimize clinical pathways, increasing compliance and clinical efficiency, and to reduce in-person contacts supporting social distancing for clinical pathways, a crucial need during the COVID-19 pandemic. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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16 pages, 3379 KiB

Open AccessFeature PaperArticle

Measuring Activities of Daily Living in Stroke Patients with Motion Machine Learning Algorithms: A Pilot Study

by Pin-Wei Chen, Nathan A. Baune, Igor Zwir, Jiayu Wang, Victoria Swamidass and Alex W.K. Wong

Int. J. Environ. Res. Public Health 2021, 18(4), 1634; https://doi.org/10.3390/ijerph18041634 - 9 Feb 2021

Cited by 32 | Viewed by 4294

Abstract

Measuring activities of daily living (ADLs) using wearable technologies may offer higher precision and granularity than the current clinical assessments for patients after stroke. This study aimed to develop and determine the accuracy of detecting different ADLs using machine-learning (ML) algorithms and wearable sensors. Eleven post-stroke patients participated in this pilot study at an ADL Simulation Lab across two study visits. We collected blocks of repeated activity (“atomic” activity) performance data to train our ML algorithms during one visit. We evaluated our ML algorithms using independent semi-naturalistic activity data collected at a separate session. We tested Decision Tree, Random Forest, Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost) for model development. XGBoost was the best classification model. We achieved 82% accuracy based on ten ADL tasks. With a model including seven tasks, accuracy improved to 90%. ADL tasks included chopping food, vacuuming, sweeping, spreading jam or butter, folding laundry, eating, brushing teeth, taking off/putting on a shirt, wiping a cupboard, and buttoning a shirt. Results provide preliminary evidence that ADL functioning can be predicted with adequate accuracy using wearable sensors and ML. The use of external validation (independent training and testing data sets) and semi-naturalistic testing data is a major strength of the study and a step closer to the long-term goal of ADL monitoring in real-world settings. Further investigation is needed to improve the ADL prediction accuracy, increase the number of tasks monitored, and test the model outside of a laboratory setting. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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11 pages, 288 KiB

Open AccessArticle

Clinician Perspectives on mRehab Interventions and Technologies for People with Disabilities in the United States: A National Survey

by John Morris, Mike Jones, Nicole Thompson, Tracey Wallace and Frank DeRuyter

Int. J. Environ. Res. Public Health 2019, 16(21), 4220; https://doi.org/10.3390/ijerph16214220 - 31 Oct 2019

Cited by 21 | Viewed by 3924

Abstract

Mobile health and mobile rehabilitation (mHealth and mRehab) services and technologies have attracted considerable interest from healthcare providers, technology vendors, rehabilitation engineers, investors and policy makers in recent years. Successful adoption and use of mHealth/mRehab requires clinician support and engagement, including the ability to identify appropriate use cases and possible barriers to use for themselves and their patients, and acquire adequate knowledge and confidence using mHealth/mRehab interventions. This article reports results from a survey of rehabilitation clinicians in the United States on their attitudes, experience, expectations and concerns regarding mHealth/mRehab interventions and technologies. Over 500 clinicians in physical, occupational, speech, recreation and psychological therapy professions, among others, participated in the survey. Respondents reported that an overwhelming majority of their patients need additional therapy after discharge from inpatient environments, and over half of outpatients need additional therapy between visits. A large majority reported prescribing specific exercises and interventions for patients to work on outside of the clinic. However, only 51% reported being comfortable integrating mRehab technology into their practice; and only 23% feel knowledgeable about rehabilitation technology currently available. Technologies to support mRehab are maturing rapidly. Clinicians recognize the need for mRehab, but their knowledge and confidence prescribing mRehab represents a significant barrier to adoption. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

Review

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23 pages, 695 KiB

Open AccessReview

Use of mHealth Technology for Patient-Reported Outcomes in Community-Dwelling Adults with Acquired Brain Injuries: A Scoping Review

by Shannon B. Juengst, Lauren Terhorst, Andrew Nabasny, Tracey Wallace, Jennifer A. Weaver, Candice L. Osborne, Suzanne Perea Burns, Brittany Wright, Pey-Shan Wen, Chung-Lin Novelle Kew and John Morris

Int. J. Environ. Res. Public Health 2021, 18(4), 2173; https://doi.org/10.3390/ijerph18042173 - 23 Feb 2021

Cited by 27 | Viewed by 5098

Abstract

The purpose of our scoping review was to describe the current use of mHealth technology for long-term assessment of patient-reported outcomes in community-dwelling individuals with acquired brain injury (ABI). Following PRISMA guidelines, we conducted a scoping review of literature meeting these criteria: (1) civilians or military veterans, all ages; (2) self-reported or caregiver-reported outcomes assessed via mobile device in the community (not exclusively clinic/hospital); (3) published in English; (4) published in 2015–2019. We searched Ovid MEDLINE(R) < 1946 to 16 August 2019, MEDLINE InProcess, EPub, Embase, and PsycINFO databases for articles. Thirteen manuscripts representing 12 distinct studies were organized by type of ABI [traumatic brain injury (TBI) and stroke] to extract outcomes, mHealth technology used, design, and inclusion of ecological momentary assessment (EMA). Outcomes included post-concussive, depressive, and affective symptoms, fatigue, daily activities, stroke risk factors, and cognitive exertion. Overall, collecting patient-reported outcomes via mHealth was feasible and acceptable in the chronic ABI population. Studies consistently showed advantage for using EMA despite variability in EMA timing/schedules. To ensure best clinical measurement, research on post-ABI outcomes should consider EMA designs (versus single time-point assessments) that provide the best timing schedules for their respective aims and outcomes and that leverage mHealth for data collection. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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10 pages, 287 KiB

Open AccessReview

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

by Mike Jones, Frank DeRuyter and John Morris

Int. J. Environ. Res. Public Health 2020, 17(2), 381; https://doi.org/10.3390/ijerph17020381 - 7 Jan 2020

Cited by 37 | Viewed by 7161

Abstract

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. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

Other

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13 pages, 2126 KiB

Open AccessConcept Paper

Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation

by Mike Jones, George Collier, David J. Reinkensmeyer, Frank DeRuyter, John Dzivak, Daniel Zondervan and John Morris

Int. J. Environ. Res. Public Health 2020, 17(3), 748; https://doi.org/10.3390/ijerph17030748 - 24 Jan 2020

Cited by 23 | Viewed by 4757

Abstract

Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for medical rehabilitation. While there are advantages to outpatient rehabilitation (e.g., lower cost, more relevant to home and community function), there are also challenges including lack of information about how patient progress observed in the outpatient clinic translates into improved functional performance at home. At present, outpatient providers must rely on patient-reported information about functional progress (or lack thereof) at home and in the community. Information and communication technologies (ICT) offer another option—data collected about the patient’s adherence, performance and progress made on home exercises could be used to help guide course corrections between clinic visits, enhancing effectiveness and efficiency of outpatient care. In this article, we describe our efforts to explore use of sensor-enhanced home exercise and big data analytics in medical rehabilitation. The goal of this work is to demonstrate how sensor-enhanced exercise can improve rehabilitation outcomes for patients with significant neurological impairment (e.g., from stroke, traumatic brain injury, and spinal cord injury). We provide an overview of big data analysis and explain how it may be used to optimize outpatient rehabilitation, creating a more efficient model of care. We describe our planned development efforts to build advanced analytic tools to guide home-based rehabilitation and our proposed randomized trial to evaluate effectiveness and implementation of this approach. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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11 pages, 2278 KiB

Open AccessConference Report

LiveWell RERC State of the Science Conference Report on ICT Access to Support Community Living, Health and Function for People with Disabilities

by John Morris, Mike Jones, Frank DeRuyter, David Putrino, Catherine E. Lang and Danielle Jake-Schoffman

Int. J. Environ. Res. Public Health 2020, 17(1), 274; https://doi.org/10.3390/ijerph17010274 - 30 Dec 2019

Cited by 2 | Viewed by 3118

Abstract

This article summarizes the proceedings of the three session State of the Science (SOS) Conference that was conducted by the Rehabilitation Engineering Research Center for Community Living, Health and Function (LiveWell RERC) in June 2019 in Toronto, Canada. RERCs customarily convene an SOS conference toward the end of their five-year funding cycle in order to assess the current state and identify potential future research, development, and knowledge translation efforts needed to advance their field. The first two sessions focused on the current and future state of information and communication technology (ICT) for mobile health (mHealth) and mobile rehabilitation (mRehab). The third session was a wide-ranging discussion of pressing needs for future research and development in the field. Several “big ideas” resulted from the discussion among participants in the SOS Conference that should inform the structure and operation of future efforts, including: (1) identifying active ingredients of interventions, (2) incorporating effective behavior-change techniques into all interventions, (3) including measures of social determinants of health in evaluation studies, (4) incorporating user-customizable features into technology solutions, and (5) ensuring “discoverability” of research and development outputs by stakeholders via structured and continuous outreach, education and training. Substantive areas of work include gaming and esports, the gamification of interventions for health and fitness, the cultivation of community supports, and continuous outreach and education wherever a person with a disability may live. Full article

(This article belongs to the Special Issue Mobile Health and Mobile Rehabilitation for People with Disabilities)

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