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AbstractThe integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device’s application programmable interface and the mobile app’s adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.

BackgroundIn the United States, 1 in 5 adults currently serves as a family caregiver for an individual with a serious illness or disability. Unlike professional caregivers, family caregivers often assume this role without formal preparation or training. Thus, there is an urgent need to enhance the capacity of family caregivers to provide quality care. Leveraging technology as an educational tool or an adjunct to care is a promising approach that has the potential to enhance the learning and caregiving capabilities of family caregivers. Large language models (LLMs) can potentially be used as a foundation technology for supporting caregivers. An LLM can be categorized as a foundation model (FM), which is a large-scale model trained on a broad data set that can be adapted to a range of different domain tasks. Despite their potential, FMs have the critical weakness of “hallucination,” where the models generate information that can be misleading or inaccurate. Information reliability is essential when language models are deployed as front-line help tools for caregivers. ObjectiveThis study aimed to (1) develop a reliable caregiving language model (CaLM) by using FMs and a caregiving knowledge base, (2) develop an accessible CaLM using a small FM that requires fewer computing resources, and (3) evaluate the model’s performance compared with a large FM. MethodsWe developed a CaLM using the retrieval augmented generation (RAG) framework combined with FM fine-tuning for improving the quality of FM answers by grounding the model on a caregiving knowledge base. The key components of the CaLM are the caregiving knowledge base, a fine-tuned FM, and a retriever module. We used 2 small FMs as candidates for the foundation of the CaLM (LLaMA [large language model Meta AI] 2 and Falcon with 7 billion parameters) and adopted a large FM (GPT-3.5 with an estimated 175 billion parameters) as a benchmark. We developed the caregiving knowledge base by gathering various types of documents from the internet. We focused on caregivers of individuals with Alzheimer disease and related dementias. We evaluated the models’ performances using the benchmark metrics commonly used in evaluating language models and their reliability for providing accurate references with their answers. ResultsThe RAG framework improved the performance of all FMs used in this study across all measures. As expected, the large FM performed better than the small FMs across all metrics. Interestingly, the small fine-tuned FMs with RAG performed significantly better than GPT 3.5 across all metrics. The fine-tuned LLaMA 2 with a small FM performed better than GPT 3.5 (even with RAG) in returning references with the answers. ConclusionsThe study shows that a reliable and accessible CaLM can be developed using small FMs with a knowledge base specific to the caregiving domain.

Background: Lung transplantation is an established treatment option for persons with advanced lung disease. After transplantation, lung function typically returns to near normal levels, however exercise capacity remains low due to chronic deconditioning, limited physical function, and inactive lifestyles which undermine the intended benefits of the highly selective, resource-intensive transplant procedure. Pulmonary rehabilitation is recommended to improve fitness and activity tolerance, however due to multiple barriers, lung transplant recipients either never participate, or fail to complete, pulmonary rehabilitation programs. Purpose: To describe the design of Lung Transplant Go (LTGO), a trial modified for the remote environment based on recommendations to preserve trial integrity during COVID. The aims are to evaluate a behavioral exercise intervention to improve physical function, physical activity, and blood pressure control in lung transplant recipients conducted safely and effectively using a telerehabilitation (telerehab) platform, and to explore the role of potential mediators and moderators of the relationship between LTGO and outcomes. Methods: Single-site, 2-group randomized controlled trial with lung transplant recipients randomized 1:1 to either the LTGO intervention (a 2-phased, supervised, telerehab behavioral exercise program), or to enhanced usual care (activity tracking and monthly newsletters). All study activities, including intervention delivery, recruitment, consenting, assessment, and data collection, will be performed remotely. Conclusion: If efficacious, this fully scalable and replicable telerehab intervention could be efficiently translated to reach large numbers of lung recipients to improve and sustain self-management of exercise habits by overcoming barriers to participation in existing, in-person pulmonary rehabilitation programs.

Background: Family caregivers with continuous caregiving responsibilities are at increased risk for adverse physical and mental health outcomes. In response to the challenges of caregiving, a mobile health system (iMHere 2.0) was developed to support caregivers. The study's objective was to gather feedback from family caregivers of older adults on the current features of iMHere 2.0 and to formulate design criteria for future iterations of the system. Methods: An exploratory qualitative study with thematic analyses of focus group feedback. Findings: A total of 10 caregivers of older adults participated in a focus group. Five themes emerged: (1) Monitoring health data, (2) Setting up customized reminders, (3) Supporting care coordination, (4) Balancing security and multiple user access, and (5) Disseminating iMHere 2.0 into the community, along with some potential barriers to implementation. Conclusions: Design criteria were developed to provide a framework for iterative design and development of the iMHere system to support caregivers of older adults.

BackgroundSelf-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials. ObjectiveThe aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m2. MethodsAll participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants’ dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal). ResultsParticipants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m2. The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: –2.12%, 95% CI –3.04% to –1.21%, P

Background: Mobile health (mHealth) apps have the potential to facilitate convenient health care delivery and self-management of health. However, many users have concerns about their privacy when they use mHealth apps. Different apps provide different solutions for protecting users’ privacy. Objective: The purpose of this study was to determine user preferences among the several privacy protection methods used in current mHealth apps and the reasons behind their preferences. Methods: Five privacy protection methods currently used in mHealth apps were presented to a group of study participants who had mild or moderate depression and expressed concerns about privacy of information when they used mental health apps. After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past. A brief interview was then conducted to collect study participants’ comments on these methods and elicit the reasons for their preference ratings. Statistical analysis was performed to determine the statistical significance of differences in participants’ preference ratings and in the PPPLs obtained for the five methods. Study participants’ comments on the privacy protection methods and suggestions were noted and summarized. Results: Forty (40) study participants were selected from a large candidate pool using the IRB approved selection criteria. All study participants viewed the app demonstration and understood the five privacy protection methods properly, which was indicated by their correct sorting of the PPPL of the five methods in their answers to the questionnaire. All study participants specified their preferences with respect to these methods and provided the rationale behind their selections on the questionnaire and during the brief interview. The results indicate that the users preferred privacy protection methods with customizable modules in multi-purpose apps because of their convenience and strong privacy protection, where the customization can be done either in the app or via a Web portal. Conclusions: This study identified user preferred privacy protection methods. These identified privacy protection methods may be used in many types of apps that perform sensitive health information management to better protect users’ privacy and encourage more users to adopt these mHealth apps.

BackgroundMobile health (mHealth) systems that support self-management can improve medical, functional, and psychosocial outcomes for individuals with disabilities and chronic conditions. The mHealth systems can potentially be expanded to support community integration. ObjectiveThe purposes of this study were to (1) partner with a community-based organization that supports community integration of individuals with disabilities; (2) identify software requirements needed to support community participation; and (3) iteratively refine an existing mHealth application to include new requirements. MethodsCommunity Living and Support Services (CLASS), a nonprofit organization that serves individuals with disabilities in Pittsburgh, Pennsylvania, was identified as the focus group for this study. Key stakeholders within the Community Partners Program at CLASS proposed design requirements for an existing mHealth application, Interactive Mobile Health and Rehabilitation (iMHere) 2.0, that has been used to support self-management. ResultsWe gathered qualitative data from a focus group composed of CLASS members to develop and iteratively revise iMHere 2.0 to include new modules and features to support community integration. A caregiver app was also developed. The new system contains features to support finance, transportation, client and caregiver communication, calendar and checklist management, upcoming medical and nonmedical appointments, social engagement, pain management, and access to a personal profile. Modifications were made to the following existing modules: education, mood, personal health record, goals, medications, and nutrition. ConclusionsA successful partnership with a community-based organization that supports individuals with disabilities resulted in a newly designed mHealth system with features to support community integration.

BackgroundMobile health systems have been shown to be useful in supporting self-management by promoting adherence to schedules and longitudinal health interventions, especially in people with disabilities. The Interactive Mobile Health and Rehabilitation (iMHere) system was developed to empower people with disabilities and those with chronic conditions with supports needed for self-management and independent living. Since the first iteration of the iMHere 1.0 app, several studies have evaluated the accessibility and usability of the system. Potential opportunities to improve and simplify the user interface were identified, and the iMHere modules were redesigned accordingly. ObjectiveIn this study, we aim to evaluate the usability of the redesigned modules within the iMHere 1.0 app. MethodsWe evaluated the original and redesigned iMHere modules—MyMeds and SkinCare. The Purdue Pegboard Test was administered to assess the participants’ dexterity levels. Participants were then asked to perform a set of tasks using both the original and redesigned MyMeds and SkinCare modules to assess their efficiency and effectiveness. Usability was measured using the Telehealth Usability Questionnaire to evaluate 10 new accessibility features that were added to the redesigned app. Participants were also asked which version they preferred. ResultsIn total, 24 participants with disabilities and varying degrees of dexterity impairments completed the entire study protocol. Participants displayed improved efficiency and effectiveness when using the redesigned modules compared with the original modules. The participants also reported improved usability and preferred the redesigned modules. ConclusionsThis study demonstrated that the iMHere system became more efficient, effective, and usable for individuals with dexterity impairments after redesigning it according to user-centered principles.

Background: Telehealth is a great approach for providing high quality health care services to people who cannot easily access these services in person. However, because of frequently reported health data breaches, many people may hesitate to use telehealth-based health care services. It is necessary for telehealth care providers to demonstrate that they have taken sufficient actions to protect their patients’ data security and privacy. The government provided a HIPAA audit protocol that is highly useful for internal security and privacy auditing on health care systems, however, this protocol includes extensive details that are not always specific to telehealth and therefore is difficult to be used by telehealth practitioners. Objective: The goal of this study was to develop and validate a telehealth privacy and security self-assessment questionnaire for telehealth providers. Methods: In our previous work, we performed a systematic review on the security and privacy protection offered in various telehealth systems. The results from this systematic review and the HIPAA audit protocol were used to guide the development of the self-assessment questionnaire. The draft of the questionnaire was created by the research team and distributed to a group of telehealth providers for evaluating the relevance and clarity of each statement in the draft. The questionnaire was adjusted and finalized according to the collected feedback and face-to-face discussions by the research team. A website was created to distribute the questionnaire and manage the answers from study participants. A psychometric analysis was performed to evaluate the reliability of the questionnaire. Results: There were 84 statements in the draft questionnaire. Five telehealth providers provided their feedback to the statements in this draft. They indicated that a number of these statements were either redundant or beyond the capacity of telehealth care practitioners, who typically do not have formal training in information security. They also pointed out that the wording of some statements needed to be adjusted. The final released version of the questionnaire had 49 statements. In total, 31 telehealth providers across the nation participated in the study by answering all the statements in this questionnaire. The psychometric analysis indicated that the reliability of this questionnaire was high. Conclusion: With the availability of this self-assessment questionnaire, telehealth providers can perform a quick self-assessment on their telehealth systems. The assessment results may be used to identify possible vulnerabilities in telehealth systems and practice or demonstrate to patients the sufficient security and privacy protection to patients’ data.

Adjunctive mobile mental health apps to supplement mental health treatment have been growing in recent years given their ability to address treatment engagement barriers. However, few studies have explicitly examined how these mobile apps impact treatment engagement, and even fewer have investigated this topic through adolescents’ perspectives. To this end, we conducted semi-structured interviews with five adolescents who used an adjunctive mobile mental health app in combination with telehealth cognitive behavioral group therapy for social anxiety. Using a multidimensional framework of treatment engagement, we elicited their perspectives on how the app impacted their engagement in telehealth group therapy and gathered their suggestions for improving the app. Using a consensual qualitative research approach, we learned that adolescents felt the app increased their comfort with others in therapy and their expectations about the effectiveness of mental health apps. They also indicated that the app prepared them for in-session participation and facilitated out-of-session skills practice. Adolescents had valuable suggestions such as adding app features to facilitate social connectedness between group members and adding appointment reminders in the app. This preliminary study highlights implications for future adjunctive mobile mental health app developers and researchers to increase adolescents’ treatment engagement in mental health services.

Telehealth is a broad term used to describe the use of electronic or digital information and communications technologies to support clinical healthcare, patient and professional health related education, and public health and health administration. Telerehabilitation refers to the delivery of rehabilitation and habilitation services via information and communication technologies (ICT), also commonly referred to as” telehealth” technologies. Telerehabilitation services can include evaluation, assessment, monitoring, prevention, intervention, supervision, education, consultation, and coaching. Telerehabilitation services can be deployed across all patient populations and multiple healthcare settings including clinics, homes, schools, or community-based worksites. This document was adapted from the American Telemedicine Association’s (ATA) “A Blueprint for Telerehabilitation Guidelines” (2010) and reflects the current utilization of telerehabilitation services. It was developed collaboratively by members of the ATA Telerehabilitation Special Interest Group, with input and guidance from other practitioners in the field, strategic stakeholders, and ATA staff. Its purpose is to inform and assist practitioners in providing effective and secure services that are based on client needs, current empirical evidence, and available technologies. Rehabilitation professionals, in conjunction with professional associations and other organizations are encouraged to use this document as a resource for developing discipline-specific standards, guidelines, and practice requirements. Keywords: American Telemedicine Association, Habilitation, Rehabilitation, Telehealth, Telepractice

We evaluated the feasibility, safety, system usability, and intervention acceptability of Lung Transplant Go (LTGO), an 8-week in-home exercise intervention for lung transplant recipients using a telerehabilitation platform, and described changes in physical function and physical activity from baseline to post-intervention. The intervention was delivered to lung transplant recipients in their home via the Versatile and Integrated System for TeleRehabilitation (VISYTER). The intervention focused on aerobic and strengthening exercises tailored to baseline physical function. Participants improved walk distance (6-minute walk distance), balance (Berg Balance Scale), lower body strength (30-second chair stand test) and steps walked (SenseWear Armband®). No adverse events were reported. Participants rated the program highly positively in regard to the technology and intervention. The telerehabilitation exercise program was feasible, safe, and acceptable. Our findings provide preliminary support for the LTGO intervention to improve physical function and promote physical activity in lung transplant recipients.

A novel mobile health platform, Interactive Mobile Health and Rehabilitation (iMHere), is being developed to support wellness and self-management among people with chronic disabilities. The iMHere system currently includes a smartphone app with six modules for use by persons with disabilities and a web portal for use by medical and rehabilitation professionals or other support personnel. Our initial clinical research applying use of this system provides insight into the feasibility of employing iMHere in the development of self-management skills in young adults (ages 18-40 years) with spina bifida (Dicianno, Fairman, McCue, Parmanto, Yih, et al., 2015). This article is focused on describing the iterative design of the iMHere system including usability testing of both the app modules and clinician portal. Our pilot population of persons with spina bifida fostered the creation of a system appropriate for people with a wide variety of functional abilities and needs. As a result, the system is appropriate for use by persons with various disabilities and chronic conditions, not only spina bifida. In addition, the diversity of professionals and support personnel involved in the care of persons with spina bifida (SB) also enabled the design and implementation of the iMHere system to meet the needs of an interdisciplinary team of providers who treat various conditions. The iMHere system has the potential to foster communication and collaboration among members of an interdisciplinary healthcare team, including individuals with chronic conditions and disabilities, for client-centered approach to support self-management skills.

Current telehealth usability questionnaires are designed primarily for older technologies, where telehealth interaction is conducted over dedicated videoconferencing applications. However, telehealth services are increasingly conducted over computer-based systems that rely on commercial software and a user supplied computer interface. Therefore, a usability questionnaire that addresses the changes in telehealth service delivery and technology is needed. The Telehealth Usability Questionnaire (TUQ) was developed to evaluate the usability of telehealth implementation and services. This paper addresses: 1) the need for a new measure of telehealth usability, 2) the development of the TUQ, 3) intended uses for the TUQ, and 4) the reliability of the TUQ. Analyses indicate that the TUQ is a solid, robust, and versatile measure that can be used to measure the quality of the computer-based user interface and the quality of the telehealth interaction and services.

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The proliferation of advanced technologies led researchers within the Rehabilitation Engineering Research Center on Telerehabilitation (RERC-TR) to devise an integrated infrastructure for clinical services using the University of Pittsburgh (PITT) model. This model describes five required characteristics for a telerehabilitation (TR) infrastructure: openness, extensibility, scalability, cost-effectiveness, and security. The infrastructure is to deliver clinical services over distance to improve access to health services for people living in underserved or remote areas. The methodological approach to design, develop, and employ this infrastructure is explained and detailed for the remote wheelchair prescription project, a research task within the RERC-TR. The availability of this specific clinical service and personnel outside of metropolitan areas is limited due to the lack of specialty expertise and access to resources. The infrastructure is used to deliver expertise in wheeled mobility and seating through teleconsultation to remote clinics, and has been successfully deployed to five rural clinics in Western Pennsylvania. Keywords: Telerehabilitation, Information Management, Infrastructure Development Methodology, Videoconferencing, Online Portal, Database

Rehabilitation service providers in rural or underserved areas are often challenged in meeting the needs of their complex patients due to limited resources in their geographical area. Recruitment and retention of the rural clinical workforce are beset by the ongoing problems associated with limited continuing education opportunities, professional isolation, and the challenges inherent to coordinating rural community healthcare. People with disabilities who live in rural communities also face challenges accessing healthcare. Traveling long distances to a specialty clinic for necessary expertise is troublesome due to inadequate or unavailable transportation, disability specific limitations, and financial limitations. Distance and lack of access are just two threats to quality of care that now being addressed by the use of videoconferencing, information exchange, and other telecommunication technologies that facilitate telerehabilitation. This white paper illustrates and summarizes clinical and vocational applications of telerehabilitation. We provide definitions related to the fields of telemedicine, telehealth, and telerehabilitation, and consider the impetus for telerehabilitation. We review the telerehabilitation literature for assistive technology applications, pressure ulcer prevention, virtual reality applications, speech-language pathology applications, seating and wheeled mobility applications, vocational rehabilitation applications, and cost-effectiveness. We then discuss external telerehabilitation influencers, such as the positions of professional organizations. Finally, we summarize clinical and policy issues in a limited context appropriate to the scope of this paper. Keywords: Telerehabilitation, Telehealth,Telemedicine, Telepractice

The purpose of this study was to gather information regarding the receptivity of clinicians, caregivers and family members, and adults with spina bifida (SB) to the use of a mHealth application, iMobile Health and Rehabilitation (iMHere) system. Surveys were administered to end user groups in conjunction with a conference presentation at the Spina Bifida Association’s 38th Annual Conference. The survey results were obtained from a total of 107 respondents. Likert scale and qualitative results are provided in consideration of future application of the iMHere system in clinical practice. The results of this survey indicate respondents were receptive and supportive with regard to adopting such a system for personal and professional use. Challenges likely to be encountered in the introduction of the iMHere system are also revealed and discussed.