Systematic Review of Mobile Health Applications in Rehabilitation

Usability Assessment Methods for Mobile Apps for Physical Rehabilitation: Umbrella Review

BACKGROUND

Usability has been touted as one determiner of success of mobile health (mHealth) interventions. Multiple systematic reviews of usability assessment approaches for different mHealth solutions for physical rehabilitation are available. However, there is a lack of synthesis in this portion of the literature, which results in clinicians and developers devoting a significant amount of time and effort in analyzing and summarizing a large body of systematic reviews.

OBJECTIVE

This study aims to summarize systematic reviews examining usability assessment instruments, or measurements tools, in mHealth interventions including physical rehabilitation.

METHODS

An umbrella review was conducted according to a published registered protocol. A topic-based search of PubMed, Cochrane, IEEE Xplore, Epistemonikos, Web of Science, and CINAHL Complete was conducted from January 2015 to April 2023 for systematic reviews investigating usability assessment instruments in mHealth interventions including physical exercise rehabilitation. Eligibility screening included date, language, participant, and article type. Data extraction and assessment of the methodological quality (AMSTAR 2 [A Measurement Tool to Assess Systematic Reviews 2]) was completed and tabulated for synthesis.

RESULTS

A total of 12 systematic reviews were included, of which 3 (25%) did not refer to any theoretical usability framework and the remaining (n=9, 75%) most commonly referenced the ISO framework. The sample referenced a total of 32 usability assessment instruments and 66 custom-made, as well as hybrid, instruments. Information on psychometric properties was included for 9 (28%) instruments with satisfactory internal consistency and structural validity. A lack of reliability, responsiveness, and cross-cultural validity data was found. The methodological quality of the systematic reviews was limited, with 8 (67%) studies displaying 2 or more critical weaknesses.

CONCLUSIONS

There is significant diversity in the usability assessment of mHealth for rehabilitation, and a link to theoretical models is often lacking. There is widespread use of custom-made instruments, and preexisting instruments often do not display sufficient psychometric strength. As a result, existing mHealth usability evaluations are difficult to compare. It is proposed that multimethod usability assessment is used and that, in the selection of usability assessment instruments, there is a focus on explicit reference to their theoretical underpinning and acceptable psychometric properties. This could be facilitated by a closer collaboration between researchers, developers, and clinicians throughout the phases of mHealth tool development.

TRIAL REGISTRATION

PROSPERO CRD42022338785; https://www.crd.york.ac.uk/prospero/#recordDetails.

Development and Use of Mobile Messaging for Individuals With Musculoskeletal Pain Conditions: Scoping Review

BACKGROUND

Population studies show that musculoskeletal conditions are a leading contributor to the total burden of healthy life lost, second only to cancer and with a similar burden to cardiovascular disease. Prioritizing the delivery of effective treatments is necessary, and with the ubiquity of consumer smart devices, the use of digital health interventions is increasing. Messaging is popular and easy to use and has been studied for a range of health-related uses, including health promotion, encouragement of behavior change, and monitoring of disease progression. It may have a useful role to play in the management and self-management of musculoskeletal conditions.

OBJECTIVE

Previous reviews on the use of messaging for people with musculoskeletal conditions have focused on synthesizing evidence of effectiveness from randomized controlled trials. In this review, our objective was to map the musculoskeletal messaging literature more broadly to identify information that may inform the design of future messaging interventions and summarize the current evidence of efficacy, effectiveness, and economics.

METHODS

Following a prepublished protocol developed using the Joanna Briggs Institute Manual for Evidence Synthesis, we conducted a comprehensive scoping review of the literature (2010-2022; sources: PubMed, CINAHL, Embase, and PsycINFO) related to SMS text messaging and app-based messaging for people with musculoskeletal conditions. We described our findings using tables, plots, and a narrative summary.

RESULTS

We identified a total of 8328 papers for screening, of which 50 (0.6%) were included in this review (3/50, 6% previous reviews and 47/50, 94% papers describing 40 primary studies). Rheumatic diseases accounted for the largest proportion of the included primary studies (19/40, 48%), followed by studies on multiple musculoskeletal conditions or pain sites (10/40, 25%), back pain (9/40, 23%), neck pain (1/40, 3%), and "other" (1/40, 3%). Most studies (33/40, 83%) described interventions intended to promote positive behavior change, typically by encouraging increased physical activity and exercise. The studies evaluated a range of outcomes, including pain, function, quality of life, and medication adherence. Overall, the results either favored messaging interventions or had equivocal outcomes. While the theoretical underpinnings of the interventions were generally well described, only 4% (2/47) of the papers provided comprehensive descriptions of the messaging intervention design and development process. We found no relevant economic evaluations.

CONCLUSIONS

Messaging has been used for the care and self-management of a range of musculoskeletal conditions with generally favorable outcomes reported. However, with few exceptions, design considerations are poorly described in the literature. Further work is needed to understand and disseminate information about messaging content and message delivery characteristics, such as timing and frequency specifically for people with musculoskeletal conditions. Similarly, further work is needed to understand the economic effects of messaging and practical considerations related to implementation and sustainability.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2021-048964.

Determinants of physical activity in newly diagnosed obstructive sleep apnea patients: testing the health action process approach

This study aims to identify the determinants associated with physical activity (PA) behavior in newly diagnosed obstructive sleep apnea (OSA) patients by applying the Health Action Process Approach (HAPA) with a longitudinal design. Anthropometric and clinical (OSA severity, subjective somnolence, use of continuous positive airway pressure (CPAP)) variables, the determinants of physical activity specified in the HAPA (motivational self-efficacy, outcome expectancies, risk perception, intention, maintenance self-efficacy, action planning, coping planning, social support), as well as physical activity behavior were assessed using a longitudinal (T1 and T2) design in a sample of 57 OSA patients in routine care. Applying regression analyses, regarding the motivation phase, the amount of explained variance in intention was 77% and 39% of the variance in physical activity. In the motivational phase, motivational self-efficacy, risk perception and outcome expectancies were associated with intention. In the volitional phase, physical activity at T1 and social support (family) were related with physical activity at T2. In conclusion, the assumptions of HAPA were partially found in the context of newly diagnosed OSA patients. This study provided additional evidence regarding the role of motivational self-efficacy, outcome expectancies and risk perception during motivational phase, and highlighted the important role of social support from the family in the PA in this population.

Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities

Physical rehabilitation and exercise training have emerged as promising solutions for improving health, restoring function, and preserving quality of life in populations that face disparate health challenges related to disability. Despite the immense potential for rehabilitation and exercise to help people with disabilities live longer, healthier, and more independent lives, people with disabilities can experience physical, psychosocial, environmental, and economic barriers that limit their ability to participate in rehabilitation, exercise, and other physical activities. Together, these barriers contribute to health inequities in people with disabilities, by disproportionately limiting their ability to participate in health-promoting physical activities, relative to people without disabilities. Therefore, there is great need for research and innovation focusing on the development of strategies to expand accessibility and promote participation in rehabilitation and exercise programs for people with disabilities. Here, we discuss how cutting-edge technologies related to telecommunications, wearables, virtual and augmented reality, artificial intelligence, and cloud computing are providing new opportunities to improve accessibility in rehabilitation and exercise for people with disabilities. In addition, we highlight new frontiers in digital health technology and emerging lines of scientific research that will shape the future of precision care strategies for people with disabilities.

Designing an Egocentric Video-Based Dashboard to Report Hand Performance Measures for Outpatient Rehabilitation of Cervical Spinal Cord Injury

Background

Functional use of the upper extremities (UEs) is a top recovery priority for individuals with cervical spinal cord injury (cSCI), but the inability to monitor recovery at home and limitations in hand function outcome measures impede optimal recovery.

Objectives

We developed a framework using wearable cameras to monitor hand use at home and aimed to identify the best way to report information to clinicians.

Methods

A dashboard was iteratively developed with clinician (n = 7) input through focus groups and interviews, creating low-fidelity prototypes based on recurring feedback until no new information emerged. Affinity diagramming was used to identify themes and subthemes from interview data. User stories were developed and mapped to specific features to create a high-fidelity prototype.

Results

Useful elements identified for a dashboard reporting hand performance included summaries to interpret graphs, a breakdown of hand posture and activity to provide context, video snippets to qualitatively view hand use at home, patient notes to understand patient satisfaction or struggles, and time series graphing of metrics to measure trends over time.

Conclusion

Involving end-users in the design process and breaking down user requirements into user stories helped identify necessary interface elements for reporting hand performance metrics to clinicians. Clinicians recognized the dashboard's potential to monitor rehabilitation progress, provide feedback on hand use, and track progress over time. Concerns were raised about the implementation into clinical practice, therefore further inquiry is needed to determine the tool's feasibility and usefulness in clinical practice for individuals with UE impairments.

Multimodal Chiropractic Management of a Postsurgical Sternoclavicular Injury Utilizing Gamified Rehabilitation: A Case Report

Objective

The purpose of this study was to describe how gamification was incorporated into postoperative rehabilitation of a patient recovering from a sternoclavicular dislocation.

Clinical Features

A 23-year-old man sought chiropractic care from an academic chiropractic clinic for persistent right-sided, sternoclavicular joint, moderate-to-severe pain that was exacerbated with shoulder movements and overhead activities. His shoulder was treated previously with reconstructive surgery and a 6-week trial of physical therapy; however, he reported minimal improvement in his pain, and his functional ability was suboptimal.

Intervention and Outcome

Multimodal chiropractic treatment consisted of manual therapy in conjunction with active rehabilitation. The rehabilitation program incorporated gamification principles, such as competition, point scoring, and task focus. After 8 treatments, a clinically significant reduction in his upper extremity functional index score and numerical pain rating was observed.

Conclusion

The patient was managed using a gamified approach to postsurgical sternoclavicular joint rehabilitation and responded positively. Chiropractors may consider including gamified, multimodal care for patients with postoperative musculoskeletal concerns.

Early postoperative step count and walking time have greater impact on lower limb fracture outcomes than load-bearing metrics

INTRODUCTION

Weight-bearing protocols for rehabilitation of lower extremity fractures are the gold standard despite not being data-driven. Additionally, current protocols are focused on the amount of weight placed on the limb, negating other patient rehabilitation behaviors that may contribute to outcomes. Wearable sensors can provide insight into multiple aspects of patient behavior through longitudinal monitoring. This study aimed to understand the relationship between patient behavior and rehabilitation outcomes using wearable sensors to identify the metrics of patient rehabilitation behavior that have a positive effect on 1-year rehabilitation outcomes.

METHODS

Prospective observational study on 42 closed ankle and tibial fracture patients. Rehabilitation behavior was monitored continuously between 2 and 6 weeks post-operative using a gait monitoring insole. Metrics describing patient rehabilitation behavior, including step count, walking time, cadence, and body weight per step, were compared between patient groups of excellent and average rehabilitation outcomes, as defined by the 1-year Patient Reported Outcome Measure Physical Function t-score (PROMIS PF). A Fuzzy Inference System (FIS) was used to rank metrics based on their impact on patient outcomes. Additionally, correlation coefficients were calculated between patient characteristics and principal components of the behavior metrics.

RESULTS

Twenty-two patients had complete insole data sets, and 17 of which had 1-year PROMIS PF scores (33.7 ± 14.5 years of age, 13 female, 9 in Excellent group, 8 in Average group). Step count had the highest impact ranking (0.817), while body weight per step had a low impact ranking (0.309). No significant correlation coefficients were found between patient or injury characteristics and behavior principal components. General patient rehabilitation behavior was described through cadence (mean of 71.0 steps/min) and step count (logarithmic distribution with only ten days exceeding 5,000 steps/day).

CONCLUSION

Step count and walking time had a greater impact on 1-year outcomes than body weight per step or cadence. The results suggest that increased activity may improve 1-year outcomes for patients with lower extremity fractures. The use of more accessible devices, such as smart watches with step counters combined with patient reported outcome measures may provide more valuable insights into patient rehabilitation behaviors and their effect on rehabilitation outcomes.

Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review

Central nervous system diseases (CNSDs) lead to significant disability worldwide. Mobile app interventions have recently shown the potential to facilitate monitoring and medical management of patients with CNSDs. In this direction, the characteristics of the mobile apps used in research studies and their level of clinical effectiveness need to be explored in order to advance the multidisciplinary research required in the field of mobile app interventions for CNSDs. A systematic review of mobile app interventions for three major CNSDs, i.e., Parkinson's disease (PD), multiple sclerosis (MS), and stroke, which impose significant burden on people and health care systems around the globe, is presented. A literature search in the bibliographic databases of PubMed and Scopus was performed. Identified studies were assessed in terms of quality, and synthesized according to target disease, mobile app characteristics, study design and outcomes. Overall, 21 studies were included in the review. A total of 3 studies targeted PD (14%), 4 studies targeted MS (19%), and 14 studies targeted stroke (67%). Most studies presented a weak-to-moderate methodological quality. Study samples were small, with 15 studies (71%) including less than 50 participants, and only 4 studies (19%) reporting a study duration of 6 months or more. The majority of the mobile apps focused on exercise and physical rehabilitation. In total, 16 studies (76%) reported positive outcomes related to physical activity and motor function, cognition, quality of life, and education, whereas 5 studies (24%) clearly reported no difference compared to usual care. Mobile app interventions are promising to improve outcomes concerning patient's physical activity, motor ability, cognition, quality of life and education for patients with PD, MS, and Stroke. However, rigorous studies are required to demonstrate robust evidence of their clinical effectiveness.

Use of Technologies in the Therapy of Social Cognition Deficits in Neurological and Mental Diseases: A Systematic Review

Objective: This article systematically reviews the effects of technology-based (TB) treatments on impaired social cognition (SC) in neurological and mental disorders. Methods: Strictly adhering to the PRISMA guidelines, a systematic search was carried out in PsycINFO, PubMed, and Web of Science (last search: April 22, 2021) to identify studies that, implementing a control group design, evaluated TB treatments targeting deficits in emotion recognition, Theory of Mind (ToM) and social behavior in adult patients with nondevelopmental and nonprogressive neurological or mental disorders. Risk of bias was assessed using the PEDro Scale, certainty assessment followed the GRADE approach. Results: Sixteen studies involving 857 patients, all focusing on psychotic disorders, were retrieved. The most pronounced effects were observed concerning emotion recognition with all studies revealing overall improvements. Regarding ToM and social behavior, results were mixed. However, the number of studies including outcome measures for these domains, is significantly lower compared to the domain of emotion recognition, limiting the validity of the results. Risk of bias and certainty assessment revealed further limitations of evidence. Conclusion: TB treatment achieves positive effects especially with regard to emotion recognition impairments, at least for patients with schizophrenia. Future research should expand the evaluation of TB training of other SC domains, ought to be carried out in more diverse patient populations, rely on different devices, and include follow-up measurements.

Effectiveness of Telerehabilitation Interventions for Self-management of Tinnitus: Systematic Review

BACKGROUND

Tinnitus is a highly prevalent symptom affecting 10%-20% of the adult population. Most patients with tinnitus have chronic tinnitus, which can directly or indirectly disrupt their daily life and negatively affect the health-related quality of life. Therefore, patients with tinnitus are frequently in need of costly and time-consuming treatments. As an answer, telerehabilitation interventions are on a rise to promote self-management in patients with tinnitus and reduce their dependency on in-person care.

OBJECTIVE

This systematic review aimed to provide an overview of the research concerning the effectiveness of telerehabilitation interventions for self-management of tinnitus.

METHODS

This systematic review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were eligible for inclusion if study participants were adult patients with complaints of primary subjective tinnitus and the study intervention comprised any possible telerehabilitation form for the self-management of tinnitus complaints. A search for eligible studies was conducted on PubMed, ScienceDirect, Scopus, Web of Science, and Cochrane Library. The Cochrane Risk of Bias 2 tool was used to the assess risk of bias.

RESULTS

In total, 29 articles were found eligible, and of these, 5 (17%) studied multiple telerehabilitation forms. Internet-based cognitive behavioral treatment with guidance by a psychologist or audiologist was examined in 17 studies (n=1767), internet-based cognitive behavioral treatment without guidance was examined in 4 studies (n=940), self-help manuals were examined in 1 study (n=72), technological self-help devices were examined in 2 studies (n=82), smartphone apps were examined in 8 studies (n=284), and other internet-based interventions were examined in 2 studies (n=130). These rehabilitation categories were proven to be effective in decreasing tinnitus severity and relieving tinnitus distress as measured by tinnitus questionnaires such as Tinnitus Functional Index, Tinnitus Handicap Inventory, or Tinnitus Reactions Questionnaire. However, dropout rates were often high (range 4%-71.4%). All studies reported between some concerns and high concerns of risk of bias, resulting in low to moderate certainty levels.

CONCLUSIONS

Overall, there is low to moderate quality evidence that telerehabilitation interventions effectively reduce tinnitus severity and distress. These interventions form a possible tool to improve the self-management capacities of the patient and the accessibility of tinnitus care as a replacement or an addition to in-person care. Nevertheless, barriers such as lack of time, engagement, motivation, and openness of the patient causing high dropout should be considered.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42021285450; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=285450.

An individualized mobile health intervention to promote physical activity in adults with obstructive sleep apnea: An intervention mapping approach

Objective

Combining continuous positive airway pressure with physical activity (PA) might be a promising strategy to treat obstructive sleep apnea (OSA). This article describes how intervention mapping (IM) can guide the development, content, and mechanisms of action of a mobile application to promote PA in adults with OSA.

Methods

To develop the program, the IM approach was followed. This article presents the first three steps of IM to develop a mixed intervention (with interventionists and a digital application) aiming to: (1) assess patients' health problems and needs in a literature review to determine their expectations and perceived facilitators and barriers to PA behavior change and thus select the determinants of behavior; (2) formulate the expected intervention outcomes and objectives to be met to achieve the overall program goals; and (3) select and implement the behavior change techniques (BCTs) to achieve the change objectives.

Results

The literature review identified the relevant determinants (e.g., self-efficacy, coping, planning, and habit) of PA behavior using the health action process approach and multiprocess action control. These results were used to specify the program outcomes for PA adapted to physical, psychological, and social parameters. Overall, 11 performance objectives and 30 change objectives were defined. Lastly, BCTs and practical applications were identified.

Conclusions

The study provides a theoretical and methodological basis for researchers and practitioners given the current paucity of evidence-based PA interventions for adults with OSA. It addresses the lack of BCTs (framing and prompts/cue techniques) and meaningful behavioral determinants (identity and habit) in most interventions.

Patient experience using digital therapy "Vigo" for stroke patient recovery: a qualitative descriptive study

BACKGROUND

The digital assistant "Vigo" is a computer-generated artificial intelligence-based application that serves as a digital assistant to a stroke patient and his family. With its conversational chatbot and gamification elements it counsels, educates, and trains the stroke patient and patient's family on stroke, rehabilitation, care, and other related issues.

AIM

This study describes insights about The digital assitant "Vigo" usability from a patients' perspective.

METHODS

Twelve patients tested the application at their home environment. Three semi-structured interviews were conducted with each participant to obtain information on the usability of the application. Deductive thematic analyses were used to analyze trancripts.

RESULTS

Participants expressed their opinions on music, pictures, video and audio files, chat options, layout, text, name of application and stand that is used for placement of devices on which "Vigo" is installed on. All participants generally evaluated application as transparent, understandable, and handy. The overall design of the application was rated as good. Participants were mostly unsatisfied with difficulty level and diversity of exercises.

CONCLUSIONS

Participants had a positive attitude towards using tablet tehchnologies in their home environment. Users of digital assistant "Vigo" acknowledged its ability to support, give educational information and increase participation in therapeutic activities.Implications for rehabilitationTablet application can support, give educational information, and increase participation in therapeutic activities for persons after stroke.As home-based rehabilitation tool, the content of the application must be simple, flexible, and diverse, to face the challenges of meeting each individual's goals, functional needs and abilities.

Feasibility of Problem-Solving Training During Inpatient Rehabilitation in Patients With Stroke

IMPORTANCE

Stroke survivors report feeling unprepared to manage challenges that arise during the transition from hospital to home. Cultivating problem-solving skills before discharge may better prepare patients for the transition home.

OBJECTIVE

To determine the feasibility of a protocol to deliver Problem-Solving Training (PST) to stroke survivors during inpatient rehabilitation to increase goal achievement.

DESIGN

Single-group feasibility study.

SETTING

Academic and county hospital inpatient rehabilitation units.

PARTICIPANTS

Adult patients with stroke and planned discharge home.

INTERVENTION

Up to six PST sessions over 2 to 3 wk followed by 3 mo of mobile health boosters.

RESULTS

Of 17 eligible participants, 15 consented and 11 completed three or more PST sessions. Six participants used electronic boosters, achieving at least one goal postdischarge. Participants reported high satisfaction with PST (Client Satisfaction Questionnaire-8 M score = 29.3, SD = 4.4; range = 8-32), moderate depression at baseline (eight-item Patient Health Questionnaire [PHQ-8] score, M = 11.0, SD = 6.1; range = 0-27), mild depression at 3 mo postdischarge (PHQ-8 score, M = 8.3, SD = 5.5), moderately high self-efficacy at baseline (General Self-Efficacy Scale [GSE] score, M = 31.1, SD = 7.3; range = 10-40), and a self-efficacy increase at 3 mo postdischarge (GSE score, M = 34.1, SD = 4.2).

CONCLUSIONS AND RELEVANCE

PST among patients with stroke during inpatient rehabilitation was feasible, and participants demonstrated improvements in clinical outcomes and goal attainment. Barriers to participation and adherence should be addressed in future studies. What This Article Adds: Teaching patients problem-solving skills early after a stroke using a metacognitive strategy is feasible and may decrease depression and increase self-efficacy while fostering independent goal setting and problem solving.

An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors

The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, and stored. The authors of this paper designed and implemented an integrated personal health data management system, which considers data-driven software and hardware sensors, comprehensive data privacy techniques, and machine-learning-based algorithmic models. It was determined that there are very few relevant and complete surveys concerning this specific problem. Therefore, the current scientific research was considered, and this paper comprehensively analyzes the importance of deep learning techniques that are applied to the overall management of data collected by data-driven soft sensors. This survey considers aspects that are related to demographics, health and body parameters, and human activity and behaviour pattern detection. Additionally, the relatively complex problem of designing and implementing data privacy mechanisms, while ensuring efficient data access, is also discussed, and the relevant metrics are presented. The paper concludes by presenting the most important open research questions and challenges. The paper provides a comprehensive and thorough scientific literature survey, which is useful for any researcher or practitioner in the scope of data-driven soft sensors and privacy techniques, in relation to the relevant machine-learning-based models.

A Mobile Phone Text Messaging Intervention to Manage Fatigue for People With Multiple Sclerosis, Spinal Cord Injury, and Stroke: Development and Usability Testing

BACKGROUND

Fatigue significantly affects daily functioning in persons with disabilities. Fatigue management can be challenging, and the information provided during routine physician visits to manage fatigue can be overwhelming. One way to address fatigue is to increase knowledge, skills, and confidence for self-management (ie, patient activation). Self-management programs have shown promising effects in targeting fatigue in persons with disabilities. However, satisfaction with self-management programs is low for persons with disabilities, and tailoring interventions to personalized needs has been recommended. SMS text messaging is increasingly being used to implement health behavior change interventions in a person's natural environment. Little has been done to link mobile health approaches with patient activation and self-management to address fatigue in persons with disabilities.

OBJECTIVE

This study aimed to develop and test a mobile phone-based fatigue self-management SMS text messaging intervention targeting patient activation in 3 groups of persons with disabilities: persons with multiple sclerosis, persons who had a stroke, and persons with a spinal cord injury.

METHODS

We used evidence-based resources and input from a consumer advisory board (CAB; composed of 2 participants from each of the 3 disability groups) and a neurologist to develop the intervention. The study was conducted using a 4-step process: development of the initial SMS text messaging library and categorization of the content into 9 content areas, review and modification of the SMS text messages by the neurologist and CAB, integration of the content library into a digital platform, and utility testing by CAB members.

RESULTS

A total of 6 CAB participants rated SMS text messages covering 9 domain areas of fatigue self-management with good clarity (mean ratings=3.5-5.0 out of 5) and relevance (mean ratings=3.2-5.0 out of 5). Overall, SMS text messaging content was reported by CAB participants as helpful, clear, and well suited for a mobile health intervention. The CAB reached consensus on the time of day that SMS text messages should be sent (morning) and their frequency (once per day). This feedback led the research team to narrow down the program to deliver 48 SMS text messages, 1 per day, Monday through Thursday only, a total of 4 SMS text messages per week, over a 12-week period. The final set of SMS text messages was programmed into a digital platform with a predefined delivery schedule. The usability of the intervention was high, with 55 (83%) out of 66 responses endorsing the highest rating.

CONCLUSIONS

This study demonstrates a step-by-step process for developing a fatigue self-management SMS text messaging intervention for persons with disabilities. For this population, whose access to health services is often limited, this intervention provides an alternative delivery model to increase access to fatigue information and deliver content that aligns with the person's needs.

A roadmap to reduce information inequities in disability with digital health and natural language processing

People with disabilities disproportionately experience negative health outcomes. Purposeful analysis of information on all aspects of the experience of disability across individuals and populations can guide interventions to reduce health inequities in care and outcomes. Such an analysis requires more holistic information on individual function, precursors and predictors, and environmental and personal factors than is systematically collected in current practice. We identify 3 key information barriers to more equitable information: (1) a lack of information on contextual factors that affect a person's experience of function; (2) underemphasis of the patient's voice, perspective, and goals in the electronic health record; and (3) a lack of standardized locations in the electronic health record to record observations of function and context. Through analysis of rehabilitation data, we have identified ways to mitigate these barriers through the development of digital health technologies to better capture and analyze information about the experience of function. We propose 3 directions for future research on using digital health technologies, particularly natural language processing (NLP), to facilitate capturing a more holistic picture of a patient's unique experience: (1) analyzing existing information on function in free text documentation; (2) developing new NLP-driven methods to collect information on contextual factors; and (3) collecting and analyzing patient-reported descriptions of personal perceptions and goals. Multidisciplinary collaboration between rehabilitation experts and data scientists to advance these research directions will yield practical technologies to help reduce inequities and improve care for all populations.

Effect of a mHealth exercise intervention compared with supervised exercise therapy in osteoarthritis management: protocol of the DigiOA trial

INTRODUCTION

Soaring prevalence of hip and knee osteoarthritis (OA) inflicts high costs on the healthcare system. A further rise in the OA incidence is expected, generating increased demand of care potentially challenging accessibility and threatening to overwhelm the healthcare system. Innovative solutions that may improve accessibility to recommended OA care for patients in primary care and maintain healthcare sustainability are warranted. Digitalising home exercise therapy may be one such solution. The primary aim of this study is to evaluate the effectiveness of a mobile health app providing digitalised home exercises, compared with supervised exercise therapy in patients with OA. Second, we will evaluate the cost-efficiency of the intervention and explore potential differences in outcome and adherence to exercises in the experimental treatment group.

METHODS AND ANALYSIS

A two-armed non-inferiority randomised controlled trial will be conducted. In total, 156 patients with hip and/or knee OA will be recruited from physiotherapy clinics in primary care in Norway. Following patient education, patients will be randomised to either 6 weeks of standard treatment (2 weekly sessions of supervised exercise therapy) or experimental treatment (home exercises via the Virtual Training (VT) app). Primary outcome is the proportion of Outcome Measures in Rheumatology-Osteoarthritis Research Society International (OMERACT-OARSI) responders at 6 weeks. Secondary outcomes include physical performance, patient-reported outcomes related to pain, fatigue, disease activity, physical function, mental health, health related quality of life, self-efficacy, utilisation of healthcare services and medication, digital competence and use of apps.

ETHICS AND DISSEMINATION

Patients will sign an informed consent form before participating in the trial. Approval has been granted by the Regional Ethics Committee (201105) and Data Protection Officer at Diakonhjemmet Hospital (00221). Patient research partners will contribute in all parts of the study.

TRIAL REGISTRATION NUMBER

NCT04767854.

Standardization of the assessment process within telerehabilitation in chronic diseases: a scoping meta-review

Background

Telerehabilitation (TR) interventions are receiving increasing attention. They have been evaluated in various scientific areas through systematic reviews. However, there is a lack of data on how to standardize assessment and report on their domains to guide researchers across studies and bring together the best evidence to assess TR for chronic diseases.

Aims and objectives

The aim of this study was to identify domains of assessment in TR and to qualitatively and quantitatively analyze how and when they are examined to gain an overview of assessment in chronic disease.

Methods

A scoping meta-review was carried out on 9 databases and gray literature from 2009 to 2019. The keyword search strategy was based on "telerehabilitation", “evaluation", “chronic disease" and their synonyms. All articles were subjected to qualitative analysis using the Health Technology Assessment (HTA) Core Model prior to further analysis and narrative synthesis.

Results

Among the 7412 identified articles, 80 studies met the inclusion criteria and addressed at least one of the noncommunicable diseases (NCD) categories of cardiovascular disease (cardiovascular accidents), cancer, chronic respiratory disease, diabetes, and obesity. Regarding the domains of assessment, the most frequently occurring were “social aspect” (n = 63, 79%) (e.g., effects on behavioral changes) and “clinical efficacy” (n = 53, 66%), and the least frequently occurring was “safety aspects” (n = 2, 3%). We also identified the phases of TR in which the assessment was conducted and found that it most commonly occurred in the pilot study and randomized trial phases and least commonly occurred in the design, pretest, and post-implementation phases.

Conclusions

Through the HTA model, this scoping meta-review highlighted 10 assessment domains which have not been studied with the same degree of interest in the recent literature. We showed that each of these assessment domains could appear at different phases of TR development and proposed a new cross-disciplinary and comprehensive method for assessing TR interventions. Future studies will benefit from approaches that leverage the best evidence regarding the assessment of TR, and it will be interesting to extend this assessment framework to other chronic diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08370-y.

Mobile health technologies for the management of spine disorders: A systematic review of mHealth applications in Brazil

BACKGROUND

Spine disorders are conditions that affect a growing number of individuals, and mobile health (mHealth) applications (apps) offer potential to assist the self-management of these conditions.

OBJECTIVES

To perform a systematic review of the availability of mHealth apps for patients with spine disorders at Brazilian online stores and evaluate the apps in terms of engagement, user interface, experience, and quality of the information.

DESIGN

Systematic review.

METHOD

A search for spine disorders mHealth apps from the Google Play Store and AppStore in Brazil was performed by two independent reviewers on June 2021. Only smartphone apps in Brazilian Portuguese directed at spine disorders that provided information about education, counseling, exercise, or monitoring of patient health were included. The quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS).

RESULTS

Of the 2775 mHealth apps found, 10 were eligible for inclusion. All apps offered exercise programs. Three apps also offered tools to track patient-reported symptoms, nutritional orientation, or educational content in addition to the exercise program. Using MARS, the apps scored poorly in terms of quality, with an overall mean score ±standard deviation of 2.75 ± 0.63 on a scale of 1-5 points. Most apps scored poorly for credibility, user interface, and engagement.

CONCLUSIONS

The mHealth apps for spine disorders currently available in Brazil are of poor quality and limited functionality. Effective collaboration between industry and researchers is needed to develop better user-centered mHealth apps that can empower patients with these conditions.

Encouraging People with Spinal Cord Injury to Take Part in Physical Activity in the COVID-19 Epidemic through the mHealth ParaSportAPP

BACKGROUND

Although mHealth tools have great potential for health interventions, few experimental studies report on their use by people with spinal cord injuries in physical activity.

OBJECTIVE

The main objective of this study was to analyze the effect of the ParaSportAPP on different physical and psychological variables in people with paraplegia.

METHODS

Fourteen of these subjects made up the final sample. All the participants performed two pre-tests (control period) and a post-test with 8 months between the evaluations (COVID-19 broke out between pre-test 2 and the post-test). The ParaSportAPP was installed on their smartphones when they performed pre-test 2. The same tests were performed in the same order in all the evaluations: (i) the questionnaires PASIPD, HADS, RS-25; SCIM III and AQoL-8D, (ii) respiratory muscle strength, (iii) spirometry and (iv) cardiopulmonary exercise test.

RESULTS

The results showed no differences in any of the variables studied between the measurement times.

CONCLUSIONS

Although none of the variables experienced improvements, the ParaSportAPP mobile application was able to lessen the impact of the pandemic on the variables studied.

Advanced Analysis of 3D Kinect Data: Supervised Classification of Facial Nerve Function via Parallel Convolutional Neural Networks

In this paper, we designed a methodology to classify facial nerve function after head and neck surgery. It is important to be able to observe the rehabilitation process objectively after a specific brain surgery, when patients are often affected by face palsy. The dataset that is used for classification problems in this study only contains 236 measurements of 127 patients of complex observations using the most commonly used House–Brackmann (HB) scale, which is based on the subjective opinion of the physician. Although there are several traditional evaluation methods for measuring facial paralysis, they still suffer from ignoring facial movement information. This plays an important role in the analysis of facial paralysis and limits the selection of useful facial features for the evaluation of facial paralysis. In this paper, we present a triple-path convolutional neural network (TPCNN) to evaluate the problem of mimetic muscle rehabilitation, which is observed by a Kinect stereovision camera. A system consisting of three modules for facial landmark measure computation and facial paralysis classification based on a parallel convolutional neural network structure is used to quantitatively assess the classification of facial nerve paralysis by considering facial features based on the region and the temporal variation of facial landmark sequences. The proposed deep network analyzes both the global and local facial movement features of a patient’s face. These extracted high-level representations are then fused for the final evaluation of facial paralysis. The experimental results have verified the better performance of TPCNN compared to state-of-the-art deep learning networks.

A Tailored Music-Motor Therapy and Real-Time Biofeedback Mobile Phone App (‘GotRhythm’) to Promote Rehabilitation Following Stroke: A Pilot Study

Background:

Stroke persists as an important cause of long-term disability world-wide with the need for rehabilitation strategies to facilitate plasticity and improve motor function in stroke survivors. Rhythm-based interventions can improve motor function in clinical populations. This study tested a novel music-motor software application ‘GotRhythm’ on motor function after stroke.

Methods:

Participants were 22 stroke survivors undergoing inpatient rehabilitation in a subacute stroke ward. Participants were randomised to the GotRhythm intervention (combining individualised music and augmented auditory feedback along with wearable sensors to deliver a personalised rhythmic auditory stimulation training protocol) or usual care. Intervention group participants were offered 6-weeks of the GotRhythm intervention, consisting of a supervised 20-minute music-motor therapy session using GotRhythm conducted 3 times a week for 6 weeks. The primary feasibility outcomes were adherence to the intervention and physical function (change in the Fugl-Meyer Assessment of Motor Recovery score) measured at baseline, after 3-weeks and at end of the intervention period (6-weeks).

Results:

Three of 10 participants randomised to the intervention did not receive any of the GotRhythym music-motor therapy. Of the remaining 7 intervention group participants, only 5 completed the 3-week mid-intervention assessment and only 2 completed the 6-week post-intervention assessment. Participants who used the intervention completed 5 (IQR 4,7) sessions with total ‘dose’ of the intervention of 70 (40, 201) minutes.

Conclusion:

Overall, adherence to the intervention was poor, highlighting that application of technology assisted music-based interventions for stroke survivors in clinical environments is challenging along with usual care, recovery, and the additional clinical load.

Influence of Core-Stability Exercises Guided by a Telerehabilitation App on Trunk Performance, Balance and Gait Performance in Chronic Stroke Survivors: A Preliminary Randomized Controlled Trial

Stroke is one of the main causes of disability. Telerehabilitation could face the growing demand and a good strategy for post-stroke rehabilitation. The aim of this study is to examine the possible effects of therapeutic exercises performed by an App on trunk control, balance, and gait in stroke survivors. A preliminary 12-week randomized controlled trial was developed. Thirty chronic stroke survivors were randomly allocated into two groups. Both groups performed conventional physiotherapy, in addition to, the experimental group (EG) had access to a telerehabilitation App to guide home-based core-stability exercises (CSE). Trunk performance was measured with the Spanish-Trunk Impairment Scale (S-TIS 2.0) and Spanish-Function in Sitting Test. Balance and gait were measured with Spanish-Postural Assessment Scale for Stroke patient, Berg Balance Scale and an accelerometer system. In EG was observed an improvement of 2.76 points in S-TIS 2.0 (p = 0.001). Small differences were observed in balance and gait. Adherence to the use of the App was low. CSE guided by a telerehabilitation App, combined with conventional physiotherapy, seem to improve trunk function and sitting balance in chronic post-stroke. Active participation in the rehabilitation process should be increased among stroke survivors. Further confirmatory studies are necessary with a large sample size.

Assessment of dual-tasking during a dynamic balance task using a smartphone app: a pilot study

[Purpose] To assess if the instrumented Timed Up and Go (iTUG) task score calculated with an iPhone application can detect gait changes under dual-tasking conditions. [Participants and Methods] Twenty participants (age 38.30 ± 12.54, 12 females) were asked to complete the TUG as a single task and under two dual-tasking conditions: 1) verbal fluency and 2) mental calculation. We used a smartphone, stopwatch, digital camera, and wearable sensor to calculate the dependent variables which included time, step count, gait speed, and iTUG score and, the dual-tasking cost (DTC) of those variables. We used Friedman analyses of variance and Wilcoxon tests for statistical analyses. [Results] the iTUG score, step count, gait speed, and the time measured by the stopwatch and wearable sensor differed significantly for all tasks, but the smartphone time did not. [Conclusion] We conclude that the iTUG score could be used as a sensitive measure for identifying gait changes under dual-tasking conditions. With the growing demands of telehealth, using technology as an objective tool for movement analysis is needed for clinicians and payers. Our findings demonstrate the potential value of the iTUG score to assess and track patient’s progress.

User-Centered Design to Enhance mHealth Systems for Individuals With Dexterity Impairments: Accessibility and Usability Study

Background

Mobile 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.

Objective

In this study, we aim to evaluate the usability of the redesigned modules within the iMHere 1.0 app.

Methods

We 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.

Results

In 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.

Conclusions

This 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.

Effects of Mobile-Based Rehabilitation in Adolescent Football Players with Recurrent Lateral Ankle Sprains during the COVID-19 Pandemic

Football is a sport involving dynamic movements, and ankle sprains are common sports injuries experienced by football players. Ankle sprains exhibit a high recurrence rate, and rehabilitation training is effective; however, expert-supervised rehabilitation (SVR) at training centers is difficult due to the recent COVID-19 pandemic. This study investigated the effects of mobile-based rehabilitation (MBR) performed at home by high school football players. Sixty players (SVR: 30 and MBR: 30) with recurrent ankle sprains were analyzed. The rehabilitation program consisted of strength and balance training, and the training intensity was gradually increased from week 1 to week 8. The SVR group underwent training at the center with experts, and the BMR group were provided with programs and feedback using mobile devices. Ankle muscle strength was evaluated by measuring isometric eversion, inversion, plantarflexion, and dorsiflexion contraction using a hand-held dynamometer, and dynamic balance was assessed using the Y-balance test (YBT; anterior, posteromedial, and posterolateral); the Foot and Ankle Outcome Score (FAOS) was used for the subjective evaluation. Measurements were conducted at weeks 1, 4, and 8. The patients visited the clinic within 1 week after the injury, and the first test was conducted after consent to participate in the research. Patients underwent the second test at an average of 3.2 weeks after the first test, and the last test at an average of 4.4 weeks after the second test. Although only the SVR group exhibited improvement in strength (eversion and dorsiflexion), YBT and subjective satisfaction at week 4, these measurements improved in both the SVR and MBR groups at week 8. Therefore, mobile–based rehabilitation could be a suitable alternative for high school athletes with ankle sprains who cannot undergo supervised rehabilitation.

Precision rehabilitation: optimizing function, adding value to health care

Precision medicine efforts are underway in many medical disciplines; however, the power of precision rehabilitation has not yet been explored. Precision medicine aims to deliver the right intervention, at the right time, in the right setting, for the right person, ultimately, bolstering the value of the care that we provide. To date precision medicine efforts have rarely focused on function at the level of a person, but precision rehabilitation is poised to change this and bring the focus on function to the broader precision medicine enterprise. To do this, subgroups of individuals must be identified based on their level of function via precise measurement of their abilities in the physical, cognitive, and psychosocial domains. Adoption of electronic health records, advances in data storage and analytics, and improved measurement technology make this shift possible. Here we detail critical components of the precision rehabilitation framework, including 1) the synergistic use of various study designs, 2) the need for standardized functional measurements, 3) the importance of precise and longitudinal measures of function, 4) the utility of comprehensive databases, 5) the importance of predictive analyses, and 6) the need for system and team science. Precision rehabilitation has the potential to revolutionize clinical care, optimize function for all individuals, and magnify the value of rehabilitation in healthcare; however, to reap the benefits of precision rehabilitation, the rehabilitation community must actively pursue this shift.

Technology-based and supervised exercise interventions for individuals with type 2 diabetes: Randomized controlled trial

AIMS

The purpose of this study was to estimate, for people with type 2 diabetes (T2D), the extent to which glycemic control was affected by a 12-week program using mobile app and wearable smartwatch in comparison to supervised exercise training.

METHODS

This study was a stratified, randomized, assessor-blind, controlled, pragmatic trial with three parallel groups which were supervised, mobile app and wearable smartwatch. Individually tailored exercise regimens delivered through a supervisor, mobile app and wearable smartwatch. Programs consisted of aerobic, resistance exercises, calisthenic, flexibility, balance, and coordination exercises. Primary outcome was change in glycemic control (HbA1c); secondary outcome was Six Minute Walk Test; and explanatory outcomes were exercise behaviour, muscle function, and physical capacity. The groups were contrasted for change in HbA1c and absolute reduction of ≥0.5% (Minimal Important Change). Linear and logistic regressions were used to compare the groups and generalized estimated equations were used to analyze the explanatory outcomes.

RESULTS

In total, 90 people were randomized, 6 were lost over 12 weeks, leaving 84 with outcome data. The difference in HbA1c did not differ between the supervised and the technology groups combined and between the mobile app and smartwatch group. Proportions of people achieving a clinically meaningful difference on HbA1c between the supervised and technology groups were similar (46% vs 43%) and the associated OR was 0.87 (95%CI:0.34-2.28). Within the two technology groups, proportions of people achieving a clinically meaningful difference in HbA1c were 48% in the mobile app and 38% in the smartwatch groups and the associated OR was 0.65 (95%CI:0.21-2.03). The groups did not differ on secondary and explanatory outcomes.

CONCLUSIONS

The results of our trial provide evidence that all outcomes have improved in all groups regardless of the exercise delivery method. Considering the supervised programs are not available for everybody, technological options are crucial to implement to help individuals self-manage most aspects of their diabetes.

Respiratory muscle training program supplemented by a cell-phone application in COPD patients with severe airflow limitation

PURPOSE

The purpose of this study was to implement a respiratory muscle training program through a mobile phone application for COPD patients with severe airflow limitation.

METHODS

We conducted an experimental study to determine the efficacy of a six-month mobile phone application. At least three times a week for six months the patients would participate in an online training session. We evaluated the lung volumes, maximal inspiratory and expiratory pressure (MIP/MEP) and diaphragm amplitude. The tests were performed at the beginning and at the end of the study.

RESULTS

Thirty-four patients with severe COPD, aged between 44 and 67 years (Mean ± SD, 59.29 ± 6.063), accepted to follow a rehabilitation program based on the use of the Pneumocontrol application. We observed on increased of MEP from the pre-rehabilitation state (83.41 cmH2O) to the post-rehabilitation state (95.03 cmH2O), z = 5.087, p < 0.001. Also, the median MIP significantly increased from the pre-rehabilitation state to the post-rehabilitation state, z = 5.052, p < 0.001. Diaphragmatic distance also increased from 2.81 cm to 3.44 cm, z = 5.069, p < 0.001.

CONCLUSION

Respiratory muscle training supplemented through a cell phone-based application can improve respiratory muscle strength and diaphragm mobility.

Mobile health technologies for the monitoring of menstrual cycle: A systematic review of online stores in Brazil

AIM

To perform a systematic review of available mHealth apps for menstrual cycle monitoring in Brazil.

METHODS

A search for menstrual cycle mHealth apps from the Google Play Store and AppStore in Brazil was performed by two independent reviewers on October 2020, and the quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS).

RESULTS

Our review identified 2400 potentially relevant mHealth apps, of which 56 were eligible for inclusion. The majority of the apps offered tools to track menstruation symptoms (63%) and educational content for users (32%). The mean ( ±SD) MARS app quality score for the 28 evaluated apps in Android was 3.5 ± 0.6 on a 0-5 scale. For the 28 evaluated apps in iOS, the mean app quality score was 3.8 ± 0.4. Most of the included apps, for both systems, scored average for credibility, user interface, and engagement.

CONCLUSION

The majority of available tools in Brazil are of moderate quality and limited functionality for menstrual cycle monitoring. This study highlights the top three mHealth apps available on each online store for individuals seeking menstrual cycle monitoring options.

mHealth Apps for Musculoskeletal Rehabilitation: State of the Practice Review (Preprint)

Background

The number of mobile health (mHealth) apps released for musculoskeletal (MSK) injury treatment and self-management with home exercise programs (HEPs) has risen rapidly in recent years as digital health interventions are explored and researched in more detail. As this number grows, it is becoming increasingly difficult for users to navigate the market and select the most appropriate app for their use case. It is also unclear what features the developers of these apps are harnessing to support patient self-management and how they fit into clinical care pathways.

Objective

The objective of this study was to scope the current market of mHealth apps for MSK rehabilitation and to report on their features, claims, evidence base, and functionalities.

Methods

A cross-sectional study of apps for MSK rehabilitation was performed across the iTunes App Store and Google Play Store. Four search terms were used, namely, physiotherapy rehabilitation, physical therapy rehabilitation, rehabilitation exercise, and therapeutic exercise to identify apps, which were then cross-referenced against set selection criteria by 4 reviewers. Each reviewer, where possible, downloaded the app and accessed supplementary literature available on the product to assist in data extraction.

Results

A total of 1322 apps were identified. After applying the inclusion and exclusion criteria and removing duplicates, 144 apps were included in the study. Over half (n=81, 56.3%) of the included apps had been released within the past 3 years. Three quarters (n=107, 74.3%) of the apps made no reference to evidence supporting the design or efficacy of the app, with only 11.1% (n=16) providing direct citations to research. Most of the apps did utilize exercise pictures (n=138, 95.8%) or videos (n=97, 67.4%); however, comparatively few harnessed additional features to encourage engagement and support self-management, such as an adherence log (n=66, 45.8%), communication portal (n=32, 22.2%), patient-reported outcome capture (n=36, 25%), or direct feedback (n=57, 39.6%). Of note and concern, many of these apps prescribed generic exercises (n=93, 64.6%) in the absence of individualized input to the user, with few providing specific patient education (n=43, 34%) and safety advice or disclaimers (n=38, 26.4%).

Conclusions

The cohort of apps included in this study contained a large heterogeneity of features, so it is difficult for users to identify the most appropriate or effective app. Many apps are missing the opportunity to offer key features that could promote exercise adherence and encourage self-management in MSK rehabilitation. Furthermore, very few developers currently offering products on the market are providing evidence to support the design and efficacy of their technologies.

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

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.

The Effectiveness of Stroke Riskometer™ in Improving Stroke Risk Awareness in Malaysia: A Study Protocol of a Cluster-Randomized Controlled Trial

BACKGROUND

Stroke is considered the second leading cause of mortality and disability worldwide. The increasing burden of stroke is strong evidence that currently used primary prevention strategies are not sufficiently effective. The Stroke Riskometer™ application (app) represents a new stroke prevention strategy distinctly different from the conventional high-cardiovascular disease risk approach.

OBJECTIVE

This proposed study aims to evaluate the effectiveness of the Stroke Riskometer™ app in improving stroke awareness and stroke risk probability amongst the adult population in Malaysia.

METHODS

A non-blinded, parallel-group cluster-randomized controlled trial with a 1:1 allocation ratio will be implemented in Kelantan, Malaysia. Two groups with a sample size of 66 in each group will be recruited. The intervention group will be equipped with the Stroke Riskometer™ app and informational leaflets, while the control group will be provided with standard management, including information leaflets only. The Stroke Riskometer™ app was developed according to the self-management model of chronic diseases based on self-regulation and social cognitive theories. Data collection will be conducted at baseline and on the third week, sixth week, and sixth month follow-up via telephone interview or online questionnaire survey. The primary outcome measure is stroke risk awareness, including the domains of knowledge, perception, and intention to change. The secondary outcome measure is stroke risk probability within 5 and 10 years adjusted to each participant's socio-demographic and/or socio-economic status. An intention-to-treat approach will be used to evaluate these measures. Pearson's χ2 or independent t test will be used to examine differences between the intervention and control groups. The generalized estimating equation and the linear mixed-effects model will be employed to test the overall effectiveness of the intervention.

CONCLUSION

This study will evaluate the effect of Stroke Riskometer™ app on stroke awareness and stroke probability and briefly evaluate participant engagement to a pre-specified trial protocol. The findings from this will inform physicians and public health professionals of the benefit of mobile technology intervention and encourage more active mobile phone-based disease prevention apps.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT04529681.

Emerging Concepts and Evidence in Telematics Novel Approaches or Treatments for Spasticity Management After Botulinum Injection

There is a strong recommendation for the use of intramuscular botulinum toxin in patients with persistent or progressive spasticity affecting one or more joints and who have an identifiable therapeutic target. After a botulinum toxin injection, a stretching intervention improves the results of the treatment, and it should be performed by patients and/or caregivers after being trained by a therapist. Adherence to this recommendation remains low once the therapist stops following the patient. The COVID-19 pandemic has increased the use of telemedicine with different approaches to treat patients. There has been an increased use of motivational applications, with virtual reality software and real-life videos, which provide a gaming experience that increases adherence. There are programs with synchronous telehealth exercises guided by physical therapists or software with sensor-based technology that shows the range of motion (ROM) and strength of the muscles of a particular joint. These new approaches to patient follow-up appear to increase adherence to exercise because they need to be “watched and controlled” is achieved.

Development and Feasibility Testing of an Animated Cartoon-Based Self-Care Application for Low-Back Pain – a Pilot Study

Objectives: Use of animated cartoon for pain management is an emerging area, however, no study have explored it as a digital platform for rehabilitation of low-back pain (LBP). This study was aimed to develop and evaluate the feasibility of an animated cartoon-based self-care (ACBSC) app for LBP, and to examine the correlation between the app rating parameters and patients’ pain. Methods: This two-phase study comprised a development and feasibility testing components. Development of the ACBSC app was based on Mckenzie’s Mechanical Diagnosis and Therapy (MDT) extension protocolplus back hygiene following standard iteration and prototyping process. Twenty-eight consecutive patients with chronic non-specific LBP with 'direction Preference’ for extension based on the MDT screening algorithm participated in the feasibility phase. The participants utilized the cartoon-based app thrice weekly for two weeks. Outcomes were assessed in terms of usability, satisfaction and user’s experience using the system usability scale and mobile application rating scale. Quadruple visual analogue scale was used to assess pain intensity of the participants. Results: On a unified scale of 20, functionality (15.4 ± 2.41) and aesthetics 14 ± 2.00 had highest and least objective quality rating on the app parameters. Total objective and subjective quality rating of the app was 16.9 ± 1.97 and 15.6 ± 2.42 respectively. Total impact and usability score was 24.1 ± 3.39 (out of 30) and 27.8 ± 3.09 (out of 50). Participants reported that back care cartoon app mostly affect mindfulness/meditation/relaxation (42.9%), increases happiness/well-being (46.4%), leads to behavioural change (60.7%) and targets physical health (100%). There was no significant correlation between participants’ pain characteristics and app rating parameters (p>0.05). Conclusion: The animated cartoon-based self-care LBP app has moderate to high usability, functionality, aesthetics and quality rating, and may serve as an effective mobile-app for self-management of long-term LBP.

Machine Learning in Medical Emergencies: a Systematic Review and Analysis

Despite the increasing demand for artificial intelligence research in medicine, the functionalities of his methods in health emergency remain unclear. Therefore, the authors have conducted this systematic review and a global overview study which aims to identify, analyse, and evaluate the research available on different platforms, and its implementations in healthcare emergencies. The methodology applied for the identification and selection of the scientific studies and the different applications consist of two methods. On the one hand, the PRISMA methodology was carried out in Google Scholar, IEEE Xplore, PubMed ScienceDirect, and Scopus. On the other hand, a review of commercial applications found in the best-known commercial platforms (Android and iOS). A total of 20 studies were included in this review. Most of the included studies were of clinical decisions (n = 4, 20%) or medical services or emergency services (n = 4, 20%). Only 2 were focused on m-health (n = 2, 10%). On the other hand, 12 apps were chosen for full testing on different devices. These apps dealt with pre-hospital medical care (n = 3, 25%) or clinical decision support (n = 3, 25%). In total, half of these apps are based on machine learning based on natural language processing. Machine learning is increasingly applicable to healthcare and offers solutions to improve the efficiency and quality of healthcare. With the emergence of mobile health devices and applications that can use data and assess a patient's real-time health, machine learning is a growing trend in the healthcare industry.

Use of mobile applications in hand therapy

INTRODUCTION

Mobile devices can be incorporated into therapy as an engaging alternative to traditional therapy options. The use of mobile devices and smartphone applications can enhance the quality of care provided by health care professionals.

PURPOSE

To find mobile apps that can be incorporated into hand therapy practice.

METHODS

Hand therapy evaluation, interventions, proprioception, laterality, and home exercise program applications can be incorporated into practice. Patient education can also be provided via the use of mobile applications.

CONCLUSION

Smartphone applications can be a valuable intervention and impact performance in individuals with impaired hand function. Smartphone applications offer a client-centered, and potentially motivating, activity option that can be utilized to aid the hand therapist.

The Development and Usability Assessment of an mHealth Application to Encourage Self-Care in Pregnant Women against COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has caused serious concerns in pregnant women. Self-care mHealth applications can provide helpful guidelines for COVID-19 prevention or management in case of infection. This study aimed to develop and then assess a self-care smartphone-based application to provide self-care for pregnant women against COVID-19. The present study was conducted in two phases. First, a needs assessment was performed based on the opinions of 30 obstetricians and pregnant women. Then, relying on the results, a smartphone-based application was prototyped and assessed in terms of its usability and user satisfaction. To assess the application, 36 pregnant women (11 infected with COVID-19) were asked to use the application for a week. The QUIS questionnaire 5.5 was used for assessment, and the results were analyzed via descriptive statistics in SPSS 23. According to the obstetricians and pregnant women, of the 41 information requirements, 35 data elements were noted to be essential in the needs assessment. Features of the application were placed in four categories of User's Profile, Lifestyle, Disease Management and Control, and Application Functions (e.g., introducing high-risk places in terms of COVID-19 prevalence in each city, introducing specialized COVID-19 medical centers to pregnant women to receive services, medication management, stress management and control, nutrition and diet management, sleep management, contacting physicians, doctor's appointment reminder, searching the available educational materials, and making application adjustments such as text font, size, and color). With an average score of 7.94 (out of 9), pregnant women rated the application at a good level. The application can be used to reduce anxiety and stress about COVID-19 in mothers, provide access to reliable information to answer possible questions, identify high-risk locations, and provide pregnant women with instant access to healthcare facilities and information related to COVID-19 self-care processes.

COVID-19: A catalyst for change in virtual health care utilization for persons with limb loss

The dramatic uptake of virtual care, or telehealth, utilization because of COVID‐19 restrictions for persons with limb loss has led to a much greater understanding of this health care delivery method for this complex patient population. However, much is still unknown. Therefore, the authors provide a comprehensive literature review of existing evidence for virtual care delivery across the phases of amputation rehabilitation, as well as anecdotal evidence, to provide a platform for further discussion and development of research and innovative opportunities. Evidence reveals that virtual care serves as a complement to in‐person health care for individuals with limb loss because it allows for increased accessibility to these services. The authors conclude that continued use of telehealth beyond the COVID‐19 restrictions to optimize outcomes across the continuum of care for persons with limb loss is warranted.

Advanced Statistical Analysis of 3D Kinect Data: A Comparison of the Classification Methods

This paper focuses on the statistical analysis of mimetic muscle rehabilitation after head and neck surgery causing facial paresis in patients after head and neck surgery. Our work deals with an evaluation problem of mimetic muscle rehabilitation that is observed by a Kinect stereo-vision camera. After a specific brain surgery, patients are often affected by face palsy, and rehabilitation to renew mimetic muscle innervation takes several months. It is important to be able to observe the rehabilitation process in an objective way. The most commonly used House–Brackmann (HB) scale is based on the clinician’s subjective opinion. This paper compares different methods of supervised learning classification that should be independent of the clinician’s opinion. We compare a parametric model (based on logistic regression), non-parametric model (based on random forests), and neural networks. The classification problem that we have studied combines a limited dataset (it contains only 122 measurements of 93 patients) of complex observations (each measurement consists of a collection of time curves) with an ordinal response variable. To balance the frequencies of the considered classes in our data set, we reclassified the samples from HB4 to HB3 and HB5 to HB6—it means that only four HB grades are used for classification algorithm. The parametric statistical model was found to be the most suitable thanks to its stability, tractability, and reasonable performance in terms of both accuracy and precision.

A Blockchain-Enabled Framework for mHealth Systems

Presently modern technology makes a significant contribution to the transition from traditional healthcare to smart healthcare systems. Mobile health (mHealth) uses advances in wearable sensors, telecommunications and the Internet of Things (IoT) to propose a new healthcare concept centered on the patient. Patients' real-time remote continuous health monitoring, remote diagnosis, treatment, and therapy is possible in an mHealth system. However, major limitations include the transparency, security, and privacy of health data. One possible solution to this is the use of blockchain technologies, which have found numerous applications in the healthcare domain mainly due to theirs features such as decentralization (no central authority is needed), immutability, traceability, and transparency. We propose an mHealth system that uses a private blockchain based on the Ethereum platform, where wearable sensors can communicate with a smart device (a smartphone or smart tablet) that uses a peer-to-peer hypermedia protocol, the InterPlanetary File System (IPFS), for the distributed storage of health-related data. Smart contracts are used to create data queries, to access patient data by healthcare providers, to record diagnostic, treatment, and therapy, and to send alerts to patients and medical professionals.

Research on Application of Health Medical Information Science Data Sharing Standard System in Sports Rehabilitation

The development of medical information technology has rapidly promoted the development of medical information technology towards intelligence. Health medical data provides basic data resource protection for intelligent medical services and smart medical services. This article abstracts the typical models of domestic and international health medical information management services, and provides theoretical basis and practical reference for the building of an evaluation index system for health management service capabilities. An system for health management service capabilities under a data sharing standard system was constructed, and the status and linkage of health management services were investigated and comprehensively evaluated to provide an index system and empirical data for evaluating hospital health management service capabilities. Finally, analyze the advantages and disadvantages of health management services under the medical consortium framework, propose countermeasures to improve the health management service system, provide decision-making references for units to improve their health management service capabilities, optimize health management service models, and formulate health management services for relevant government departments Provisional policies to promote the implementation of health management.

Knee osteoarthritis: key treatments and implications for physical therapy

BACKGROUND

Knee osteoarthritis (OA) is a chronic progressive disease that imparts a substantial socioeconomic burden to society and healthcare systems. The prevalence of knee OA has dramatically risen in recent decades due to consistent increases in life expectancy and obesity worldwide. Patient education, physical exercise, and weight loss (for overweight or obese individuals) constitute the first-line knee OA treatment approach. However, less than 40% of patients with knee OA receive this kind of intervention. There is an unmet need for healthcare professionals treating individuals with knee OA to understand the current recommended treatment strategies to provide effective rehabilitation.

OBJECTIVE

To guide physical therapists in their clinical decision making by summarizing the safest and most efficacious treatment options currently available, and by delineating the most traditional outcome measures used in clinical research for knee OA.

CONCLUSION

There is a need for healthcare providers to abandon low-quality and ineffective treatments and educate themselves and their patients about the current best evidence-based practices for knee OA.

A Survey on Gamification for Health Rehabilitation Care: Applications, Opportunities, and Open Challenges

Research trends in gamification have shown a significant diversity in various areas of e-health, particularly in addressing the issues of rehabilitation and physical activity. Rehabilitation requires better engaging tools that help to increase the patient’s motivation and engagement in particular forms of rehabilitation training. Adopting gamification in rehabilitation offers different treatment and care environments when implementing rehabilitation training. As gamification is increasingly being explored in rehabilitation, one might not realize that using various techniques in gamified applications yields a different effect on gameplay. To date, varied gamification techniques have been utilized to provide useful experiences from the perspective of health applications. However, a limited number of surveys have investigated the gamification of rehabilitation and the use of suitable game techniques for rehabilitation in the literature. The objective of this paper is to examine and analyze the existing gamification techniques for rehabilitation applications. A classification of rehabilitation gamification is developed based on the rehabilitation gamifying requirements and the gamification characteristics that are commonly applied in rehabilitation applications. This classification is the main contribution of this paper. It provides insight for researchers and practitioners into suitable techniques to design and apply gamification with increased motivation and sustainable engagement for rehabilitation treatment and care. In addition, different game elements, selection blocks, and gamification techniques are identified for application in rehabilitation. In conclusion, several challenges and research opportunities are discussed to improve gamification deployment in rehabilitation in the future.

Mobile health technologies for the management of urinary incontinence: A systematic review of online stores in Brazil

BACKGROUND

Urinary incontinence (UI) is a serious condition for which often times insufficient non-surgical treatment options are provided or sought. Mobile health (mHealth) applications (apps) offer potential to assist with the self-management of UI.

OBJECTIVE

To perform a systematic review of available mHealth apps for UI in Brazil.

METHODS

A search for UI mHealth apps from the Google Play Store and AppStore in Brazil was performed by two independent reviewers on June 4 2020, and the quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS).

RESULTS

Of the 1111 mHealth apps found, 12 were eligible for inclusion. Four offered exclusively exercise programs, six offered exercise and educational content, and two offered tools to track patient-reported symptoms. The included apps scored poorly on the MARS quality scale, with a mean ± standard deviation score of 2.7 ± 0.6 on a 0-5 scale. Most apps scored poorly based on credibility, user interface and experience, and engagement.

CONCLUSION

Although there is growing interest in the development of mHealth technologies to support patients with UI, currently available tools in Brazil are of poor quality and limited functionality. Effective collaboration between industry and research is needed to develop new user-centered mHealth apps that can empower patients with UI.

Mobile health technologies for the management of rheumatic diseases: a systematic review of online stores in Brazil

Rheumatic diseases are serious conditions with a low uptake of conservative treatments. Mobile health (mHealth) applications (apps) offer potential to assist the self-management of rheumatic diseases. Our goal was to perform a systematic review of available mHealth apps for rheumatic diseases in Brazil. We focused on the most prevalent rheumatic diseases: osteoarthritis, rheumatoid arthritis, fibromyalgia, systemic lupus erythematosus, osteoporosis, and axial spondylarthritis. Google Play Store and AppStore in Brazil were queried by two independent reviewers on September 2020, and the quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS). Of the 3173 mHealth apps found, five were eligible for inclusion. Two for fibromyalgia and two for axial spondylarthritis offered exercise, educational content, and tools to track patient-reported symptoms; and one for osteoporosis offered educational content and tracking tools only. The included apps scored moderately on the MARS quality scale, with a mean score (SD) of 3.1 (0.7) on a 0-5 scale. Most apps scored poorly based on credibility, user interface and experience, and engagement. There is growing interest in the development of mHealth technologies to support rheumatic diseases patients. Although the majority of the included apps came from non-profit organizations, they are still of poor quality and limited functionality. This study is a call for to the development of new user-centered mHealth apps that can empower rheumatic diseases patients in Brazil, especially in the area of osteoarthritis, rheumatoid arthritis, and lupus, since no apps were found.

Advanced Statistical Analysis of 3D Kinect Data: Mimetic Muscle Rehabilitation Following Head and Neck Surgeries Causing Facial Paresis

An advanced statistical analysis of patients’ faces after specific surgical procedures that temporarily negatively affect the patient’s mimetic muscles is presented. For effective planning of rehabilitation, which typically lasts several months, it is crucial to correctly evaluate the improvement of the mimetic muscle function. The current way of describing the development of rehabilitation depends on the subjective opinion and expertise of the clinician and is not very precise concerning when the most common classification (House–Brackmann scale) is used. Our system is based on a stereovision Kinect camera and an advanced mathematical approach that objectively quantifies the mimetic muscle function independently of the clinician’s opinion. To effectively deal with the complexity of the 3D camera input data and uncertainty of the evaluation process, we designed a three-stage data-analytic procedure combining the calculation of indicators determined by clinicians with advanced statistical methods including functional data analysis and ordinal (multiple) logistic regression. We worked with a dataset of 93 distinct patients and 122 sets of measurements. In comparison to the classification with the House–Brackmann scale the developed system is able to automatically monitor reinnervation of mimetic muscles giving us opportunity to discriminate even small improvements during the course of rehabilitation.

User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study

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.