Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study

Exploring the Complexity of Falls in People With Multiple Sclerosis: A Qualitative Study

BACKGROUND

The complexity of falls in people with multiple sclerosis (MS) needs further exploration to develop strategies to reduce fall risk. The aim of this study is to explore and describe factors contributing to falls and the complexity of fall situations in people with MS.

METHODS

This longitudinal study used individual interviews shortly after prospective reporting of falls. Manifest analysis was used to describe frequency, place, and time of falls. The International Classification of Functioning, Disability and Health (ICF) was used for deductive content analyses to describe fall-inducing factors. Participants were adults with MS (N = 33) who had experienced falls during the past year and who did not use walking aids.

RESULTS

The 25 participants who fell during the study period reported 94 falls, mainly during the day (61%) and outdoors (56%). Fall situations were complex, with interaction between triggering and circumstantial factors related to all domains in the ICF, the impact of preceding factors, and fluctuating symptoms.

CONCLUSIONS

The complexity of fall situations can be more clearly understood and managed by considering the preceding activities and circumstances in addition to describing single risk factors. This may facilitate discussions of fall risk between health care professionals and people with MS. Individualized fall risk assessments and interventions that strengthen self-management are recommended.

A scoping review assessing the usability of digital health technologies targeting people with multiple sclerosis

Digital health technologies (DHTs) have become progressively more integrated into the healthcare of people with multiple sclerosis (MS). To ensure that DHTs meet end-users' needs, it is essential to assess their usability. The objective of this study was to determine how DHTs targeting people with MS incorporate usability characteristics into their design and/or evaluation. We conducted a scoping review of DHT studies in MS published from 2010 to the present using PubMed, Web of Science, OVID Medline, CINAHL, Embase, and medRxiv. Covidence was used to facilitate the review. We included articles that focused on people with MS and/or their caregivers, studied DHTs (including mhealth, telehealth, and wearables), and employed quantitative, qualitative, or mixed methods designs. Thirty-two studies that assessed usability were included, which represents a minority of studies (26%) that assessed DHTs in MS. The most common DHT was mobile applications (n = 23, 70%). Overall, studies were highly heterogeneous with respect to what usability principles were considered and how usability was assessed. These findings suggest that there is a major gap in the application of standardized usability assessments to DHTs in MS. Improvements in the standardization of usability assessments will have implications for the future of digital health care for people with MS.

Tablet app-based dexterity training in multiple sclerosis (TAD-MS): a randomized controlled trial

PURPOSE

Mobile health applications (mHealth apps) may lead to health benefits. In recent years, the use of apps in multiple sclerosis (MS) has increased. Apps to train and improve dexterity in MS are scarce. This study investigated the effectiveness of a tablet app-based home-based training to improve dexterity in individuals with MS.

MATERIALS AND METHODS

In a randomized controlled trial, two standardized 4-week home-based interventions focussing on different aspects of dexterity and upper limb function were compared. Assessments were done at baseline, post-intervention and 12-week follow-up. The primary endpoint was the Arm Function in Multiple Sclerosis Questionnaire, a dexterity-related measure of patient-reported activities of daily living. Secondary endpoints were dexterous function, grip strength and health-related quality of life.

RESULTS

Forty-eight individuals were randomly assigned to a tablet app-based program (n = 26) or a control strengthening exercise program (n = 22). No significant differences were found for the primary endpoint (p = 0.35). Some significant differences in favour of the app-group were found in fine coordinated finger movements and strength. No significant differences were found at the 12-week follow-up for all endpoints. Adherence in both groups was above 90%.

CONCLUSIONS

App-based training was not superior compared to a control strengthening exercise program concerning the arm- and hand function from the participant's perspective. However, app-based training was found to be effective in improving specific dimensions (finger movements and strength), and can easily be applied at home. Therefore, individuals living with MS with impaired dexterity should consider app-based training.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov NCT03369470.

A Closed-Loop Falls Monitoring and Prevention App for Multiple Sclerosis Clinical Practice: Human-Centered Design of the Multiple Sclerosis Falls InsightTrack

BACKGROUND

Falls are common in people with multiple sclerosis (MS), causing injuries, fear of falling, and loss of independence. Although targeted interventions (physical therapy) can help, patients underreport and clinicians undertreat this issue. Patient-generated data, combined with clinical data, can support the prediction of falls and lead to timely intervention (including referral to specialized physical therapy). To be actionable, such data must be efficiently delivered to clinicians, with care customized to the patient's specific context.

OBJECTIVE

This study aims to describe the iterative process of the design and development of Multiple Sclerosis Falls InsightTrack (MS-FIT), identifying the clinical and technological features of this closed-loop app designed to support streamlined falls reporting, timely falls evaluation, and comprehensive and sustained falls prevention efforts.

METHODS

Stakeholders were engaged in a double diamond process of human-centered design to ensure that technological features aligned with users' needs. Patient and clinician interviews were designed to elicit insight around ability blockers and boosters using the capability, opportunity, motivation, and behavior (COM-B) framework to facilitate subsequent mapping to the Behavior Change Wheel. To support generalizability, patients and experts from other clinical conditions associated with falls (geriatrics, orthopedics, and Parkinson disease) were also engaged. Designs were iterated based on each round of feedback, and final mock-ups were tested during routine clinical visits.

RESULTS

A sample of 30 patients and 14 clinicians provided at least 1 round of feedback. To support falls reporting, patients favored a simple biweekly survey built using REDCap (Research Electronic Data Capture; Vanderbilt University) to support bring-your-own-device accessibility-with optional additional context (the severity and location of falls). To support the evaluation and prevention of falls, clinicians favored a clinical dashboard featuring several key visualization widgets: a longitudinal falls display coded by the time of data capture, severity, and context; a comprehensive, multidisciplinary, and evidence-based checklist of actions intended to evaluate and prevent falls; and MS resources local to a patient's community. In-basket messaging alerts clinicians of severe falls. The tool scored highly for usability, likability, usefulness, and perceived effectiveness (based on the Health IT Usability Evaluation Model scoring).

CONCLUSIONS

To our knowledge, this is the first falls app designed using human-centered design to prioritize behavior change and, while being accessible at home for patients, to deliver actionable data to clinicians at the point of care. MS-FIT streamlines data delivery to clinicians via an electronic health record-embedded window, aligning with the 5 rights approach. Leveraging MS-FIT for data processing and algorithms minimizes clinician load while boosting care quality. Our innovation seamlessly integrates real-world patient-generated data as well as clinical and community-level factors, empowering self-care and addressing the impact of falls in people with MS. Preliminary findings indicate wider relevance, extending to other neurological conditions associated with falls and their consequences.

Older Adult Falls in Emergency Medicine, 2023 Update

Of 4 older adults, 1 will fall each year in the United States. Based on 2020 data from the Centers of Disease Control, about 36 million older adults fall each year, resulting in 32,000 deaths. Emergency departments see about 3 million older adults for fall-related injuries with falls having the ability to cause serious injury such as catastrophic head injuries and hip fractures. One-third of older fall patients discharged from the ED experience one of these outcomes at 3 months.

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.

Mobile apps used for people living with multiple sclerosis: A scoping review

BACKGROUND

Multiple Sclerosis (MS) is a chronic neurodegenerative disorder. People living with MS (plwMS) require long-term, multidisciplinary care in both clinical and community settings. MS-specific mHealth interventions have advanced in the form of clinical treatments, rehabilitation, disease monitoring and self-management of disease. However, mHealth interventions for plwMS appear to have limited proof of clinical efficacy. As native mobile apps target specific mobile operating systems, they tend to have better interactive designs leveraging platform-specific guidelines. Thus, to improve such efficacy, it is pivotal to explore the design characteristics of native mobile apps used for plwMS.

OBJECTIVES

This study aimed to explore the design characteristics of native mobile apps used for adults living with MS in academic settings.

METHODS

A scoping review of studies was conducted. A literature search was performed through PubMed, CINAHL, MEDLINE and Cochrane Library. Per native mobile apps, characteristics, persuasive technology elements and evaluations were summarized.

RESULTS

A total of 14 native mobile apps were identified and 43% of the identified apps were used for data collection (n=6). Approximately 70% of the included apps involved users (plwMS) whilst developing (n=10). A total of three apps utilized embedded sensors. Videos or photos were used for physical activity interventions (n=2) and gamification principles were applied for cognitive and/or motor rehabilitation interventions (n=3). Behavior change theories were integrated into the design of the apps for fatigue management and physical activity. Regarding persuasive technology, the design principles of primary support were applied across all identified apps. The elements of dialogue support and social support were the least applied. The methods for evaluating the identified apps were varied.

CONCLUSION

The findings suggest that the identified apps were in the early stages of development and had a user-centered design. By applying the persuasive systems design model, interaction design qualities and features of the identified mobile apps in academic settings were systematically evaluated at a deeper level. Identifying the digital functionality and interface design of mobile apps for plwMS will help researchers to better understand interactive design and how to incorporate these concepts in mHealth interventions for improvement of clinical efficacy.

The Usability of a Smartphone-Based Fall Risk Assessment App for Adult Wheelchair Users: Observational Study

Background

Individuals who use wheelchairs and scooters rarely undergo fall risk screening. Mobile health technology is a possible avenue to provide fall risk assessment. The promise of this approach is dependent upon its usability.

Objective

We aimed to determine the usability of a fall risk mobile health app and identify key technology development insights for aging adults who use wheeled devices.

Methods

Two rounds (with 5 participants in each round) of usability testing utilizing an iterative design-evaluation process were performed. Participants completed use of the custom-designed fall risk app, Steady-Wheels. To quantify fall risk, the app led participants through 12 demographic questions and 3 progressively more challenging seated balance tasks. Once completed, participants shared insights on the app’s usability through semistructured interviews and completion of the Systematic Usability Scale. Testing sessions were recorded and transcribed. Codes were identified within the transcriptions to create themes. Average Systematic Usability Scale scores were calculated for each round.

Results

The first round of testing yielded 2 main themes: ease of use and flexibility of design. Systematic Usability Scale scores ranged from 72.5 to 97.5 with a mean score of 84.5 (SD 11.4). After modifications were made, the second round of testing yielded 2 new themes: app layout and clarity of instruction. Systematic Usability Scale scores improved in the second iteration and ranged from 87.5 to 97.5 with a mean score of 91.9 (SD 4.3).

Conclusions

The mobile health app, Steady-Wheels, has excellent usability and the potential to provide adult wheeled device users with an easy-to-use, remote fall risk assessment tool. Characteristics that promoted usability were guided navigation, large text and radio buttons, clear and brief instructions accompanied by representative illustrations, and simple error recovery. Intuitive fall risk reporting was achieved through the presentation of a single number located on a color-coordinated continuum that delineated low, medium, and high risk.

The Developments and Iterations of a Mobile Technology-Based Fall Risk Health Application

Falls are a prevalent and serious health concern across clinical populations. A critical step in falls prevention is identifying modifiable risk factors, but due to time constraints and equipment costs, fall risk screening is rarely performed. Mobile technology offers an innovative approach to provide personalized fall risk screening for clinical populations. To inform future development, this manuscript discusses the development and testing of mobile health fall risk applications for three unique clinical populations [older adults, individuals with Multiple Sclerosis (MS), and wheeled-device users]. We focus on key lessons learned and future directions to improve the field of fall risk mHealth. During the development phase, we first identified fall risk factors specific to each population that are measurable with mobile technology. Second, we determined whether inertial measurement units within smartphones can measure postural control within the target population. Last, we developed the interface of each app with a user-centered design approach with usability testing through iterative semi-structured interviews. We then tested our apps in real-world settings. Our cumulative work demonstrates that mobile technology can be leveraged to provide personalized fall risk screening for different clinical populations. Fall risk apps should be designed and tailored for the targeted group to enhance usefulness and feasibility. In addition, fall risk factors measured with mobile technology should include those that are specific to the population, are measurable with mobile technology, and can accurately measure fall risk. Future work should improve fall risk algorithms and implement mobile technology into fall prevention programs.

Development and Usability of a Text Messaging Program for Women With Gestational Diabetes: Mixed Methods Study

Background

Gestational diabetes mellitus (GDM) affects 5%-10% of pregnancies and can lead to serious fetal and maternal complications. SMS text messaging is an effective way to improve diabetes management outside of pregnancy, but has not been well studied in GDM.

Objective

This study aimed to perform user experience testing and assess usability and acceptability of an SMS text messaging program (Text 4 Success) for women with GDM.

Methods

An automated 2-way texting program was developed. It included (1) reminders to check blood glucose levels, (2) positive feedback to user-reported glucose levels, (3) weekly educational messages, and (4) weekly motivational messages. For the user experience testing, women received simulated messages. For the usability study, women were enrolled in the program and received messages for 2 weeks. All women participated in semistructured interviews. For women in the usability study, data from glucose measuring devices were downloaded to assess adherence to self-monitoring of blood glucose (SMBG), measured as the percentage of recommended SMBG checks performed (a secondary outcome).

Results

Ten women participated in user experience testing. Suggestions for optimization included further customization of message timing and minimization of jargon, which were incorporated. Ten women participated in the usability study. All 10 would recommend the program to other women with GDM. Participants liked the immediate feedback to glucose values. Suggestions included further flexibility of messages related to mealtimes and the ability to aggregate blood glucose data into a table or graph. Overall, adherence to SMBG testing was high at baseline (222/238 recommended checks, 93%). In comparing the week prior to the trial with the 2 weeks during the trial, there was a small but statistically insignificant difference (P=.48) in the percentage of recommended SMBG performed (median 93% [25th-75th IQR 89%-100%] vs median 97% [25th-75th IQR 92%-100%]).

Conclusions

Overall, women with GDM would recommend the Text 4 Success in GDM program and think it is helpful for GDM self-management. The program was usable and acceptable. The program may be better suited to those who have low levels of adherence to SMBG at baseline or to women at time of their diagnosis of GDM. Adaptations to the program will be made based on user suggestions. Further study of SMS text messaging to improve SMBG in GDM is needed.

Smartphone applications to assess gait and postural control in people with multiple sclerosis: A systematic review

BACKGROUND

Methods to effectively assess gait and balance impairments are necessary to guide interventions among people with Multiple Sclerosis (PwMS). Smartphone-based evaluations are becoming popular due to the ubiquitous use of smartphones in society.

OBJECTIVE

To determine the current state of smartphone applications that assess gait and balance among PwMS.

METHODS

Two independent reviewers screened articles retrieved from PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss. Articles meeting eligibility criteria were summarized and qualitatively discussed. Participant characteristics, validity, reliability, sensitivity and specificity measures, and main results of smartphone-based gait and balance evaluations were summarized. Methodological quality appraisal of the studies was performed using the quality assessment tool for observational cohort and cross-sectional studies.

RESULTS

Eight articles were included in this review. The studies present mostly with low risk of bias. All studies successfully tested the use of smartphone applications in assessing gait and balance among PwMS. In total, 75% of the studies evaluated the validity; 38% evaluated the reliability, sensitivity, and specificity of smartphone applications to assess gait and balance. Of those, all studies except one found smartphone applications to be appropriately valid, reliable, sensitive, and specific in assessing gait and balance. Most studies (88%) reported PwMS and clinicians as their intended users.

CONCLUSION

There is evidence supporting the use of smartphone applications to assess gait and balance among PwMS. Future studies should further examine the psychometric properties of smartphone-based gait and postural control assessments as well as the sensitivity and specificity to improve the interpretation of the results.