Activity monitor use among persons with multiple sclerosis: Report on rate, pattern, and association with physical activity levels

Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals

BACKGROUND

Physical activity is central to maintaining the quality of life for patients with complex chronic conditions and is thus at the core of neurorehabilitation. However, maintaining activity improvements in daily life is challenging. The novel Stay With It program aims to promote physical activity after neurorehabilitation by cultivating self-monitoring skills and habits.

OBJECTIVE

We examined the implementation of the Stay With It program at the Valens Rehabilitation Centre in Switzerland using the normalization process theory framework, focusing on 3 research aims. We aimed to examine the challenges and facilitators of program implementation from the perspectives of patients and health care professionals. We aimed to evaluate the potential of activity sensors to support program implementation and patient acceptance. Finally, we aimed to evaluate patients' engagement in physical activity after rehabilitation, patients' self-reported achievement of home activity goals, and factors influencing physical activity.

METHODS

Patients were enrolled if they had a disease that was either chronic or at risk for chronicity and participated in the Stay With It program. Patients were assessed at baseline, the end of rehabilitation, and a 3-month follow-up. The health care professionals designated to deliver the program were surveyed before and after program implementation. We used a mixed methods approach combining standardized questionnaires, activity-sensing data (patients only), and free-text questions.

RESULTS

This study included 23 patients and 13 health care professionals. The diverse needs of patients and organizational hurdles were major challenges to program implementation. Patients' intrinsic motivation and health care professionals' commitment to refining the program emerged as key facilitators. Both groups recognized the value of activity sensors in supporting program implementation and sustainability. Although patients appreciated the sensor's ability to monitor, motivate, and quantify activity, health care professionals saw the sensor as a motivational tool but expressed concerns about technical difficulties and potential inaccuracies. Physical activity levels after patients returned home varied considerably, both within and between individuals. The self-reported achievement of activity goals at home also varied, in part because of vague definitions. Common barriers to maintaining activity at home were declining health and fatigue often resulting from heat and pain. At the 3-month follow-up, 35% (8/23) of the patients withdrew from the study, with most citing deteriorating physical health as the reason and that monitoring and discussing their low activity would negatively affect their mental health.

CONCLUSIONS

Integrating aftercare programs like Stay With It into routine care is vital for maintaining physical activity postrehabilitation. Although activity trackers show promise in promoting motivation through monitoring, they may lead to frustration during health declines. Their acceptability may also be influenced by an individual's health status, habits, and technical skills. Our study highlights the importance of considering health care professionals' perspectives when integrating new interventions into routine care.

Formative evaluation of an exercise training program for persons with multiple sclerosis who are wheelchair users

Exercise training is an effective and safe second-line therapy for improving multiple sclerosis (MS) symptoms and disease progression among adults. This study aimed to determine the appropriateness of a novel exercise training program for wheelchair users with MS. Ten wheelchair users with MS were recruited from a previous cross-sectional research study to attend one of three focus groups with 3-4 participants that lasted between 69 and 87 min. The focus groups were conducted online using a semi-structured format and participants were invited to complete an evaluation survey. During the focus groups, participants provided qualitative feedback regarding the exercise prescription, exercise modes (resistance and aerobic), training manual, exercise equipment, fitness tracker, rating scale, newsletters, logbook, and coaching. Most feedback focused on minor considerations such as avoiding the color red as it can be an issue for individuals with optic neuritis. Among quantitative evaluation survey ratings, coaching calls were rated the highest 4.7 ± 0.4 on a 5-point scale, followed by the exercise prescription (4.4 ± 0.8) and fitness tracker (4.3 ± 0.9). Focus group participants provided invaluable feedback for finalizing a novel exercise training program for wheelchair users with MS and provided focal suggestions for further improvements.

The Role of Remote Monitoring in Evaluating Fatigue in Multiple Sclerosis: A Review

Fatigue is one of the most common multiple sclerosis (MS) symptoms. Despite this, monitoring and measuring fatigue (subjective lack of energy)- and fatigability (objectively measurable and quantifiable performance decline)- in people with MS have remained challenging. Traditionally, administration of self-report questionnaires during in-person visits has been used to measure fatigue. However, remote measurement and monitoring of fatigue and fatigability have become feasible in the past decade. Traditional questionnaires can be administered through the web in any setting. The ubiquitous availability of smartphones allows for momentary and frequent measurement of MS fatigue in the ecological home-setting. This approach reduces the recall bias inherent in many traditional questionnaires and demonstrates the fluctuation of fatigue that cannot be captured by standard measures. Wearable devices can assess patients' fatigability and activity levels, often influenced by the severity of subjective fatigue. Remote monitoring of fatigue, fatigability, and activity in real-world situations can facilitate quantifying symptom-severity in clinical and research settings. Combining remote measures of fatigue as well as objective fatigability in a single construct, composite score, may provide a more comprehensive outcome. The more granular data obtained through remote monitoring techniques may also help with the development of interventions aimed at improving fatigue and lowering the burden of this disabling symptom.

Rates, patterns, and correlates of fitness tracker use among older adults with multiple sclerosis

BACKGROUND

Older adults with multiple sclerosis (MS) engage in alarmingly low levels of physical activity. Fitness trackers may be a promising approach for promoting and monitoring physical activity among older adults with MS.

OBJECTIVE/HYPOTHESIS

This study reports on the rates, patterns of fitness tracker use in adults with MS who are over 60 years of age. We hypothesized that older adults with MS who use fitness trackers "users" would report significantly more physical activity than those who don't "non-users."

METHODS

Participants across the United States completed an online survey that included self-reported demographic and clinical characteristics, fitness tracker use questionnaire, and Godin Leisure-Time Exercise Questionnaire (GLTEQ) for measuring total and health-promoting physical activity (GLTEQ-HCS).

RESULTS

Of the 440 participants who completed the full survey, 112 (28%) identified as fitness tracker users. The most common activity monitors were Fitbit®, Smartphone app, Apple® watch, and Garmin®. Fitness tracker users mostly reported having relapsing-remitting MS, less disability (i.e., lower Patient Determined Disability Steps), higher income, and higher rates of employment. There was a statistically significant difference in GLTEQ Total (t(438) = -3.8, p = .001) and GLTEQ-HCS (t(438) = -2.8, p = .006) scores between fitness tracker users and non-users. Self-reported step counts were strongly correlated with both GLTEQ Total (ρ = .50) and GLTEQ-HCS (ρ = 0.54) scores in fitness tracker users.

CONCLUSIONS

Further research is warranted investigating fitness tracker use and interests among older adults with MS and how technology may be applied as a behavioral tool to increase physical activity among this growing portion of the MS population.