The overall study aims are to explore the feasibility, acceptability, and usability of More Stamina, a mobile app for fatigue self-management for persons with MS.
Multiple sclerosis (MS) is one of the world's most common neurologic disorders of the young adults leading to severe disability. Fatigue is one of most common symptoms that persons with MS experience, having significant impact on their quality of life and limiting their activity levels. Self-management strategies are used to support them in the care of their health. Mobile health (mHealth) solutions are a way to offer persons with chronic conditions tools to successfully manage their symptoms and problems. User-centered design (UCD) is a design philosophy that proposes placing end-users' needs and characteristics in the center of software design and development and involving users early in the different phases of the software life cycle. More Stamina is an mHealth solution created following UCD principles to help persons with MS manage their fatigue. A mixed methods study was used to assess the feasibility, acceptability, and usability of More Stamina. The study took place between January and March of 2023 in Finland. A longitudinal cohort study took take place, along with think-aloud protocols, open-ended interviews and short answer questionnaires. The study enrolled 20 persons with MS that met the criteria who utilized the More Stamina solution for 60 days.
Study Type
OBSERVATIONAL
Enrollment
20
More Stamina is a gamified task organization tool designed to help persons with MS manage their energy, to minimize the impact of fatigue in their day to day life.
Oulu University Hospital
Oulu, Finland
App Engagement Patterns
Participants' engagement with the "More Stamina" app, categorized into power, regular, and light users based on daily session averages. Engagement analyzed through session frequency, timing, and activity types.
Time frame: Over the 60-day study period.
Qualitative Insights into Usability and Barriers
Insights into usability challenges and facilitators were gathered using think-aloud protocols and semi-structured interviews. Common themes, including cognitive load, technical issues, and emotional responses, were analyzed.
Time frame: Day 1, Day 15, Day 30, and Day 60.
Association Between User Categories and Fatigue Severity Scores
User categories (power, regular, and light users) were determined by average daily app sessions. Fatigue severity was measured using the Fatigue Severity Scale (FSS), with scores ranging from 1 (no fatigue) to 7 (severe fatigue). The relationship between user engagement categories and FSS scores was analyzed using Spearman's rank-order correlation and linear regression models.
Time frame: Over the 60-day study period.
Association Between User Categories and Health-Related Quality of Life Scores
User categories defined by app engagement patterns (power, regular, and light users). HRQoL was assessed using the 15D instrument, with scores ranging from 0 (death) to 1 (full health). Scores were inverted (1 - HRQoL score) to align with worse QoL. Correlations and regression models explored associations between user categories and QoL.
Time frame: Over the 60-day study period.
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