Sensing Physical Activity to Evaluate and Monitor a Routine Aftercare Program (SensE-M)

Overview

Conditions such as multiple sclerosis (MS) and cardiovascular diseases (CVDs) are severe and prevalent health conditions which decrease life expectancy and increase morbidity. Key symptoms of MS and CVDs include restrictions in physical activity which increase over time and severely affect individuals' quality of life. As such, promoting physical activity is at the core of state-of-the-art treatment for these diseases. However, any improvements in daily activity levels and physical fitness that may be achieved are typically challenging to maintain in daily life. Once back in their daily life environment, persons with chronic diseases face multiple barriers to physical activity such as fatigue, a less structured environment, or time restrictions associated with care responsibilities, employment, or the like. Thus, a key challenge relates to the effective adaptation of physical activity-promoting routines and structures from the supportive rehab clinic environment to individuals' everyday lives. An example of an inpatient routine aftercare program which is designed to bridge this transition is the 'Stay with it'-program (Swiss German: 'Bliib dra'-program) developed by the Kliniken Valens. The program is designed to empower participants and promote self-efficacy and expertise - for example, in terms of self-management and self-monitoring skills. In addition, novel types of consumer-grade sensors, such as the Fitbit activity tracker, allow the assessment of a broad range of real-time activity- and sleep-related features and could complement the routine aftercare program. While these technical developments facilitate personalization and tailoring of health programs, it is often an untapped resource. However, health care professionals face time- and resource constraints. Consequently, any technical extensions of routine care programs tapping novel technical resources would need to be very scalable, streamlined, and efficient. Objectives: The present project will thus explore the potential of leveraging novel technical development in the form of consumer-grade activity sensors to complement a routine aftercare program aiming to translate structures and skills from the inpatient stay to individuals' daily lives. Specifically, the project will examine whether and how concomitant evaluation of the 'Bliib dra'-program is effective, feasible, accepted, and sustainable. To this end, we will carefully examine the experiences and needs of both program participants and therapists and conclude with recommendations which can be generalized to similar types of routine aftercare programs which are conceptualized for adult persons for whom maintenance and increase of physical activity is vital (e.g., MS, CD, other chronic diseases and acute conditions that are at risk for a chronic course such as stroke).

Primary hypothesis (hypothesis 1 - effective integration): The investigators hypothesize that integrating the Fitbit effectively into the program to measure activity goals will support program participants in pursuing their daily activity goals, particularly, once they have returned home. A prerequisite for the Fitbit's effective integration into individuals' daily lives will be the definition of activity goals which can be measured and tracked conveniently with the Fitbit. Analysis plan: The analysis strategy will depend on the final sample size. Using a descriptive approach, the investigators will compute the difference between average daily activity after their return home and their predefined activity goals which have been defined as part of the 'Bliib dra'-program (e.g., active zone minutes of different intensity, steps per day) relative to previously agreed activity level goals. Furthermore, the investigators will examine participants' free text replies concerning challenges and facilitators in pursuing their activity goals in daily life and potential/difficulties of activity trackers in this regard. To extract relevant information, the investigators will evaluate Fitbit-related statements using natural language processing techniques. Secondary hypothesis (hypothesis 2 - daily-life activity at home): Further, the investigators hypothesize that program participants will maintain a consistent and relatively stable level of physical activity. Analysis plan: The analysis strategy will depend on the final sample size. The investigators will examine different activity level outcomes (e.g., active zone minutes, step count, high- /medium-intensity minutes) the time series data using descriptive and visual methods. If the sample size allows for more complex models, they will model physical activity over time and explore individual level-factors using a (multilevel) regression framework whereby controlling for individual-level factors. The investigators will investigate decline in activity levels defined as abrupt decrease or a steady decrease over an extended period of time (i.e., at least a week). Exploratory: The investigators will further explore what challenges program participants and therapists experience, what they appreciate, and what they need to effectively integrate activity trackers such as the Fitbit device effectively into routine care program 'Bliib dra'. They will also explore how individual-level health measures (e.g., PROMIS-10) change over time. Analysis plan: The investigators will examine therapists' and program participants' replies to the open questions using natural language processing techniques. With regard to the time series data, the analysis strategy will depend on the final sample size. They will examine the time series data using descriptive and visual methods. If the sample size allows for more complex models, the investigators will use a multivariable regression framework whereby controlling for individual-level factors.