PRECISE Decision Support Tool for Guiding Exercise Recommendation

D1: PRECISE DSS: Precision-based Recreation, Exercise in Community Inclusive Settings and

Environments- Decision Support Tool

Background

The development of suitable strategies for recommending appropriate exercise/recreation programs for people with disabilities is a dynamic, iterative process that involves complex decision-making between the user and the practitioner (e.g., health professional, fitness instructor)1.  Despite the abundance of evidence that people with disabilities are receiving less than adequate exercise/recreation services from health care providers2, poorer quality exercise/recreation opportunities3, and have substantially greater health disparities compared to the general population4, there is currently no decision support system (DSS) that addresses their unique needs.

There is a need for a decision support tool that can guide healthcare providers and exercise/rehabilitation professionals in assisting people with disabilities to lead an active lifestyle.  Today, big data technology has advanced to such a degree that abundant new data sources can be converted into smart software, thereby allowing more decisions to be made based on data and analysis rather than experience and intuition.  Such DSS can also have the ability to update new data sources and over time increase its predictability for subgroups of people with similar characteristics.

Aims

To develop a health informatics infrastructure that integrates participant-specific computational models delivered through clinical decision support tools, which referred to as Precision-based Recreation, Exercise in Community Inclusive Settings and Environments Decision Support Tool (PRECISE DSS).

Methods

The PRECISE DSS will be conceptually based on the International Classification of Functioning, Disability and Health (ICF)5 and will have the capability to process the following inputs: a) clinical inputs that describe the physiological profile of a person, b) behavioral factors such as self-efficacy and motivation, c) environmental factors such as transportation and caregiver support, and d) demographics and health history. The PRECISE DSS will be developed following 3 steps.

  • Step 1 will focus on developing the PRECISE DSS prototype and gathering user interface requirements. A rules-based approach will be developed that accounts for person-specific inputs such as barriers and preferences, as well as clinical inputs as shown on the left side of the model in the Figure The PRECISE DSS will contain a) a module that will be used to catalog information mapping equipment, which means that the database will have the ability to provide information about the choice of exercise equipment for improving a specific physiological function and b) a home-based module that will catalog information about the different exercises and resources available to improve adherence to an exercise recommendation/prescription in a home-based or remote setting.

Additional inputs will be accounted using the American College of Sports Medicine’s guidelines, literature reviews and mining our own data sets for exercise prescription and management, issues associated with behavioral (e.g., motivation, interest, exercise self-efficacy, decisional balance) and environmental factors (e.g., social support, transportation, built environment) factors. Furthermore, we will use a) our extant data from multiple exercise training studies conducted under the UAB/Lakeshore Research Collaborative, which will include a sample size over 600 that provide information about anthropometric measures, muscular strength, aerobic capacity, functional mobility, as well as social cognitive theory constructs including self-efficacy and outcome expectations; b) the technology we created in previous grant applications, which allowed our team to design and build a health information technology platform (POWERS, Personalized Online Weight and Exercise Response System) that demonstrated success in achieving weight loss in adults with physical/mobility disability6,7 to help develop the PRECISE DSS.

An iterative usability assessment will be performed to design and develop the information display across different groups of disabilities. Twenty people with disabilities and 10 exercise trainers will respond to a series of questions using an adaptation of the System Usability Scale and the results of this scale will drive our choice of user interface.  

  1. Step 2 will involve the software development based on feedback from step 1. We will conduct a round of testing to ensure that the DSS is ready for use by other participants.  This will be done side-by-side with a researcher and a developer in order to attain the richest feedback and most effective and efficient development iterations possible.
  2. Step 3 will involve training/educational sessions for staff and people with disabilities at Lakeshore Foundation about how to use and interpret the PRECISE DSS. Detailed evaluation including testing the feasibility and efficacy of the PRECISE DSS as well as qualitative feedback.

Final Outcomes

A decision support tool that guides healthcare providers and exercise/rehabilitation professionals in assisting people with disabilities to make better choices regarding exercise/recreation programs, facilities, equipment and services will be developed.

References

  1. Grim K, Rosenberg D, Svedberg P, Schon UK. Development and usability testing of a web-based decision suport for users and health professionals in psychiatric services. Psychiatr Rehabil J. 2017;E pub ahead of print.
  2. Learmonth Y, Adamson BC, Balto JM, Chiu JM, Molina-Guzam, IM, Finlayson M, Riskin BJ, Motl RW. Multiple sclerosis patients need and want information on exercise promotion from healthcare providers: A qualitative study. Health Expectations,. in press,.
  3. Martin Ginis K, Ma JK, Latimer-Cheung AE, Rimmer, JH. A systematic review of review articles addressing factors related to physical activity participation among children and adults with physical disabilities. Health Psychol Rev. 2016;10:478-494.
  4. Carroll D, Courtney-Long EA, Stevens AC, Sloan ML, Lullo C, Visser SN, Fox MH, Armour BS, Campbell VA, Brown DR, Dorn JM. Vital signs: disability and physical activity – United States, 2009-2012. 2014;63(18):407-413.
  5. Rimmer JH. Use of the ICF in identifying factors that impact participation in physical activity/rehabilitation among people with disabilities. Dis & Rehabil. 2006;28(17):1087-1095.
  6. Rimmer J, Rauworth A, Wang E, Heckerling P, Gerber BS. A randomized controlled trial to increase physical activity and reduce obesity in a predominantly African American group of women with mobility disabilities and severe obesity. Prev Med. 2009;48:473-479.
  7. Rimmer JH, Wang E, Pellegrini CA, Lullo C, Gerber B. Telehealth weight management intervention for adults with physical disabilities. A randomized controlled trial. Am J Phys Med Rehabil 2012;92:1084-1094.