Summary
Understanding the technology elements for a study utilizing wearable and mobile technologies will assist researchers during the study planning process in several ways.
- Build a more accurate study budget.
- Develop a Data Management & Sharing Plan, which can be a requirement for funders and journal submissions.
- Prepare for regulatory and compliance processes, like an Information Assurance (IA) review, if needed
Body
Summary
Understanding the technology elements for a study utilizing wearable and mobile technologies will assist researchers during the study planning process in several ways.
- Build a more accurate study budget.
- Develop a Data Management & Sharing Plan, which can be a requirement for funders and journal submissions.
- Prepare for regulatory and compliance processes, like an Information Assurance (IA) review, if needed
Download the document provided on the right toolbar titled (Technology Elements for a study with mobile technologies.xls). The information below will guide you in completing the information in the document.
A Mobile Study Consultation guides investigators through these decisions and resources.
Technology Elements
| Technology Element |
|
Planning & Budget Impacts |
|
Mobile Data Measures
Study objectives will determine what mobile data measures are necessary and will drive device selection.
Resources:
|
|
Studies using mobile data require additional skills for managing and cleaning data before it can be analyzed. Many factors can impact the time needed to manage and clean data, including:
- Collecting data from more than one device type. e.g.: fitness tracker + continuous glucose monitor
- Collecting data from different brands or models of the same device type. e.g.: Apple watch + Fitbit or Fitbit Inspire + Fitbit Charge
|
|
Data Sensitivity Classification
Investigators should know the classification of the data they are collecting to ensure they are handling the data appropriately.
Resources:
U-M Data Classification Levels
|
|
Options for handling and storing data can be driven by the data classification level.
|
|
Wearable & Mobile Devices
Not all wearable & mobile devices are validated for use in research. Investigators should select devices that collect data necessary to meet their study objectives.
If purchasing computers, please consult with HITS.
|
|
It is recommended that devices be provided to study participants. The cost of devices should be part of the study budget.
|
|
Study, Survey, or Data Management Technology
U-M Approved Technology Options
|
|
There are many options for study platforms that can collect mobile data and manage various aspects of a study. The cost for these platforms varies dramatically and depends on the study design. |
|
Non-Mobile Data
Many studies need data in addition to data collected from mobile devices. This can include data from the following sources: Data Direct, Epic, and 3rd party mobile apps.
|
|
Adding additional data sources can increase the time necessary to merge, manage, and clean study data impacting staffing costs.
|
|
Study Data Storage
Resources:
Data Architecture & Data Pipelines
|
|
It is recommended to store data in a study database so advanced data analysis and data visualization tools can be used.
|
|
Data Analysis & Visualization Tools
Resources:
Tools of the Trade for Mobile Data
|
|
Some tools have a licensing cost. |
|
Location of Code for Automation & Analysis
Resources:
Mobile Technologies Core GitHub Repository
|
|
It is recommended to store code in a repository, like GitHub and to document processes associated with code. |
|
Long-term Data Storage Locations
Resources:
|
|
Some options have a cost. |
About the Author
 |
As the Mobile Technologies Core Manager at the University of Michigan’s Eisenberg Family Depression Center, Victoria Bennett helps investigators navigate the university’s robust resources while perpetually looking for opportunities to curate new resources. She aims to reduce friction for investigators who wish to utilize mobile technologies in health research. Drawing from her extensive experience with entrepreneurship, Victoria applies an entrepreneurial mindset to create efficient systems, improving operational effectiveness and impact.
|
|