Ang Li1 Steven Chall, MS2 1 DNSc1 PhD1 · Ang Li1 Steven Chall, MS2 Sherry Wenshun Liu1 Allison...
Transcript of Ang Li1 Steven Chall, MS2 1 DNSc1 PhD1 · Ang Li1 Steven Chall, MS2 Sherry Wenshun Liu1 Allison...
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Results
The Challenges of Disparate Data Formats: Analysis and Visualization in the SLIDES Project Ang Li1 ● Steven Chall, MS2 ● Sherry Wenshun Liu1 ● Allison Vorderstrasse, DNSc1 ● Constance M. Johnson, PhD1
1 Duke University, Durham, North Carolina 2 Renaissance Computing Institute, Chapel Hill, North Carolina
To evaluate preliminary effects of VE participation on metabolic outcomes in the SLIDES
study, we developed an Internet visualization tool with a user-friendly interface for
dynamic processing of multidimensional data.
This visualization tool was designed to accommodate data in disparate formats.
Multidimensional Process Data from SLIDES Project
We collected multidimensional data over a period of 6 months.
Quantitative data included but were not limited to:
• Movement, interactions with objects and other participants, proxemics
• Time spent in the site, frequency of log-ins
Qualitative data included: Observational data, voice, text, email, forum, focus groups
Visual data included: Photos, videos
Quantitative variables included:
Demographics
Perceived usefulness
Perceived ease of use
Presence
Co-presence
Metabolic indicators: BMI, HbA1c, BP
Diabetes knowledge
Self-efficacy
Self-management behaviors
• Diet, exercise, foot care, glucose testing, smoking
Perceived support for diabetes management
• Professional, family, friends
Initially, visualizations were created using the
R environment (open-source data analysis
and statistical computing software).
Visualization capabilities were extended by:
Incorporating R-Shiny libraries (which include
a larger repertoire of visualization approaches
plus web deployment).
Applying D3.js JavaScript libraries (which add
capability to animate results, as well as more
versatility and power).
User interface includes an animated dashboard
(shown at right).
Provides multiple views of multidimensional data beyond the traditional 2-D perspective.
Using color, shapes, volume, and animation facilitates exploration of the data through visual images.
Dynamic drawings can uncover evolutionary paths of change over time.
Animation allows combination of multiple types of data, highlighting temporal aspects of the data.
Visualization: Why?
Text transcribed from
audio recordings of
participant conversations
Survey
results
Biometric
measurements
Numerical
avatar positions
within the VE
Images
video
&
Visualization
Tool
Sees New
Thematic
Patterns
in Data
The dashboard which shows different visualizations
of our data are animated.
Moving the mouse over the various visualizations
provides different views of the data on a single
screen, yielding more in-depth understanding.
If a user wants to view just one or two visualizations,
the functionality of this dashboard allows the user
to drill down to look at the specifics of the data.
The Dashboard Visualization: How?
Methods: Analysis and Visualization
Development of Visualization Tool
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Visualization allowed us to see through animation how each subject’s weight, HbA1c
(indicator of metabolic control), and corresponding VE activity level changed over the
course of the study (6 months).`
Results
Heat Maps: Visualization of Locations in VE Visited by Subjects
Animated Visualization of Changes in
Subjects’ Weight, Hb1AC, and Activity in Virtual Environment
Animated Visualization Showing the Amount of Participation
by Each Subject at Each Location in the Virtual Environment
This visualization shows that Subject 7
clicked on objects in the site 386 times
during the 6-month SLIDES study.
S13:
90 times
S7:
386 times
Subjects Subjects
Objects in
the virtual
environment
Objects in
the virtual
environment
This visualization shows that Subject 13
clicked on 90 different food items over
the course of the 6-month SLIDES study.
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The sequence of screen shots above is from an animated browser-based visualization
which shows these characteristics for SLIDES at baseline, 3 months, and 6 months.
In each graph, the horizontal axis is weight and the vertical axis is HbA1c.
Each subject is represented by a circle with a unique color, so individuals can be followed
over time.
When the mouse is clicked over any circle, the visualization will identify the subject.
The area of the circle represents the amount of that person’s participation in the site.
Screenshots below show that Subject A decreased her HbA1c and lost weight over the 6 months.
Weight
Hb
A1
c
Weight Weight
Hb
A1
c
Hb
A1
c
Baseline 3 months 6 months
Heat maps show the locations
within the virtual environment
that were visited by SLIDES
participants within a single week.
The heat map is not automatically
animated; use slide bar at bottom
to select a week for analysis.
Screenshots of heat maps that
show locations visited by
participants during:
• first week of the study (“0”, left)
• first week of the second half of the study (“12”, right).
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Type 2 Diabetes (T2D) is a chronic disease epidemic in the U.S.
Individuals with T2D provide 99% of their own care.
Self-management includes diet, exercise, glucose testing, etc.
Self-management goal for persons with T2D: Achieving metabolic control, which reduces the
morbidity and mortality associated with this disease.
Achieving this goal through self-management is challenging for many persons with T2D.
Innovative interventions to empower patients in diabetes self-management are
needed.
In response to this need, we developed and tested the SLIDES Project, an intervention for
adults with T2D which uses a virtual environment (VE) to provide education about diabetes
self-management and ongoing support.
To analyze the multidimensional data collected during a 6-month test of this intervention,
we employed innovative visualization techniques.
SLIDES (eHealth: Second Life Impacts Diabetes Education and Self-Management)
This intervention uses a virtual environment (VE) to provide ongoing education and
support to adults with T2D.
SLIDES Program was designed within the popular online multi-user platform Second Life.
The VE was available 24/7 on the Internet, minimizing access barriers.
The SLIDES Program offered:
Weekly synchronous diabetes education classes
Group meetings
Social networking in a virtual community in which participants practiced real-world skills such as
grocery shopping, exercising, and dining out, allowing for interactive knowledge application.
SLIDES Study Design
One group, Pre-Mid-Post Study
Phase 1: First month
Oriented to the site
Baseline survey administered
Metabolic information (HbA1c, height, weight, BP)
Visit site 2x / week (classes, interactive sessions, other)
Phase 2: Next five months
Visit site at will (classes, interactive sessions, other)
Survey and metabolic information at 3rd month
Phase 3: Sixth month
Survey, metabolic information, and focus groups
The SLIDES community
Background
` SLIDES Project: Intervention for Adults with T2D
SLIDES Study Sample
20 participants with Type 2 Diabetes
21 ‒ 75 years old
Computer and internet literate
Broadband connection
No severe diabetes-related complications
or late-stage chronic disease
Graphics can be combined
to compare changes over time
in variables with disparate
data formats.
Composite graphics at left
allow comparison of objects
touched to changes in
subjects’ visits to VE sites.
Combining Graphics
BMI Change Over 180 days
Conclusions
Changes in Self-Efficacy and
Social Support Over 6 Months
Hovering the mouse over each line shows the
participant and change in BMI over 6 months
This animated browser-based visualization
shows how self-efficacy and social support
changed from baseline to six months. These
changes were statistically significant.
Further Examples of Visualization
Self-Efficacy
So
cia
l S
up
po
rt
Baseline
6 months
We developed an internet data visualization tool for analysis of data in disparate formats
from the SLIDES Project.
The tool generates a variety of visual representations to facilitate recognition of patterns
and temporal relationships in the data.
These visualizations help to show how data clusters, which in turn helps researchers to
see new dimensions in large and diverse data sets
Spatial transformation of data collected from SLIDES participants in disparate formats
revealed trends and phenomena that could not be identified using traditional graphs.
Visual representation of the data with animation made salient information more apparent,
and enhanced our understanding of how time and group dynamics may affect
self-management of T2D.
Major challenges remain in integrating the wide variety of data gathered in the SLIDES
study, including problems with rendering raw audio data into a format suitable for analysis,
extracting meaning from the resulting text, and especially performance.
Finding solutions to these problems could be beneficial to researchers who use mixed
methods approaches to analyze healthcare “big data”.
As the interactive web becomes a popular mode of delivery of health information, we need
interactive research tools to better understand the outcomes of these studies.