daihua yu, ms 1,3 , bambang parmanto , phd 1 , 3 & brad dicianno , md 2,3
DESCRIPTION
The Accessibility Needs of Patients with Dexterity Impairments to Use mHealth Apps on Smartphone. Daihua Yu, MS 1,3 , Bambang Parmanto , PhD 1 , 3 & Brad Dicianno , MD 2,3 . 1 Department of Health Information Management 2 Department of Physical Medicine and Rehabilitation - PowerPoint PPT PresentationTRANSCRIPT
Daihua Yu, MS1,3, Bambang Parmanto, PhD1, 3 & Brad Dicianno, MD2,3
1Department of Health Information Management2Department of Physical Medicine and Rehabilitation
3Rehabilitation Engineering Research Center (RERC) on Telerehabilitation
THE ACCESSIBILITY NEEDS OF PATIENTS WITH DEXTERITY IMPAIRMENTSTO USE MHEALTH APPS ON SMARTPHONE
OBJECTIVE & TARGET POPULATION
Goal: to explore and to identify the accessibility needs and preferences for Persons with disabilities (PwDs) to use mobile health smartphone apps.
Target Population: Persons with dexterity impairments
MOTIVATION Market penetration (US) reached 55% in early 2013 (comScore Incorporation, 2013).
4.04 million dexterity impairments in US (Pleis et. al., 2010) .
The smartphone is an ideal tool for implementing wellness programs for PwDs (Holman, 2004).
Smartphones poses accessibility challenges: 1)Lack of screen space (Brewster, 2002); 2)Small form factors, low contrast and tiny text,
and undifferentiated keys (Abascal & Civit, 2000; Kane et. al., 2009);
3)Unnecessary steps (Kurniawan et. al., 2006).
METHOD – INTRODUCTION TO IMHEREiMHere ( iMobile Health and Rehabilitation), a novel
mHealth platform that has been developed to support self-care in the management of chronic and complex conditions (Parmanto et. al., 2013).
Two-way Communicati
on
METHODDexterity impairments: Purdue Pegboard Assessment (Lafayette Instrument, 2002)
Face-to-face orientationOne-week field trial Lab test with in-depth interview
1) Task 1: scheduling a new medication alert;
2) Task 2: modifying a medication reminder;
3) Task 3: scheduling a skin check up alert;
4) Task 4: responding to a skincare reminder.
METHODS – MEASUREMENTS 1. Error Ratio 2. Difficulty-on-Performance (DP): the sum of weighted scores
are divided by the total steps to complete a task. Weighted scores have been added to all errors:
1 – solve the problem without any help, 2 – need help in one sentence, 3 – need help in two to four sentences, 4 - unable to solve the problem.
3. Telehealth Usability Questionnaire (TUQ) 4. Structured Open-ended Questions
RESULT – BACKGROUND N = 9 subjects with dexterity impairments 4 tasks Ages ranged: 18 – 55 4 women, 5 men 8 spina bifida patients, & 1 patients with spinal cord injury (SCI)
RESULTS – ERROR RATIO
ANOVA: F (2, 33) = 3.604, p=0.038, significantPearson Correlation: A moderately negative correlation was identified between subjects’
dexterity levels and their error ratios, r = -0.434, n=36, p= 0.004
Sub Task 1 Task 2 Task 3 Task 4 AverageGroup Avg
Group 1: Mild
5 6.25% 12.50% 0.00% 10.00% 7.19%
8.83%
6 12.50% 12.50% 0.00% 0.00% 6.25%7 12.50% 25.00% 0.00% 12.50% 12.50%9 0.00% 25.00% 0.00% 12.50% 9.38%
Group 2: Moderate
1 13.33% 12.50% 0.00% 10.00% 8.96%
9.69%3 0.00% 0.00% 0.00% 0.00% 0.00%4 6.25% 37.50% 16.67% 20.00% 20.10%
Group 3: Severe
2 17.65% 25.00% 16.67% 37.50% 24.20%19.65%8 6.25% 25.00% 16.67% 12.50% 15.10%
Total Avg 8.30% 19.44% 5.56% 12.78% 11.52% 12.72%
RESULTS – DIFFICULTY-ON-PERFORMANCE
Pearson Correlation: An increasing in error ratio might significantly increase the difficulty-on-
performance for user in completing tasks (r=0.724, n=36, p<0.001).
ANOVA: F(2, 33), p=0.983
Sub Taks 1 Task 2 Task 4 Task 5 Average Group AvgGroup 1: Mild
5 25.00% 50.00% 0.00% 40.00% 28.75%
20.47%
6 43.75% 37.50% 0.00% 0.00% 20.31%7 25.00% 25.00% 0.00% 37.50% 21.88%9 6.25% 25.00% 0.00% 12.50% 10.94%
Group 2: Moderate
1 33.33% 25.00% 0.00% 40.00% 24.58%
20.63%3 0.00% 0.00% 0.00% 0.00% 0.00%4 25.00% 87.50% 16.67% 20.00% 37.29%
Group 3: Severe
2 23.53% 25.00% 16.67% 37.50% 25.67%21.69%8 16.67% 25.00% 16.67% 12.50% 17.71%
Total Average: 22.06% 33.33% 5.56% 22.22% 20.79% 20.93%
RESULTS – TELEHEALTH USABILITY QUESTIONNAIRE
Average TUQ score: 5.9 out of 7 (84.29%)
DISCUSSIONInstructive Guidance: About 51% of errors were self-corrected without any help, but other errors
called for resolution from a researcher and received higher-weighted scores for difficulty-on-performance.
Personalized target size: User frustrations were identified regarding text entry and accessing buttons. Functional button: Subjects with severe dexterity impairments needed help from a family member
or clinical staff to take a photo. Several of them are not very comfortable using the in-screen camera button.
The use of colors: Suggested to extended to application level. Contrast: They might be more comfortable with dark text on a white background or try
different pictures.
Need
sPr
efer
ence
s
Needs for Personalization
CONCLUSION Users want to have simpler apps with easier processes Approach to accessible and personalized smartphone apps:
Accessible Smartpho
ne App
Physical Presentation
(User Interface)
Navigation(Streamlined procedures)
Preferences Shortcuts
ACKNOWLEDGEMENT
This study is funded by Grant #1R21HD071810-01-A1 from the National
Institute of Child Health and Human Development (NICHD), USA.
REFERENCESPleis, J. R., Ward, B. W., & Lucas, J. W. (2010). Summary health statistics for U.S. adults: National Health
Interview Survey, 2009. Vital and health statistics. Series 10, Data from the National Health Survey(249), 1-207.
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Brewster, S. (2002). Overcoming the Lack of Screen Space on Mobile Computers. Personal Ubiquitous Computing. 6(3), 188-205.
Cipresso, P., Serino, S., Villani, D., Repetto, C., Selitti, L., & Albani, G. (2012). Is your phone so smart to affect your state? An exploratory study based on psychophysiological measures. Neurocomputing, 84(23-30).
comScore Incorporation. (2013). comScore Reports January 2013 U.S. Smartphone Subscriber Market Share.
Han, D., Lee, M., & Park, S. (2010). THE-MUSS: Mobile u-health service system. Comput Methods Programs Biomed. 97(2), 178-188.
Holman, H. (2004). Chronic disease--the need for a new clinical education. JAMA : the journal of the American Medical Association. 292(9), 1057-1059.
Kane, SK, Jayant, C., Wobbrock, JO, & Ladner, RE. (2009). Freedom to roam: a study of mobile device adoption and accessibility for people with visual and motor disabilities. Paper presented at the 11th international ACM SIGACCESS conference on Computers and accessibility.
QUESTIONS?
THANKS!
Contacts:Daihua Yu, [email protected] Parmanto, [email protected] Dicianno, [email protected]
RESULT: DEXTERITY LEVELS
Group 1) Mild: From -3 S.D. to -2 S.D including subject #5, #6, #7 and #9;
Group 2) Moderate: below -3 S.D. including subject #1, #3, #4;
Group 3) Severe: Not able to complete Purdue Pegboard tests, including subject #2 and #8.
Male & FemaleGeneral factory Work (n=282)Average = 46.76,-1S.D.= 42.72,-2S.D.= 38.68, -3S.D.= 34.64.