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.

Abascal, J., & Civit, A. (2000). Mobile Communication for Older People: New Opportunities for Autonomous Life. Paper presented at the The 6th ERCIM Workshop.

Boyer, EW, Smelson, D., Fletcher, R., Ziedonis, D., & Picard, RW (2010). Wireless Technologies, Ubiquitous Computing and Mobile Health: Application to Drug Abuse Treatment and Compliance with HIV Therapies. J Med Toxicol, 6(2), 212-216.

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, dxy1@pitt.eduBambang Parmanto, parmanto@pitt.eduBrad Dicianno, dicianno@pitt.edu

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.