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Uncovering the Drivers and Inhibitors of Mobile Health Information Services Usage in the United States
Dr. Arun RaiRegents’ Professor and Harkins Chair
Center for Process Innovation & CIS Department
Robinson College of BusinessGeorgia State University
Atlanta, U.S.A.E-mail: [email protected]
Web site: arunrai.us
3rd International Conference on Transforming Healthcare with IT 31st Aug.-1st Sep. 2012Hyderabad, India
Liwei ChenDoctoral Student
Center for Process InnovationRobinson College of Business, Georgia State University
Atlanta, U.S.A.E-mail: [email protected]
Jessica PyeDoctoral Student
Center for Process InnovationRobinson College of Business, Georgia State University
Atlanta, U.S.A.E-mail:[email protected]
Study Background
PurposeAdoption status of mHealth in the U.S.
Channel preference between in-person doctor visits and mHealth
What influences adoption and channel preference
ProcedureOnline survey assisted by a market research company
Pilot followed by a large scale study
1132 valid responses
Sample Characteristics
• AgeMean = 45 yrsRange: 18 – 86 years20% over 60 years
Balanced gender distribution
• Income38% < 25 K USD/year30%: >=25 K & <50K/year19%:>= 50K & <75K /year12%: >= 75 K/year
• Education1.6%: Below high school 18.6%: High school (12th std)30.4%: Some college, no degree13.6%: Associate’s degree25.3%: Bachelor’s degree10.5%: Advanced degree
Adoption of mHealth Services
Intention to Use mHealth Services
Mean = 4.09, s.d. = 2.02 Mean= 3.20, s.d.= 2.23
Usage Frequency of mHealth Services
Comparative Snapshot of Mobile Services Adoption
work
Coarse Framing of Channel Preference:In-Person Doctor Visit or mHealth?
Mean= 2.36, s.d.=1.83
Example Item: “My overall feeling is that…”
Digging Deeper into Channel Preference: Substitutes or Complements?Using mHealth as a substitute to doctor visits?
Using mHealth as a complement to doctor visits?
Example Item: • “I am willing to use mobile health services instead of doctor visits”.
Example Item: • “I am willing to use mobile health services in addition to doctor visits”.
47%67%
(I) Candidate Predictors: Health Conditions
Example Item: • “I feel I am…”.
Example Item: • “I feel vulnerable to severe chronic diseases in the next five years”.
Mean=5.29, s.d.=1.46 Mean=4.01, s.d.=2.02
Healthiness Vulnerability78.9% 60.8%
(II) Candidate Predictors : Innovativeness with IT/Mobile Services
Mobile IT innovativeness Usage Innovativeness of Mobile Service
Example Item: “If I heard about a new mobile service, I would look for ways to experiment with it”.
Index Measure: weighted sum of mobile services use, where the weight is
Mean= 21.85, s.d.= 10.06Mean= 4.18, s.d.= 1.93
Predicting Adoption: Intention to Use mHealth Services
Higher intention to use mhealth for those more innovative with IT. Intention becomes stronger for those who are also more vulnerable or more healthy.
Predicting Adoption: Frequency of mHealth Use
Greater frequency of mhealth use by those more innovative with IT. This increases for those who are also more vulnerable or more healthy.
Predicting Channel Preference: mHealth Use as a Substitute to In-Person Doctor Visits
Greater preference for mhealth as a substitute by those more innovative with IT. This increases for those who are also more vulnerable or more healthy.
Predicting Channel Preference: mHealth Use as a Complement to In-Person Doctor Visits
Greater preference for mhealth as a complement by those more innovative with IT. This increases for those who are also more vulnerable or more healthy.
Wrap-Up
mHealth diffusion: 38% initiated use; 19% @ regular use Preference (No surprise): Much stronger preference for doctor visitsPreference (Surprise): 47% favorable to mHealth as a substitute; 67% favorable to mhealth as a complement Adoption/channel preference: Promoted by IT innovativeness and reinforced by health vulnerability and state of healthiness Practical implication: Differentiate mHealth on-boarding and progression strategies based on (i) IT innovativeness, (ii) health vulnerability, and (iii) state of healthiness; shift from coarse demographics to health and IT dispositions
Uncovering the Drivers and Inhibitors of Mobile Health Information Services Usage in the United States
3rd International Conference on Transforming Healthcare with IT 31st Aug.-1st Sep. 2012Hyderabad, India
Dr. Arun [email protected]
Web site: arunrai.us
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