Presentation made at the American Public Health Association Meeting, San Francisco, CA. 30 October 2012.
This presentation includes images from the PSFK 'Future of Health' report; content developed from the mHealth Evidence Workshop convened at the National Institutes of Health [16 October 2011]; and mHealth marketing recommendations from Lefebvre RC. Integrating cell phones and mobile technologies into public health practice: A social marketing perspective. Health Promotion Practice, 2009; 10:490-494.
Cervical screening – taking care of your health flipchart (Vietnamese)
Creating the Evidence Base for mHealth
1. Creating the Evidence
Base for mHealth
Txt4Health: Using Mobile Technology in Public
Health Communication and Education Campaigns
American Public Health Association
San Francisco, 30 October 2012
2. Presenter Disclosures
R. Craig Lefebvre, aka chiefmaven
The following personal financial relationships with
commercial interests relevant to this presentation
existed during the past 12 months:
“No relationships to disclose”
3. Mobile Thoughts
When the expectations of
wireless experts are
realized everyone will
have his own pocket
telephone and may be
called wherever he
happens to be…When
that invention is
perfected, we shall have
a new series of daily
miracles (circa 1908).
4. It Took About 100 Years, But Then
It Went Mainstream - Fast.
5. The 7th Mass Media Channel
1 - first personal mass media
2 - permanently carried media
3 - always-on mass media
4 - built-in response
mechanisms
5 - at the point of creative
inspiration
6 - accurate audience
measurement
7 - captures the social context
Tomi T Ahomen. Communities
of people’s lives Dominate Brands blog, 2 May 2008.
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14. mHealth Evidence
Challenges
• Create and evaluate scalable systems capable of
collecting unprecedented amounts of data
• Analyze and integrate that data with other health
information
• Field interventions—some in real time—while at
the same time providing value and protecting the
safety of participants.
15. mHealth Opportunities
• Contributes novel measurement methods and
processes
• Enable the design and delivery of novel
interventions that can be delivered remotely and in
real time
• Offers new methods of data collection and
analysis that can improve the speed and efficiency
of health research and evidence of an intervention
or treatment effect.
16. mHealth Research
Challenges
• Difficult to create controlled and reproducible
environments
• mHealth devices are frequently used by
individuals with little training that may affect their
reliability and validity
• Few gold standard measurements exist in the
mobile environment, self-report measures may be
the most accepted existing assessment
• Risks to privacy and security
17. Evidence Requirements
• Statistical Conclusion Validity - evidence of a
meaningful, causal effect
• Internal Validity - rule out confounders
• Construct Validity - validity of outcome measures
• External Validity - generalizability across
persons, settings, and times
• Ecological Validity – can be implemented in real-
world settings and integrated into life and work
flow
18. When are Randomized
Clinical Trials Indicated?
• Interventions have been shown to be feasible and
acceptable
• Whose efficacy has been demonstrated in quasi-
experimental designs
• There is the desire to demonstrate superiority to
exiting approaches to the same problem
19. Quasi-Experimental Designs
for mHealth
• Pretest-posttest (with and without comparison
conditions)
• N of 1 (with multiple crossover – ABABAB)
• Interrupted Times Series Design – (AAAAB, with
and without comparison groups)
• Stepped Wedge (or delayed treatment)
20. Other Research
Considerations
• Continuous Evaluation of Evolving Interventions
(CCEI) – new versions are added to original
protocol
• Adaptive Interventions - personal tailoring
21. Quality Considerations for
mHealth Interventions
• Selection of • Timing of
appropriate communication
technology
• Understanding of
• Privacy assurances priority group
• Linguistic and literacy • Long-term evaluation
competency
Gurman et al (2012). Effectiveness of
• 2-way mHealth behavior change
communication communication interventions in
developing countries: A systematic
• Targeting & tailoring
review of the literature. Journal of
content Health Communication; 17 (suppl 1):
82-104.
23. Marketing and
mHealth
• How do I use these
technologies to
overcome
psychological and
social barriers
(costs)
• develop new
incentives and
reinforcers
• create new ways of
providing social
support to people
who are trying to
change behaviors?
social support to people who are trying to
change behaviors?
24. Marketing and
mHealth
How can I place-
shift; use SNS, co-
presence and
virtual worlds; and
add GPS to create
scalable behavior
change
programs??
28. R. Craig Lefebvre, PhD
Lead Change Designer, RTI International
University of South Florida College of Public Health
socialShift, Sarasota, FL
social|design, marketing and media
On Social Marketing and Social Change
http://socialmarketing.blogs.com
http://twitter.com/chiefmaven
Editor's Notes
Unisys study – 26 hours to report a loss wallet; 68 minutes for a phone2. Replaces the wrist watch3. 80% physically take it to bed – alarm, txt, phone callsMobile health (mHealth) has the potential to reduce the cost of health care and improve health by providing continuous remote sensing of biological and psychological status at both the individual and population level, encouraging healthy behaviors to prevent or reduce health problems, reducing health care visits, and providing personalized, localized and on-demand interventions in the mobile environment
Recent developments have begun addressing tailoring and optimizing interventions. In Multiphase Optimization Strategy (MOST), promising components of an intervention are identified in a screening phase (say, via factorial or fractional factorial analysis of variance design), the promising components are then refined, and a confirmatory trial such as RCT or Stepped Wedge is conducted on the final intervention. For refining the intervention, Sequential Multiple Assignment Randomized Trial (SMART) can be used where individuals are randomly assigned to various intervention choices several times; in SMARTs scientists decide which treatment decisions require investigation and then use SMARTs to randomize individuals among feasible/ethical options at each treatment decision [Collins’07].
mobile communications are changing our expectations about when and how others are available to us
Mobile phones are not the next ‘magic bullet’ – we need to think of them as part of the personalized media space our people formerly know as ‘audiences’ are creating for themselves. Ubiquity in this increasingly mobile environment will be a key factor for our future successes in public health.