Creating the Evidence Base for mHealth


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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.

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  • 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.
  • Creating the Evidence Base for mHealth

    1. 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. 2. Presenter Disclosures R. Craig Lefebvre, aka chiefmavenThe following personal financial relationships withcommercial interests relevant to this presentationexisted during the past 12 months: “No relationships to disclose”
    3. 3. Mobile ThoughtsWhen the expectations ofwireless experts arerealized everyone willhave his own pockettelephone and may becalled wherever hehappens to be…Whenthat invention isperfected, we shall havea new series of dailymiracles (circa 1908).
    4. 4. It Took About 100 Years, But Then It Went Mainstream - Fast.
    5. 5. The 7th Mass Media Channel1 - first personal mass media2 - permanently carried media3 - always-on mass media4 - built-in responsemechanisms5 - at the point of creativeinspiration6 - accurate audiencemeasurement7 - captures the social context Tomi T Ahomen. Communitiesof people’s lives Dominate Brands blog, 2 May 2008.
    6. 6. 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.
    7. 7. 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.
    8. 8. 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
    9. 9. 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
    10. 10. 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
    11. 11. 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)
    12. 12. Other Research Considerations• Continuous Evaluation of Evolving Interventions (CCEI) – new versions are added to original protocol• Adaptive Interventions - personal tailoring
    13. 13. 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.
    14. 14. Marketing andmHealthHow do I addmHealth featuresto my behaviorchangeproducts, services andprograms??
    15. 15. Marketing andmHealth• 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?
    16. 16. Marketing andmHealthHow can I place-shift; use SNS, co-presence andvirtual worlds; andadd GPS to createscalable behaviorchangeprograms??
    17. 17. Marketing andmHealthHow do I facilitateconversationsamongpeople, not aimmessages atthem?
    18. 18. Are we available when, whereand how people want us to be?
    19. 19. R. Craig Lefebvre, PhD Lead Change Designer, RTI InternationalUniversity of South Florida College of Public Health socialShift, Sarasota, FL social|design, marketing and media On Social Marketing and Social Change