Personally Tailored Health Information: a Health 2.0 Approach [4 Cr3 1100 Bonander]Presentation Transcript
Bonander, J. Personally Tailored Health Information: A Health 2.0 Approach
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Personally Tailored Health Information: A Health 2.0 Approach Jason Bonander, MA Centers for Disease Control and Prevention National Center for Public Health Informatics Atlanta, Georgia, USA September 4, 2008
Tailored health information and Web 2.0 thinking
Hypothesis and logic model
Findings / discussion
20, lives in a suburb of San Francisco, CA; a student at the local community college, a social drinker and doesn’t consider himself a smoker (though he smokes socially); enjoys the outdoors (mountain biking, skate boarding) has many friends, and passionate about music and movies; uses multiple social networking sites (MySpace, Facebook, Ning)..
What if tailored health information could be delivered to Jacob that addressed key health protection themes such as alcohol use, smoking related health issues, injury prevention, STD prevention, positive social and emotional health?
36, working mom, married with children and living in St Paul, MN; a social drinker and non-smoker, but her husband smokes; shares family pictures and has a long list of favorite television shows and movies; uses social networking sites to keep in touch with current friends and to make new ones; also a member of specific health causes (e.g. fighting breast cancer).
What if tailored health information could be delivered to Sally that addressed key health protection themes for herself and her family such as physical activity, chronic conditions, reproductive health, cancer, smoking-related health issues, social well being, immunizations?
Online social networking and health conceptual landscape KEY growth online social network use and health info seeking Online health SNA research Christakis & Fowler Moreno Behavior Change Models Tailoring Informatics tools NLP Text analytics Vocab/ ontology Chronic / infectious disease prevalence strong emergent nascent Behavioral economics Trust Reciprocity Groups
Tailoring and Changing Behavior
Increasing interest and focus in tailoring health information to change behavior and improve health and wellbeing
Effective with smoking cessation, weight loss, physical fitness, cancer screening, nutrition
High touch / low reach vs. low touch / high reach
Engagement over time
Time consuming questionnaires
Content development / availability
Recent work in SNS and Health
Christakis and Fowler (NEJM 2007; 2008)
Social distance over geographical distance risk influencer for obesity
Collective interventions may be more effective than individual interventions
Moreno, et al (MedGenMed 2007)
Significant risk behavior demonstrated among teens in MySpace
Sexual activity, alcohol, drug and cigarette use
Mishra, et al (on going research at CDC)
NLP and text analytics applied to online risk behavior
Enough information exists on an individual’s social networking page(s) to be useful in generating meaningful, tailored health messages ......
If so, could informatics tools be used to “discover” such information
If so, what would the context of engagement look like so as to not feel creepy , to stimulate behavior change and potentially even stimulate this through social networks
Logic Model Knowledge garnered and tailored information presented Altruism & sharing with public health Social distance Collective interventions risk behavior Improved health and wellbeing Informatics Tools Theoretical models Interest Trust Reciprocity I T R I T R I T R I T R I T R