Harnessing information technologies to promote

Transcription

Harnessing information technologies to promote
Harnessing Information
Technologies to Promote PopulationWide Behavioral Health Solutions
Abby C. King, PhD
Healthy Aging Research & Technology Solutions Lab
Stanford Prevention Research Center (SPRC)
Health Research & Policy Dept.
Stanford University School of Medicine
© Stanford University
NIA AG16587, NCI CA127511, NHLBI HL116448, OCH, CIGH
Stanford Prevention Research
Center’s Vision
Drive the Science of Healthy
Living for All
through cutting-edge health
promotion & chronic disease
prevention/ management strategies
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Targeting “actual” drivers of noncommunicable disease
3 Risk Factors
lead to
4 Major Chronic
Diseases
Tobacco
Diet
50%
of
Global
Mortality
Oxford Health Alliance
www.oxfordvision2020.org
Inactivity
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Advancing Strategies for Inciting Healthy
Behavior Change on a global scale:
• Nudge: Individual-level interventions that alter
propensity to engage in a behavior
• Disrupt: Interventions aimed at systems/environments
that facilitate problematic habits
• Leapfrog: Bundle and link interventions to promote
synergy
• Reach: Seek out marginalized groups to address
differential risks/disparities
Scalable
Nudge:Improving decisions about health, wealth, and
happiness , by Richard Thaler & Cass Sunstein, 2008
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“Borderless” Health Promotion
Information Technology Solutions (examples)
Nudge: IVR & Smartphone apps
for evidence-based, customized
health behavior advice & support
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(CHAT)
Estimated Energy Expenditure in MVPA (7-day PAR)
1.85
*
MVPA (kcal/kg-1/day-1)
1.70
*
Human
Phone Advice
1.55
*
1.40
†
(N.S.)
Automated
Phone Advice
1.25
Control
1.10
.95
.80
0
Baseline
6 mo.
*Intervention > control, p < .01;
12 mo. 18 mo.
†Intervention > control, p = .05
King AC et al., Health Psychol, 2007; 2013
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MILES – ‘Walk more, Sit less’ Apps
Analytic Affect/Game-like
Social
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MILES – Early Results
(n = 30 inactive, smartphone-naive adults ages > 45 yrs)
2-mos Daily Increases in MVPA
MVPA Daily Minutes Smartphone Accelerometer
20
15
10
5
Analytic
King, Hekler, Grieco, et al., PLOS One, 2013
Affect
Which App for WHOM?
Social
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“Borderless” Health Promotion
Communication Technology Solutions (examples)
Nudge: IVR & Smartphone apps for
evidence-based, customized health
behavior advice & support
Disrupt: Empower “citizen
scientists” to assess & advocate
for healthier neighborhoods
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residents use Stanford Healthy
Neighborhood Discovery Tool
Electronic
Tablet
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Aggregated View for Policymakers
(‘crowd-sourcing’ tool to empower residents)
Runnymeade Gardens Senior Housing, East Palo Alto
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NEAAT Successes
• Older low-income Residents identified
neighborhood barriers to PA/food &
advocated for changes
• East Palo Alto City Council allocated
~$400,000 for needed city-wide sidewalk
repairs & improvements (e.g., shade trees) to
facilitate walking
• This “citizen scientist” model is being
tested in N. Fair Oaks & other countries
(Mexico, UK, Israel)
Stanford Prevention
Research Center
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“Borderless” Health Promotion
Communication Technology Solutions (examples)
Nudge: IVR & Smartphone apps for
evidence-based, customized health
behavior advice & support
Disrupt: Empower “citizen
scientists” to assess & advocate for
healthier neighborhoods (crowd-sourcing)
Leapfrog: Combine
neighborhood advocacy with
clinical provider outreach
+
Stanford Prevention
Research Center
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“Borderless” Health Promotion
Communication Technology Solutions (examples)
Nudge: IVR & Smartphone apps for
evidence-based, customized health
behavior advice & support
Disrupt: Empower “citizen
scientists” to assess & advocate for
healthier neighborhoods (crowd-sourcing)
Leapfrog: Combine neighborhood
advocacy with clinical provider
outreach
Reach: Multi-lingual virtual
advisors for pops. with low literacy
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Carmen
(Culturally adapted, bi-lingual)
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COMPASS - RESULTS
4-month Change in Minutes of Walking/Week [CHAMPS]
(N = 40)
*
300
* p < .0008
Change in Mins/Wk
250
200
150
100
50
0
Wait-list Control
King, Bickmore et al., J Health Communication, 2013
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At 4-month Post-test, Intervention
participants indicated that . . .
• ‘Carmen’cared about them (mean rating = 6.2
out of 7)
• Felt close to & trusted ‘Carmen’ (mean= 6 out
of 7)
• Were interested in continuing to work with
‘Carmen’
(from Working Alliance Inventory);
King, Bickmore et al., J Health Communication, 2013
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Areas for Collaboration include:
• Biomonitoring/sensor linkages (enhanced
personalized, dynamic feedback)
• Adaptations to other underserved populations
(local, global)
• Diffusion of behavior change through social
networks & media
• Experimentation within Cohort studies
• Healthcare system linkages
• Others?
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Thanks!
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