8 1 2012 rapid presentation 3 creatingbehaviorchange

7/29/2019 8 1 2012 Rapid Presentation 3 CreatingBehaviorChange

1/38

RAPID PRESENTATION 3:

Creat ing Behavior Change

Willa Doswel l , PhD, Universit y of Pit t sburgh Tere sia O Connor, MD, Baylor Coll ege of Medi cine

Eri n McClur e, PhD, Johns Hopkins Universit y Bri e Turn er- McGrievy, PhD, Univer sit y of Sout h Caroli na Raj ani Sadasivam , PhD, Uni versit y of Massachusett s Medi cal School


2/38

Using the eButton in Studies

Monitoring ObesityDr. Willa Doswell

Associate Professor

University of Pittsburgh School ofNursing


3/38

The eButton

It is a fully functional wearable computer withsophisticated electronic sensors to collectvisual, location, motion, orientation, acoustic

and/or physiological data (e.g., ECG)automatically.

It is as smart as an iPhone but can be naturallyworn. Since it is unattended and always on,the device has many important applications,such as monitoring diet or physical activity.


4/38

The eButton

Fig. 1 Our prototype eButton.


5/38

How it Works

This small and lightweight eButton has an array of sensors to

perform a variety of measurements, including a GPS, one or

two cameras, a 3-axial accelerometer, a 3-axial gyroscope, a

temperature sensor, a audio sensor, and an indoor/outdoor

sensor.

The cameras take pictures either manually or automatically at

selected rates. The acquired pictures contain foods and

beverages consumed during the day, sedentary and physicalactivities performed, and social interactions with people.

The GPS sensor records geographical information of the wearer

providing information such as outdoor activity locations.


6/38

Freshman-15 Study Revisited

The problem is obesity which has been handledthru classes, public health campaigns, weightreduction programs.

Study Objective: Investigate the changes in bodyweight, BMI, body composition and fatdistribution among college freshmen womenduring their 1st year of college.

Study Objective: Investigate the changes in bodyweight, BMI, body composition and fatdistribution among college freshmen womenduring their 1st year of college.


7/38

Research Questions

What is the % weight gain in college freshmanfrom baseline semester to month 4 and month8?

What is the food intake of students at baseline,month 4 and month 8?

What psychosocial variables affect intake atbaseline, month 4 and month 8?

What are the ethnic differences

What is relationship of stress (3 levels) to weightgain/food intake?


8/38

More Specific Aims

Examine acceptability, and functionality of theeButton in the study of eating habits and weight gain

Refine the development of the eButton device for itsuse in the study of eating habits and weight gain inyoung adults.

Conduct laboratory tests to assess device accuracy.

Modify device design and software to improve

performance during the project according to receivedfeedback.


9/38

IRB Questions

How to preserve confidentiality and privacy in thereal world of eating, working, learning.

How to prevent wear and tear on clothing the

eButton is affixed to. Is the gain worth the problems the device may

cause?

Can it be used in children?


10/38


11/38

Pediatrics

Feasibility of a mHealth childobesity 'app' targetingparents

Teresia OConnor, MD, MPH

Assistant Professor of PediatricsUSDA/ARS Childrens Nutrition Research CenterAcademic General PediatricsBaylor College of Medicine


12/38Pediatrics

Problem: Childhood Obesity 1/3 US children overweight or obese (NHANES data)

Childhood overweight tripled in 25 years (NHANES data)

Overweight Children Overweight Adults (Whitaker 1997, Magarey 2003)

Medical expenditures of obesity related conditions: $147

billion(Health Affairs 2009)

Parents are an important influence on children's behaviorsand therefore their weight status.

- Parenting styles child obesity (Rhee 2006, Brotman 2012)

- Parenting practices child behaviors (Fisher 2002, OConnor 2010, Davison 2003)


13/38Pediatrics

Historical Obesity Interventions

School, childcare and community interventions with no-to-minimal effects

Systematic Review of primary care interventions (Sargent 2010)

- Obesity treatment initiated by pediatricians offers promise of improving

childrens weight status

- Only 1/17 primary care interventions targeted parenting

USPSTF: Evidence for moderate to high intensityinterventions (25 contact hours over 6 months) for children 6 years old. (Barton 2010)


14/38Pediatrics

Helping HAND Pilot Study

First line obesity intervention for primary care 5-8 year old children with 85% BMI > 99%

Monthly visits for 6-months

Delivered by Health Plan health promotion specialistsusing patient-centered counseling

Parent & child self-selected behaviors to target, setgoals and plans, and monitored

Recruited 40 families randomized

20 % attrition; positive feedback; change

in some child and parenting behaviors

(OConnor , C:CHD2011)


15/38

Pediatrics

Parent and neighborhood influenceson Hispanic preschool childrens PA

QStarz BT1000X

GPS data loggers

Actigraph GT3Xaccelerometer

(NIH NICHD-1R21-HD060925)

Variables Whole Sample Sub-sample wore(n= 240) Monitors (n=84)

Neighborhood type (n, %)

High crime, High traffic (orange) 67 (28%) 22 (26%)

High crime, low traffic (green) 22 (9%) 5 (6%)

Low crime, high traffic (pink) 75 (31%) 31 (37%)

Low crime, low traffic (blue) 76 (32%) 26 (31%)


16/38

Pediatrics

How will mHealth Help?

Propose to develop Helping HAND into a mobileHealth app for Smartphones

- Allows increased accessibility of program and increasedcontact with families

- Build in behavior change tools: behavior assessment, goalsetting, implementation plans, monitoring, and feedback

- Remote counseling by Health Advisor via phone

- Has potential to include additional features in future:

GPS specific feedback for PA venues, healthy stores

Accelerometer based assessment with feedback

Similation games for behavior training (KIDDIO)


17/38


18/38

Smoking cessation:

Incentives for behavior changeErin A. McClure

Medical University of South Carolina

2012 NIH mHealth Summer Training Institute


19/38

What is the problem?

Smoking is the leading cause ofpreventable death in the United States

Annual health care expenditures related to

smoking are approximately $96 billion Smoking disproportionately affects ethnic

minorities, socioeconomically

marginalized, and vulnerable populations(Centers for Disease Control, 2008)


20/38

How has the problem beenaddressed?

Psychosocial education, motivational interviewingand enhancement, pharmacotherapy

Incentives to promote abstinence Delivered contingently on biologically-verified

confirmation of abstinence

Highly effective in promoting abstinence fromsmoking, but also (Higgins & Silverman, 2007) Abstinence from other substances of abuse

Medication compliance

Exercise, weight loss, nutrition


21/38

How has the problem beenaddressed?

Implementation and adoption has beenslow

Problems:

Costly (incentives and biological testing)

Frequent samples required

Immediacy of test results and incentive

delivery


22/38

Some mHealth solutions.

Reducing clinic visits Assessments and self-report measures via

voice or text

Frequent monitoring Remote physiological monitoring

Inertial sensors to detect smokingmovements

Immediacy of reinforcer Delivered or alerted via text or voice


23/38

Some mHealth solutions.

Beyond incentive-based interventions

Motivational support upon request at timesof high need

Assessments of real-time craving, lapse,and relapse (Ecological MomentaryAssessment, mobile apps)

GPS-enabled devices to indicate high-risk areas


24/38


25/38

mHealth and Obesity

Brie Turner-McGrievy, PhD, MS, RD

Assistant Professor

University of South Carolina

Arnold School of Public Health

Department of Health Promotion,Education, and Behavior


26/38

Public Health Issue/Problem

Obesity and

prevention/treatment/management ofchronic diseases

Through diet and physical activity


27/38

Obesity Treatment

Behavioral weight loss treatment

How my research is addressing the


28/38

How my research is addressing theissue

Self-monitoring using mHealth

Behavioral counseling delivered viapodcast

Group support via social networks


29/38

How mHealth can help

Improve accuracy

Lower burden (time, memory, etc.)

Lower cost

Increase reach

Lengthen time of support


30/38

Whats next: mHealth and Obesity

Tapping into location-based services

and GPS Learning from behaviors recorded on

mobile devices and tailoring based on

those Predicting who engages in social

networks and why

Customizing interventions based onpersonal preference (one size doesnthave to fit all!)


31/38


32/38

Get to Know Me

Rajani S. Sadasivam, Ph.D.Div. of Health Informatics and Implementation Science

Dept. of Quantitative Health Sciences

Univ . of Massachusetts Medical School

[email protected]

S ki ti h ll


33/38

Smoking cessation challenges

How to increase demand for and use of proven cessation

treatments (NIH State-of-the-Science conference on tobacco use )

How to make existing treatments more attractive?

C t WATI ff ti b t


34/38

Current WATIs are effective, but

Expert-to-patient interventions have a natural limit

Peer-to-peer, collective intelligence, gaming, mHealth

Sh 2Q it P t P f l


35/38

Share2Quit - Peer to Peer referrals

Products exclusively

marketed by peerreferrals

Farmville has over 80

million users on Facebook

Can peer referrals be

used to market health

interventions?Facebook referral

Email referral

Collecti e intelligence for comp ter tailoring


36/38

Collective intelligence for computer tailoring

Amazon, Netflix Products like these, People like you

Computer tailoring Messages like these, Smokers like

you

CraveOut: mHealth gaming platform


37/38

CraveOut: mHealth gaming platform

A fun way to distract from cravings and reinforce

benefits of quitting

Available on iTunes (Total downloads: 1067 as of 7/24/12)


38/38

8 1 2012 rapid presentation 3 creatingbehaviorchange

Documents