Presentation on theme: "Michael P. O’Donnell, PhD, MBA, MPH AMSO & His POSSE: A Framework to Develop Effective Organization and Individual Behavior Change Programs."— Presentation transcript:
Michael P. O’Donnell, PhD, MBA, MPH AMSO & His POSSE: A Framework to Develop Effective Organization and Individual Behavior Change Programs
What Works Best? Strategy to Develop the Framework Systematic Benchmarking study –Good, very good, best programs Systematic literature reviews –Health impact of programs –Financial impact of programs Refining framework Background C Everett Koop Award –Health impact –Financial impact Composite reviews –1800+ manuscripts Design/manage programs –100+ organizations
Sampling of Theories Not to mention the statistics! Individual level Learning Theories Information processing Health Belief Model Protection Motivation Theory; Extended Parallel Process Model Theories of Reasoned Action, Planned Behavior, and Integrated Behavior Model Goal-Setting Goal goal-directed behavior Automatic behavior, impulse behavior, habits Transtheoretical Model of Behavior Change Precaution Adoption Process Model and risk communication Attribution Theory and Relapse Prevention Communication-Persuasion Matrix Elaboration Likelihood Model Self Regulation Interpersonal environment Social Cognitive Theory Stigma and Discrimination Diffusion of Innovation Social networks and social support Multi-level Systems Power Empowerment Organization level Stage Theory of Organization Change Stakeholder Theory Community level Coalition Theory Social Capital Theory Social norms Conscientization Community Organization Society and government level Agenda-building Multiple Streams Advocacy Coalition Source: Bartholomew LK, Parcel GS, Kok G, Gottleib NH, Fernandez ME, Planning Health Promotion Programs, 3 rd 2011, Jossey-Bass
Note: Data from participating states and the District of Columbia were aggregated to represent the United States. Source: Behavioral Risk Factor Surveillance System CD-ROM (1984-1995, 1996, 1998) and Public Use Data Tape (2000, 2003, 2005, 2007), National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 1997, 1999, 2000, 2001, 2004, 2006, 2008. Trends in Consumption of Five or More Recommended Vegetable and Fruit Servings for Adults 18 and Older, US, 1994-2007
Trends in Prevalence (%) of No Leisure-Time Physical Activity, by Educational Attainment, Adults 18 and Older, US, 1992-2007 Note: Data from participating states and the District of Columbia were aggregated to represent the United States. Educational attainment is for adults 25 and older. Source: Behavioral Risk Factor Surveillance System CD-ROM (1984-1995, 1996, 1998) and Public Use Data Tape (2000, 2002, 2004, 2005, 2006, 2007), National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 1997, 1999, 2000, 2001, 2003, 2005, 2006, 2007, 2008. Adults with less than a high school education All adults
Effects of Integrated Medication and Behavioral Interventions 0 5 10 15 20 25 30 No Behavioral Therapy Brief Advice Behavioral Therapy No Medication Medication Typical Long Term Quit Rates Rates doubled with brief advice & triple combining pharmacological and behavioral inventions Hughes JR. CA Cancer J Clin. 2000; 50: 143-151.
Best Science for Tobacco Treatment Meta-analyses of 27 different topics Combined approaches: Brief MD advice+ behavior therapy + medication Minutes of therapy: 300 Number sessions: 8 Type and number of staff: 2-3 including one physician Medication type: outcomes by medication Behavioral therapy type: outcomes by type Treating Tobacco Use and Dependence: 2008 Update, Fiore, et al, HHS
Best Methods for Weight Control? ? ? ? ? ? ? ? ?
Workplace Health Promotion Overall Processes What Works in Worksite Health Promotion: Systematic Review Findings and Recommendations from the Task Force on Community Preventive Services Robin E. Soler, Nicholaas Pronk, Ron Goetzel American Journal of Preventive Medicine Volume 38(2) Supplement 2, February, 2010 The Community Guide http://www.TheCommunityGuide.org/worksite
Methodology Search databases: Medline, Employees Benefits,NTIS, Sports Information Resource Guide, Cambridge Scientific Abstracts, Business Week, ABI Inform, Health Promotion and Education, Cumulative Index to Nursing and Allied Health Literature, Office of Smoking and Health, AIDSLine, PsychInfo, and Sociological Abstracts Inclusion Criteria 1. Primary research in peer review journal or technical report 2. Published January 1980-June 2005 3. Meet research quality criteria 4. Evaluate impact of workplace health promotion program 5. Measure change in one or more outcomes of interest Studies found 1. Abstracts and titles: 4,584 2. Studies examined in detail: 334 3. Studies meeting all criteria: 86 Ratings 1. Study design: threats to internal validity: greatest, moderate, least 2. Quality of execution: good, fair, limited 3. Effect size: quantitative, qualitative
Scope of Review Health Assessment with Feedback vs Health Assessment with Feedback Plus Intervention Incentives and Competition to Reduce Tobacco Use Smoke-free Policies to Reduce Tobacco Use Point of Decision Prompts to Increase Stair Use
Health Assessment with Feedback Conclusion Conclusion: Insufficient evidence to recommend Reasons Reasons: Small effect size Small number of studies (32) Poor study design
Health Assessment with Feedback Plus Intervention* Conclusion Conclusion: Strong evidence of effectiveness Tobacco use (30) - 1.5 % pp prevalence- 2.3 % consumption Dietary fat consumption (11) - 5.4 % pp prevalence Blood Pressure control (31) - 4.5 % pp prevalence Cholesterol management (36)- 6.6 % pp prevalence- 4.8 mg/dl Absence from work (10)- 1.2 days/year less Conclusion Conclusion: Sufficient evidence of effectiveness Seat belt use (10)- 27.6 % pp prevalence Heavy drinking (9)- 2.0 % pp prevalence Physical activity (18)-15.3 % pp prevalence Health risk score (21) Medical utilization (7) Conclusion Conclusion: Insufficient evidence of effectiveness Fitness (9)positive outcomes small effect sizes, multiple measures Body composition (27) - BMI (8)-.5 BMI unitconsistent findings - Weight (17)-.56 pdssmall effect size - Fat (6)-2.2 %small effect size Conclusion Conclusion: Not effective Fruit and vegetable consumption (8)minimal changes observed *Numbers of studies are shown in parentheses ( )
Incentives and Competition to Reduce Tobacco Use Conclusion Conclusion: Insufficient evidence of effectiveness Incentives and Competition Only Number of studies:1, 0 qualified Conclusion Conclusion:Strong evidence of effectiveness Incentives and Competition Plus Other Interventions Number of studies:26; 14 qualified Impact: All studies - 4.4% pp median (2.7%-9.4%) prevalence67% improvement - 13.7% median quit rate (8% -20.5%) Incentives + skills+ social support (5) - 10% pp median (2.7%-9.4%) prevalence168% improvement - 21% median quit rate Participation rates (11) 28% median participation of smokers (12%-84%)
Become Obese Probability That an Ego Will Become Obese According to the Type of Relationship with an Alter Who May Become Obese in Several Subgroups of the Social Network of the Framingham Heart Study Christakis NA, Fowler JH. N Engl J Med 2007;357:370-379 Likelihood & degrees of separation 1: 45% 2: 20% 3: 10% Geographic separation Effect maintained 0,.26,1.5,3.4,9.3,471 miles
Quit Smoking Probability That a Subject Will Quit Smoking According to the Type of Relationship with a Contact Who Quits Smoking, in the Social Network of the Framingham Heart Study Christakis NA, Fowler JH. N Engl J Med 2008;358:2249- 2258
Sprawl Is Associated with More Health Problems Ewing, AJHP, 2003
The Impact of Sprawl on Health and Behavior Urban Sprawl Utilitarian walking Leisure time walking Increases BMI Increases in BP Source: Ewing et al. (2003) AJHP
A national study of US adolescents (N=20,745)* found a greater number of physical activity facilities is directly related to increased physical activity and inversely related to risk of overweight Gordon-Larsen P, Nelson MC, Page P, Popkin BM. Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics 2006; 117(2): 417-424. http://www.pediatrics.org/cgi/content/full/117/2/417http://www.pediatrics.org/cgi/content/full/117/2/417 *using Add Health data Odds of having 5 or more bouts of MVPA Odds of being overweight 1.26.68 Referent
The Effect of Mixed Use on Obesity Participants were divided into four groups based on the level of land use mix Each quartile increase in land use mix was associated with a 12.20% reduction in the odds of being obese. The difference in weight for an average 5’ 10” white males in the lowest quartile of mixed use and the highest quartile of mixed use was 10 pounds. Frank, L., Andresen, M., and Schmid, T., Obesity Relationships With Community Design, Physical Activity, and Time Spent in Cars. American Journal of Preventive Medicine. June 2004.
Frank L, Kerr J, Chapman J, Sallis J. Urban form relationships with walk trip frequency and distance among youth. American Journal of Health Promotion 2007; 21(4S): 305. ALR Funded Data collected in 2001-2002 from 3,161 Atlanta children show 5 to 18 year olds were more likely to walk for transportation if they lived in mixed-used neighborhoods with parks, schools, and commercial destinations nearby.
Wener RE, Evans GW. A morning stroll: Levels of physical activity in car and mass transit commuting. Environment and Behavior 2007; 39(1): 62-74. Pedometer data collected from over 100 New Jersey train and car commuters revealed that those who commuted by train walked 30% more steps a day and were 4 times more likely to meet recommended 10,000 steps daily than car commuters.
Lopez-Zetina J, Lee H, Friis R. The link between obesity and the built environment. Evidence from an ecological analysis of obesity and vehicle miles of travel in California. Health & Place 2006; 12(4):656-664. A study of 33 California cities found that adults who drove the most had obesity rates (27%) that were three times higher than those who drove the least (9.5%).
The Impact of Driving and Walking on Obesity Every additional 30 minutes spent driving per day translates into a 3% increase in the odds of being obesity Every additional Kilometer (.6 miles) walked translates into nearly a 5% reduction in the odds of being obese Frank, L., Andresen, M., and Schmid, T., Obesity Relationships With Community Design, Physical Activity, and Time Spent in Cars. American Journal of Preventive Medicine. June 2004.
Built Environment and Physical Activity Research Conclusions Living in Activity Friendly Communities could… –Generate 2 more walk/bike trips per person per week –Prevent up to 1.7 pounds of weight gain per year –Positively affect walking/cycling for transportation –Positively impact the total number of minutes of physical activity (40% more physical activity) –Decrease amount of time spent in a car. Each hour spent in a car is associated with a 6% increase in the likelihood of obesity. –Increase life expectancy by 4 years. Ewing et al 2003, Saelens et al 2003, Giles-Corti 2003, Frank et al 2003, Sturm et al 2004, Frank et al 2004, Lopez 2004