1. Media & the Politics of Implementation: Competition, Coverage & Complexity in Affordable Care Act Messaging Erika Franklin Fowler Wesleyan University @efranklinfowler

3. Funding from: Robert Wood Johnson Foundation through its State Health Care Access Reform Evaluation (SHARE), Grant ID# 72179 Wesleyan University Colleen L. Barry, John Hopkins Bloomberg Laura Baum, Wesleyan Jeff Niederdeppe, Cornell Pinar Karaca-Mandic, Andrew Wilcock & Sarah E. Gollust (Co-PI), UMN Collaborators:

4. Why Affordable Care Act Messaging? Public opinion starkly divided since well before the law’s passage; substance of messaging may matter less under extreme polarization (Druckman, Peterson and Slothuus 2013) Yet… Public knowledge was low (Kaiser Family Foundation 2013) Multiple actors invested, not all partisan Outcomes matter

5. Larger Project: Geographic Variation & Why It Matters Large gov’t investment with varying types of state administration carried out substantially through private means Explaining differences in volume from different sources & over time Explaining differing content of messaging Influence on enrollment Influence on broader public assessment of the law Longer-term effects on future possibilities for reform?

6. Larger Project: Geographic Variation & Why It Matters Large gov’t investment with varying types of state administration carried out substantially through private means Explaining differences in volume from different sources & over time Explaining differing content of messaging Influence on enrollment Influence on broader public assessment of the law Longer-term effects on future possibilities for reform?

7. Marketing of Insurance Options was Prevalent Volume of Health Insurance Ads Aired During OE1

8. But Not the Only Source of Information… “taking away our healthcare choices”

9. Evidence So Far Suggests… Higher levels of insurance marketing (measured through TV advertising) correlate with decreases in uninsurance rates (Gollust et al. working paper) But also that partisans (at least during the initial roll-out) viewed insurance ads through partisan lens (Fowler et al. forthcoming at JHPPL)

10. Data & Methods (Fowler et al. forthcoming at JHPPL) WMP content analysis of ads and news (10/1-10/17/2013) October 2013 wave of Kaiser Family Foundation (10/18-10/23) DVs: Perceived info: “Do you feel you have enough information about the health reform law to understand how it will impact you and your family or not?” Favorability: “Given what you know about the health reform law, do you have a generally favorable or generally unfavorable opinion of it?” Weighted estimations with clustered SEs at the market Key IVs: self-reported attention x message volume (e.g., Slater et al. 2009)

11. Results: (Fowler et al. forthcoming at JHPPL) **p<.01; *p<.05. Additional controls for: gender, self-reported health, has health insurance, ideology, education, race, income, state exchange, % voting for Obama in 2012, % county uninsured 2013 Independent VariablesAll Respondents Estimated potential exposure to ACA news stories 0.0802 (0.0607) Estimated potential exposure to insurance advertising 0.4463** (0.1439) Estimated potential exposure to political advertising 0.1076 (0.1469) Pure Independents (reference is Democrats) -0.2409 (0.446) Republican (reference is Democrats) -0.8406* (0.3916) Insurance ad exposure*Independent -0.8717** (0.2715) Insurance ad exposure*Republican -0.6758** (0.215)

12. Initial Roll-Out Effects: Insurance Ads Very Unfavorable View of ACAVery Favorable View of ACA

13. Evidence So Far Suggests… Higher levels of insurance marketing (measured through TV advertising) correlate with decreases in uninsurance rates (Gollust et al. working paper) But also that partisans (at least during the initial roll-out) viewed insurance ads through partisan lens (Fowler et al. forthcoming at JHPPL) Political ads attacking the ACA do not correlate with uninsurance rates or attitudes about the law, however…

14. October 2013 and Open Enrollment Period 1 Both featured very low numbers of political advertising October 2013: average of 20 ads per market (compared to an average of 419 for insurance ads) Full Open Enrollment Period: Volume of Political Ads Aired Volume of Health Insurance Ads Aired

15. Volume of Insurance and Political Messages

16. 2014 Battlegrounds vs. Other Markets

17. Insurance vs. Political ACA Ads

18. Empirical Differences, Unknown Consequences Large geographic variation in type of advertising messaging Ramp up to OE2 looked very different in some places compared to OE1 and OE3 Theory and evidence suggests that prior exposure conditions subsequent media influence (Gaines et al. 2007; Druckman & Leeper 2012, Fowler & Gollust 2015)

19. Expectations Exposure to political advertising attacking the ACA will reduce favorability toward the law Areas heavily targeted by ACA insurers may respond differently

20. Data & Measures WMP political and insurance advertising data from prior week Late October 2014 SSI survey sample (n=1,396) ACA Favorability Question Attention to upcoming enrollment x market level volume of advertising [Also reported TV watching, so can create an alternative exposure measure] Standard demographics including health ins, but no self-reported health ACS 2013 county uninsurance rates 2012 county level percentage voting for Obama ACA marketing target & total number of political ads

21. Results: Favorable View of the ACA **p<.01; *p<.05. Ordered logit clustered at the media market level. Additional controls for: gender, has health insurance, ideology, education, race, income, % voting for Obama in 2012, % county uninsured 2013, total election ads. Independent VariablesCoeff. (SE) Est. potential exposure to political advertising week prior -1.20** (0.37) ACA Targeted Market (Above Avg. OE1 Insurance Targeting) 0.03 (0.05) Partisanship (7-pt, Republican) -0.31** (0.03) Does not have health insurance -0.39** (0.12)

22. Results: Favorable View of the ACA **p<.01; *p<.05. Ordered logit clustered at the media market level. Additional controls for: gender, has health insurance, ideology, education, race, income, % voting for Obama in 2012, % county uninsured 2013, total election ads. Independent VariablesCoeff. (SE) Est. potential exposure to political advertising week prior -1.20**0.39 (0.37)(0.57) ACA Targeted Market (Above Avg. OE1 Insurance Targeting) 0.030.29* (0.05)(0.13) ACA Target * political ad exposure -2.33** (0.72) Partisanship (7-pt, Republican) -0.31** (0.03) Does not have health insurance -0.39**-0.38** (0.12)

23. Predicted Probability (“Somewhat Favorable”)

25. Results: Favorable View of the ACA **p<.01; *p<.05. Ordered logit clustered at the media market level. Additional controls for: gender, has health insurance, ideology, education, race, income, % voting for Obama in 2012, % county uninsured 2013, total election ads. Independent Variables Coeff. (SE) Est. potential exposure to political advertising week prior -1.20**-0.88** (0.37)(0.33) Est. potential exposure to insurance advertising week prior -1.93** (0.57) ACA Targeted Market (Above Avg. OE1 Insurance Targeting) 0.030.33 (0.05)(0.03) Partisanship (7-pt, Republican) -0.31** (0.03) Does not have health insurance -0.39**-0.38** (0.12)

26. Results: Favorable View of the ACA **p<.01; *p<.05. Ordered logit clustered at the media market level. Additional controls for: gender, has health insurance, ideology, education, race, income, % voting for Obama in 2012, % county uninsured 2013, total election ads. Independent Variables Coeff. (SE) Est. potential exposure to political advertising week prior -1.20**-0.88**0.390.46 (0.37)(0.33)(0.57)(0.59) Est. potential exposure to insurance advertising week prior -1.93**0.08 (0.57)(0.91) ACA Targeted Market (Above Avg. OE1 Insurance Targeting) 0.030.330.29*0.83** (0.05)(0.03)(0.13)(0.23) ACA Target * political ad exposure -2.33**-1.95* (0.72)(0.76) ACA Target * insurance ad exposure -2.66* (1.07) Partisanship (7-pt, Republican) -0.31** (0.03) Does not have health insurance -0.39**-0.38** -0.36** (0.12) (0.13)

27. Predicted Probability (“Somewhat Favorable”)

28. Implications & Next Steps Political messaging may matter more during heat of election seasons Or perhaps timing matters more than type of messaging? Policy implications for most heavily targeted areas… Needed next steps Replicate with other survey datasets (KFF, Pew, etc) Add in news coverage Further investigate the content of messaging

29. Media & the Politics of Implementation: Competition, Coverage & Complexity in Affordable Care Act Messaging Erika Franklin Fowler Wesleyan University @efranklinfowler

32. Public vs. Private References

33. Initial Roll-Out Effects: Local TV News

34. Initial Roll-Out Effects: Insurance Ads Very Unfavorable View of ACAVery Favorable View of ACA

35. Volume of Insurance & Political Ads by Month *Only includes April 1-April 15, 2014

36. Volume of Local Evening News Hits by Month *Only includes April 1-April 15, 2014

38. Google Searches For ACAFor Obamacare

39. Google Searches For Health InsuranceFor Obamacare