title: Effects of mass media coverage on timing and annual receipt of influenza vaccination among Medicare elderly.
abstract: OBJECTIVE
  To measure the association between mass media coverage on flu-related topics and influenza vaccination, regarding timing and annual vaccination rates, among the nationally representative community-dwelling elderly.
  
  
  METHODS
  Years 1999, 2000, and 2001 Medicare Current Beneficiary Survey.
  
  
  METHODS
  Cross-sectional survival analyses during each of three influenza vaccination seasons between September 1999 and December 2001. The outcome variable was daily vaccine receipt. We measured daily media coverage by counting the number of television program transcripts and newspaper/wire service articles, including keywords of influenza/flu and vaccine/shot shortage/delay. All models' covariates included three types of media, vaccine supply, and regional/individual factors.
  
  
  RESULTS
  Influenza-related reports in all three media sources had a positive association with earlier vaccination timing and annual vaccination rate. Four television networks' reports had most consistent positive effects in all models, for example, shifting the mean vaccination timing earlier by 1.8-4.1 days (p<.001) or increasing the annual vaccination rate by 2.3-7.9 percentage points (p<.001). These effects tended to be greater when reported in a headline rather than in text only and if including additional keywords, for example, vaccine shortage/delay.
  
  
  CONCLUSIONS
  Timing and annual receipt of influenza vaccination appear to be influenced by media coverage, particularly by headlines and specific reports on shortage/delay.
authors.affiliation: Department of Community and Preventive Medicine, Division of Health Policy and Outcomes Research, School of Medicine and Dentistry, University of Rochester, 601 Elmwood Avenue, Box 644, Rochester, NY 14642, USA. byung-kwang_yoo@urmc.rochester.edu
authors.forename: Byung-Kwang
authors.initials: BK
authors.lastname: Yoo
authors.forename: Margaret L
authors.initials: ML
authors.lastname: Holland
authors.forename: Jay
authors.initials: J
authors.lastname: Bhattacharya
authors.forename: Charles E
authors.initials: CE
authors.lastname: Phelps
authors.forename: Peter G
authors.initials: PG
authors.lastname: Szilagyi
mesh_terms: D000368:Aged; D003430:Cross-Sectional Studies; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D007252:Influenza Vaccines / Q000600:supply & distribution; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D008297:Male; D008402:Mass Media / Q000706:statistics & numerical data*; D006278:Medicare / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D009524:Newspapers as Topic / Q000706:statistics & numerical data; D017063:Outcome Assessment, Health Care; D010342:Patient Acceptance of Health Care / Q000523:psychology / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D012621:Seasons; D016019:Survival Analysis; D013690:Television / Q000706:statistics & numerical data; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D014611:Vaccination / Q000523:psychology / Q000706:statistics & numerical data*
chemical_list: D007252:Influenza Vaccines