scholarly article | Q13442814 |
P50 | author | David A. Broniatowski | Q56261549 |
Mark Dredze | Q56430878 | ||
Karen M Hilyard | Q117231440 | ||
P2860 | cites work | A theory of medical decision making and health: fuzzy trace theory | Q24651866 |
Responding to parental refusals of immunization of children | Q28248175 | ||
Do personal stories make patient decision aids more effective? A critical review of theory and evidence | Q30579883 | ||
Anti-vaccine activists, Web 2.0, and the postmodern paradigm--an overview of tactics and tropes used online by the anti-vaccination movement | Q34029837 | ||
Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: a fuzzy-trace theory approach | Q34514193 | ||
Risk perception and communication in vaccination decisions: a fuzzy-trace theory approach | Q35899214 | ||
Does narrative information bias individual's decision making? A systematic review | Q37308377 | ||
All stories are not alike: a purpose-, content-, and valence-based taxonomy of patient narratives in decision aids | Q39536552 | ||
Effect of narrative reports about vaccine adverse events and bias-awareness disclaimers on vaccine decisions: a simulation of an online patient social network | Q44167488 | ||
Social media and organ donor registration: the Facebook effect | Q46177624 | ||
Fuzzy‐Trace Theory, Risk Communication, and Product Labeling in Sexually Transmitted Diseases | Q51948931 | ||
What works best: objective statistics or a personal testimonial? An assessment of the persuasive effects of different types of message evidence on risk perception | Q80572294 | ||
Dr. Jekyll or Mr. Hyde? (How) the Internet influences vaccination decisions: recent evidence and tentative guidelines for online vaccine communication | Q83800630 | ||
Comparing the Relative Efficacy of Narrative vs Nonnarrative Health Messages in Reducing Health Disparities Using a Randomized Trial | Q87173060 | ||
Who gets a teach-back? Patient-reported incidence of experiencing a teach-back | Q87403973 | ||
Theoretically motivated interventions for reducing sexual risk taking in adolescence: a randomized controlled experiment applying fuzzy-trace theory | Q87769044 | ||
P433 | issue | 28 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | measles | Q79793 |
P304 | page(s) | 3225-3228 | |
P577 | publication date | 2016-05-06 | |
P1433 | published in | Vaccine | Q7907941 |
P1476 | title | Effective vaccine communication during the disneyland measles outbreak | |
P478 | volume | 34 |
Q54259524 | "I wouldn't really believe statistics" - Challenges with influenza vaccine acceptance among healthcare workers in Singapore. |
Q40210988 | "To each his own": Discussions of vaccine decision-making in top parenting blogs |
Q92249768 | A visual content analysis of vaccine coverage in the print media |
Q48626545 | Addressing barriers to vaccine acceptance: an overview |
Q47685149 | African American adults and seasonal influenza vaccination: Changing our approach can move the needle |
Q89526732 | Exploring the relationship between newspaper coverage of vaccines and childhood vaccination rates in Spain |
Q46264244 | Facebook and Twitter vaccine sentiment in response to measles outbreaks |
Q51336172 | Intentions to use a novel Zika vaccine: the effects of misbeliefs about the MMR vaccine and perceptions about Zika. |
Q57093068 | Public health responses during measles outbreaks in elimination settings: Strategies and challenges |
Q91733100 | Using classification and regression tree analysis to explore parental influenza vaccine decisions |
Q52609188 | Vaccine Images on Twitter: Analysis of What Images are Shared. |
Q47790943 | Vaccine opponents' use of Twitter during the 2016 US presidential election: Implications for practice and policy |
Q56248891 | Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate |
Q64904486 | Zika discourse in the Americas: A multilingual topic analysis of Twitter. |
Q24261326 | Zika vaccine misconceptions: A social media analysis |
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