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This study examines scientists’ strategic communication sensibilities, specifically in terms of their valuation of five goals for online public communication. These goals include informing the public about science, exciting the public about science, strengthening the public’s trust in science, tailoring messages about science, and defending science from misinformation. We use insights from extant research, the Theory of Planned Behavior, and procedural justice theory to identify likely predictors of scientists' views about these communication goals. Results show that scientists most value communication designed to defend science from misinformation. Regression analyses reveal factors associated with valuing each of these specific communication goals (n = 390).
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Scientists’ Prioritization of Goals for Online Public Communication Anthony Dudo, Ph.D.Assistant ProfessorDept. of Advertising & PRTexas at Austin
John C. Besley, Ph.D.Associate Professor & Ellis N. Brandt ChairDept. of Advertising & PRMichigan State
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Broad context the three moments of science communication
What brings people to science? (focus on public)
What brings science to people? (focus on scientists)
How do gatekeepers contribute? (focus on media / PIOs / bloggers)
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More attention to PES on the ground
• More PES training
• Pedagogical shifts
• Scientist-to-scientist advice
• Popular books
• Third-party resources
• Active blogging community
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More research on PES
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This research …has provided a strong baseline understanding of scientists’ perceptions and activity related to PES
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Research has removed the PES peel …
… it’s now time to focus on the PES fruit
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Aim to examine the nature of PESthink about PES from the perspective of strategic communication
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When a scientist engages …what is she or he hoping to accomplish? what are their goals?
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5 goals
EducateDefend science
ExciteBuild trust
Tailor messages
Strategic goals
Traditional goals
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Research Questions
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3
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What goals do scientists prioritize when communicating with the public?
To what extent do scientists think their colleagues share these same goals?
What factors shape scientists’ goals for communicating with the public?
To what extent do these factors vary across different communication goals?
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Method
Sample
• U.S.-based, university-based Ph.D.s who were AAAS members
2013 AAAS Scientist Survey
Distribution
• Online (Qualtrics), Tailored Design Method
• All requests sent from AAAS Membership Dept. (to protect privacy)
• Incentive: 1/200 chance to win $500 amazon.com gift card or donation to AAAS
Response Rate
• 390/5,000 = 8% (not adjusted for undeliverable emails)
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Descriptive Results
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2013 Scientist Survey: Goals
messaging goal average (r = .54)
describing … in ways that make them relevant
framing research … {to} resonate …
trust goals average (r = .54)
demonstrating … openness & transparency
hearing what others think …
getting people excited about science
knowledge goals average (r = .41)
ensuring that scientists … are part of …
ensuring that people are informed …
defensive goals average (r = .63)
defending science …
correcting scientific misinformation
1 2 3 4 5 6 7
4.96
5.34
4.59
5
5.22
4.76
5.59
5.88
5.72
6.04
5.96
5.79
6.14
Strate-gic
goals
“How much should each of the following be a priority for online public engagement?”
All questions had a range of 1-7 where 1 was the “lowest priority” and 7 was the “highest priority”
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2013 Scientist Survey: Goals
defensive knowledge excite trust messaging1
2
3
4
5
6
7
5.96 5.885.59
5 4.96
5.725.35
5.18
4.184.44
Own priorities
Colleagues' priorities
“How big a priority … for your colleagues?”
All questions had a range of 1-7 where 1 was the “lowest priority” and 7 was the “highest priority”
Respondents believe they value all communication goals more than their colleagues; biggest discrepancy is associated with “trust”
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Multivariate Results
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Predictors of each of the 5 online comm goalsModel specification for hierarchical regressions
DVs
Controls
Norms
Attitudes
Scientific field
Efficacy
age, gender, ideology, productivity, career level, science news online / offline, engagement experience
biomedicine, chemistry, physics/astronomy, social science
fairness: external procedural, fairness: external distributive, personal enjoyment, goal ethicality (goal-specific)
communication training, external efficacy (goal-specific), internal efficacy (goal-specific)
subjective norms, descriptive norms, perceptions of colleagues’ communication priorities (goal-specific)
defend | educate | excite | build trust | messaging
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Regression results
Models yield strong explanatory power
Standardized betas* p<.05, ** p<.01, ***p<.001
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Regression results
Not much going on with demographics or field
Standardized betas* p<.05, ** p<.01, ***p<.001
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Regression results
Predictors that cut across the goals
Standardized betas* p<.05, ** p<.01, ***p<.001
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Regression results
The education goal is the most different in terms of its predictors
Standardized betas* p<.05, ** p<.01, ***p<.001
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Key findings
Scientists prioritize online public communication that is designed to defend science and educate
Scientists find the least value in the goals that are most likely to lead to positive engagement outcomes: building trust and tailoring messages
Scientists’ valuations of specific communication goals are associated with key predictors from the TPB (attitudes, norms, efficacy)
The traditional goal of educating the public turns on a somewhat different set of factors than the other goals
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Practical Applications
Increase perceived ethicality of specific communication goals
Change beliefs about colleagues’ priorities for online communication
Increase perceived impacts of specific communication goals
Increase perceived personal skills related to specific communication goals
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What’s next? Long-term goal: help build a community focused on evidence-based science communication
Upcoming project PES research needs
‣ 2-year NSF-AISL “Pathways” project that will enable:
‣ Qualitative interviews with engagement trainers
‣ Surveys with members from > 10 scientific societies
‣ Experiments testing messages related to communication goals
‣ Identify more goals
‣ Better theorizing
‣ Longitudinal data
‣ Operational consistency
‣ International data
