SRA summary presentation

1. 1
Scientists’ perceptions of online public
engagement (and the need for theory!)
Anthony Dudo, Ph.D.
Assistant Professor
Dept. of Advertising & PR
Texas at Austin
John C. Besley, Ph.D.
Associate Professor & Ellis N. Brandt
Chair
Dept. of Advertising & PR
Michigan State

2. Broad context
3
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)

3. More attention to PES on the ground
5
• More PES training
• Pedagogical shifts
• Scientist-to-scientist advice
• Popular books
• Third-party resources
• Active blogging community
• Risk communication is
key underlying theme

4. More research on PES
6

5. 7
This research …
has provided a strong baseline understanding of
scientists’ perceptions and activity related to
PES

6. 8
Aim to examine the nature of PES
think about PES from the perspective
of strategic communication:
planned communication with a goal in mind

7. 9
When a scientist engages …
what is she or he hoping to accomplish?
what are scientists’ goals?
what impact do these goals have?

8. 10
Communication theory?…
theory focuses on communication effects …
theory focuses on information seeking …
theory predicting communication choices?
Communication strategy
as planned behavior?

9. 5 goals from the literature …
12
Educate
Defend
science
Excite Build trust
Frame
debates
Strategic goalsTraditional goals

10. Research Questions
1
2
X
What goals do scientists prioritize when
communicating with the public?
Are these goals associated with willingness to engage
(Past research focused on predictors of goal selection)

11. Method
14
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)

12. 15
Descriptive Results

13. 2013 Scientist Survey: Past Engagement
16
“About how many total days … did you devote to … online engagement through
websites, blogs and/or social networks (e.g., Facebook, Twitter) aimed at
communicating science with ADULTS who are not scientists?”
0
10
20
30
40
50
60
0 days about 1 day about 2 days about 3-4
days
about 5 days 6-10 Days 11+ days
note: treated as continuous
(using dummy variable made no
difference; relationship is linear)

14. 2013 Scientist Survey: Willingness to engage (%)
17
“How willing would you be to take part in … online engagement through
websites, blogs and/or social networks (e.g., Facebook, Twitter) aimed at
communicating science with ADULTS who are not scientists?”
0
5
10
15
20
25
not at all
willing
very willing

15. 2013 Scientist Survey: Goals
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
1 2 3 4 5 6 7
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
Strategic
goals
18
“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”

16. 2013 Scientist Survey: Goals
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
1 2 3 4 5 6 7
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
Strategic
goals
19
“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”
Paper in Revision– Predictors of goals:
• Perceived goal ethicality
• Goal-specific external efficacy
• Goal-specific internal efficacy
• Perceptions of colleagues goals

17. 20
Additional multivariate results:
Willingness to engage online
RQ: If you prioritize a goal (any goal), does that
mean you might be more willing to engage?

18. Predictors of online engagement willingness
21
Model specification for hierarchical regressions
(based on theory of planned behavior)
Engage!
Controls
Goals
Attitudes
Field and Funding
Efficacy and
Norms
age, gender, ideology, productivity,
science news online / offline,
engagement experience, comm.
training
biomedicine, chemistry, physics/astronomy,
social science, DOD, NSF, NIH, private, other
funding
fairness: respect, fairness: career outcome,
personal enjoyment
external efficacy, internal efficacy,
subjective norms, descriptive norms
defend, educate, excite, build trust, messaging
willingness to engage online

19. Predictors of online engagement willingness
22
Model specification for hierarchical regressions
(based on theory of planned behavior)
Engage!
Controls
Goals
Attitudes
Field and Funding
Efficacy and
Norms
age, gender, ideology, productivity,
science news online / offline,
engagement experience, comm.
training
biomedicine, chemistry, physics/astronomy,
social science, DOD, NSF, NIH, private, other
funding
fairness: respect, fairness: career outcome,
personal enjoyment
external efficacy, internal efficacy,
subjective norms, descriptive norms
defend, educate, excite, build trust, messaging
willingness to engage online

20. Additional multi-item measures
23
Model specification for hierarchical regressions
fairness: external procedural, four items, alpha = .86
(e.g., I would be treated rudely …)
fairness: external distributive, three items, alpha = .93
(e.g. I would see my research hurt …)
subjective norms, two items, r = .83
(e.g. Scientists who engage online … well-regarded by … peers)
descriptive norms, two items, r = .61
(e.g. Most scientists do not take part in …)
efficacy – external impact of goals, seven items, alpha = .88
(e.g. How effective … each of the following …)
efficacy – personal skill/ability toward goals, seven items, alpha = .90
(e.g. How effective do you think could be … each of the following
…)
(All other items single-item measures)

21. 24
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Adjusted r2 = .10
Regression
results (betas)
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

22. 25
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Older people
less willing to
engage online
Adjusted r2 = .10
Regression
results (betas)
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

23. Regression
results (betas)
26
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Experience
predicts future
willingness
Adjusted r2 = .26
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

24. Regression
results (betas)
27
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Field and
funding do not
seem to matter
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

25. Regression
results (betas)
28
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Some fear of
hostile audience
impact on career
Adjusted r2 = .27
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

26. Regression
results (betas)
29
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Perceived
skill may
affect
willingness
Adjusted r2 = .30
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

27. Regression
results (betas)
30
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
age
male
conservative-Liberal
# of peer reviewed pubs
amount of training
past online engagement
past online media use
past offline media use
biomedical scientist
chemical scientist
physics/astromony scientist
social scientist
DOD funding
NIH NIH funding
NSF funding
federal funding-other
private sector fudning
funding-other
fairness (audience will treat with respect)
fairness (audience will hurt career)
enjoyment of communication
subjective norms
descriptive norms
efficacy - expected reach
efficacy - external impact
efficacy - personal skill/ability
education goal
defense of science goal
excite people goal
build trust goal
strategic message delivery goal
r Beta
Goals do
not seem to
matter?
Correlation coefficients
Light orange, p > .05
Standardized betas
(dark orange = p > .05)

28. Key findings
31
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’ willingness to engage online a function of past experiences
with engagement and social media, concern about impact, internal efficacy
Prioritizing specific goals has little impact on willingness to engage online

29. What’s next?
32
Long-term goal: help build a community focused on evidence-based science
communication
Current project PES research needs
‣ 2-year NSF-AISL “Pathways”
project that will enable …
‣ Qualitative interviews with
science engagement trainers
‣ Surveys with members from
10+ major US scientific societies
‣ Experiments testing messages
related to communication goals
‣ Identify most important goals
‣ Establish whether TPB is best
‣ Longitudinal/experimental data
‣ Operational consistency
‣ International data
‣ What role risk?
‣ How to maximize response rate?

30. 33
Contact us
Anthony Dudo
dudo@utexas.ed
u
John C. Besley
jbesley@msu.edu

31. Regression
results
34
Predictors
that cut
across the
goals
Standardized betas
* p<.05, ** p<.01, ***p<.001

32. Regression
results
35
The education
goal is the
most different
in terms of its
predictors
Standardized betas
* p<.05, ** p<.01, ***p<.001