Broader Impacts 2014 Presentation (Draft)
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This document summarizes research on scientists' communication behavior and willingness to engage with the public. Key findings include: - Scientists have negative views of the public and media, but want to be helpful. They lack training in public engagement. - Willingness to engage online is predicted by younger age, higher efficacy beliefs, and a desire to contribute to debates. - Defending science against misinformation is scientists' top priority for online engagement goals. Prioritizing strategic goals depends on attitudes, norms, and efficacy related to those goals.
Broader Impacts 2014 Presentation (Draft)
- 1. Understanding Scientists’ Communication Behavior John C. Besley, Ellis N. Brant Chair in Public Relations, Michigan State … with Anthony Dudo Advertising and Public Relations, University of Texas
- 2. What I want to highlight today… Assumptions: • Our society needs strong support for science to flourish • Scientists can help build through effective communication with fellow citizens Key questions: • What shapes scientists willingness to communicate • What shapes scientists willingness to communicate effectively/strategically? We must “supplement our studies and activities on the understanding of science by the public, with studies and activities on the understanding of the public by scientists.”
- 3. Lots of great qualitative work … Summary of key findings … • Scientists don’t think much of the public • Scientists don’t think much of the media • Scientists want to be helpful • Scientists know little of “public engagement” idea • Primary solution is BELIEVED TO BE education
- 4. A key problem is … • Evidence suggests limited relationship between science knowledge and attitudes (Allum, Strugis, & Tabourazi, 2008) • Limited evidence that scientific knowledge is going to change in near future Allum, N., Sturgis, P., Tabourazi, D., & Brunton-Smith, I. (2008). Science knowledge and attitudes across cultures: A meta-analysis. Public Understanding of Science, 17, 35-54.
- 5. Past Research on What gets scientists to “engage” Attitudes/Norms/Efficacy • Past Behavior (Poliakoff and Web, 2007) • Positive engagement attitude (Poliakoff and Web, 2007, Besley, Oh, & Nisbet, 2013 Dudo, 2013) • Perceived skills (efficacy) (Poliakoff and Web, 2007, Besley, Oh, & Nisbet, 2013, Dudo, 2013) • Belief that others are engaging (norms) (Poliakoff and Web, 2007) • Perceived moral obligation(Bentley & Kvik, 2011, Dudo, 2013, Besley, Oh, & Nisbet, 2013) • Perceived personal benefits (Besley, Oh, & Nisbet, 2013) Demographics • Field (Bentley & Kvik, 2011, Besley, Oh, & Nisbet, 2013 , Marcinowski et al, 2014) • Seniority/Rank/Age (Bentley & Kvik, 2011, Besley, Oh, & Nisbet, 2013, Dudo 2013) • Gender (Bentley & Kvik, 2011) Other factors • Resources (money/time) (Bentley & Kvik, 2011, Marcinowski et al, 2014, Besley, Oh, & Nisbet, 2013) • Training (Dudo, 2013) Most recent work: Surveys with AAAS members … • Fall 2012 (n = 431): Views about online engagement • Fall 2013 (n = 390): Views about online engagement goals
- 6. Most recent work In the last two years, about how many total days did you devote to engagement in the following forms (i.e., two half days = 1 day)? 32.7 45.8 53.7 54.1 64.6 65.7 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Face-to-Face engagement - Adults Face-to-Face engagement - Youth Media interviews - Print/Online Online engagement - Adults Media interviews - Audio/Video Online engagement - Youth. 0 Days About 1 day About 2 days About 3 days About 4-10 days More than 10 days M = 2.76 M = 2.31 M = 1.82 M = 2.34 M = 1.86 M = 1.67 Combined M (alpha = .83) = 2.12 Fall 2012 (n = 431): Views about online engagement Many scientists are engaging: F2F is the most popular; Online engagement is least popular.
- 7. Most recent work How willing would you be to take part in the following types of engagement or outreach? All questions had a range of 1-5 and were asked using a scale anchored by “not at all willing” and “very willing” 3.0 3.1 3.1 3.9 3.9 3.9 3.4 3.6 3.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Online engagement - Adults Online engagement - Youth. Online Willingness (alpha = .87) Face-to-Face engagement - Adults Face-to-Face engagement - Youth F2F Willingness (alpha = .83) Media interviews - Audio/Video Media interviews - Print/Online Media Willingness (alpha = .94) Overall, respondents said they be willing to give about 7.6 days, but that’s affected by outliers (100+ days) Fall 2012 (n = 431): Views about online engagement
- 8. Most recent work Fall 2012 (n = 431): Views about online engagement Please select the point between the two options that captures your views about ONLINE public engagement All questions had a range of 1-6 and were asked using a bipolar scale 4.2 4.6 4.4 2.4 2.9 2.6 0.0 1.0 2.0 3.0 4.0 5.0 Scientists not well regarded/Well ... Colleagues would not approve/Would … Subjective Norms Average (alpha = .76) Most scientists do not take part/Do take part … My colleages do not take part/Do take part … Descriptive Norms Average (alpha = .75) Subjective Norms Most scientists think their colleagues like online engagement, but don’t do it very much
- 9. Most recent work Fall 2012 (n = 431): Views about online engagement Please select the point between the two options that captures your views about ONLINE public engagement 3.5 5.1 5.1 5.1 4.7 4.7 4.9 4.8 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 Do not have time/Have time Do not think can make difference/Can make … Think engagement waste of time/Do not … External Efficacy (alpha = .75) Do not have skills/Have skills Expertise too specialized/Not too … Expertise not interesting/Is … Internal efficacy (alpha = .75) All questions had a range of 1-6 and were asked using a bipolar scale ExternalEfficacyInternalEfficacy Most scientists feel they have little time for engagement but think it can be effective and that they have skills
- 10. Online Engagement Willingness Standardized and reduced OLS regression Beta estimates Things that predict engagement: • Being younger • Efficacy • Desire to contribute to debate Things that don’t: • (Most) demos. • Academic field* • Research type* • University type* • Most objectives* • Most reasons* *Dropped from model -0.35 -0.06 0.04 -0.02 0.08 0.05 0.05 0.05 -0.02 0.04 0.24 0.11 0.09 0.09 0.19 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 Age Female White Liberal (5 point scale) Retired Fairness: Distributive Fairness: Procedural Problem: Low Knowledge Norms: Subjective Norms: Descriptive Efficacy: Time Efficacy: Internal Efficacy: External Identity: Pride Goal: Contribute to Debate Adjusted r2: .26 Fall 2012 (n = 431): Views about online engagement
- 11. Online Engagement Willingness Standardized and reduced OLS regression Beta estimates Things that matter: • Being younger • Efficacy • Desire to contribute to debate Things that don’t seem to matter: • (Most) demos. • Academic field* • Research type* • University type* • Most objectives* • Most reasons* *Dropped from model -0.35 -0.06 0.04 -0.02 0.08 0.05 0.05 0.05 -0.02 0.04 0.24 0.11 0.09 0.09 0.19 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 Age Female White Liberal (5 point scale) Retired Fairness: Distributive Fairness: Procedural Problem: Low Knowledge Norms: Subjective Norms: Descriptive Efficacy: Time Efficacy: Internal Efficacy: External Identity: Pride Goal: Contribute to Debate Adjusted r2: .26 Fall 2012 (n = 431): Views about online engagement Conclusions from 2012 data: • If you want scientists to engagement, it may help to… • Decrease perceived time commitment • Increase perceived skill • Increase perceived impact • Increase perceived broader impacts • Implications for … • How we promote engagement opportunities and training
- 12. Most recent work: Goals Fall 2013 (n = 390): Views about online engagement All questions had a range of 1-7 where 1 was “lowest priority” and 7 “was “highest priority” How much should each of the following be a priority for online public engagement … 6.14 5.79 5.96 6.04 5.72 5.88 5.59 4.76 5.22 5.00 4.59 5.34 4.96 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Correcting scientific misinformation Defending science … Defensive goals average (r = .63) Ensuring that people are informed … Ensuring that scientists' ... are part of ... debate Knowledge goals average (r = .41) Getting people excited about science Hearing what others think .. Demonstrating … openness and transparency Trust goals average (r = .54) Framing research … *to+ resonate … Describing … in ways that make them relevant … Messaging goal average (r = .54) Strategic Comm. Priorities
- 13. All questions had a range of 1-7 where 1 was “lowest priority” and 7 “was “highest priority” How much should each of the following be a priority for online public engagement … 6.14 5.79 5.96 6.04 5.72 5.88 5.59 4.76 5.22 5.00 4.59 5.34 4.96 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Correcting scientific misinformation Defending science … Defensive goals average (r = .63) Ensuring that people are informed … Ensuring that scientists' ... are part of ... debate Knowledge goals average (r = .41) Getting people excited about science Hearing what others think .. Demonstrating … openness and transparency Trust goals average (r = .54) Framing research … *to+ resonate … Describing … in ways that make them relevant … Messaging goal average (r = .54) Best predictors are … (Adj. R2 = .31-37) • Attitudes • If you think a goal is ethical • Norms • If you think your colleagues prioritize a goal • Efficacy • If you think a goal works (external efficacy) • If you think you can do a goal (internal efficacy) Most recent work: Goals Fall 2013 (n = 390): Views about online engagement
- 14. All questions had a range of 1-7 where 1 was “lowest priority” and 7 “was “highest priority” How much should each of the following be a priority for online public engagement … 6.14 5.79 5.96 6.04 5.72 5.88 5.59 4.76 5.22 5.00 4.59 5.34 4.96 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Correcting scientific misinformation Defending science … Defensive goals average (r = .63) Ensuring that people are informed … Ensuring that scientists' ... are part of ... debate Knowledge goals average (r = .41) Getting people excited about science Hearing what others think .. Demonstrating … openness and transparency Trust goals average (r = .54) Framing research … *to+ resonate … Describing … in ways that make them relevant … Messaging goal average (r = .54) Most recent work: Goals Fall 2013 (n = 390): Views about online engagement Conclusions from 2013 data: • If you want scientists to engage more strategically … • Increase perceived ethicality of strategic goals • Increase perceived impact of strategic goals • Increase perceived skills related to strategic goals • Implications for … • What we emphasize in engagement training (Do we focus on skills at expense of goal selection?)
- 15. Bonus Material: Not for Presentation
- 16. Past Online Engagement Standardized and reduced OLS regression Beta estimates Things that matter: • Funding • Norms • Efficacy Things that don’t seem to matter: • Views of the public • Demographics • Academic field* • Research type* • University type* • Communication objectives* • Reasons for becoming a scientist* *Dropped from model -0.10 0.06 -0.05 -0.05 0.02 0.03 -0.07 0.15 -0.02 0.06 -0.02 0.00 -0.13 0.16 0.14 0.20 0.10 0.04 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 Age Female White Liberal (5 point scale) Retired Funding: DOD Funding: NIH Funding: NSF Funding: Other Federal Fairness: Distributive Fairness: Procedural Problem: Low Knowledge Norms: Subjective Norms: Descriptive Efficacy: Time Efficacy: Internal Efficacy: External Identity: Pride Adjusted r2: .18 Fall 2012 (n = 431): Views about online engagement
- 17. All questions had a range of 1-7 where 1 was “lowest priority” and 7 “was “highest priority” How much should each of the following be a priority for online public engagement … 6.14 5.79 5.96 6.04 5.72 5.88 5.59 4.76 5.22 5.00 4.59 5.34 4.96 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Correcting scientific misinformation Defending science … Defensive goals average (r = .63) Ensuring that people are informed … Ensuring that scientists' ... are part of ... debate Knowledge goals average (r = .41) Getting people excited about science Hearing what others think .. Demonstrating … openness and transparency Trust goals average (r = .54) Framing research … *to+ resonate … Describing … in ways that make them relevant … Messaging goal average (r = .54) Things that predict ‘defending science’ as priority (Adj. R2 = .36) • Attitudes • Views about the public (procedural/interpersonal fairness) • If you think defending science is ethical • Norms • If you think your colleagues engage (descriptive norms) • If you think your colleagues prioritize defending science • Efficacy • If you think defending science works (external efficacy) • If you think you can defend science (internal efficacy) Fall 2013 (n = 390): Views about online engagementMost recent work: Goals
- 18. Most recent work All questions had a range of 1-7 where 1 was “lowest priority” and 7 “was “highest priority” How much should each of the following be a priority for online public engagement … 6.14 5.79 5.96 6.04 5.72 5.88 5.59 4.76 5.22 5.00 4.59 5.34 4.96 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Correcting scientific misinformation Defending science … Defensive goals average (r = .63) Ensuring that people are informed … Ensuring that scientists' ... are part of ... debate Knowledge goals average (r = .41) Getting people excited about science Hearing what others think .. Demonstrating … openness and transparency Trust goals average (r = .54) Framing research … *to+ resonate … Describing … in ways that make them relevant … Messaging goal average (r = .54) Things that predict ‘informing’ as priority (Adj. R2 = .36) • Attitudes • Views about the public (procedural/interpersonal fairness) • Enjoying engagement • If you think defending science is ethical • Norms • If you think your colleagues engage and value engagement (descriptive and subjective norms) • Demographics • Being female (-), Being in chemistry (-) • News consumption Most recent work: Goals Fall 2013 (n = 390): Views about online engagement
Editor's Notes
- #11: When it comes to willingness instead of past behavior, we can see that internal efficacy, time, pride and a desire to contribute to the debate are the variables that matter.Younger respondents were also relatively more likely to say they were willing to engage And, once again, we see that scientists’ views about the public had little relationship with willingness.
- #12: When it comes to willingness instead of past behavior, we can see that internal efficacy, time, pride and a desire to contribute to the debate are the variables that matter.Younger respondents were also relatively more likely to say they were willing to engage And, once again, we see that scientists’ views about the public had little relationship with willingness.
- #17: First, let’s look at past engagement. What you should see here is that the things most associated with engagement are scientists perceptions of what their colleagues think and efficacy.Remember internal efficacy is the belief that the scientists can do a good job while external efficacy is the belief that engagement can make a difference.It’s noteworthy that scientists’ views about the public appears to have little relationship with engagement.This is quite surprising to me, at least, because I really thought that scientists’ views about the public would affect engagement. The negative relationship with subjective norms is also noteworthy.It’s quite possible that the causal direction here is that those who are engaging are finding that their colleagues are less supportive than they might hope.Those who support the NSF’s efforts to ensure broader impacts may also be happy to note that NSF funding is associated with more engagement.There’s a whole list of thing on the left here that do not appear to be associated with past engagement, including most demographics.Some of these were dropped from the model because they were doing so little and it makes the presentation more manageable.Finally, if you replace the “online engagement” dependent variable with a general variable that includes all forms of engagement, you get very similar results.