Conflict of interest perceptions and risk-related research partnerships

John C. Besley, Aaron M. McCright, Kevin C. Elliott, Nagwan Zahry (graduate assistant), Tsuyoshi Oshita (graduate assistant)

Business University Government NGO

SRA 2015

A philosopher A sociologist An historian

A scientist A …Another scientist

Our interdisciplinary research group …

We want to do researchResearch costs money

Industry has moneyPeople worry about industry money

There are some ways to mitigate real problems (!)Are there ways to mitigate perceptual problems?

A problem…

What do we know so far…

• Clear evidence that groups such as doctors (and others) question validity of industry funded research

What do we know so far…

• Some evidence that people use perceptions of procedural fairness to assess whether decisions taken in situations of uncertainty (such as scientific research) are valid

What do we know so far…

• Suggestion that procedural fairness perceptions can be used to operationalize perceptions of …

“conflict of interest”

… a conflict of interest can be understood as a situation where an individual or organization has a decision-making role that might allow them to improperly benefit from the decisions the individual might make*

*See: Davis, M. (2001). Introduction. In M. Davis & A. Stark (Eds.), Conflict of Interest in the Professions (pp. 3-19). New York, NY: Oxford University Press.

2 Experiments(And maybe a bonus experiment)

Study 1: Does partner choice affect fairness and legitimacy perceptions?

Design• Four partners (University, Industry, Government, NGO)• 15 combinations (2 x 2 x 2 x 2 [- 1])

• All 4 partners, all 3 of 4 partner combos, etc. • Pre-test used to identity partners with

high positive and low negative perceptions

• Context: Regulation of low levels of transfats• Sample: 626 US-based mTurkers

• Multiple attention/manipulation checks (data excluded)

Study 1: What it looked like …

Partner manipulation(also repeated in question stems)

Study 1: What it looked like …

• Six statements for procedural fairness DV as bias control + voice• Cronbach’s alpha = .93

• Highly correlated with direct measure of conflict of interest

Study 1: What it looked like …

• Four statements for legitimacy DV as willingness to use results• Cronbach’s alpha = .79

• MLE factor analysis suggests itemsdifferent from fairness items, r = .64

Study 1: Fairness for Partnership

Industry = Relative Low Fairness

Shared letter = Not significantly different based on a post-hoc test

Kelloggs

(a)

Kelloggs

+ CDC (ab)

Kelloggs

+ UCS (ab)

Purdue +

Kelloggs +

CDC (abc)

Purdue + Kello

ggs (

abc)

Kelloggs

+ CDC + UCS (abcd

)

Purdue + Kello

ggs + CDC + UCS (

bcd)

Purdue + Kello

ggs +

UCS (bcd

)

Purdue + CDC (b

cd)

CDC (bcd

)

Purdue (b

cd)

Purdue + CDC + UCS (

cd)

UCS (d)

CDC + UCS (d

)

Purdue +

UCS (d)

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Study 1: Fairness for Partnership

Some benefit to adding partners

Shared letter = Not significantly different based on a post-hoc test

Kelloggs

(a)

Kelloggs

+ CDC (ab)

Kelloggs

+ UCS (ab)

Purdue +

Kelloggs +

CDC (abc)

Purdue + Kello

ggs (

abc)

Kelloggs

+ CDC + UCS (abcd

)

Purdue + Kello

ggs + CDC + UCS (

bcd)

Purdue + Kello

ggs +

UCS (bcd

)

Purdue + CDC (b

cd)

CDC (bcd

)

Purdue (b

cd)

Purdue + CDC + UCS (

cd)

UCS (d)

CDC + UCS (d

)

Purdue +

UCS (d)

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Study 1: Same pattern for legitimacy …

Shared letter = Not significantly different based on a post-hoc test

Kelloggs

+ UCS (a)

Purdue + Kello

ggs +

CDC (ab)

Kelloggs

+ CDC (abc)

Purdue + Kello

ggs (abc)

Kelloggs

(abc)

Kelloggs

+ CDC + UCS (abc)

UCS (abc)

Purdue + CDC (a

bc)

Purdue +

Kelloggs +

UCS (abc)

CDC + UCS (b

c)

Purdue (b

c)

Purdue + Kello

ggs +

CDC + UCS (bc)

CDC (bc)

Purdue + CDC + UCS (

bc)

Purdue + UCS (c

)1.00

2.00

3.00

4.00

5.00

6.00

7.00

Study 1: As a mediation model in PROCESS …

Shared letter = Not significantly different based on a post-hoc test

B SE Sig. B SE Sig.Outcome: Perceived Fairness Direct and Indirect Effects(Constant) 4.88 .15 .00 Direct effects of Kellogg's -.07 .11 .51Partnership includes Kellogg's -.92 .11 .00 Indirect effects of Kellogg's -.61 .08 [-.79, -.46]Partnership includes Purdue .21 .12 .07Partnership includes CDC -.02 .11 .87 Direct effects of Purdue -.02 .10 .81Partnership includes UCS .41 .12 .00 Indirect effects of Purdue .14 .07 [-.01, .30]

r2 .15Outcome: Perceived Legitimacy Direct effects of CDC .28 .10 .00(Constant) 1.17 .23 .00 Indirect effects of CDC -.01 .08 [-.16, .14]Perceived fairness of partnership .66 .04 .00Partnership includes Kellogg’s -.07 .11 .51 Direct effects of UCS .06 .10 .54Partnership includes Purdue -.02 .10 .81 Indirect effects of UCS .27 .07 [.12, .41]Partnership includes CDC .28 .10 .00Partnership includes UCS .06 .10 .54

r2 .42• Industry hurts fairness• NGO/university(?) helps fairness• Fairness mediates the

relationship with legitimacy• Government has direct effect

Study 2: Replicate study in context of GMO partnership

Design• Same 4-partner design• DVs: Fairness and Legitimacy• New context: GMO safety testing• Sample: 627 US-based mTurkers, with attention test

Study 1: Fairness for Partnership

Shared letter = Not significantly different based on a post-hoc test

Purdue +

Kelloggs +

CDC (a)

Kelloggs

(a)

Kelloggs

+ UCS (ab)

Kelloggs

+ CDC (abc)

Purdue + Kello

ggs (

abc)

Kelloggs

+ CDC + UCS (abcd

)

Purdue + Kello

ggs +

UCS (abcd

)

CDC + UCS (a

bcd)

Purdue + Kello

ggs +

CDC + UCS (abcd

)

Purdue + CDC (a

bcd)

CDC (bcd

)

Purdue + CDC + UCS (

cd)

Purdue (c

d)

UCS (cd)

Purdue +

UCS (d)

1.00

2.00

3.00

4.00

5.00

6.00

7.00Industry = Relative Low Fairness (again)

• A similar pattern again for legitimacy

Study 1: Transfats Study 2: GMOs B SE Sig. B SE Sig.Outcome: Perceived Fairness(Constant) 4.88 .15 .00 4.77 .14 .00Partnership includes Kellogg's -.92 .11 .00 -.73 .11 .00Partnership includes Purdue .21 .12 .07 .18 .11 .09Partnership includes CDC -.02 .11 .87 -.03 .11 .77Partnership includes UCS .41 .12 .00 .27 .11 .01

r2 .15 .09Outcome: Perceived Legitimacy(Constant) 1.17 .23 .00 1.81 .20 .00Perceived fairness of partnership .66 .04 .00 .60 .03 .00Partnership includes Kelloggs -.07 .11 .51 -.09 .09 .34Partnership includes Purdue -.02 .10 .81 .14 .09 .12Partnership includes CDC .28 .10 .00 .12 .09 .17Partnership includes UCS .06 .10 .54 -.01 .09 .90

r2 .42 .61Direct and Indirect EffectsDirect effects of Kelloggs -.07 .11 .51 -.09 .09 .34Indirect effects of Kellogg's -.61 .08 [-.79, -.46] -.44 .07 [-.61, -.32]

Direct effects of Purdue -.02 .10 .81 .14 .09 .12Indirect effects of Purdue .14 .07 [-.01, .30] .11 .07 [-.03, .24]

Direct effects of CDC .28 .10 .00 .12 .09 .17Indirect effects of CDC -.01 .08 [-.16, .14] -.02 .06 [-.15, .11]

Direct effects of UCS .06 .10 .54 -.02 .09 .90Indirect effects of UCS .27 .07 [.12, .41] .16 .07 [.03, 30]

• Industry still a problem• NGO still helps• University still a (weak) positive• No direct effect for government

Bonus Study: Beyond Partners to ProceduresDesign• 4 partner combos x 4 procedures• Same 3-partners (no government), between subjects

• Four types of procedures to protect research• No procedure• Transparency• Third party review• Arm’s length agreement

• Context: Back to transfats• DV: Fairness (also legitimacy) • Sample: 962 US-based mTurkers, with attention test

Bonus Study: Beyond Partners to Procedures

Procedural manipulation

Partner combo manipulation

Fairness by partnership and type of procedure

Any Kelloggs

Involvement

Kelloggs

+ UCS

Purdue + Kello

ggs

Purdue + Kello

ggs + UCS

Purdue + UCS

1.00

2.00

3.00

4.00

5.00

6.00

7.00

No procedureTransparency3rd partyArm's Length

ab

abb ab

b

[F(3, 958) = 6.24, p = .00]

Fairness by procedure and type of partnership

No procedure Transparency 3rd party Arm's Length0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Any Kelloggs InvolvementKelloggs + UCSPurdue + KelloggsPurdue + Kelloggs + UCSPurdue + UCS

GLM Parameter Estimates for Fairness B SE Sig. Part-

Eta2Intercept 5.33 .23 .00 .30Purdue .31 .10 .00 .01UCS .06 .10 .56 .00Kelloggs -1.31 .18 .00 .04

Arm's Length .17 .22 .45 .00Kelloggs*Arm's Length .34 .25 .17 .00

Transparency -.22 .21 .28 .00Kellogg's*Transparency .52 .24 .03 .00

3rd Party -.13 .20 .53 .00Kellogg's*3rd Party .53 .23 .02 .00

• University partner good for fairness

• Arm’s length policy n.s.• Transparency procedure

helpful with industry partner• 3rd party oversight help

with industry partner• Arm’s length (b = .42)

and 3rd party procedures (b = .28) are significant without interaction terms

Adjusted r2 = .13

Discussion …

When it comes to perceptions of fairness (and legitimacy)1. An industry partner (even a nice one) hurts perceptions2. Adding additional partners doesn’t help much3. Adding procedural safeguards doesn’t help much

Should academic scientists never accept industry collaboration?

Discussion …

What if we were to add multiple procedures?What about other issues, including non-risk issues?Is it all collaboration or just ones involving funding?

Does it really matter in the ‘real’ world?