Examining the Impact of Expert Voices: Communicating the Scientific Consensus on Genetically-modified Organisms

Figures & data

Table 1. Our sample demographics compared to the 2015 ACS demographic and housing estimates (https://factfinder.census.org).

	Sample n	Sample %	Census %	Χ^2 Statistic	p value
Race/Ethnicity	1983
White	1571	79.22	76.13	10.26	0.001
Black	160	8.06	13.77	133.00	< .001
Hispanic	150	7.56	17.13	127.23	< .001
Asian	153	7.72	6.06	101.54	< .001
Native American	42	2.12	1.68	2.08	0.150
Pacific Island	9	0.45	0.40	0.04	0.833
Education
Less than 9th	1	0.06	5.72	101.54	< .001
Some HS	6	0.30	7.63	133	< .001
High School	197	9.93	27.77	277.23	< .001
Some College	500	25.21	21.06	64.51	< .001
Associates	271	13.67	8.05	92.12	< .001
Bachelors	715	36.06	18.52	366.14	< .001
Grad School	289	14.57	11.25	46.33	< .001

Table 2. Coefficients (b) and averaged predicted probabilities (pp) from multinomial logistic regression.

	NASEM (ref) n = 94		NOBEL n = 88		ENSSER n = 111		KRIM n = 89
	b	pp	b	pp	b	pp	b	pp
“safe” (ref)	–	0.95	–	0.83	–	0.05	–	0.08
“not safe”	–	0.02	0.51	0.03	5.04***	0.18	5.26***	0.30
“wait”	–	0.03	1.56*	0.14	6.06***	0.77	5.49***	0.62

*^{p <.05.}

**^{p< .01.}

***^{p <.001.}

Note: The predicted probabilities (pp) reflect the averaged probability of the participants in each message condition (NASEM, NOBEL, ENSSER, or KRIM) interpreting the message they read as meaning GMOs are “safe”, “not safe” or we need to “wait and see” whether they are safe or not safe. The predicted probabilities in each column add up to 1. In the regression, “safe” was the referent for the message interpretation variable and the NASEM message was the referent for the message condition variable. Coefficients (b) reflect the probabilities for those conditions compared to the referents.

Table 3. Summary of study results.

	Representative	Argument strength	GMO concern	% Scientists
Message
F value	6.55	9.36	161	0.640
p value	<.001	<.001	0.170	0.632
Effect size $\left({\eta }_p^2\right)$	0.05	0.07	0.01	0.01
descriptives	1 to 6	1 to 5	−1.84 to 2.15	0 to 100
NASEM (n = 94)	4.16 (1.30)	3.83 (1.12)	−0.18 (0.85)	63.71% (18.25)
NOBEL (n = 88)	4.11 (1.27)	3.79 (0.99)	−0.09 (0.82)	61.43% (19.72)
ENSSER (n = 111)	3.59 (1.38)	3.84 (0.95)	0.22 (0.85)	53.85% (21.12)
KRIM (n = 89)	3.61 (1.16)	4.11 (0.70)	0.15 (0.83)	59.39% (20.57)
Control (n = 101)	NA	NA	0.03 (0.95)	59.64% (24.12)
Purchase non-GMO labeled foods
F value	10.62	14.74	172.96	29.48
p value	.001	<.001	< .001	< .001
Effect size $\left({\eta }_p^2\right)$	0.03	0.04	0.06	0.02
Message x Purchase non-GMO labeled foods
F value	12.17	11.65	0.504	0.270
p value	.008	<.001	0.733	0.887
Effect size $\left({\eta }_p^2\right)$	0.03	0.09	0.00	0.00

Note: For the descriptives statistics section, the mean is reported with standard deviation in parenthesis. For reference, the minimum and maximum values for each variable are reported above the descriptives in italics.

Figure 1. Interaction effect of message by the frequency with which people purchase non-GMO labeled foods on the perception that the message represents the stance taken by the scientific community as a whole. Shaded areas represent 95% confidence intervals.

Figure 2. Interaction effect of Message by the frequency with which participants purchased non-GMO labeled foods on the perception that the message represents the stance taken by the scientific community as a whole. Shaded areas represent 95% confidence intervals.

Figure 3. Violin plot of percent of scientists perceived to agree by condition. The “violins” illustrate kernel probability density (i.e. width is representative of the proportion of responses located at that value on the Y-axis). The thick black line is located at the mean value for each message and the error, illustrated by the white box, is the Bayesian high density interval.