Maintenance or change? Examining the reinforcing spiral between social media news use and populist attitudes

Figures & data

Table 1. Means, Standard Deviations, and Bi-variate Correlations (Study 1).

	Variable	M (SD)	1	2	3	4	5	6
1	Populist attitudes	3.66 (1.20)	1
2	Social media	4.97 (2.68)	.17*	1
3	TV	4.02 (2.52)	.29**	.27**	1
4	Radio	3.86 (2.51)	−.01	−.02	.32**	1
5	Newspaper	2.64 (2.12)	−.20**	.11	.25**	.32**	1
6	Online newspaper	5.88 (2.43)	−.09	.17*	.00	−.10	.10	1

Note. * p < .05 ** p < .01.

Table 2. Means and Standard Deviations (Study 2).

Variables	Wave 1	Wave 2	Wave 3	Wave 4
	M (SD)	M (SD)	M (SD)	M (SD)
Populist attitudes	5.06 (1.06)	5.02 (1.07)	4.98 (1.14)	4.91 (1.09)
Social media	2.46 (2.84)	3.11 (2.98)	2.81 (2.95)	2.71 (2.88)
TV	4.66 (2.67)	4.92 (2.70)	5.02 (2.57)	4.86 (2.63)
Newspaper	2.89 (2.76)	2.93 (2.77)	2.99 (2.76)	2.80 (2.72)
Radio	3.88 (2.71)	4.48 (2.64)	4.38 (2.71)	4.30 (2.70)
Mean score (TV, newspaper, radio)	3.81 (1.98)	4.11 (1.98)	4.13 (1.91)	3.99 (1.97)
N	386	373	385	322

Figure 1. Conditional LCM-SR with four repeated measures for social media use (s) and populist attitudes (p). Factor loadings for slopes (β) are set to 0, 1, 2, 3; for intercepts (α) to 1, 1, 1, 1; for residuals (ϵ) to 1. Full lines represent the final model following a strict modeling strategy. Full lines combined with dashed lines represent the final model following a loose modeling strategy.

Table 3. Intraindividual autoregressive, cross-lagged, contemporaneous, and indirect effects.

	Estimate	SE
Conditional LCM-SR (effects constrained to equality over time)
Autoregressive effect on social media use	−.02	.08
Autoregressive effect on populist attitudes	.03	.08
Contemporaneous residual covariance	.09*	.04
Cross-lagged effect on social media use	.68**	.23
Cross-lagged effect on populist attitudes	.03*	.02
Conditional LCM-SR (freely estimated cross-lagged effects for each mediation)
Indirect effect with social media use t2 as mediator (a)	.01	.02
Indirect effect with social media use t3 as mediator (b)	.03	.03
Indirect effect with populist attitudes t2 as mediator (c)	.02	.02
Indirect effect with populist attitudes t3 as mediator (d)	.03	.02

Note. N = 384. Table shows unstandardized coefficients. **p < .01, *p < .05.

Fit indices for mediation models:

^a χ²(27) = 59.10, p < .001, RMSEA = .06, CFI = .99, TLI = .98

^b χ²(27) = 59.70, p < .001, RMSEA = .06, CFI = .99, TLI = .98

^c χ²(27) = 59.72, p < .001, RMSEA = .06, CFI = .99, TLI = .98

^d χ²(27) = 59.80, p < .001, RMSEA = .06, CFI = .99, TLI = .98

Table 4. Covariance, variance matrix for latent growth factors.

	Latent factor	1	2	3	4
1	Int. populist attitudes	.89 (.08)***
2	Int. social media news use	.32 (.15)*	5.46 (.59)***
3	Slp. populist attitudes	.01 (.01)	.01 (.03)	.01 (.01)
4	Slp. social media news use	−.03 (.04)	−.04 (.16)	−.02 (.01)°	.11 (.09)

Note. N = 384. Int. = Intercept, Slp. = Slope. Values in parentheses represent standard errors. Diagonals represent variances. Lower left triangle represent covariances. ***p < .001, *p < .05, °p < .10.