Building Social Capital in Young People: The Role of Mass Media and Life Outlook

Figures & data

Table 1 Factor loadings (standardized), correlations between latent variables, paths from indicators of pessimistic life outlook to social capital factors, and goodness of fit indices

Factors and fit indices	Coeff.	Prob.	Paths between pessimism indicators and social capital
			Hopelessness		Fatalism
			Coeff.	Prob.	Coeff.	Prob.
Civic activity			−.025	.455	−.137	.000
Participate in clubs or extracurricular activities	.644
Volunteer time for a worthy cause	.532	.000
Social trust			−.229	.000	−.114	.000
People will take advantage of me (reversed)	.672
Most people are selfish (reversed)	.472	.000
Correlation between factors	.128	.007
Goodness of fit
χ^2 (df)	11.150 (5)	.049
CFI	.990
RMSEA (90% confidence interval)	.026 (.001, .047)
Note. Coefficients without probability values were fixed at 1.0 in the unstandardized model. CFI = comparative fit index; RMSEA = root mean square error of approximation. Coefficients with probabilities less than. 05 are in bold.

Table 2 Standardized coefficients between media uses and social capital controlling for demographic predictors with and without pessimism indicators

Predictor	Social trust				Civic activity
	No control		Pessimism control		No control		Pessimism control
	Coeff.	Prob.	Coeff.	Prob.	Coeff.	Prob.	Coeff.	Prob.
Hours of TV	−.081	.019	−.074	.036	−.132	.000	−.126	.000
TV shows	.047	.129	.057	.067	.003	.937	.002	.959
National TV news	.045	.139	.052	.091	.123	.000	.123	.000
Informational Internet	.040	.240	.025	.458	.220	.000	.216	.000
Books	.067	.040	.067	.039	.189	.000	.185	.000
Hopelessness			−.200	.000			.004	.902
Fatalism			−.089	.009			−.064	.045
In school	.083	.023	.061	.093	.185	.000	.297	.000
Age	−.090	.006	−.096	.004	−.111	.000	−.112	.000
Male gender	.026	.466	.006	.850	.027	.402	.030	.358
Black identity	−.215	.000	−.211	.000	.073	.042	.070	.050
Hispanic identity	.012	.730	.023	.507	−.117	.000	−.116	.000
Other identity	−.098	.000	−.085	.004	.040	.199	.041	.179
Neighborhood income	.074	.026	.072	.029	.074	.033	.074	.032
Urban location	−.019	.672	−.002	.957	−.011	.800	−.005	.901
Suburban location	−.040	.398	−.029	.520	−.059	.177	−.053	.222
Survey year	−.010	.738	−.013	.658	.021	.483	.018	.543
Note. Goodness of fit for model without pessimism: χ^2(73) = 141.28, p = .000, CFI = .980, RMSEA = .023 (.017, .028); fit for model with pessimism: χ^2(83) = 151.59, p = .000, CFI = .980, RMSEA = .021 (.016, .027). CFI = comparative fit index; RMSEA = root mean square error of approximation. Coefficients with probabilities less than. 05 are in bold.

Table 3 Comparisons between models with different causal directions between media use and social capital factors

Model	χ^2	df	CFI	RMSEA (90% CI)	AIC
1a: Trust → civics → media	113.21	57	.983	.023 (.017, .029)	−0.79
1b: Civics → trust → media	229.23	56	.948	.041 (.036, .047)	117.23
2a: Media → trust → civics	226.81	57	.949	.041 (.035, .046)	112.81
2b: Media → civics → trust	112.71	57	.984	.023 (.017, .029)	−1.29
3a: Trust → media → civics	107.07	54	.984	.023 (.017, .030)	−0.93
3b: Civics → media → trust	104.05	54	.985	.023 (.016, .029)	−3.95
Note. CFI = comparative fit index; RMSEA-Root mean square error of approximation with 90% confidence interval; AIC = Akaike information criterion.

Table 4 Standardized coefficients between measures of social capital and media use

Media variable	Civic activity to media		Media to trust
	Coeff.	Prob.	Coeff.	Prob.
Hours of TV	−.160	.000	−.074	.035
TV shows	.000		.061	.051
National TV news	.170	.000	.054	.078
Informational Internet	.275	.000	.000
Books	.248	.000	.069	.030
Note. Coefficients without probability values were restricted to zero. Coefficients with probabilities less than. 05 are in bold.