Building Social Capital in Young People The Role of Mass Media and Life Outlook
    Daniel Romer and Kathleen Hall Jamieson1
    University of Pennsylvania
    
    Josh Pasek
    Stanford University
    
    Forthcoming: Political Communication Keywords: Political Socialization, Media Use, Civic Activity, Social Capital, Trust, Pessimism
    
    Abstract
    In this study we evaluate different models of media use to determine whether television and other popular media facilitate or hinder the development of social capital in young people. We surveyed a nationally representative sample of 14- to 22-year olds (N = 1800) to assess the media-social capital relationship controlling for pessimistic life outlook. Consistent with Beck’s (1967) theory of depression, we hypothesized that young people with a pessimistic life outlook will be less trusting of others, will withdraw from civic activity, and will turn to media that have low cognitive demand (e.g., television shows) and avoid media that require greater cognitive resources (e.g., books and informational use of the Internet). Using structural equation modeling, we found that despite support for those predictions, total time spent viewing television remained inversely related to both social trust and civic engagement. However, model tests indicated that civic activity enhances trust by reducing time spent with television and increasing book reading. Furthermore, moderate consumption of entertainment television does not reduce trust. Hence, the results reaffirm the favorable relationships between social capital and media use, including television, in young people but continue to reveal adverse relationships with heavy television use.
    Please direct correspondence to Daniel Romer, Director, Adolescent Risk Communication Institute, Annenberg Public Policy Center, 3535 Market St, Suite 550, Philadelphia, PA 19104-3309. Phone: 215-8986776; fax: 215-573-2667. Email: dromer@asc.upenn.edu. The authors would like to thank Jack McLeod and Dhavan Shah as well as the authors of the other articles in this special issue for their constructive comments. We also acknowledge Mary Bock for ideas that helped shape the manuscript.
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    Building Social Capital in Young People: The Role of Mass Media and Life Outlook Adolescence and young adulthood are critical transition periods for civic and political socialization. Civic participation in youth and early adulthood stimulates long-term engagement (Jennings & Stoker, 2004), and school and family experiences contribute to the process (Davies, 1965; Nie, Junn, & Stehlik-Barry, 1996; Niemi & Junn, 1998). These influences form the building blocks of social capital, including participation in voluntary group activity, that stimulate general interpersonal trust (Brehm & Rahn, 1997; Putnam, 2000). There is also evidence that mass media use can play a role in both political and civic socialization (John & Morris, 2004; McLeod, 2000; McLeod, Rush, & Friederich, 1968; Pasek, Kenski, Romer, & Jamieson, 2006). In an ideal world, mediated experience would provide a valuable civic resource. Media transmit the political and civic information that should help to create an informed citizenry and shared cultural knowledge (Delli Carpini, 2000; Zukin, Keeter, Andolina, Jenkins, & Delli Carpini, 2006). For these reasons, many have suggested that public affairs media use has the power to connect people, building social capital (McLeod, 2000; McLeod et al., 1968). But not all media effects have proven positive. For example, Putnam (1995b; 2000) suggests that television can induce malaise and a variety of negative effects. Putnam proposes two mechanisms to explain how television and other media may undermine social capital: one relies on the cultivation of a “mean world” and the other on time-replacement. In his mean-world prediction, Putnam follows Gerbner and colleagues’ (1980) argument that television – with its focus on violence, fear, and abuse of power – induces a pessimistic worldview, which reduces interpersonal trust (but see Hirsch, 1981). In addition, time spent engaged with the media is time not spent engaging in civic activities and building trusting relationships. Hence, Putnam expects heavy use of media, especially television, to reduce both civic engagement and social trust. For both use of television and the Internet, research offers a mixed verdict. Several studies (Pasek et al., 2006; Shah, McLeod, & Yoon, 2001) identified positive effects associated with use of news and social dramas, in contrast to Putnam (1995b) and John and Morris (2004) who find overall negative effects. A recent study of 15 to 25 year olds by Orlowski (2007)) also found that heavy television use was associated with less civic engagement. Jennings and Zeitner (2003) identify civic benefits from Internet use while Nie and Erbring (2000) find detrimental effects. Inconsistent relationships between media use and social capital have led some researchers to posit that the effects of media use depend on its content (Norris, 1996; Shah, 1998; Shah, McLeod et al., 2001) or that uncontrolled exogenous variables underlie the relationship (Norris, 2002; Scheufele & Shah, 2000; Uslaner, 1998). Perhaps the most well known explanation pointing to an exogenous factor was Uslaner’s (1998) study of adults which found that pessimistic life outlook (dissatisfaction with life and a pessimistic worldview) produced the relationship between television use and interpersonal trust (also see Scheufele & Shah, 2000; Shah, 1998). In particular, pessimistic life outlook was positively related to television use and inversely related to trust. After holding these relations constant, no residual relationship between television use and trust was observed. Once trust and life outlook were controlled, Uslaner also found no time-replacement 2
    
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    effect of television use on civic engagement. Hence, Uslaner’s (1998) analysis disputed both of Putnam’s arguments for the effects of television on social capital. In this research, we begin with Uslaner’s insight that pessimism may be an important factor in the media-social capital relationship and use it to examine the relationship in greater detail in youth ages 14 to 22 who are still undergoing political socialization (cf. McLeod, 2000). In a previous study, Pasek et al. (2006) examined the relationships between use of media and measures of social capital. Like Putnam (1995b; 2000), they found that heavy use of television was inversely related to civic engagement. However, they also found that, in aggregate, media consumption had positive relations. Even moderate use of television helped to facilitate community attachment in young people, by providing shared entertainment and informational resources for group activity. This explanation relies on the same mechanism proposed by Putnam (2000), who argued that team bowling could help to build social capital. However, the Pasek study did not control for life outlook, nor did it examine the effects of media on trust. This study reexamined Pasek et al.’s (2006) hypothesized relation between media use and social capital in young people, including civic engagement and social trust, by including controls for pessimistic life outlook. Additionally, it explored a larger battery of media uses than examined by Uslaner (1998), including book reading and informational Internet use in addition to total time spent watching television. Furthermore, specific forms of television use were examined to separate the amount of time spent with the medium (which has been found to interfere with social capital formation) from its potentially helpful components (news and certain types of entertainment television shows) (Norris, 1996; Shah, McLeod et al., 2001). Finally, the study used structural equation techniques to identify the direction of media-social capital relations. Before developing our hypotheses, we review the literature regarding the potential effects of life outlook on media use and social capital in young people. Life Outlook Research on the effects of pessimistic life outlook in young people (e.g. Abramson, Metalsky, & Alloy, 1989) can be traced to Beck’s (1967) theory of depression. This theory views pessimistic cognitive style as an early developmental predisposition to view the world as unfriendly and unsupportive of the self. Persons with this outlook form unfavorable beliefs about themselves, the world, and their futures. Uslaner (2002) also finds that lack of trust in others appears early in life and is strongly related to pessimistic outlook. According to Beck and more recent cognitive theories of depression (Abramson et al., 1989), those who exhibit a pessimistic life outlook are more prone to experience hopelessness and depression and tend to see the world as confirming their non-optimistic expectations. They also tend to withdraw from social activity, a move that may increase their susceptibility to mediated social experience. Since depression is likely to emerge in adolescence, the effects of this style will be evident in the age range of this study. Although Beck does not fully develop any predictions regarding life outlook and media use, he suggests that persons with a pessimistic style may be drawn to television (Beck, 1967, p. 29), and indeed, Potts and Sanchez (1994) found support for this prediction. Several processes may underlie the preference among persons with a pessimistic outlook for different uses of media. Beck (1967) suggests that individuals experiencing the “depresso-
    
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    genic” effects of pessimistic outlook will lack energy, leading them to prefer less cognitively demanding sources of information and entertainment. Television requires less attention to enjoy than more cognitively demanding media, such as book reading or informational Internet use. It is not surprising therefore that television draws a wider audience than other more cognitively demanding media. Alternatively, based on Gerbner et al.’s (1980) analysis of television, persons with a pessimistic life outlook may be drawn to media that confirm this worldview, a prediction consistent with Uslaner’s (1998) explanation for the relationship between television viewing and trust of others It is also possible that media use triggers pessimism and potentially depressive symptoms. For example, some evidence suggests that heavy Internet use, sometimes called Internet addiction (Sanders, Field, Diego, & Kaplan, 2000; Young & Rogers, 1998), might increase depression (Kraut et al., 1998). However, more recent research suggests that this conclusion may be overwrought (Amichai-Hamburger, 2005; Gross, 2004; Jackson et al., 2006) and that depression is more likely triggered by stressful personal events than heavy media use (Schou, Ekeberg, Sandvik, & Ruland, 2005). Furthermore, we focus on informational use of the Internet, which is more cognitively demanding and similar to book reading (Bennett, Rhine, & Flickinger, 2000). Hence, in developing our hypotheses, we expected that pessimistic life outlook and the emergence of hopelessness are more likely to influence media use and social capital formation than the other way around. The Current Investigation Beck’s (1967) theory appears able to explain a major source of covariation between pessimistic life outlook, media use, interpersonal trust, and civic engagement. In particular, to the extent that persons with a pessimistic outlook experience depressive symptoms, we would expect them to view others as untrustworthy and to withdraw from social activity (Hypothesis 1a). In addition, we expected persons with a pessimistic outlook to spend more time with entertainment media (Hypothesis 1b), especially those that are easy to consume such as television. However, persons who do not exhibit the effects of a pessimistic life outlook should be more likely to use cognitively demanding informational and entertainment media, such as books and information on the Internet, and should be more likely to participate in voluntary group activities that help to develop generalized trust in others (Hypothesis 1c). Because persons with a pessimistic life outlook view the world as unsupportive and may be drawn to television, we expected the negative relation between heavy television use and social capital to be a partial product of pessimistic life outlook. Hence, we expected to replicate Uslaner’s(1998) finding that, after controlling for life outlook, the negative relation between heavy television viewing and social capital will be reduced (Hypothesis 2a). Nevertheless, the effects of television were not expected to be monolithic. As Pasek et al. (2006) found, following television shows and national news may have favorable relations with indicators of social capital, especially after controlling for overall use of television (Hypothesis 2b). Furthermore, we expected to replicate positive relations with social capital for book reading and informational Internet use even after controlling for pessimistic life outlook (Hypothesis 2c). Aside from testing the predictions of Uslaner using Beck’s theory, we were also interested in the causal ordering of relations between media use and social capital formation.
    
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    Considerable research indicates that civic activity in high school foreshadows continued community participation in later life (Jennings & Stoker, 2004; Smith, 1999; Zaff, Moore, Papillo, & Williams, 2003). However, the causal role of civic activity in building social capital is not clear. Jennings and Stoker (2004) argue that trust is the more important factor in promoting civic activity in adults. On the other hand, Brehm and Rahn (1997) suggest that civic activity is a stronger influence on trust. Nevertheless, little is known about these relations and even less about the media’s role in building social capital in adolescents and young adults. As noted above, we expect a strong relation between media use and civic engagement even after controlling for life outlook. However, the direction of the relation is not clear. Consuming media connects youth to others by providing a common culture. From this perspective, greater media use should enable civic activity. It is also possible that individuals engaged in civic activities use media instrumentally, gathering information for conversations with peers. For example, peers may create interest in media content that would otherwise not be accessed. Nevertheless, under either model, excessive use of media should eventually compete with civic activity, an effect that will be particularly apparent among heavy television users (Pasek et al., 2006; Orlowski, 2007; Putnam, 2000). Practitioners seeking optimal social policies to encourage greater social capital formation in young people should choose interventions that take advantage of relations between civic activity, media use, and social trust. For example, if civic activity plays an important role in spurring either favorable media use or social trust, then policies that facilitate continued schooling should be emphasized. Indeed, apart from its ability to increase human capital, school attendance encourages social capital formation by providing increased opportunities for extra-curricular activity (Jennings & Stoker, 2004), such as community service (Niemi, Hepburn, & Chapman, 2000). On the other hand, if some types of media use are favorable for social capital formation, then policies that encourage youth to engage with those media may also be important. Whatever the role of civic activity, it is possible that media use mediates the relation between civic activity and trust. For example, if civic activity influences media use, and media use influences trust, then media use could serve as a link between these outcomes that could be targeted to increase social trust. In testing these alternative models, we hypothesized that media use facilitates the relation between trust and civic engagement (Hypothesis 3) rather than merely serving as an offshoot of social capital. This hypothesis requires testing alternative models for relations between media use and indicators of social capital. Analysis Strategy To disentangle the potential causal relations between the variables in this study, we examined the relation between media use and indicators of social capital using structural equation modeling (SEM). This strategy depends on having indicators that can serve as “exogenous” predictors of both media use and social capital (Kline, 2005). In our analysis, both pessimism and background demographics serve as exogenous predictors of the “endogenous” measures of media use, social trust, and civic engagement under the assumption that the endogenous variables do not affect the exogenous variables. However, to identify the best model, we test alternative directions of influence between media use, trust, and civic engagement. We first estimate a version of the model in which (a) media use is a
    
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    consequence of social capital. We test two versions of this model on the assumption that civic activity could either be a cause or consequence of social trust: in one, civic activity influences trust which then influences media use, and in the other trust influences civic activity which then influences media use. These models represent a weaker role for media use. We compare the two weak models to two sets of alternative arrangements in which media use plays a more central role. In the first of these (b), media use creates social capital. We again test two versions of this model, one in which media use influences trust which then influences civic activity, and the other in which media use influences civic activity which then influences trust. Finally, we test models in which media use mediates the relation between trust and civic activity (c). We again test two versions of these models, one in which trust influences media use which then influences civic activity, and one in which civic activity influences media use which then influences trust. Our overarching question is to determine which, if any, of these models provides the best fit to the data. We hypothesized that one of the two sets of models that includes media use as either an instigator of social capital (b) or a mediator (c) will provide a better fit to the data than the ones (a) in which media use is merely a consequence of social capital.
    
    Methods
    Data for this study come from the Annenberg Public Policy Center’s 2005 and 2006 National Annenberg Survey of Youth (NASY), a nationally representative sample of 14- to 22- year olds (N = 900 per year) identified using random digit dialing procedures (see Pasek et al., 2006, for a description of the procedure). The data from the two survey years were combined for this study. Respondents were surveyed on media uses, interpersonal trust, pessimistic life outlook, and civic engagement during the spring and summer of each year. In 2006, a $10 incentive was provided to encourage participation. The response rates for the survey (AAPOR formula 3) were 45.7% (2005) and 48.4% (2006). The survey was approved by the Institutional Review Board of the University of Pennsylvania. Dependent Variables Interpersonal trust and civic engagement have been central concepts in quantifying social capital. Interpersonal trust was assessed with two items coded on a four-point scale from “strongly agree” (0) to “strongly disagree” (3). Respondents were asked whether they agreed or disagreed with the statements that “Most people will try to take advantage of you if they get the chance” (M = 1.44, SD = 1.06) and “Most people only look out for themselves” (M = 1.24, SD = .95). The correlation between the items was .299 and .335 in each year respectively (p’s = .000). Civic engagement was indexed with two items assessing the frequency of club participation and volunteering. These items were assessed on threepoint scales of “never” = 0, “some days” = 1, and “most days” = 2. Respondents expressed how often they “participate in a club or other extra-curricular activity” (M = .91, SD = .82) and how often they “volunteer [their] time for a worthy cause such as community service” (M = .65, SD = .64). The correlation between the items was .342 in each year (p’s = .000). Although these items do not assess the potential breadth of social ties, they do provide information about the intensity of civic engagement.
    
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    Life Outlook Two items assessed life outlook among the respondents. Students with a pessimistic life outlook are those who have experienced two weeks of hopelessness in the past year to the point where it interfered with their normal activities (cf. Beck, Weissman, Lester, & Trexler, 1974) or who do not expect to live past age 30 (Fischhoff et al., 2000; Jamieson & Romer, 2008). Hopelessness was assessed as a dichotomous variable (M = .20), and fatalistic life expectation was measured on a four-point agree-disagree scale with the item: “I don’t expect to live much past the age of 30.” Approximately 16% of respondents expressed less than strong disagreement with this statement. This level of disagreement is clearly unrealistic and is not strongly related to either income or urban vs. rural residence (Jamieson & Romer, 2008). However, both Hispanic and African American youth as well as males report higher levels of fatalism. Hopelessness, on the other hand, is more prevalent among female youth but is not related to income or to racial-ethnic identity. The correlation between the items was .130 and .143 in each year (p’s = .000). Because both measure potentially different aspects of life outlook (Jamieson & Romer, 2008), we treated them as separate predictors in our models. Media Use To assess the effects of television, we examined total time spent with the medium per day (in hours) as well as use of national television news on either broadcast or cable stations and following of television shows. Although heavy use of television may interfere with civic engagement, we expected that use of national news and following of shows would be positively related to indicators of social capital once overall use of television was controlled. In addition, we included informational use of the Internet and book reading as media uses that also exhibit positive relations with indicators of social capital but that are negatively related to hours of daily television use (r’s = -.10 and -.08, p’s< .001, respectively). Including these uses allowed us to test the prediction that pessimistic outlook discourages the use of more cognitively demanding media. In addition, controlling for these uses helps to rule out the possibility that heavy television use is detrimental to social capital formation simply because it displaces these more supportive uses of media. Respondents reported the frequency of their media use with a four-point scale ranging from 0 = “never” to 3 = “most days.” They were asked how frequently they “Read a book” (M = 1.78, SD = 1.04), “Go online to get information” (M = 2.30, SD = .99), “Watch the national nightly TV news or a cable station like CNN” (M = 1.41, SD = 1.12), and “Watch a show that they follow on television” (M = 2.08, SD = 1.00)2 . Daily hours of television use were assessed in five categories: “Less than 1 hour” = 0.5, “1 to 2 hours” = 1.5, “3 to 5 hours” = 4.0, “5 to 8 hours” = 6.5, “more than 8 hours” = 9.0 (M = 2.80, SD = 2.08). However, because there was little difference in either measures of trust or civic engagement between the two lowest levels of television viewing, we collapsed these categories. There were no differences between the two waves of the survey for any of the media measures with the exception of Internet use, which registered a small gain from 2005 to 2006 (2.23 to 2.37, p = .002).
    Our measures of television use do not cover the entire spectrum of television content. There are movies and other non-continuing shows as well as advertising that are heavily represented on this medium.
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    Demographic and Control Variables Our analysis uses controls for eight demographic variables that in previous research have been shown to be related to social capital and media uses. Education has consistently emerged as one of the strongest indicators of social capital (Helliwell & Putnam, 1999; Putnam, 1995a). We control age, which is highly correlated with the highest grade level achieved by respondents (r = .72), and whether they were currently in school or not. Age was coded into three levels (14-16, 17-19, and 20-22). Student status was a dichotomous variable based on whether respondents indicated that they were currently attending school either full or part time (1) versus not (0) (M = .77, SD = .42). To control for socioeconomic status, we also assessed the median income of the zip code where they lived using 2000 Census data (M = 45.14, SD = 18.28 in thousands of dollars). Variation due to race, ethnicity, and gender was also included. Though racial-ethnic differences are not regarded as particularly strong for civic engagement (Lopez, 2002), significant differences have been apparent for interpersonal trust (Hart & Atkins, 2002). Gender differences have also been found for various political outcomes (see Kenski & Jamieson, 2000). There was a slight increase in the proportion of black (.10 vs. .14, p = .014) and Hispanic respondents (.15 vs. .19, p = .041) from 2005 to 2006. However, the representation of other non-white race respondents remained the same (M = .08). Whites served as a reference category. A dummy variable was also created for male respondents (M = .50). Access to civic activity and media may vary depending on urbanicity (Hart & Atkins, 2002). Hence, dummy variables for urban (M = .31) and suburban (M = .48) status were included to control for these differences. Analysis Hypotheses were examined in a SEM estimated using the EQS program (Bentler, 2004). The program allows for the simultaneous estimation of direct and mediating effects on latent variables. Additionally, EQS offers robust statistics, which adjust for the effects of departures from multivariate normality due to skewness and kurtosis. All coefficients shown in the results have probabilities evaluated with robust standard errors. EQS was used first to assess the adequacy of our measurement of social trust and civic activity as latent variables. In the next analysis, relationships between media uses and trust and civic engagement were examined while controlling for other media uses as well as potential effects of background demographic variables. We tested the model with and without controls for pessimistic life outlook to evaluate the prediction that life outlook accounts for relations between media use and social capital. In the final set of analyses, we tested different models to identify the role of media use in relations between social trust and civic activity. In these analyses, media uses were treated as endogenous variables that could be affected by demographics as well as by either trust or civic engagement. We used goodness of fit indices described below to assess differences between alternative models. To evaluate alternative SEMs, we looked at four different measures of overall goodness of fit. First, a Chi-square test (χ2 ) was used to compare the predicted covariance matrix with the observed matrix. We used the Yuan-Bentler(1998) scaled χ2 which is provided for models with robust estimates (Bentler, 2004). A significant value for this measure indicates that the predicted model does not account for all of the covariation between measures.
    
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    Chi-square tests, however, are very sensitive to sample size, and significant values do not necessarily indicate a poor fit with large samples. For this reason, we augment this measure with additional indices that are not as sensitive to sample size and represent a graded index of fit (Hu & Bentler, 1995): the Comparative Fit Index (CFI) and Root Mean Square Error of Approximation (RMSEA). CFI is a comparison of two fit functions: one from the covariance matrix estimated from the fitted model and one from a model that assumes no association between the observed variables. Higher values reflect the relative advantage of the proposed model over a model with no association. Values greater than .90 are considered acceptable (Hu & Bentler, 1995). The RMSEA measures the mean residuals between the observed and predicted covariance matrix. Departures from zero represent poorer fit. RMSEA values less than or equal to .05 are considered acceptable (Kaplan, 2000, p. 113). One additional index was included that is designed to distinguish models that are not nested within each other: the Akaike Information Criterion (AIC) (1987). We used this index to assess the fit of models with different directions of influence between media uses and social capital. The index (χ2 - 2df) takes both overall fit as well as the number of parameters needed to achieve the fit into account where df represents the degrees of freedom in the model. Better fitting models have lower values even if the degrees of freedom are smaller. To account for non-responses for certain variables, we used full information maximum likelihood imputation of missing data using procedures implemented in EQS. Approximately 6.9% of respondents did not know their zip codes or provided ones that could not be matched to an income, and 2.9% were missing one or more other demographic variables.
    
    Results
    Before testing our hypotheses, it is important to verify that our measures adequately assessed each of our latent constructs. As seen in Table 1, a model containing both pessimism items as exogenous predictors of social trust and civic activity exhibited a good fit to the data with each indicator highly related to its latent variable. In addition, as predicted, measures of pessimistic life outlook were negatively related to both outcomes (Hypothesis 1a). Fatalistic life expectations were related to both social trust (-.114) and civic activity (.137). Episodes of hopelessness were negatively related to trust (-.229) but not with activity (-.025). Social trust and civic engagement were positively correlated (.128). Relationships between Pessimism and Media Use As predicted by hypothesis (1b) that pessimism would be positively related to television use, both hopelessness (.059) and fatalism (.102) were related to hours of television use, and hopelessness was related to following of entertainment television shows (.070). Following of national news on television was not related to either measure of pessimism (-.008, .032). Consistent with the hypothesis (1c) that pessimism would be negatively related to media requiring greater cognitive demand, we found that hopelessness (-.066) and fatalism (-.097) were negatively related to informational Internet use and fatalism to book reading (-.090).
    
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    Relationships between Media and Social Capital The results of the SEM in Table 2 provide estimates of the relations between media uses and both trust and civic activity holding constant demographic differences and relations between media. The table compares these estimates with and without controls for pessimistic life outlook. It is clear the relations between hours of television viewing and both trust and civic activity are negative and that these relations decline slightly when holding constant pessimistic outlook (Hypothesis 2a). Nevertheless, if we fix these coefficients to the values they obtained in the model without pessimism controlled, the fit of the overall model remains virtually unchanged, χ2 (2) = 0.52, ns. This finding indicates that controlling for pessimistic life outlook does not alter relationships between time spent with television and either measure of social capital3 . In fact, pessimism does not serve as a moderator or mediator of demographic or media use influences on either social capital variable. None of the six significant coefficients for media uses and only one of the ten demographic influences is substantially changed by the inclusion of pessimism in the model. The exception is that the tendency of in-school youth to be civically active is strengthened (.185 to .297 after controls). Despite the negative relationship between time spent with television and social capital, both types of television content were positively related to the factors (Hypothesis 2b), especially use of news and civic activity. Although both television news and entertainment shows were only marginally positively related to trust, these relations stand in contrast to the negative relationship between time spent with television and trust. These findings indicate that when overall television use is held at its mean, use of both components of television content tend to be favorable for social capital. As predicted by Hypothesis 2c, both book reading and informational Internet use (high cognitive demand media) were positively related to social capital. The only relation that was not significant was between Internet use and trust. Several of the demographic variables were related to each social capital factor. In particular, current school attendance was a strong predictor of both trust and civic activity. In addition, age was negatively related to both indicators of social capital. Not surprisingly, age was also negatively related to current school attendance (-.412), one of the strongest correlates of each social capital factor4 . Living in wealthier neighborhoods was also strongly related to each factor. Nevertheless, some demographic differences were only related to one factor. Black youth and those with other identities tended to report less trust of others than white youth. In addition, Hispanic youth tended to engage in less civic activity than white youth. The relationship between trust and civic activity was no longer significant when holding constant pessimism, media use, and background factors, r = .057, p = .262. This finding suggests that media use and demographic differences help to explain the relation between civic activity and social trust, but they do not tell us what role media use plays in explaining
    Although controlling for pessimism did not eliminate relations between media use and social capital, it was still possible that pessimism moderated the relation. However, both graphic and interaction tests revealed no evidence of moderation by either indicator of pessimism. 4 Because age was a potent correlate of social capital, we examined relations between media uses and each social capital indicator by age. These relations tended to follow the same pattern with little evidence of systematic differences by age group.
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    the relationship. To explore this question further, we turn to more explicit models that test alternative relations between trust and civic activity. Models of Media Use and Social Capital The models we have estimated tested the hypothesis that pessimism and background factors could account for relations between media use and social capital. Having rejected this hypothesis, we tested models in which media use could play different roles in the trust-civic activity relationship. In performing these comparisons, we used the results of the estimates in Table 2 to trim non-significant coefficients from further model tests. All subsequent tests also assumed that the models could account for the relation between trust and civic activity without correlating the errors in the two factors. Consistent with Hypothesis 3, tests of alternative models revealed that the best fit indices were obtained for the model (C2) in which civic activity affected media use and media use affected social trust (Table 3). Models in which media use merely reflected social capital (A1 and A2) did not fare as well. Alternative models (A1, B2, and C1) that had a direct connection between media use and civic activity were nearly as successful, suggesting that this component of the model was a strong contributor to model fit. Nevertheless, the model with media use mediating the relation between civic activity and trust provided the best fit. Furthermore, the model accounted for all of the correlation between trust and civic activity that was explained by the initial analysis that controlled all predictors (Table 2): the residual correlation between the factors was .066 (p = .207), not different from the .057 observed in the initial analysis. The coefficients between media use and social capital for the best fitting model are shown in Table 4. According to this model, civic activity reduces time spent with television, which enhances trust (-.160 * -.074 = .012). It also increases book reading, which enhances trust (.248 * .069 = .017). The combined influence of these paths (.029) accounts for nearly 50% of the correlation between trust and civic activity (.128 - .066 = .062) that is explained by the model. In addition, youth who engage in civic activity use the Internet for information and watch national television news to a greater degree than those who are less active. Although consumption of entertainment television is not directly affected by civic activity, it is marginally positively related to trust. These findings indicate that television has a complex and contradictory role. Holding time spent with television at its mean, the effect of entertainment shows on trust is favorable. In addition, civically active youth spend less time with television, although they follow entertainment shows as much as less active youth and watch news to a greater degree.
    
    Discussion
    This study provides strong support for predictions regarding the effects of pessimistic life outlook derived from Beck’s theory of depression. This theory leads to the expectation that pessimists should be less trusting of others in general and should withdraw from civic activity (Hypothesis 1a). Furthermore, such persons should fill their time with relatively low cognitive demand media, such as television, rather than cognitively demanding uses, such as reading books and using Internet to gather information (Hypotheses 1b and c). Our results confirmed these predictions.
    
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    Having established these findings, we examined the relations between media use and both social trust and civic activity with and without controls for pessimism. We replicated previous findings indicating that time spent with television interferes with the development of social capital. However, contrary to Hypothesis 2a, although pessimism was related to both use of television and to trust and civic activity, holding it constant did not reduce the inverse relation between time spent with television and social capital. In addition, following national news and entertainment shows on television was marginally related to trust, and national television news was related to civic activity even after controlling for pessimism (Hypothesis 2b). These findings fail to confirm Uslaner’s hypothesis with regard to time spent with television and suggest that young people’s pessimism is not the source of the negative relation between use of television and social capital. Indeed, the results suggest that heavy use of television reduces trust, despite the finding that specific uses of television need not do so, especially when total time spent with television is held constant. Consistent with results of Pasek et al. (2006) in a similar youth sample, we again find that informational Internet use and book reading are positively related to civic activity (Hypothesis 2c). This study extends this pattern to effects on social trust, at least with regard to book reading. Other research also suggests that informational Internet use is positively related to social trust in adults (Shah, Kwak, & Holbert, 2001; Shah, McLeod et al., 2001). The results of our model tests confirmed our third hypothesis that media play a role in the generation of social capital. However, contrary to the common assumption that television displaces civic activity, it appears just as likely that civic engagement displaces total time spent with television. In retrospect, this is not surprising since access to television is ubiquitous but opportunities for engaging in civic activity are more restricted. Although early time use studies indicated that television displaced other activities in adults, including civic endeavors (Robinson & Godbey, 1997), today’s youth grew up in an environment in which television was the norm. Desisting from its use would therefore require a competing interest, and engaging in civic activity would surely qualify. Interpreting the Role of Television and Other Media Despite the apparent displacement of television by civic engagement, civically-active youth still appear to use entertainment television as much as and use televised news programs more than other youth. Since some forms of viewing, for example exposure to entertainment shows, are positively related to trust in others, television as a medium is difficult to characterize. Indeed, one is left with the conclusion that excessive use of television reduces interpersonal trust while specific uses, such as following entertainment shows, do not. One possible explanation for this pattern is that it is only when television use is excessive that its harmful effects emerge. Recall that we found that reports of television viewing up to two hours per day did not compete with either indicator of social capital. This is sufficient time to follow shows or watch news on a daily basis. Another possibility is that it is other content besides news and entertainment that drives the trust-inhibiting effects of the medium. One source that could be responsible is advertising. Large amounts of programming are devoted to advertising, and these messages have been found to have ill effects on youth, including the creation of body image problems (Groesz, Levine, & Murnen, 2002; Hargreaves & Tiggemann, 2004; Kilbourne, 1999) and poor eating habits (Kaiser
    
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    Family Foundation, 2004). Milner’s (2004) in-depth studies of high school cultures suggest that the consumerist messages contained in advertising and marketing create status envy in youth that may reduce trust in others. The effects of advertising are also consistent with Rahn and Transue’s (1998) conclusion that an increase in materialist values has subverted interpersonal trust in young people. The link between television viewing and materialist values is an hypothesis worthy of exploration. Our finding that civic activity leads to use of media, apart from heavy use of television, is also consistent with the interpretation of media use posited by Shah et al. (2001) in adults and Pasek et al. (2006) in youth. These authors suggested that media promote social capital by helping to build community and a common culture. Although this hypothesis may seem at odds with the causal direction we find in the best fitting model (C2), youth who are civically active may turn to media to gain information and experiences that they can share with their colleagues. Hence, the media may provide a community-building resource even if the primary causal direction goes from activity to media use. Another possibility is that discussion with peers during civic activity increases cognitive competence to process news and other more cognitively demanding media content5 . This hypothesis is also consistent with the findings of Hively and Eveland in the present collection that discussion with family and peers enhances knowledge potentially transmitted through the media. While we find that the path from civic engagement to media use to trust (model C2) is most robust, other models also fit the data. Indeed, the two models that fit least well (A2 and B1) contain trust as a mediator of civic activity and media use. If we rejected these models but took a more equivocal view of the others, we would conclude that media use and civics are closely aligned and potentially reciprocal in influence while trust either initiates the social capital cycle (A1 and C1) or is a consequence of the other factors (B2 and C2). Hence, connections between civic engagement and media use are particularly strong, and we have suggested some likely causal processes that underlie these relationships. Effects of Age on Social Capital We found that as adolescents age, they tend to withdraw from civic activity and to report less trust in others. This pattern conforms to the findings of Jennings and Stoker (2004), who suggest that diminished civic opportunities and the demands of post-adolescent life crowd out civic activity and reduce trust. Nevertheless, examination of the pattern of relations between age, school attendance, and social capital in the strongest model (C2) indicates that youth who continue schooling beyond high school exhibit much less reduction in civic activity. In particular, school attendance is the strongest predictor of civic activity (.269, p = .000), and age is barely significant as a predictor after holding school attendance and demographics constant (-.068, p = .051). The positive effects of school attendance then carry-over to trust by virtue of the favorable effects of civic activity on media use (Table 4). Indeed, the effect of schooling is no longer significant in predicting trust apart from media use (.067, p = .060). Hence, the results of the mediated model suggest that schooling is a major source of the beneficial effects of civic activity on media use and trust. Of course, this should not be entirely surprising as educational institutions provide civic opportunities. Nevertheless, not all is well in the relation between age and trust. The model
    5
    
    We thank Michael McDevitt for this suggestion.
    
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    indicates that despite holding constant media use and demographics, age is still a negative predictor of trust in others (-.093, p = .004). Hence, other factors remain that reduce young people’s trust apart from their withdrawal from schooling. As Jennings and Stoker (2004, page 372) note, the transition to adulthood when young people have to “go it alone” is not a particularly fertile period for the generation of social capital. Why Are Our Results Different from Uslaner’s? Several potential explanations may account for our failure to replicate Uslaner’s findings. First, we studied a decidedly younger population than he did. It is possible that pessimistic beliefs have not yet had the widespread effects that he found in adults. Nevertheless, we did find that pessimism was negatively related to both civic activity and trust in young people. Furthermore, indicators of pessimism were related to media use in predictable ways. Despite these confirmed predictions, the relations with overall time spent with television were not sufficiently strong to explain the very powerful negative effects of television viewing. Another possibility is that our measures of pessimism were not as robust as his. However, our measures should have captured the extremes of the pessimism continuum. Indeed, they tend to correlate with suicidal ideation in youth and predict adverse outcomes such as school leaving (Jamieson & Romer, 2008). A third possibility is that we analyzed relations between media use and social capital using latent variables. This analysis may be more sensitive to the underlying construct than using a single indicator. A final possibility is that Uslaner would have found the same result if he had not over-controlled for trust in his models. In addition to his measure of pessimism (“It’s unfair to bring a child into the world”), he also included items that may have correlated with trust because they were measures of the same underlying life outlook. Here we are thinking of items measuring “satisfaction with friends” and agreement with the statement that “Officials don’t care for the average person.” These items could just as easily be indicators of trust in others as measures of pessimism. Inclusion of such items as predictors in the model may have reduced the relation between television use and trust by controlling on the dependent variable. Similar factors may have entered into Uslaner’s analysis of civic participation. Our results suggest that trust is a consequence of television use and so holding it constant in a model for civic activity may control for the effects of television on this outcome. Implications for Policy Our findings suggest that the media are an important resource for the development of social capital in youth. However, excessive use of television is not helpful and any programs that encourage young people to get involved in civic activity should help to reduce television use. The results indicate that youth who attend school at whatever level are more likely to be civically engaged. Hence, policies that enable youth to continue schooling are an obvious recommendation. Furthermore, schooling is likely to increase attraction to more cognitively demanding media, such as informational Internet use and book reading that may compete with and help reduce heavy television use. Since informational Internet use also enhances political awareness (Delli Carpini, 2000; Pasek et al., 2006), the use of this medium in school curricula may help to increase interest in political and civic activity. Indeed, research on school civics interventions such as the Student Voices program (Feldman, Pasek, Romer, & Jamieson, 2007; Pasek, Feldman, Romer, & Jamieson, 2008) indicates that use of Internet
    
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    resources in the classroom may increase knowledge about political candidates and motivate voting. In this regard, it is encouraging that informational Internet use appeared to rise from 2005 to 2006, the only change we observed in the media we examined in this study. Furthermore, the Student Voices program has been successful in poor urban school districts where our demographic predictors suggest that trust in others and civic activity may be weaker. Hence, greater informational use of the Internet in school civics curricula may help to increase both political and civic engagement. Limitations and Further Research A number of questions emerge from this study that require additional research. First, the life outlook variables we utilized could be further refined. The current measures focus on the pessimistic end of the dimension. It would be valuable to examine the optimistic end of the continuum in greater detail to see whether variation in positive outlooks also relates to increased trust and the consumption of high cognitive demand media. Though there is significant theoretical support for our use of life outlook as a predictor of media use (Abramson et al., 1989; Beck, 1967), it is possible that some media uses are able to change life outlook. Because we used a cross sectional design, some of the relationships we found may have been caused by media use rather than the other way around. Nevertheless, the failure to eliminate relations between television use and trust when holding pessimism constant suggests that even if the relation were bidirectional, it would not account for the robust relations that we observe. It is also possible that the relation between civic activity and trust is more complex than our models can account for. Our finding that the relation was primarily from civic activity to trust is consistent with Brehm and Rahn’s (1997) conclusion that this direction of influence is stronger. In addition, the correlation between trust and civic activity was no longer significant in our best fitting model. However, it is worth recognizing that whatever the causal relationship between civic activity and social trust, that relationship is quite modest at best, suggesting that other sources of each component of social capital may be more fruitfully studied than the relation between them. Nevertheless, a longitudinal study would help to identify these reinforcing influences and potentially provide evidence for a “virtuous circle” in the civic activity and trust relationship. Conclusion This study reexamines Uslaner’s (1998) finding that pessimism accounts for the negative relationship between television use and interpersonal trust. While pessimism is related to more television use and lower trust in a youth sample, it does not account for a significant portion of the relationship. Further, Uslaner’s proposed spurious relationship does not account for other more favorable media-social capital relationships. We posit that many young people are using media to reinforce social ties leading to a robust relationship between civic activity and media use. As a result, civic activity may facilitate both favorable use of media and social trust.
    
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    References
    Abramson, L. Y., Metalsky, G. I., & Alloy, L. B. (1989). Hopelessness Depression: A Theory-Based Subtype of Depression. Psychological Review, 96(2), 358-372. Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317-332. Amichai-Hamburger, Y. (2005). The social net: Human behavior in cyberspace. New York: Oxford University Press. Beck, A. T. (1967). Depression: Clinical, Experimental, and Theoretical Aspects. Philadelphia: University of Pennsylvania Press. Beck, A. T., Weissman, A., Lester, D., & Trexler, L. (1974). The measurement of pessimism: The Hopelessness Scale. Journal of Consulting and Clinical Psychology, 42(6), 861-865. Bennett, S. E., Rhine, S. L., & Flickinger, R. S. (2000). Reading’s Impact on Democratic Citizenship in America. Political Behavior, 22(3), 167-195. Bentler, P. M. (2004). EQS 6: Structural Equations Program Manual. Encino, CA: Multivariate Software Inc. Brehm, J., & Rahn, W. (1997). Individual-Level Evidence for the Causes and Consequences of Social Capital. American Journal of Political Science, 41(3), 999-1023. Davies, J. C. (1965). The Family’s Role in Political Socialization. Annals of the American Academy of Political and Social Science, 361, 10-19. Delli Carpini, M. X. (2000). Gen.com: Youth, Civic Engagement, and the New Information Environment. Political Communication, 17, 341-349. Feldman, L., Pasek, J., Romer, D., & Jamieson, K. H. (2007). Identifying Best Practices in Civic Education: Lessons from Student Voices Philadelphia. Amercian Journal of Education, 114(1), 75-100. Fischhoff, B., Parker, A. M., Bruin, W. B. d., Downs, J., Palmgren, C., Dawes, R., et al. (2000). Teen Expectations for Significant Life Events. Public Opinion Quarterly, 64(2), 189-205. Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1980). The “Mainstreaming” of America: Violence Profile No. 11. Journal of Communication, 30(3), 10-29. Groesz, L. M., Levine, M. P., & Murnen, S. K. (2002). The effect of experimental presentation of thin media images on body satisfaction: A meta-analytic review. International Journal of Eating Disorders, 31, 1-16. Gross, E. F. (2004). Adolescent Internet use: What we expect, what teens report. Journal of Applied Developmental Psychology, 25, 633-649. Hargreaves, D., & Tiggemann, M. (2004). Idealized media images and adolescent body image: “Comparing” boys and girls. Body Image, 1(4), 351-361. Hart, D., & Atkins, R. (2002). Civic Competence in Urban Youth. Applied Developmental Science, 6(4), 227-236. Helliwell, J. F., & Putnam, R. D. (1999). Education and Social Capital. NBER Working Paper Series, 7121. Hu, L., & Bentler, P. M. (1995). Evaluating Model Fit. In R. H. Hoyle (Ed.), Structural Equation Modeling: Concepts, Issues, and Applications (pp. 76-99). Newbury Park, CA: Sage. Jackson, L. A., von Eye, A., Biocca, F. A., Barbatsis, G., Zhao, Y., & Fitzgerald, H. E.
    
    LIFE OUTLOOK, MEDIA USE, AND SOCIAL CAPITAL AMONG ADOLESCENTS
    
    17
    
    (2006). Children’s home internet use: Predictors and psychological, social, and academic consequences. In R. Kraut, M. Brynin & S. Kiesler (Eds.), Computers, phones, and the Internet: Domesticating Information Technology (pp. 145-167). New York: Oxford University. Jamieson, P. E., & Romer, D. (2008). Unrealistic fatalism in U. S. youth ages 14 to 22: Prevalence and characteristics. Journal of Adolescent Health, 42, 154-160. Jennings, M. K., & Stoker, L. (2004). Social Trust and Civic Engagement across Time and Generations. Acta Politica, 39, 342-379. Jennings, M. K., & Zeitner, V. (2003). Internet Use and Civic Engagement: A Longitudinal Analysis. Public Opinion Quarterly, 67, 311-334. John, P., & Morris, Z. (2004). What are the Origins of Social Capital? Results from a Panel Survey of Young People. British Elections and Parties Review, 14, 94-112. Kaiser Family Foundation. (2004). The role of the media in childhood obesity. Menlo Park, CA: The Henry J. Kaiser Family Foundation. Kaplan, D. (2000). Structural Equation Modeling. Thousand Oaks, CA: Sage. Kenski, K., & Jamieson, K. H. (2000). The Gender Gap in Political Knowledge: Are Women Less Knowledgeable Than Men About Politics? In K. H. Jamieson (Ed.), Everything You Think You Know About Politics. and why you’re wrong (pp. 83-89, +238-241). New York: Basic Books. Kilbourne, J. (1999). Deadly persuasion: Why women and girls must fight the addictive power of advertising. New York: The Free Press. Kline, R. (2005). Principles and practices of structural equation modeling. New York: Guilford Press. Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukopadhyay, T., & Scherlis, W. (1998). Internet Paradox: A Social Technology that Reduces Social Involvement and Psychological Well-Being? American Psychologist, 53(9), 1017-1031. Lopez, M. H. (2002). Civic Engagement Among Minority Youth (Fact Sheet). College Park, MD: CIRCLE. McLeod, J. M. (2000). Media and the Civic Socialization of Youth. Journal of Adolescent Health, 27S(2), 45-51. McLeod, J. M., Rush, R. R., & Friederich, K. H. (1968). The Mass Media and Political Information in Quito, Equador. The Public Opinion Quarterly, 32(4), 575-587. Milner, M. (2004). Freaks, geeks, and cool kids: American teenagers, schools, and the culture of consumption. New York: Routledge. Nie, N. H., & Erbring, L. (2000). Internet and Society: A Preliminary Report (Report): Stanford Institute for the Quantitative Study of Society. Nie, N. H., Junn, J., & Stehlik-Barry, K. (1996). Education and Democratic Citizenship in America. Chicago: University of Chicago Press. Niemi, R. G., Hepburn, M. A., & Chapman, C. (2000). Community Service by High School Students: A Cure for Civic Ills? Political Behavior, 22(1), 45-69. Niemi, R. G., & Junn, J. (1998). Civic Education: What Makes Students Learn. New Haven: Yale University Press. Norris, P. (1996). Does Television Erode Social Capital? A Reply to Putnam. PS: Political Science and Politics, 29(3), 474-480. Norris, P. (2002). The Bridging and Bonding Role of Online Communities. The Harvard
    
    LIFE OUTLOOK, MEDIA USE, AND SOCIAL CAPITAL AMONG ADOLESCENTS
    
    18
    
    International Journal of Press/Politics, 7(3), 3-13. Orlowski, A. P. (2007). Television consumption and civic engagement among 15 to 25 year olds. College Park, MD: CIRCLE. Pasek, J., Feldman, L., Romer, D., & Jamieson, K. H. (2008). Schools as incubators of democratic participation: Building long-term efficacy with civic education. Applied Development Science, 26-37. Pasek, J., Kenski, K., Romer, D., & Jamieson, K. H. (2006). America’s youth and community engagement: How use of mass media is related to political knowledge and civic activity among 14 to 22 year olds. Communication Research, 33(3), 115-135. Potts, R., & Sanchez, D. (1994). Television Viewing and Depression: No News is Good News. Journal of Broadcasting and Electronic Media, 38, 79-90. Putnam, R. D. (1995a). Bowling Alone: America’s Declining Social Capital. Journal of Democracy, 6(1), 65-78. Putnam, R. D. (1995b). Tuning In, Tuning Out: The Strange Disappearance of Social Capital in America. PS: Political Science and Politics, 28(4), 664-683. Putnam, R. D. (2000). Bowling Alone: The Collapse and Revival of American Community. New York: Touchstone. Rahn, W. M., & Transue, J. (1998). Social Trust and Value Change: The Decline of Social Capital in American Youth, 1976-1995. Political Psychology, 19, 545-565. Robinson, J. P., & Godbey, G. (1997). Time for Life: The Surprising Ways Americans Use Their Time. University Park, PA: Pennsylvania State University Press. Sanders, C. E., Field, T. M., Diego, M., & Kaplan, M. (2000). The relationship of Internet Use to Depression and Social Isolation Among Adolescents. Adolescence, 35(138), 237-242. Scheufele, D. A., & Shah, D. V. (2000). Personality Strength and Social Capital: The Role of Disproportional and Informational Variables in the Production of Civic Participation. Communication Research, 27(2), 107-131. Schou, I., Ekeberg, O., Sandvik, L., & Ruland, C. M. (2005). Stability in OptimismPessimism in Relation to Bad News: A Study of Women with Breast Cancer. Journal of Personality Assessment, 84(2), 148-154. Shah, D. V. (1998). Civic Engagement, Interpersonal Trust, and Television Use: An Individual-Level Assessment of Social Capital. Political Psychology, 19(3), 469-496. Shah, D. V., Kwak, N., & Holbert, R. L. (2001). “Connecting” and “Disconnecting” With Civic Life: Patterns of Internet Use and the Production of Social Capital. Political Communication, 18, 141-162. Shah, D. V., McLeod, J. M., & Yoon, S.-H. (2001). Communication, Context, and Community: An Exploration of Print, Broadcast, and Internet Influences. Communication Research, 28(4), 464-506. Smith, E. S. (1999). The Effects of Investments in the Social Capital of Youth on Political and Civic Behavior in Young Adulthood: A Longitudinal Analysis. Political Psychology, 20(3), 553-575. Uslaner, E. M. (1998). Social Capital, Television, and the “Mean World”: Trust, Optimism, and Civic Participation. Political Psychology, 19(3), 441-467. Uslaner, E. M. (2002). The moral foundations of trust. New York: Cambridge University Press. Young, K. S., & Rogers, R. C. (1998). The Relationship Between Depression and Internet
    
    LIFE OUTLOOK, MEDIA USE, AND SOCIAL CAPITAL AMONG ADOLESCENTS
    
    19
    
    Addiction. Cyberpsychology and Behavior, 1(1), 25-28. Yuan, K. H., & Bentler, P. M. (1998). Normal theory based statistics in structural equation modeling. British Journal of Mathematical and Statistical Psychology, 51, 289-309. Zaff, J. F., Moore, K. A., Papillo, A. R., & Williams, S. (2003). Implications of extracurricular activity participation during adolescence on positive outcomes. Journal of Adolescent Research, 18(6), 599-630. Zukin, C., Keeter, S., Andolina, M., Jenkins, K., & Delli Carpini, M. (2006). A new engagement? Political participation, civic life, and the changing American citizen. New York: Oxford University Press.
    
    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.
    
    Paths between Pessimism Indicators and Social Capital Hopelessness Coef. -.025 .644 .532 .000 -.229 .672 .472 .128 .000 .007 .000 -.114 .000 Prob. Coef. Prob. .455 Fatalism Coef. -.137 Prob. .000
    
    Factors and Fit indices
    
    Civic Activity Participate in clubs or extra-curricular activities Volunteer time for a worthy cause
    
    Social Trust People will take advantage of me (Reversed) Most people are selfish (Reversed)
    
    Correlation between factors
    
    LIFE OUTLOOK, MEDIA USE, AND SOCIAL CAPITAL AMONG ADOLESCENTS
    
    Goodness of Fit Chi-Square (DF) 11.15 (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.
    
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    Table 2: Standardized coefficients between media uses and social capital controlling for demographic predictors with and without pessimism indicators.
    
    Social Trust No Control Pessimism Control No Control Coef. -.074 .057 .052 .025 .067 .036 .067 .091 .458 .039 -.132 .003 .123 .220 .189 .000 .937 .000 .000 .000 -.126 .002 .123 .216 .185 Prob. Coef. Prob. Coef. Prob. .000 .959 .000 .000 .000 Pessimism Control
    
    Civic Activity
    
    Predictor -.081 .047 .045 .040 .067 .019 .129 .139 .240 .040
    
    Coef.
    
    Prob.
    
    LIFE OUTLOOK, MEDIA USE, AND SOCIAL CAPITAL AMONG ADOLESCENTS
    
    Hours of TV TV Shows National TV News Informational Internet Books
    
    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 Goodness of fit for model without pessimism: χ2 (73) = 141.28, p = .000, CFI = .980, RMSEA = .023 (.017, .028) Fit for model with pessimism: χ2 (83) = 151.59, p = .000, CFI = .980, RMSEA = .021 (.016, .027).
    
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    Table 3: Comparisons between models with different causal directions between media use and social capital factors.
    
    Model A1: Trust → Civics → Media A2: Civics → Trust → Media B1: Media → Trust → Civics B2: Media → Civics → Trust C1: Trust → Media → Civics C2: Civics → Media → Trust
    
    Chi-Square 113.21 229.23 226.81 112.71 107.07 104.05
    
    Df 57 56 57 57 54 54
    
    CFI .983 .948 .949 .984 .984 .985
    
    RMSEA (90% CI) .023 (.017,.029) .041 (.036,.047) .041 (.035,.046) .023 (.017,.029) .023 (.017,.030) .023 (.016,.029)
    
    AIC -0.79 117.23 112.81 -1.29 -0.93 -3.95
    
    Note: CFI is the Comparative Fit Index; RMSEA is the root mean square error of approximation with 90% confidence interval; AIC is the Akaike Information Criterion.
    
    Table 4: Standardized coefficients between measures of social capital and media use.
    
    Civic Activity to Media Media Variable Coef. Prob. Coef.
    
    Media to Trust Prob. .035 .051 .078 .030 to zero.
    
    Hours of TV -.160 .000 -.074 TV Shows .000 .061 National TV News .170 .000 .054 Informational Internet .275 .000 .000 Books .248 .000 .069 Note: Coefficients without probability values were restricted

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