A social cognitive theory of Internet uses and gratifications: toward a new model of media attendance.

Compared to an NTIA (2002) study completed in fall of 2001, the present sample tended to be older, better educated (including more with advanced degrees and fewer with high school diplomas), and disproportionately male. There were no income differences. There were few significant relationships between demographic variables and the main explanatory variables (females had lower self-efficacy, r = .26, and less deficient self regulation, r = .20, than males, and age was negatively, r = -.15, related to self-efficacy), and no significant correlations with the dependent variable so sample bias was not deemed an important issue. Within Social Cognitive Theory, demographic differences are attributed to explanatory variables (e.g., females have lower Internet self-efficacy due to the nature of their past experiences with the Internet).

Operational Measures

The questionnaire was introduced with the following description of Internet use: "Internet use includes sending or receiving electronic mail, visiting chatrooms, participating in discussion groups and visiting locations on the World-Wide Web." No distinction was made between work and leisure activity.

The usual procedure for analyzing gratifications in the uses and gratifications tradition is to conduct an exploratory factor analysis of the gratification items. However, in the present research a priori theoretical assumptions about the nature of the expected outcomes were available, in the form of the incentive categories recognized in SCT. Items were collected from prior uses and gratifications studies, rephrased as outcome expectations (i.e., "using the Internet how likely are you to ..." on a scale of 1-7, where 1 was very unlikely and 7 very likely, cf. Ajzen, 1985). These statements of outcome expectations were classified into SCT incentive categories by consulting the conceptual definitions found in Bandura (1986, pp. 233) and supplemented with items reflecting status and monetary incentives that were underrepresented in uses and gratifications research (cf. LaRose et al., 2001). Six categories of expected outcomes, one representing each incentive category, were subjected to confirmatory factor analyis. The means and standard deviations of the scales and their component items, along with confirmatory factor analysis results and their alpha coefficients, are found in Table 1.

Previous research (LaRose et al., 2003) left the distinction between habit strength and deficient self-regulation unclear. Accordingly, new items were developed by drawing upon theoretical works describing habitual behavior (Aarts et al, 1998; Bargh & Gollwitzer, 1994; Oulette & Wood, 1998) and LaRose et al.'s previous description of deficient self-regulation. The pool of items was subjected to an exploratory principal components factor analysis using varimax rotation. Two interpretable factors emerged, also shown in Table 1. These factors seemed to reflect the distinction between the self-observation subfunction of self-regulation on the one hand and the judgmental process and self-reactive subfunctions on the other hand.

The Internet Self-Efficacy Scale (Eastin & LaRose, 2000) was replicated (Table 1). Also from that study, a measure of Internet experience was computed by asking the number of years and months it had been since the respondent first started using the Internet.

The dependent Internet usage variable was the sum of the total number of minutes spent on the Internet in the typical weekday, the typical weekend day, and the day prior to the survey. An inspection of the distributions of responses to these items revealed that outliers were present and so a log10(1 + value) transform was applied to each one before summing the three items. The resulting composite index had a Cronbach alpha of .66 (M = 5.17, S.D. = 1.59).

Data Analysis

Pearson product-moment correlation coefficients and exploratory factor analyses were calculated using SPSS version 11.5 (SPSS, Inc., 2002). Structural equation analysis was completed with Amos version 4.0 (Arbuckle, 1999).

Results

Pearson product-moment correlations among the independent and dependent variables are shown in Table 2 and the results of structural equation modeling are shown in Figure 1. The model shown was a good fit to the data ([chi square] = 62.3, df = 34, RMSEA = .994, CFI = .071). As hypothesized, Internet usage was directly predicted by expected Internet outcomes ([rho] = .29), Internet habit strength ([rho] = .26), and deficient Internet self-regulation ([rho] = .15). The individual activity (r = .40), monetary (r = .27), novel (r = .36), social (r = .44), self-reactive (r = .46), and status (r = .53) expected outcome categories all had significant (p < .001) zero-order correlations with usage. Expected Internet outcomes were a second-order factor consisting of status, activity, self-reactive, social, novel sensory, and monetary incentives, preceded by Internet self-efficacy ([rho] = .55). Internet habit strength was predicted by expected Internet outcomes ([rho] = .26). Deficient self-regulation predicted Internet habit strength ([rho] = .39) and was itself causally determined by self-reactive outcomes ([rho] = .43). Finally, Internet self-efficacy was also predicted by prior Internet experience ([rho] = .38). However, the hypothesized relationships between prior experience and Internet habit strength was not significant ([rho] = .03, p = .63). The relationship between Internet self-efficacy and habit strength ([rho] = .14, p = .069) narrowly missed significance.

An inspection of the modification indices suggested a causal link from self-efficacy to novel expected outcomes. Since this outcome category represents information seeking on the Internet and the task of seeking useful information is likely to require a high degree of confidence in one's ability, this was accepted as a logical extension to the model. Correlated error terms between self-reactive outcomes and both activity (r = .44) and social outcomes (r = .18), and between novel and monetary outcomes (r = .37), not shown, were added to improve fit. The model explained 42.2% of the variance in the dependent variable, Internet usage.

Discussion

The present results both affirm the uses and gratifications paradigm and extend it to a theory of media attendance grounded in Social Cognitive Theory. A basic implication of uses and gratifications, that media exposure may be predicted from media gratifications, was upheld. Indeed, by instituting new operational measures of expected gratifications, it was possible to predict media consumption to an unprecedented degree. However, new variables from SCT improved the explanatory power of gratifications, here reconstrued as outcome expectations.

Expected activity outcomes, which closely parallel entertainment gratifications in uses and gratifications research, and social outcomes/gratifications were significantly related to usage, as they had been in prior uses and gratifications research involving college students (e.g., Kaye, 1998; Papacharissi & Rubin, 2000), but with more variance explained by the current expected outcomes formulation. Unlike the previous studies, novel outcomes (paralleling information gratifications), self-reactive outcomes (parallel to "pass time" gratifications) were also significantly related to usage, when conceived as expected outcomes of Internet usage. Monetary outcomes, somewhat overlooked in previous research, were also significantly related to usage. Status outcomes, a gratification/outcome dimension identified by SCT but underrepresented in prior uses and gratifications research, had the highest zero-correlations with Internet usage of all. The perceived ability of the Internet to improve one's lot in life thus emerges as a powerful motivating factor for the use of the medium.

Uses and gratifications research, including Internet studies, have tended to subsume habit in other gratifications dimensions, usually under either an entertainment or "pass time" factor. Here, it emerged as a powerful and independent predictor of media exposure even after the effects of gratifications sought/expected outcomes had been accounted for. This finding supports the conceptualization of habit strength as a distinct construct from gratifications/expected outcomes. The correlation between habit strength and expected outcomes perhaps indicated the availability of memories of past active media selection processes, in the form anticipated by uses and gratifications research, that had become dormant with repetition. In this vein, among newer Internet users (those who had been online less than three years) the correlations between expected outcomes and usage were higher than among those with more experience. For example, the correlation between activity outcomes and usage was .54 for new users, compared to .34 for the more experienced ones. This could well indicate that the newer users were making active media selection decisions on the basis of expected outcomes while veteran users had lapsed into more habitual modes of Internet consumption.