Left to Their Own Devices

Abstract

New media provide college students with an unprecedented number of ways to spend their unstructured time. Research on decision making suggests that choosers low in self-control presented with proximate options will eschew tasks that provide delayed benefit in favor of immediate gratification and will experience guilt when they are aware of the tradeoff between immediate gratification and long-term benefits. A survey of college students (N = 458) suggests that users are aware of overuse of leisure media because of deficits in self-control, in particular two proximate media experience (social networking sites [SNS] and online video). Of these, only online video viewing is associated with less time spent on schoolwork. Though this study is correlational and thus does not definitively establish causality, the evidence suggests that the interaction between the high-choice media environment and users’ self-control may account for a decline in learning among college students.

Keywords

Facebook social media college students Internet self-control

The transition from high school to college represents a profound change in the lives of young people, from the highly structured, highly supervised home environment to the relatively unsupervised, unstructured campus environment. Though many college students have as many curricular and extracurricular demands on their time as they did before coming to college, they are not required to physically be in a single building for 8 hours each day nor are their leisure activities monitored by parents. Without these external constraints, college students are free to spend their time as they wish: socializing, completing schoolwork, or engaging in entertainment experiences at various times throughout each day.

The generation making its way through college at the start of the second decade of the 21st century has an unprecedented number of options as to what to do with their leisure time. Their adolescence coincided with the popularization of new media that served to multiply the quantity of experiences and the places and times in which these experiences could be accessed: mobile communication devices (e.g., cell phones), time-shifting television viewing technologies (e.g., digital video recorder or “DVR”), and the Internet. There is concern over the possibility that time spent using some or all of these leisure media may be substituting for time spent on school-related activities. Evidence suggests that the amount of media use a student engages in can affect the student’s scholastic performance. Children aged 8 to 18 who spend less time using media do better in school than those who use more media (Kaiser Family Foundation, 2010). Though these survey findings are correlational and thus cannot account for all third variables, they do suggest that time spent using media for leisure purposes may be time that students are not studying, leading to lower grades.

Of the students who are unable to maintain a balance between schoolwork and leisure pursuits, it is likely that some make deliberate decisions to neglect their schoolwork, which offers a delayed gratification in the form of better grades and a better job, in favor of other pursuits. The preference for activities offering smaller, short-term gain over those offering larger, long-term gain is not necessarily an irrational or uncommon behavior. Such a preference may be indicative of a difference in values. These students’ failures to devote more time to schoolwork are the results of rational, deliberative choices based on their valuation of expected outcomes of activities. At the same time, other students may not deliberately choose to spend less time on schoolwork but may end up doing so anyway. Such behavior comes about when students low in self-control make choices in an environment that offers sufficiently tempting alternatives. Knowing the difference between extracurricular activities that are selected based on a rational consideration of options and experiences that are selected when self-control has failed is essential to understanding college students’ time budgeting.

Individuals’ susceptibility to temptation may vary as well as the extent to which choice environments test the resolve of individuals. Some leisure activities may be seen by students as temptations—such as alcohol consumption or video game playing—while others are more often chosen by those who decide that they are more important than schoolwork—such as athletics or club activities. Media researchers have noted the frequency with which the term “guilty pleasure” is used to refer to certain types of media use, including reality-based television viewing (Baruh, 2010; Pozner, 2010), reading romance novels (Radway, 1984), or personal Internet use at work (i.e., “cyberloafing”) (Stratton, 2010). Gauntlett and Hill (1999) found that many television viewers refer to TV viewing as a guilty pleasure regardless of the content being viewed. New media technologies—mobile devices and the Internet—are not obviously or exclusively used for activities regarded as “guilty pleasures” or for activities that one consciously values as much or more than schoolwork such as professional advancement. Researchers must differentiate among specific uses of the Internet and mobile devices to determine the extent to which various uses of new media are indicative of lapses in self-control and to determine what characteristics of some of these media experiences make them particularly tempting.

This study establishes evidence indicating the extent to which popular leisure media experiences function as distracting temptations for college undergraduates. Determining whether media use correlates with trait levels of self-control, feelings of guilt, and the amount of time students dedicate to schoolwork is an important step in understanding media selection behavior in a choice environment in which more options are temporally and physically proximate to choosers than ever before. This article presents a review of the literature on temptation and self-control, followed by a review of literature on self-control and media choice, leading to the hypotheses.

Media Temptations and Self Control

Goods and experiences from which individuals choose can be more or less tempting. Options that are experienced as initially tempting during the preconsumption phase are often pleasurable during the consumption phase and are associated with feelings of guilt during the postconsumption phase. These “guilty pleasures” appeal to one’s desire for immediate pleasure rather than one’s belief that they should partake of a product or experience so as to obtain long-term benefits such as cultural enrichment, enhanced ability to perform the duties of a responsible, informed citizen, or increased earning potential (Shiv & Fedorikhin, 1999). Guilty pleasures can be thought of as offering smaller, earlier rewards in contrast to options that offer delayed gratification value. In media terms, one might consider a lowbrow comedy to be a guilty pleasure, while an intellectually challenging foreign film would not be a guilty pleasure (Read, Loewenstein, & Kalyanaraman, 1999).

To forgo guilty pleasures, choosers may call on self-control or willpower: the conscious act of restraining one’s self from engaging in an activity (Baumeister, 2008; LaRose, 2009). Hoch and Loewenstein (1991) make the distinction between two means of preventing one’s self from making such selections: reducing desire by avoiding or distracting one’s self from the tempting options or overcoming desire by exercising willpower. If those who are low in self-control are put in environments that have tempting options, the tendency to select such options increases (Babin & Darden, 1995; Baumeister, Sparks, Stillman, & Vohs, 2008; Gul & Pesendorfer, 2004).

The close physical proximity of various leisure media experiences via mobile communication technology amounts to having a temptation nearby in all places at all times. In addition, various “time-shifting” on-demand entertainment technologies such as DVR and online video (e.g., Hulu) bring desired entertainment experiences out of the scheduled availability choice environment in which desired options are often temporally remote from a media user into a choice environment in which all options are unscheduled and are thus always in close temporal proximity to the user. This constant presence of tempting media options makes it difficult for choosers who are low in self-control to resist these options.

Users’ exposure to various leisure media experiences is contingent on the availability of the users (Webster, 1985). For example, prime-time (8 p.m.-10 p.m.) television ratings have, historically, been the highest partly due to the fact that most individuals are not at work and are not asleep at that time (Webster, 1985). However, the constraints of work hours are not the same for all populations. The lack of regular structure in college students’ lives, relative to that of high school students or those working full-time jobs, and their relative autonomy present them with opportunities to select leisure media experiences immediately before use (Chak & Leung, 2004; Young, 2001). Given these conditions, college students are more apt to use more tempting, proximate media than their counterparts who either have restrictive schedules or do not possess technologies that give them access to tempting options in various places. This proximate temptation effect has been shown to be moderated by self-control (Babin & Darden, 1995): those with higher levels of self-control are capable of refraining from temptations despite their constant presence.

Media Selection

To the extent that the research on media selection conceives of media use as influenced by users’ levels of self-control, much of it concerns so-called abuse of a medium or addiction. There has been much debate over what it means to be addicted to a medium. Byun et al.’s (2009) meta-analysis of 39 quantitative studies of Internet addiction from 1996-2006 concludes that there is little consensus on how to define addiction in this context. Nevertheless, Internet addiction studies continue to proliferate. In many of these studies, Internet addiction is regarded as a behavioral impulse control disorder in which individuals who exhibit loneliness, depression, or low self-esteem use the Internet to temporarily alleviate feelings of emotional tension (e.g., Dell’Osso, Altamura, Allen, Marazziti, & Hollander, 2006; Young, 1998, 2007).

By focusing on the relatively small portion of the population that suffer from what might be called addiction, researchers may be missing an opportunity to understand the basic dynamics of motivations and rewards that underlie all new media use. There are circumstances, which have been referred to as “benignly problematic” use (Hall & Parsons, 2001) or “unregulated media behavior” (LaRose, Lin, & Eastin, 2003), in which use does not interfere significantly with one’s life and, therefore, does not meet the clinical criteria for addiction. Still, this behavior is not entirely under one’s conscious control and can, over time, interfere with users’ abilities to achieve long-term goals. The ability to forgo immediate gratification in favor of distant goals (i.e., future-oriented self-control) is associated with superior scholastic performance, superior coping skills, and better relationships (Shoda, Mischel, & Peake, 1990; Tangney, Baumeister, & Boone, 2004). This suggests that there is merit in not limiting studies of the negative consequences of Internet use to include only those who exhibit signs of addiction.

Among a general sample of undergraduate Internet users, the amount of Internet usage was found to be positively correlated with deficiencies in self-regulation (LaRose et al., 2003). Research on television viewing has shown that the amount of time adults spend on television viewing is negatively associated with self-control (Kubey & Csikszentmihalyi, 1990). Though these studies demonstrate negative correlations between various media use and self-control, their approach provides a limited insight as to what characteristics of the media, the content, and the audience explain these correlations. LaRose et al.’s (2003) study does not indicate what applications or websites on the Internet are used more by those who have deficient self-regulation. Given the wide variety of social and entertainment leisure activities one can engage in via new media technology, it is essential to establish correlations between certain popular online activities and self-control rather than treating all Internet use as the same. Similarly, in their analysis of self-control and television use, Kubey and Csikszentmihalyi assume a certain degree of homogeneity to the leisure media choice environment and to the television viewing experience in particular. Benesch, Frey, and Stutzer (2010) find that the likelihood that individuals with low self-control watch more television than they had intended to was positively related to the number of available television channels. This suggests that the relationship between the amount of leisure media use and self-control depends on the number of leisure options from which one chooses. Since the finding linking television use to deficits in self-control, the number of alternative leisure activities has grown significantly. Assuming that the user has access and flexibility in his or her schedule, portable networked devices (e.g., laptops) are often physically and temporally proximate to the user and, thus, are just as (if not more) likely to test the willpower of users as television.

The aforementioned research on the effects of proximity on the tendency of low self-control choosers to select immediately gratifying options and the research on self-control and media selection lead to the hypotheses that the level of students’ self-control will be negatively associated with the amount of leisure media use.

Hypothesis 1 (H1): College students’ self-control is negatively associated with amounts of leisure media use.

Experiences of failed self-control in the face of temptation are likely to be coupled with the self-reactive attitude of guilt (Bandura, 1991; LaRose et al., 2003). Guilt has been hypothesized to be a symptom of deficient self-control (Ainslie, 1996), but it may also be an indication that the individual is aware that they have lost control, indicative of some degree of successful self-monitoring (LaRose & Eastin, 2002) and allowing for subsequent improvement in self-control (Baumeister & Heatherton, 1996). The constant presence of tempting, proximate media options is hypothesized to result in more lapses in restraint and thus lead to greater feelings of guilt.

Hypothesis 2 (H2): College students’ guilt about media use is positively associated with amounts of leisure media use.

After leaving for college, young people spend significant amounts of time using these media for various leisure activities, ranging from text messaging to social networking websites to online video viewing, in addition to the dominant form of leisure media use: television viewing (Junco & Cole-Avent, 2008). One survey found that college students spent 51% of their time on socializing and recreation while spending only 7% of their time studying (Arum & Roksa, 2011). The amount of time college students dedicate to studying has steadily declined over the past five decades (Babcock & Marks, 2010), which suggests that the recent advances in technology are not entirely to blame for the decline. Nevertheless, the combination of an unscheduled time environment and an unprecedented multiplicity of appealing diversions make the leisure time choices of these individuals somewhat unique and, based on extant knowledge of self-control and decision making in high-choice environments, are likely to exacerbate the existing trend. It is thus hypothesized that time spent using leisure media will substitute for time spent on schoolwork.

Hypothesis 3 (H3): The amount of time college students spend on schoolwork is negatively associated with amounts of leisure media use.

College students’ leisure media use may be explained or predicted in other ways. Media users’ stated that “gratifications sought” have proved an effective means of predicting amounts of use of traditional and new forms of media (e.g., Papacharissi & Rubin, 2000). It is possible that the amount of time students spend using leisure media can be better explained by their stated motives rather than their levels of self-control. To address the argument that greater amounts of use of these leisure media are attributable to certain motives rather than the user’s level of self-control, an analysis was performed that compared the power of factors derived from Flanagin and Metzger’s (2001) measure of motivations for Internet use with that of self-control to predict the amount of use of two popular online applications used by students—SNS and online video. It is hypothesized that self-control will predict amount of media use to a greater degree than stated motivations for using media.

Hypothesis 4a (H4a): Self-control will predict amounts of SNS use by college students to a greater extent than students’ stated reasons for Internet use.

Hypothesis 4b (H4b): Self-control will predict amounts of online video use by college students to a greater extent than students’ stated reasons for Internet use.

Much of the research on self-control and media use examines different media (e.g., cell phones, television) in isolation. To provide an insight into which media or online applications are the most tempting or distracting to students and which media or applications interfere with students’ abilities to complete schoolwork, an analysis was conducted that compares the significance and the strength of the relations between amounts of use, self-control, guilt, and the amount of time on schoolwork across various popular leisure media and online applications.

Research Question 1: What media or online applications have the strongest associations with self-control, feelings of guilt, and time spent on schoolwork among students?

Method

Participants

A survey was administered online during the fall 2010 semester and winter 2011 semester to students enrolled in a communications class at a large Midwestern university. Participants received credit in exchange for participation. Four hundred fifty eight students took the survey; 74% (336) of these participants were female and the median age was 19 (M = 18.8, SD = .80). The entire sample’s ethnic make-up was not determined; however, a subsample of 173 students drawn from the sample consisted primarily of Caucasians (70%) and Asians or Asian Americans (15%).

Measures

The survey to assess media use was developed after consulting the most recent studies tracking the media habits of adolescents (Kaiser Family Foundation, 2010; Lenhart, Purcell, Smith, & Zickuhr, 2010). To verify that this information accurately and exhaustively reflected the ways in which college students were using media, a round of individual interviews were conducted with 30 undergraduate students in 2010. From this, several leisure media or applications emerged as popular among the population of interest: SNS use, watching television as it is broadcast, watching online video, watching previously recorded programs on a DVR, and watching DVDs.

To assess various kinds of video use, participants were asked, “On average, how much time do you spend engaging in these activities with your TV or laptop each day?” and told to provide the answer in minutes. There were four video use measures: “watching online video,” “watching recorded programs when you want (On-demand, DVR, or TiVo),” “watching DVDs,” “watching TV programs at the times they are broadcast (not recorded programs). Amount of SNS use was assessed by asking students how many times each day they visited an SNS site such as Facebook and, on average, how much time they spent on the site each time they visited.¹ These variables were added together to create a single daily leisure media use variable (known hereafter as “leisure media use”).

To assess individual differences in self-control, Tangney et al.’s (2004) 13-item measure of self-control was used. Participants rated 13 statements based on the degree to which they felt each statement described them (1 = “not at all like me” to 5 = “just like me”; example of an item: “Rate the degree to which you feel these statements describe you: ‘I am good at resisting temptation’”). This measure was considered appropriate for this study given the fact that it was conceived by its creators as a way to assess, in particular, individuals’ abilities to “interrupt undesired behavioral tendencies (such as impulses) and refrain from acting on them” (p. 274). The internal reliability of the measure was .85 in this sample, which is comparable to validations in previous samples (alpha = .89; Tangney et al., 2004).

To assess guilt, participants were asked to rate the degree to which they felt the following four statements described themselves (1 = “not at all like me” to 5 = “just like me”): “I often feel guilty about the amount of television I watch”; “I often feel guilty about having watched certain TV programs”; “I often feel guilty about the amount of time I spend online”; “I often feel guilty about having engaged in certain activities online.” These questions measured guilt associated with the amount and type of television and Internet consumption. Together, they had an alpha = .73 and were combined in a single measure of media guilt by adding them together and dividing them by four.

Given the amount and frequency of new media use among young people and given the increasingly “user-friendly” nature of the various online applications, it is likely that many young users have achieved a level of mastery of the use of such technologies and that self-efficacy plays a diminishing role in predicting amounts of use. To ensure that self-efficacy is not significantly predictive of media use within this population, a proxy for self-efficacy (e.g., age of media technology adoption) is included as another independent variable in the regression models. So as to control for differences in use between males and females, gender was also assessed (Female =1; Male = 2).

To assess the amount of time participants spent on schoolwork each day, they were also asked to report the number of hours they spent doing schoolwork on an average day.

To assess motivations for using SNS and online video, participants were asked to report the extent to which they used the Internet for 20 different reasons (examples of items: “To get information,” “To be entertained”; 1 = “Never” to 5 = Very Often”).

Analysis

To test the first hypothesis, the composite leisure media use variable was used as a dependent variable in a two-step regression. Gender and the composite measure of age of media technology adoption were used as simultaneous independent variables in the first step, and self-control as the independent variable in the second step. To test the second hypothesis, a two-step regression was run with gender and the composite measure of age of media technology adoption as simultaneous independent variables in the first step, and the composite measure of media use as the dependent variable. In the second step, the composite measure of guilt over amount and type of media use was the independent variable. To test the third hypothesis, a regression was run with students’ self-reports of the composite measure of media use as the dependent variable, gender and age of adoption of media technologies as simultaneous independent variables in the first step, and the amount of schoolwork per day as the independent variable in the second step.

To test the fourth hypothesis, principle component analysis was performed on the 20 item Internet users index. This yielded four factors with eigenvalues greater than 1 (see Table A1 of appendix). The following nine items loaded highest on the first factor: “to generate ideas,” “to learn more about myself and others,” “to get to know others,” “to impress people,” “to have something to do with others,” “to gain insight into myself,” “to feel less lonely,” “to feel important,” and “to stay in touch.” These items related primarily to social uses and are thus labeled “social” (alpha = .89). These seven items loaded heaviest on the second factor: “to get information,” “to be entertained,” “to learn how to do things,” “to do schoolwork,” “to provide others with information,” “to play,” and “to contribute to a pool of information.” These items relate primarily to information gathering and entertainment and are thus labeled “information/entertainment” (alpha = .89). The third factor consists of two items: “to solve problems” and “to make decisions,” both of which could be considered utilitarian use of the Internet and are thus labeled “utilitarian” (alpha = .70). Finally, the fourth factor consisted of two items: “to pass time when bored” and “to relax,” both of which connote using the Internet as a way to pass time and are thus labeled “to pass time” (alpha = .77). These four uses were used along with self-control as independent variables in two regressions, the first of which used SNS use as a dependent variable and the second of which had online video use as a dependent variable. As with the aforementioned regressions, gender and age of adoption were controlled for using stepwise regression.

Results

In this population, participants averaged just over 4 hours each day on schoolwork (4.20; SD = 1.84), roughly 95 minutes using SNS (95.51; SD = 78.27), about 25 minutes watching television as it is broadcast (24.87; SD = 36.20), roughly 23 minutes watching online video (23.19; SD = 33.58), 14 minutes watching prerecorded video (14.00; SD = 28.58), and 7 minutes watching DVDs (7.36; SD = 22.00). The total average amount of time spent using the five popular leisure media or applications was roughly 2 hours 45 minutes (164.43; SD = 111.01). The large variance in this sample reflected positively skewed kurtotic distributions in which many of the participants did not use media in some of these ways and several other participants used them frequently and/or for long durations. The mean score of the 5-point scale self-control variable was 3.1 with a standard deviation of .62, while the mean score of the 5-point scale composite guilt variable was 2.41 with a standard deviation of .80. In addition, the average age of media technology adoption was 12.26 with a standard deviation of 1.30, confirming that this sample is relatively homogenous in terms of its levels of experience with these technologies.

Hypothesis 1 was supported. Step 1 of the stepwise regression explained 2.3% of the variance in leisure media use (R² = .023, p = .01). Males used roughly 28 fewer minutes of use than females (unstandardized B = −28.42, p = .02). The age at which students adopted media did not significantly affect the amount of media they used (unstandardized B = −7.86, p = .06). The independent variable in step two of this regression explained 6.3% of the variance in leisure media use (R² = .063, p = .001). Self-control was negatively associated with leisure media use. For every point on the 5-point self-control scale, students used roughly 36 fewer minutes of leisure media (unstandardized B = −35.61, p = .001).

Hypothesis 2 was also supported. The variables in step two of the regression explained 8.1% of the variance in leisure media use (R² = .081, p = .001). Media use guilt was significantly positively associated with amount of leisure media use. For every point on the 5-point guilt scale, students consumed roughly 34 minutes of leisure media (unstandardized B = 33.69, p = .000).

Hypothesis 3 was not supported. Step two of the regression explained 3.1% of the variance in leisure media use (R² = .031, p = .006). The amount of time spent on schoolwork was not significantly associated with leisure media use (unstandardized B = −5.46, p = .07).

Accounting for Motivation

To assess the power of self-control to predict amounts of SNS use and online video use relative to that of students’ reported uses, two regressions were conducted. Hypothesis 4a was supported. Step two of the first stepwise regression accounted for 14.4% of the total variance in the amount of SNS use (R² = .144, p = .001). Self-control significantly predicted the amount of SNS use (unstandardized B = −31.10, p = .001), while “social,” “information/entertainment,” “utilitarian,” and “to pass time” were not significantly associated with the amount of SNS use. This indicates that for every point on the 5-point self-control scale, students spend roughly 31 fewer minutes using SNS. Hypothesis 4b was supported as well. Self-control significantly predicted the amount of online video use (unstandardized B = −11.12, p = .001), while the four uses were not significantly associated with the amount of online video use. This indicates that for every point on the self-control scale, students spend roughly 11 fewer minutes watching online video.

Self-Control, Guilt, Schoolwork, and Individual Media

To address the research question, a bivariate correlation was conducted with the following variables: SNS, online video, DVD, DVR, broadcast TV, self-control, guilt, and schoolwork (see Table 1). This disaggregation of media uses shows self-control to be negatively associated with SNS use and online video use. Self-control is not associated with DVD, DVR, or broadcast TV use. Feelings of guilt are positively associated with SNS use and, to lesser extents, with online video use and broadcast television use. Finally, online video use is negatively associated with the amount of time students’ spend on schoolwork, while no other media use is significantly correlated with amount of schoolwork.

Table 1.

Media Use, Self-Control, Guilt, and Schoolwork Correlation Matrix.

	SNS	Online video	DVR	DVD	TV	Self-control	Guilt
SNS
DVR	.03	−.04
DVD	−.05	−.04	.34 **
TV	.09	−.06	.17**	.11*
Self-control	−.25**	−.21**	−.01	−.03	.06
Guilt	.21**		.08	.06	.03*	−.32**
Schoolwork	−.06	−.13**	.05	−.03	.02	.23**	−.05

Note. Pearson correlation statistics presented.

p < .05. **p < .01.

Discussion

This study provides support for the claim that students who are low in self-control are apt to spend more time using leisure media and are apt to feel guilty about doing so. Findings suggest that levels of self-control are a more accurate predictor of the amount of SNS use and online video use than the users’ stated reasons for using the Internet. In addition, the analysis differentiates among many media activities engaged in by college undergraduates and establishes associations among self-control, guilt, and some uses, while demonstrating that no such associations exist for other uses. In doing so, it increases understanding of the characteristics of tempting media experiences beyond the basic medium-specific understanding of self-regulation and media use. Specifically, this analysis suggests that online video use and SNS use are associated with deficits in self-control and feelings of guilt, while television viewing, DVR use, and DVD use are not. Despite the fact that SNS use functions as a temptation for college students, it does not take away from the amount of time students spend on schoolwork. Of the popular leisure media surveyed, only online video viewing is negatively associated with the reported amount of time spent on schoolwork. Together, these findings suggest that the constant presence of online video and SNS tests the self-control of students to a greater degree than other media in their choice environment, that students are aware of this, and that online video viewing displaces time spent on schoolwork. Though there is concern about the degree to which SNS and mobile phones distract students (e.g., Hanson, Drumheller, Mallard, McKee, & Schlegel, 2010), there is relatively little research concerning the extent to which streaming video applications do so. This study suggests that more research on the role of these applications is essential to understanding students’ time budgeting.

The absence of a negative correlation between SNS use and the amount of time spent on schoolwork is consistent with some prior findings on this phenomenon (Junco, 2012) and inconsistent with others (Kirschner & Karpinski, 2010). Kirschner & Karpinski’s (2010) finding that Facebook users spent less time studying was based on a sample that was nearly one-third nonusers and assessed SNS use with a yes/no question. Ninety-nine percent of the samples in this study used SNS that is roughly consistent with the proportion of Facebook users in Junco’s (2012) sample. Similar to the results of the current study, Junco found no evidence of a strong negative correlation between the amount of time students spent using SNS and the amount of time they spent on schoolwork. This suggests that the negative correlation between SNS use and schoolwork is only observable when users are compared with nonusers. Given the extremely high rates of SNS adoption in the college student population, it will be more useful going forward to use the amount or type of SNS use in analyses of schoolwork and leisure media use.

One possible explanation for the absence of negative correlation between SNS use and time spent on schoolwork is that students are engaging in serial or sequential use of SNS and schoolwork, rapidly toggling back and forth between the two activities (Koolstra, Ritterfeld, & Vorderer, 2009). It is easier for users to toggle between SNS and schoolwork than to toggle between watching a video and schoolwork by virtue of the fact that SNS requires attention for mere seconds, while online video typically requires attention for several minutes or more. It is also possible that SNS use may be substituting for other social activities such as spending time with dorm-mates or talking on the phone. Further research on time displacement should consider these possibilities.

Anytime/Anywhere Media and Self-Control

Physical and temporal proximity of the options are known to affect the extent to which products or experiences test the self-control of choosers: the closer one is to a tempting option, in time or in space, the more likely one is to choose that option over less tempting alternatives (Ainslie, 1975; Hoch & Loewenstein, 1991; Mischel, 1974). The past two decades have seen a steady shift toward increasingly physically and temporally proximate leisure media options; however, television viewing remains constrained by place and time—viewers typically watch only in their homes and content is only available at scheduled times. The presence of associations among self-control, guilt, and anytime/anywhere media such as online video and SNS, combined with the absence of such associations for television use, suggests that constantly present media may test the self-control of individuals with flexible schedules to a greater extent than media experiences constrained by time and place.

The study did not find any associations among self-control, guilt, and DVD or DVR use. Of the media use options presented in the survey, DVD and DVR had the lowest mean amount of use, suggesting that, at least for this population, they are not as attractive an option as the other temporally proximate leisure media options. Many students do not have access to DVR, while almost all students have access to the Internet and, hence, to SNS and online video. Regardless of how one accesses DVDs (e.g., via library loan or postal service), one must choose from fewer titles than when selecting an online video. There is also the possible influence of duration: DVDs and DVRs offer experiences of relatively long duration, typically between 30 minutes and 2 hours, while online video and SNS do not require users to commit such large chunks of time. A student asking herself whether she wants to watch a 2-hour movie may be making a deliberative decision that is not as prone to be affected by deficits in self-control as less deliberative decisions (Shiv & Fedorikhin, 1999). Finally, DVR users typically choose from a menu of predetermined options. This array of options is assembled at a time that is temporally remote from the moment of viewing and thus may be chosen in a deliberative, reflective way. The act of DVR viewing, then, may be an unscheduled act (one may sit down and view DVR programs whenever one likes) but the DVR viewers’ options are circumscribed by available options assembled by a deliberating, reflective self.

Limitations

This cross-sectional survey relies on self-report data, which may misrepresent the actual amount of media use engaged in by the participants given individuals’ tendencies to misestimate the amount of media they use (Collopy, 1996). Specifically, media users have tended to overestimate the amount of time they spend online and underestimate the amount of time they spend watching television (Bloxham, Holmes, Moult, & Spaeth, 2009), though one wonders whether this may change the more people associate time spent online with leisure.

Though this study uses self-report survey data to determine media users’ durations and types of media use, it does not simply take the users at their word as to why they chose what they chose. By demonstrating that students’ levels of self-control are better predictors of amount of various kinds of media use than stated reasons for use, this study establishes preliminary evidence that these experiences are, to some degree, not selected mindfully. Such evidence should prompt researchers interested in explaining why users select certain media experiences to supplement assessments of self-reported media use motivations with a measure of self-control, in particular when studying SNS use and online video viewing.

There was no measure of overall Internet use, nor any measure of cell-phone use or videogame playing, activities known to be engaged in more by those with lower levels of self-control (Billieux et al., 2011; Billieux, Van der Linden, d’Acremont, Ceschi, & Zermatten, 2007; Seay & Kraut, 2007), both of which are more prevalent than viewing online video (Nielsen, 2009). All these measures should be included in future studies.

Among the variables not assessed in this study that may affect media use, guilt, and self-control is the perception of social norms (LaRose, Mastro, & Eastin, 2001). Though guilt can be understood as evidence of knowledge of such norms and acknowledgment that one has violated them (Baumeister, Stillwell, & Heatherton, 1994), there are other feasible ways of isolating the effects of the perception of one’s leisure media selection relative to social norms. In future studies, media users could be asked to estimate the average amount of daily use of various kinds of media and applications.

In this study of individuals with unstructured time, there is no comparison group comprising those who have more structured time. To address this, the findings in this study should be compared with survey results from a group of individuals of the same age (18-20 years old) who are currently employed at fulltime jobs. It may not be the lack of structure of the college environment that leads those with low self-control to use more SNS, but rather the fact that SNS happens to be an especially important mode of social surveillance, used to track minute changes in the status of peers among this population at this time. If there were a population that had more regular, regimented schedules that had similarly high needs for social surveillance and communication with peers, one might expect to see the same correlation between self-control and SNS use.

Conclusion

Medium-specific theories about overuse efface the difference between various types of Internet use, different media choice environments, and different media users. In some cases, the amounts of time users spend using various applications or functions of a medium are highly correlated with variables of interest such as self-control, guilt, and the amount of time students spend on schoolwork, justifying a medium-specific conceptualization of media use. In others, such as the case of online video, a particular application has different antecedents and consequences than other applications on the very same medium. It is therefore essential to develop theories of media use that conceptualize media uses in terms of attributes such as the degree to which their uses are constrained by time and place.

The continuing project of understanding college students’ time budgeting as well as the project of defining, diagnosing, and treating problematic Internet use require a thorough understanding of the ways in which all users relate to media options in general, the unique attributes of new media experiences, and the circumstances in which users select such media from a variety of leisure-time options. Differentiating among uses and establishing the psychological mechanisms and choice environments that are associated with the repeated selection of leisure media options not only provide a basis for effective interventions aimed at improving college-student achievement but may help all individuals intending to curb the “guilty pleasure” use of media.

Footnotes

Appendix

Table A1.

Principle Component Matrix of 20 Internet Uses (Flanagin & Metzger, 2001).

Uses	Social	Information/entertainment	Utilitarian	To pass time
To get information	−.07	.67	.35	−.18
To generate ideas	.61	.21	.45	−.17
To learn more about myself and others	.69	.20	.09	.17
To be entertained	−.03	.83	.10	−.05
To get to know others	.79	.11	.18	−.01
To learn how to do things	.02	.82	.10	−.09
To impress people	.83	.01	.03	.16
To do school work	−.08	.63	.36	−.37
To have something to do with others	.67	.12	.37	.06
To provide others with information	.25	.77	.07	.06
To solve problems	.20	.13	.76	.05
To play	.23	.76	.01	−.07
To stay in touch	.47	.23	.47	−.13
To relax	.24	−.17	−.09	.84
To make decisions	.37	.07	.67	.04
To contribute to a pool of information	.33	.72	−.07	−.08
To gain insight into myself	.75	−.09	.16	.23
To pass the time away when bored	.09	−.20	.10	.87
To feel less lonely	.72	.08	.19	.07
To feel important	.60	.47	−.33	.00

Note. Bold values signify that they are part of the factor listed at the top of each column.

Acknowledgements

The author wishes to thank Sara H. Konrath at the University of Michigan Institute for Social Research for her insightful feedback on various drafts of this article.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Author Biography

Elliot Panek is a Visiting Fellow at Drexel University. He examines new media uses and effects, persuasion, and narrative form from sociological and psychological perspectives using interviews, surveys, and experiments to understand the antecedents and consequences of media selection in high-choice media environments. He has published research on social networking site use and narcissism, media use and self-control, and the effects of parental restrictions on their children’s media use.

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