Information Overload In Undergraduate Students

Information Overload 1

Acknowledgements I would like to thank Dr. Barbara Wildemuth for her aid in the research and statistical analysis of this thesis. My gratitude also goes out to the perpetually patient Dr. Barreau, and to Mr. Fred Stutzman, who first showed me that one can turn a college pastime into a scientific study. I also cannot thank my parents enough for their love and encouragement in my pursuit of knowledge. This project was supported by the Sarah Steele Danhoff Undergraduate Research Fund, administered by the Honors Office at the University of North Carolina at Chapel Hill.

Information Overload 2

Table of Contents Acknowledgements ....................................................................................................... 1 Table of Contents .......................................................................................................... 2 Tables and Figures ........................................................................................................ 3 Introduction ................................................................................................................... 4 Literature Review .......................................................................................................... 5 Methods ....................................................................................................................... 14 Results ......................................................................................................................... 16 Discussion ................................................................................................................... 23 Conclusion .................................................................................................................. 26 References ................................................................................................................... 28 Appendix A: Recruitment E-mails .............................................................................. 33 Appendix B: Consent Form......................................................................................... 35 Appendix C: Survey .................................................................................................... 39 Appendix D: Statistics Tables ..................................................................................... 46

Information Overload 3

Tables and Figures Table 1. Demographic breakdown of the respondents ................................................ 17 Table 2. Response to the item “I feel overloaded by the amount of information I have to handle.”................................................................................................................... 18 Table 3. Correlations between information sources and frequency of experiencing information overload ................................................................................................... 19 Table 4. SNS behaviors and how they correlate with experiencing information overload. ...................................................................................................................... 20 Table 5. How SNS behaviors correlate with the perception of SNSs as sources of information overload ................................................................................................... 20 Table 6. A distribution of the number of coping strategies employed by students. .... 22 Table 7. How gender and GPA correlate with frequency of feeling information overload ....................................................................................................................... 24 Table 8. Enrollment statistics for the University of North Carolina, Spring 2009 ..... 46 Table 9. Response distributions to items about information sources .......................... 50 Table 10. Response distributions SNS usage behavior items ..................................... 52 Table 11. Response distributions to coping strategy items ......................................... 56 Table 12. Correlations between SNS usage behaviors and feeling information overload. ...................................................................................................................... 57 Table 13. Correlations between information sources and feelings of information overload ....................................................................................................................... 58

Information Overload 4

Introduction With the advent of the Internet and ubiquitous information technology, there is not only a greater capability for one to find needed information, there is also a greater demand to stay informed about current events in the world, one’s profession, and one’s social life. These pressures can be overwhelming enough to cause a malady known as information fatigue syndrome, analysis paralysis, or information overload. The phenomenon, henceforth known as information overload, is the sense of being overwhelmed by one’s information demands. Ellington (2005) cites class, e-mail, personal web browsing, instant messaging, and seven other sources of information overload in an undergraduate student’s lifestyle. I suspect the relative impact of these sources have changed, however, and will investigate whether social networking sites are another source of information overload. The questions to be researched are: •

To what extent are students experiencing information overload, and what are the primary sources of this overload?

•

How do students cope with information overload?

•

What is the relationship between social networking site usage and reported feelings of information overload?

This study reviews the literature on information overload, then reports the findings of an online survey administered during the spring 2009 semester of a public university. The survey, a more quantitative extension of Ellington’s (2005) research, looks to analyze the frequency of information overload experienced by undergraduate students, coping strategies used to alleviate the feelings of overload, and what role social networking sites have in these feelings of information overload.

Information Overload 5

Literature Review

Information overload has become an increasingly salient issue in the wired world. The annual costs of lost productivity caused by this modern malady has been estimated by one consulting firm to be $650 billion (Richtel, 2008), and the stress induced by too much information can pose a health risk to the overwhelmed worker (White, 2000). Because of its dual threat to mind and money, we must have a clear definition of information overload and understand what the primary sources of information overload are. Likewise, strategies that reduce information overload need to be evaluated and optimized to confront this problem that plagues so many citizens of the information society. The concept of information overload has seen many labels and definitions over the years, depending on the context and severity of the situation in which it is experienced. Regardless of the name, information overload is a result of the tremendous influx of information and our inherent compulsion to know all we can. A look at the psychological and physiological impact of information overload is warranted, as well as an examination of the mechanisms people employ to reduce information overload. Finally, looking at information overload in other types of computer-mediated communication can reinforce the concepts named above, as well as provide a suitable bellwether for how social networking sites (SNS) may serve to exacerbate or ameliorate information overload in the undergraduate student’s life.

Information Overload 6 Defining the Problem Information overload has been called by many names and has been studied in many subject domains (Eppler & Mengis, 2004). It has had objective criteria applied to its measurement (Jacoby, 1974; Galbraith, 1974), and it has been subjectively selfreported (Farhoomand & Drury, 2002; Ellington, 2005). Broadbent (1958) and Miller (1956) demonstrated the cognitive limits of individuals for processing information, but did not comment on the effects of chronically pressing these limits. Nevertheless, the majority of the studies concerning information overload use the term to describe the disparity between one’s information processing capability and the volume of information available to parse. In addition to the chronological and psychological limits of processing information, information irrelevance and fragmentation (Karger & Jones, 2006) are also key contributors to feelings information overload (Farhoomand & Drury, 2002; Ellington, 2005). Fragmentation is especially problematic, as having to maintain multiple software applications (Bergman, Beyth-Marom, & Nachmias, 2006), multiple devices (Dearman & Pierce, 2008), and interleaving activities (Bellotti et al., 2005) add directly to the cognitive overhead of managing information. Perhaps new techniques or technologies may mitigate fragmentation, but first it is necessary to understand the extent of its impact among many different population sectors, such as undergraduate students.

Information Overload 7 The Need to Know One of the more insidious elements of information overload is that it is sometimes driven by a personal compulsion to know as much as one can. The research of Cacioppo et al. (1982, 1984, 1996) and Cohen et al. (1955) indicates that some people are innately wired to enjoy thinking. Need for cognition is a personality trait that indicates one’s tendency to retrieve, interpret, and evaluate information. Cacioppo et al. group people as either cognitive misers, who use experts and heuristics in seeking information, or chronic cognizers, who seek and evaluate information on their own (1996). Cacioppo et al. have also found several studies which have shown a positive correlation between ACT scores and need for cognition, as well as between grade point averages and need for cognition (1996).When considering undergraduate students at a selective university such as the University of North Carolina, one could reasonably infer that they have a high need for cognition. Their curiosity and intellectual independence, when combined with the volume of information available and social pressures to seek as much of that information as possible, can result in a self-induced overload. On the other hand, research in internet usage behaviors has not shown significant differences in browsing habits between people with high need for cognition and people with low need for cognition (Amichai-Hamburger et al., 2007, Kaynar & Armichai-Hamburger, 2008). This latter fact is comforting to an extent, especially considering that Google has indexed over 1 trillion unique pages from the Internet in the past decade (Alpert & Hajaj, 2008).

Information Overload 8 The aforementioned social pressures provide an irresistible impetus to retrieve and consume as much information as possible. Wilson (1997) laments the pressure on interdisciplinary researchers to stay current with all of their disciplines. Decision makers in organizations often feel a need to amass an excessive quantity of information to justify their decisions and reduce uncertainty, often to diminishing returns (Butcher, 1995). In the context of social networking sites, having a profile and consistently checking it is an obligation with undesirable social consequences when it is unmet (boyd, 2007).

Computer-Mediated Communication Social networking sites (SNS) are the latest trend in computer-mediated communication. These avenues often provide private, asynchronous communication in the manner of e-mail, public postings similar to Usenet or bulletin board systems, and even instant messaging, incurring the advantages, as well as disadvantages, of all three technologies. Looking at some of SNSs’ analogues could give us insight into how significant SNSs may be in the information overload field. As the single most common use of the Internet (Edmunds & Morris, 2000), email is also often the primary culprit in contributing to feelings of information overload (Bawden et al., 1999; Janssen & Poot, 2006). Farhoomand and Drury (2002) and Ellington (2005) found that e-mail is the second most common source of information overload behind organizational sources. A study from the Pew Internet & American Life Project (Madden, 2008) notes that 53% of American workers use separate e-mail accounts for work and personal use, yet another instance of

Information Overload 9 information fragmentation. Nevertheless, coping strategies such as filtering, ignoring, organizing, and delegating e-mail messages can be transferred to the interfaces of many SNSs. In Jones et al.’s study (2004) of Usenet postings, they found users are more likely to respond to simpler messages in overloaded mass interaction, to generate simpler responses as the overloading of mass interaction increases, and to end active participation as the overloading of mass interaction increases. Could there be a social saturation point in SNSs in which users “end active participation” in them in the manner described by Milgram (1970)?

Friends or Foes? When individuals must keep up with dozens of e-mails per day (Fisher et al., 2006; Whittaker, Bellotti, and Gwizdka, 2006), one might wonder why an individual might burden himself with yet another tributary for the information flood: the social networking site. However, Facebook reports over 110 million active users worldwide and an 85% market share of 4-year universities in the United States (Statistics | Facebook, 2008). Its widespread appeal is generally acknowledged, but Facebook’s exact impact on students’ information habits have yet to be examined. SNSs could provide good avenues for information delegation and filtration, letting friends weed out irrelevant information for each other. On the other hand, SNSs could wind up as another technology that pushes unsolicited information to the users. The amount of agency users have in retrieving information from SNSs could influence their perception of information overload. Hopefully, all of these issues will come to light

Information Overload 10 through further study. In this particular study, however, I will investigate the following hypotheses: H1a) There is a positive correlation between social networking site usage frequency and frequency of feeling information overload. H1b) There is a positive correlation between social networking site usage duration and frequency of feeling information overload.

To Your Health! Information overload is more than a drain on companies’ productivity and time; it is a genuine health threat to 21st century workers. According to a recent study by the Pew Internet & American Life Project (Madden, 2008), 49% of workers feel that information and communications technologies have increased the amount of stress they feel about their job. This stress can manifest itself physically in cardiovascular problems, headaches, digestive disorders, fatigue, and blurred vision (de Rijk et al., 1999; White, 2000). Psychologically, the stress can lead to depression (Klausegger et al., 2007; Zeldes et al., 2007) and diminished attention span (Hallowell, 1995). If too much information does not place a person into “analysis paralysis” (Shenk, 1997; White, 2000), the complete inability to make a decision, it may still lead to overconfidence and other adverse effects in decision making (Eppler & Mengis, 2004; Klausegger et al., 2007). For the long-term health of current undergraduate students, more research will be useful in determining the most significant contributors to information overload stress and in evaluating effective coping strategies.

Information Overload 11 Lightening the Load Humans have adapted two main strategies to reduce information overload: they either seek to increase their information processing capacity, or they reduce the cognitive effort involved in processing the information (de Bakker, 2006). Ways of increasing the information processing capacity of individuals include compressing and aggregating information, training and acquiring skills such as speed reading (Eppler et al., 2004; Koniger & Janowitz, 1995), multitasking, and employing features in information technology (Allan & Shoard, 2006). Ways of decreasing the cognitive effort involved in information processing include filtering out irrelevant (Savoleinen, 2007) or redundant information, delegating the responsibility of handling the information, or simply dedicating less attention to processing the information (Agosto, 2002). The merits of multitasking, defined as working on several tasks in quick succession, are questionable. Studies have shown that there is a cognitive cost in switching between tasks that is detrimental to workers’ effectiveness (Dzubak, 2006). Moreover, the learning potential for students is drastically reduced when their attention is divided between several tasks (Gardner, 2008; Levine et al., 2007). This coping strategy may actually be exacerbating the feelings of information overload among undergraduate university students. Allan and Shoard (2006) found that when police officers were issued personal digital assistants to handle e-mail in the field, the officers were able to spread their email loads throughout the day and reduce their feelings of information overload. Email users who reduced their inbox queues through frequent organizing and

Information Overload 12 immediate message response were less likely to report being overloaded (Dabbish and Kraut, 2006; Fisher et al., 2006; Whittaker, Bellotti, & Gwizdka, 2006; Whittaker & Sidner, 1996). In several studies researchers saw e-mail clients being used for file archival, file transfer, and task management, indicating the tendency for people to centralize their software habits, often through satisficing strategies (Barreau, 1995), in order to reduce fragmentation. Once the information is centralized, users organize their information center to aid in retrieval and manage overload (Fisher et al., 2006). In the context of this study, I will investigate the use of coping strategies categorized by Farhoomand and Drury (2002) and Ellington (2005). Prominent among these are prioritizing information, organizing work, delegating, filtering information and eliminating the source. These are strategies that are very similar to those employed by urban dwellers in Milgram’s (1970) work on the experience of living in cities, indicating that abstract principles of information overload can be applied in different contexts and implying the broader applicability of this study. This leads me to the following hypothesis: H2) There is a negative correlation between the number of coping strategies employed by an individual and their frequency of feeling information overload.

Information Overload 13 Need For Research When social networking sites have become as prevalent as they have among internet users, and especially among college students, it signals a paradigm shift in how people gather and share social information. But do users perceive SNSs as a source of information overload? Are there particular usage behaviors – such as frequently logging in to an SNS or remaining logged in for extended periods of time – that influence feelings of information overload? How might the employment of certain coping strategies determine the frequency of feeling information overload? Finally, is there a relation between a student’s grade point average, which has been linked to need for cognition, and reporting information overload? Through an online survey, this study aims to provide the quantitative data that will answer these questions.

Information Overload 14

Methods This fixed design study consisted of an online survey, as I wanted to begin a quantitative orientation in extending the findings of Farhoomand & Drury (2002) and Ellington (2005). I provided ordinal Likert-type items for the sources of information overload listed in Ellington’s study to better measure the relative prevalence each source had in contributing to students’ sense of information overload. I administered a pilot study (N=25) in December 2008 to get feedback on item wording and form input design. There were sixty items in the final survey, although if the respondent answered in the negative to using social networking sites, they were immediately brought to the demographic items section of the survey. Also, items in this survey pertaining to SNS usage habits were based on a 2008 Educause Center for Applied Research study (Salaway & Caruso). As this was the third administration of the ECAR study, I was confident in the wording of its survey items. Moreover, the report could provide some corroborative evidence to this study’s statistical findings on students’ SNS usage. The final survey and informed consent form are in the Appendix of this thesis. The most recent statistics on the student population at the University of North Carolina indicate that during the spring 2009 semester there were 9,780 females and 6,763 males enrolled as undergraduates, for a total of 16,543 students in the population (“SAID”, 2009). However, not all of these students were subscribers to the informational e-mail mailing list through which I sent the study’s recruitment e-mails. Participants were solicited via two e-mail announcements which contained a link to

Information Overload 15 the online Qualtrics survey. The survey was open for completion during the weeks of January 26, 2009 through February 13, 2009. The initial recruitment e-mail was sent on January 26, and a week later (February 2) the second e-mail with a link to the survey was sent out to the participant pool. Once the three-week data collection period was over, I closed the online survey to further submissions and began to clean out the data. Data was unacceptable if survey takers did not agree to the informed consent form item given on the first page. Submissions were also excluded if no items were answered after the initial informed consent input. This yielded a final count of N=343. Because this was a non-random population, N was a sufficiently large sample from which I may extrapolate findings from the data analysis of this study.

Information Overload 16

Results Demographics Of the 343 respondents to the survey, 92 were male and 249 were female, with two respondents unreported. The gender percentage of respondents had a much higher female representation (73%) than that of the university’s undergraduate populace (59%, or 9,780 out of 16,543 total students). Also, members of the senior class were overrepresented, constituting 36% (5,894 out of 16,543) of the undergraduate population but accounting for 53% (181 out of 341) of respondents to the survey. I was unable to find enrollment statistics for part-time versus full-time students in the general university population, but 97% (319 out of 341) of the respondents were fulltime, compared to 3% (22 out of 341) of the part-time student respondents. See Appendix for the University of North Carolina’s enrollment statistics. There was no breakdown by age or ethnicity for the survey.

Information Overload 17

Study Demographics Grade Point Average GPA Count Prob A 57 0.16814 A96 0.28319 B+ 62 0.18289 B 55 0.16224 B27 0.07965 C+ 13 0.03835 C 9 0.02655 C4 0.01180 Decline to 16 0.04720 Report Total 339 1.00000 Class Standing Class Count Prob Senior 181 0.53079 Freshman 47 0.13783 Other 113 0.33138 class Total 341 1.00000

Gender Female Male Total

Gender Count 249 92 341

Prob 0.73021 0.26979 1.00000

Full-Time Status Status Count Prob Full 319 0.93548 Time Part 22 0.06452 Time Total 341 1.00000

Table 1. Demographic breakdown of the respondents by GPA, gender, class standing and full-time status

Feelings of Information Overload and Their Sources Undergraduates reported feeling overloaded by the information they had to handle at least occasionally (M=3.47, SD=0.82). The highest rated sources of information overload were Class Assignments (M=3.61, SD=1.00), E-mail (M=3.47, SD=1.17), and Work (M=3.21, SD=1.07). Students had a neutral or undecided attitude toward social networking sites as a source of information overload (M=3.09, SD=1.17). The source least likely to be perceived as a source of information overload

Information Overload 18 was instant messaging (M=2.47, SD=1.03), which is surprising, giving the interrupting nature of the communication. See Table 9 in the Appendix for the complete statistics on attitudes about sources of information overload.

5

Mean

3.4723032

4

SD

0.8227164

Std Err Mean

0.0444225

upper 95%

3.5596789

lower 95%

3.3849275

3 2 1 0

Disagree

N 1) 2) 3) 4) 5)

Key Never Very Rarely Occasionally Frequently Very Frequently

343

Item 1: “I feel overloaded by the amount of information I have to handle.”

Table 2. Response to the item “I feel overloaded by the amount of information I have to handle.” Most students felt overloaded at least occasionally.

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Variable Class Assignments Courseware E-mail Work TV Extracurricular Other Internet Text/Voice Phone Paper SNS IM

Spearman ρ Prob>| ρ| 0.3778 <.0001 0.3589 0.3410 0.2875 0.2494 0.2384 0.2366 0.2086 0.1574 0.1275 0.1270 0.1258

<.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0001 0.0038 0.0189 0.0191 0.0207

Table 3. Correlations between information sources and frequency of experiencing information overload. Class assignments, courseware, and e-mail were the sources most closely correlated with a higher frequency of experiencing information overload.

Social Networking Site Usage Behaviors Most of the respondents had over 300 friends in their profiles, and tended to visit their profiles at least daily. They would also spend six hours per week or less on the social networking site, and were actively involved in zero to five groups. Although there was a very weak correlation between perceptions of SNSs as a source of information overload and admitted feelings of information overload (ρ=0.1270, p<0.05), none of the specific behaviors could draw a significant correlation between it and the perception of SNSs as a source of information overload, nor were there any behaviors that had a significant correlation directly with the frequency of feeling information overload. This disproved both aspects of Hypothesis 1, as neither the frequency, duration (hours per week), nor intensity (profile changes and messages) of students’ usage of SNSs were significantly correlated with the frequency of feeling information overload. For the complete statistics, see Table 12 in the Appendix.

Information Overload 20

Variable

Spearman ρ

Prob>| ρ |

0.1270

0.0191

Visit Frequency

0.0612

0.2705

Hours/Wk

0.0612

0.2721

PM/Wall

0.0442

0.4279

Groups 2

0.0360

0.5174

Friends

0.0321

0.5639

-0.0276

0.6204

SNS (as a source of information overload)

Change Frequency

Table 4. SNS behaviors and how they correlate with experiencing information overload. There were no significant correlations between usage behaviors and information overload frequency.

Variable

Spearman ρ

Prob>| ρ|

Friends

0.1020

0.0667

Hours/Week

0.0972

0.0821

-0.0968

0.0825

0.0847

0.1287

-0.0710

0.2038

0.0089

0.8733

Visit Frequency Change Frequency PM/Wall Posts Groups

Table 5. How SNS behaviors correlate with the perception of SNSs as sources of information overload. There were no significant correlations between usage behaviors and the perception of SNSs as a source of information overload.

Information Overload 21 Coping Strategies for Information Overload The most common strategy for coping with information overload was filtering out irrelevant information (91.8%, n=313), followed by multitasking (90.9%, n=311) and organizing the information (86.2%, n=293). The least commonly employed were ignoring the information (32.5%, n=111) and delegation (32.7%, n=112). On average, respondents reported using about six of the ten coping strategies (M=5.96, SD=2.07). A table with the complete distribution statistics is in the Appendix. The results of the survey did not support Hypothesis 2; there was no significant correlation between the number of coping strategies and reported frequency of feeling information overload (ρ =0.0414, p=0.4451).

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-1 0

1 2 3 4

5 6 7 8

9 10 11

Mean

5.9620991

SD

2.0721682

Std Err Mean

0.1118866

upper 95%

6.1821716

lower 95%

5.7420267

N

Variable “I feel overloaded…”

343

Spearman ρ

Prob>|ρ|

0.0414

0.4451

Table 6. A distribution of the number of coping strategies employed by students. There was not a significant correlation between the number of strategies and reported frequencies of information overload

Information Overload 23

Discussion When clustered by gender, it is revealed that males do not associate SNSs with feelings of information overload (ρ=0.070, p=0.510) while females do, to a slight degree (ρ=0.144, p<0.05). This could be a function of the gender bias of the sample, as Ellington (2005) showed males reporting a higher incidence of information overload from technological sources. Also, 92 male respondents may be an insufficient size to achieve the power necessary to derive any statistically significant findings. When broken down by GPA, “A” students have a weak but significant correlation (ρ=0.186, p<0.05) between SNS and feelings of information overload, while “B” students do not have a significant correlation (ρ=0.089, p=0.292) between perceptions of SNS and feelings of information overload. This finding could be a budding indicator of a relationship between need for cognition and feelings of information overload. While SNSs are correlated with information overload at about the same rate as instant messaging, e-mail, classes, and courseware are more strongly correlated with the frequency of feeling overloaded. These results confirm the findings from Ellington (2005) and Farhoomand & Drury (2002) that e-mail and organizational sources rank higher than other sources for information overload. This could lead to some interesting research into the agency and emotional affect of retrieving information and its relation to information overload. E-mail, classes, and courseware tend to “push” information to users, often in great volumes and with no consideration of the user’s will. SNSs are more of a “pull” phenomenon, where users actively seek

Information Overload 24 out information they wish to know, and derive some social satisfaction for finding it. Later studies could investigate the “push/pull” dichotomy, incorporating other technologies such as RSS feeds and intelligent search agents to see if agency plays a part in feelings of information overload.

n

Variable

by Variable

Spearman ρ

Prob>|ρ|

249 Female

SNS

Feel Overloaded

0.1444

0.0232

92 Male

SNS

Feel Overloaded

0.0696

0.5099

153 “A” Students

SNS

Feel Overloaded

0.1855

0.0217

144 “B” Students

SNS

Feel Overloaded

0.0888

0.2917

Table 7. How gender and GPA correlate with frequency of feeling information overload. Females and “A” average students have a significant, positive correlation.

Limitations & Extensions To improve the instrument, I would refine several of the items focused on social networking site usage habits. For instance, the frequency of logging in, time spent, and personal messages sent would permit more granular analysis as continuous variables. I would try to find out what the “Other Internet uses” are that are more greatly perceived as sources of information overload than SNSs. Another improvement would be to introduce an ordinal scale to measure the frequency of employing particular coping strategies, allowing researchers to draw better correlations between coping strategies and their influence, or lack thereof, on frequency of feeling information overload. Perhaps most importantly, instead of relying on an explicit reporting of the frequency of experiencing information overload, future studies can turn the intensity or frequency of information overload

Information Overload 25 into a latent variable comprising feelings of stress, employment of coping strategies, and other elements that my obliquely reveal the understanding and experience of information overload for each respondent. With enough iterations and refinement to this instrument, researchers could develop a reliable Likert scale to evaluate feelings of information overload. An index to determine social network site usage intensity, based on frequency of usage and level of involvement within the SNS, could be developed to help better answer questions such as those posited in this study. Despite the flaws in the instrument, the data yielded from this survey still has rich possibilities for analysis and interpretation. Other ideas for future research may expand this study to examine factors such as a student’s major, age, or ethnicity. The survey can also be refined for nonacademic settings to investigate how people in certain professions experience information overload, and which factors they would cite which contribute to their feelings of information overload. Researchers may wish to look into how the design of a user interface may influence experiences and attitudes of information overload in e-mail clients, social networking site profiles, or courseware systems. Finally, studies that more closely examine the relationship between need for cognition and information overload can give us more insight into how a personal disposition can influence, and be influenced by, the copious amounts of information available because of modern technology.

Information Overload 26

Conclusion This study has concluded that social networking site usage behaviors are not linked with the frequency of experiencing information overload in undergraduate students. The number of times a respondent logged into his or her profile, how much time they spent per week on the SNS, and the messaging and other habits enacted on the sites played no significant role in how respondents perceived SNSs as information overload triggers. Likewise, the number of coping strategies employed by respondents had no significant correlation with the frequency of experiencing information overload. When grouped by gender, female respondents showed a slight correlation in viewing SNSs as a source of information overload, whereas males did not exhibit this perception. After clustering respondents by grade point average, there was a small but statistically significant positive correlation between GPA and frequency of experiencing information overload. For a concept that has been studied for more than half a century, information overload is still a remarkably fertile field for research. Qualitative research can shed light into what factors contribute to information overload, eventually yielding a way to measure information overload as a latent variable. User interface designers can find ways to minimize information overload in their software, and they can capitalize on other research on how users rely on particular coping strategies in a technological environment. This specific study can be refined and, eventually, administered to the general population to gauge just how severe a threat information overload is, how SNSs contribute to this load, and how best to cope with this unique challenge of the 21st century.

Information Overload 27 We are only human, with finite amounts of time and cognitive capacity to process nearly infinite amounts of information. Although we have a predisposition to gather as much information as we can, overindulging in information can be detrimental to our mental and physical well-being. Social networking sites, which pique our intellectual curiosity and exploit our social natures, will become major components in the information habits of upcoming generations. With further investigation, perhaps we will come to know whether this new form of computermediated communication is more a blessing or a bane when considered in the context of information overload.

Information Overload 28

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Information Overload 29 Butcher, H. (1995). Information overload in management and business. In Information Overload, IEE Colloquium on (pp. 1/1-1/2). Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116-131. Cacioppo, J. T., Petty, R. E., & Chuan Feng Kao. (1984). The efficient assessment of need for cognition. Journal of Personality Assessment, 48(3), 306. Cacioppo, J. T., Petty, R. E., Feinstein, J. A., & Jarvis, W. B. G. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 119(2), 197-253. Cohen, A. R., Stotland, E., & Wolfe, D. M. (1955). An experimental investigation of need for cognition. The Journal of Abnormal and Social Psychology, 51(2), 291-294. Dabbish, L. A., & Kraut, R. E. (2006). Email overload at work: an analysis of factors associated with email strain. In Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work (pp. 431-440). Banff, Alberta, Canada: ACM. Dearman, D., & Pierce, J. S. (2008). It's on my other computer!: computing with multiple devices. In Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems (pp. 767-776). Florence, Italy: ACM. de Rijk, A. E., Schreurs, K. M. G., & Bensing, J. M. (1999). What is behind "i'm so tired"? fatigue experiences and their relations to the quality and quantity of external stimulation. Journal of Psychosomatic Research, 47(6), 509-523. Dzubak, C. (2008). Multitasking: The good, the bad, and the unknown. ejournal of the Association of the Tutoring Profession, 1(2). Edmunds, A., & Morris, A. (2000). The problem of information overload in business organisations: a review of the literature. International Journal of Information Management, 20(1), 17-28 Ellington, V. (2005). An analysis of information overload components, sources, frequency, effect on performance and coping strategies utilized by full-time undergraduate university students. Master’s thesis, University of North Carolina, Chapel Hill, NC. Eppler, M., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. INFORMATION SOCIETY, 20(5), 325-344.

Information Overload 30 Farhoomand, A., & Drury, D. (2002). Managerial information overload. Commun. ACM, 45(10), 127-131. Fisher, D., Brush, A. J., Gleave, E., & Smith, M. A. (2006). Revisiting Whittaker & Sidner's "email overload" ten years later. In Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work (pp. 309312). Banff, Alberta, Canada: ACM. Galbraith, J. R. (1974). Organization design: An information processing view. Interfaces, 4(3), 28-36. Gardner, J.S.. (2008). Simultaneous media usage: Effects on attention. Retrieved October 27, 2008, from http://scholar.lib.vt.edu/theses/available/etd-02142008172617/. Hallowell, E. M. (2005). Overloaded circuits: why smart people underperform. Harvard Business Review, 83(1), 54-62. Jacoby, J., Speller, D. E., & Kohn, C. A. (1974). Brand choice behavior as a function of information load. Journal of Marketing Research, 11(1), 63-69. Janssen, R., & Poot, H. D. (2006). Information overload: why some people seem to suffer more than others. In Proceedings of the 4th Nordic conference on Human-computer interaction: changing roles (pp. 397-400). Oslo, Norway: ACM. Jones, Q., Ravid, G., & Rafaeli, S. (2004). Information overload and the message dynamics of online interaction spaces: A theoretical model and empirical exploration. Information Systems Research, 15(2), 194-210. Karger, D. R., & Jones, W. (2006). Data unification in personal information management. Commun. ACM, 49(1), 77-82. doi: 10.1145/1107458.1107496. Kaynar, O., & Amichai-Hamburger, Y. (2008). The effects of need for cognition on internet use revisited. Computers in Human Behavior, 24(2), 361-371. Klausegger, C., Sinkovics, R. R., & Zou, H. (2007). Information overload: a crossnational investigation of influence factors and effects. Marketing Intelligence & Planning, 25(7), 691 - 718. Koniger, P., & Janowitz, K. (1995). Drowning in information, but thirsty for knowledge. International Journal of Information Management, 15(1), 5-16. Levine, L. E., Waite, B. M., & Bowman, L. L. (2007). Electronic media use, reading, and academic distractibility in college youth. CyberPsychology & Behavior, 10(4), 560-566.

Information Overload 31

Madden, Mary. Networked workers. (2008) Washington, D.C.: Pew Internet and American Life Project. Retrieved September 30, 2008, from http://www.pewinternet.org/PPF/r/264/report_display.asp. Miller, G. A. 1956. The magical number seven, plus or minus two: Some limits on our capacity to process information. Psych. Rev. 63. 81–97. Milgram, S. (1970). The Experience of Living in Cities. Science, New Series., 167(3924), 1461-1468. Richtel, M. (2008, June 14). Lost in E-Mail, Tech Firms Face Self-Made Beast. The New York Times. Retrieved November 11, 2008, from http://www.nytimes.com/2008/06/14/technology/14email.html?_r=1&oref=slog in&partner=rssnyt&pagewanted=print. SAID :: Enrollment statistics - census date | Statistics | Office of the University Registrar. (n.d.). Retrieved March 20, 2009, from http://registrar.unc.edu/stats/census_data.php. Salaway, G., Caruso, J.B. (2008). The ECAR study of undergraduate students and information technology, 2008 (Research Study, Vol. 8). Boulder, CO: EDUCAUSE Center for Applied Research, available from http://www.educause.edu/ecar. Savolainen, R. (2007). Filtering and withdrawing: strategies for coping with information overload in everyday contexts. Journal of Information Science, 33(5), 611-621. Shenk, D. (1997). Data smog : Surviving the information glut. San Francisco, Calif.: Harper Edge. Statistics | Facebook. (2008). Retrieved October 2, 2008, from http://www.facebook.com/press/info.php?statistics. White, M. (2000). Technology briefs: Confronting information overload. Journal of School Health, 70(4), 160-161. Whittaker, S., Bellotti, V., & Gwizdka, J. (2006). Email in personal information management. Commun. ACM, 49(1), 68-73. Whittaker, S., & Sidner, C. (1996). Email overload: exploring personal information management of email. In Proceedings of the SIGCHI conference on Human factors in computing systems: common ground (pp. 276-283). Vancouver, British Columbia, Canada: ACM.

Information Overload 32 Wilson, P. (1997). Interdisciplinary research and information overload. Library Trends, 45(2), 192. Zeldes, N., Sward, D., & Louchheim, S. (2007). Infomania: Why we can’t afford to ignore it any longer. First Monday, 12(8).

Information Overload 33

Appendix A: Recruitment E-mails INFORMATIONAL: Participants Needed for Online Study Do you feel overwhelmed by information? Participants are needed for a study investigating information overload. To be eligible to participate, you must be: • •

At least 18 years of age Enrolled as an undergraduate at UNC

To participate, complete an online survey at [http://uncodum.qualtrics.com/SE?SID=SV_bOCCVT1QjEN65bS&SVID=Prod]. The survey will take approximately 15 minutes to complete. Four randomly selected participants who complete the survey will each be awarded a $25 Amazon.com gift card. Choosing or declining to participate in this study will not affect your class standing or grades at UNC-Chapel Hill. You will not be offered or receive any special consideration if you take part in this research; it is purely voluntary. This study has been approved by the UNC Behavioral IRB (IRB Study 08-2117; Approval Date: January 16, 2009). For more information, contact John Weis ([email protected]).

Information Overload 34

INFORMATIONAL: Feeling Overloaded? Tell Us About It! A study investigating information overload in undergraduates is still going on. To be eligible to participate, you must be: • •

At least 18 years of age Enrolled as an undergraduate at UNC

To participate, complete an online survey at [http://uncodum.qualtrics.com/SE?SID=SV_bOCCVT1QjEN65bS&SVID=Prod]. It takes approximately 15 minutes to complete. Four randomly selected participants who complete the survey for the study will each be awarded a $25 Amazon.com gift card. Choosing or declining to participate in this study will not affect your class standing or grades at UNC-Chapel Hill. You will not be offered or receive any special consideration if you take part in this research; it is purely voluntary. This study has been approved by the UNC Behavioral IRB (IRB Study 08-2117; Approval Date: January 16, 2009).

For more information, contact John Weis ([email protected]).

Information Overload 35

Appendix B: Consent Form University of North Carolina-Chapel Hill Consent to Participate in a Research Study Adult Participants Social Behavioral Form _____________________________________________________________________ ___ IRB Study #___08-2117__________________ Consent Form Version Date: _____01/12/2009_________ Title of Study: Information Overload in University Undergraduate Students Principal Investigator: John Weis UNC-Chapel Hill Department: SILS UNC-Chapel Hill Phone number: 966-5042 Email Address: [email protected] Faculty Advisor: Dr. Deborah Barreau Faculty Contact telephone number: 966-5042 Faculty Contact email: [email protected] Funding Source and/or Sponsor: UNC Honors Office Study Contact telephone number: (910) 554-8752 Study Contact email: [email protected] _________________________________________________________________ What are some general things you should know about research studies? You are being asked to take part in a research study. To join the study is voluntary. You may refuse to join, or you may withdraw your consent to be in the study, for any reason, without penalty. Research studies are designed to obtain new knowledge. This new information may help people in the future. You may not receive any direct benefit from being in the research study. There also may be risks to being in research studies. Details about this study are discussed below. It is important that you understand this information so that you can make an informed choice about being in this research study. You will be given a copy of this consent form. You should ask the researchers named above, or staff members who may assist them, any questions you have about this study at any time. What is the purpose of this study? The purpose of this research study is to learn about sources of information overload in undergraduate students’ lifestyles. It will try to determine what role participation in social networking sites has in feelings of information overload, and it will look at strategies students use to cope with information overload.

Information Overload 36

How many people will take part in this study? If you decide to be in this study, you will be one of approximately 300 people in this research study. How long will your part in this study last? The survey should take about fifteen minutes to complete. What will happen if you take part in the study? You will complete a survey that features questions about your perceptions of information overload, your social networking site usage habits, and general demographic information. What are the possible benefits from being in this study? Research is designed to benefit society by gaining new knowledge. You may not benefit personally from being in this research study. What are the possible risks or discomforts involved from being in this study? The research involves no more than minimal risk to subjects. There may be uncommon or previously unknown risks. You should report any problems to the researcher. How will your privacy be protected? Participants will not be identified in any report or publication about this study. Although every effort will be made to keep research records private, there may be times when federal or state law requires the disclosure of such records, including personal information. This is very unlikely, but if disclosure is ever required, UNCChapel Hill will take steps allowable by law to protect the privacy of personal information. In some cases, your information in this research study could be reviewed by representatives of the University, research sponsors, or government agencies for purposes such as quality control or safety. The survey system used in the study is provided by Qualtrics, Inc. The Qualtrics system maintains data behind a firewall and all data are accessed only by the owner of the survey who must provide password and user id. All pieces of data are keyed to that owner identification and cannot be accessed by anyone other than the owner or, by the owner's request, technical assistance staff. Technical assistance staff include server administrators at Qualtrics who will respond to hardware or software failures, or Teresa Edwards, the UNC administrator for the Qualtrics Software Agreement. Ms. Edwards has completed Human Subjects Research certification at UNC-CH, and will only access survey data at the account owner's request. The Qualtrics system has been used by government agencies, hundreds of universities and in many dissertations involving human subjects and even disadvantaged and at risk populations, including government sponsored studies collecting data about

Information Overload 37 physical and dependency abuse for adults and children. These are extremely confidential studies that have passed the highest level of scrutiny from human subjects committees. If you enter your e-mail address for the Amazon.com gift card drawing, the information will be encrypted and stored in a password-protected file on a USB key accessible only by the researcher. Once the drawing is complete, the file containing the e-mail addresses will be completely erased.

Will you receive anything for being in this study? After completing the survey, you will have the opportunity to enter a raffle for one of four $25 gift certificates to Amazon.com. Will it cost you anything to be in this study? There will be no costs for being in the study What if you are a UNC student? You may choose not to be in the study or to stop being in the study before it is over at any time. This will not affect your class standing or grades at UNC-Chapel Hill. You will not be offered or receive any special consideration if you take part in this research. What if you have questions about this study? You have the right to ask, and have answered, any questions you may have about this research. If you have questions, or concerns, you should contact the researchers via email at [email protected] or [email protected]. What if you have questions about your rights as a research participant? All research on human volunteers is reviewed by a committee that works to protect your rights and welfare. If you have questions or concerns about your rights as a research subject you may contact, anonymously if you wish, the Institutional Review Board at 919-966-3113 or by email to [email protected].

------------------------------------------------------------Title of Study: Information Overload in Undergraduate Students Principal Investigator: John Weis Faculty Advisor: Deborah Barreau

Information Overload 38

Participant’s Agreement: I have read the information provided above. I have asked all the questions I have at this time. I voluntarily agree to participate in this research study.

Information Overload 39

Appendix C: Survey *Information overload is the feeling of receiving too much information to be able to handle it effectively.

With this definition in mind, indicate how much you agree with the following statements: Never

Very Rarely Occasionally Frequently

Very Frequently

I feel overloaded by the amount of information I have to handle I have enough time to process the information I need to process When I perform an internet search, the results are relevant to me Information that is sent to me is relevant to me When I perform an internet search, the results are redundant Information that is sent to me is redundant

How much do you agree that the following items are sources of information overload for you? Strongly Disagree Class assignments

Disagree Undecided/Neutral

Agree

Strongly Agree

Information Overload 40 Courseware Systems (such as Blackboard or Sakai) E-mail Instant Messaging Social Networking Sites (such as Facebook or MySpace) Other Internet use Newspaper Television Phone Calls Voicemail and Text Messaging Work, internship, or other employment Extracurricular activities

I handle information overload by No Ignoring the information presented to me Filtering out irrelevant information Eliminating or discontinuing sources of information Delegating responsibilities for handling the information to

Yes

Don't Know

Information Overload 41 others Multitasking Checking sources of information more frequently Checking sources of information less frequently Organizing my information Consolidating my information in one place Looking for a technical solution

Do you use any social networking websites (Facebook, MySpace, Bebo, LinkedIn, etc.)? Yes

No

Don't Know

Which of the following social networking websites do you use? Check all that apply. Bebo Facebook Friendster LinkedIn MySpace Windows Live Spaces Yahoo! 360 Other

How many profiles do you currently have at social networking websites? 0 1

Information Overload 42 2 3 4 5 More than 5

How do you use social networking websites? Check all that apply. Stay in touch with friends Make new friends I have never met in person Find out more about people (I may or may not have met) Find someone to date As a forum to express my opinions and views Share photos, music, videos, or other work For professional activities (job networking, etc.) Communicate with classmates about course-related topics Communicate with instructors about course-related topics Participate in special interest groups Plan or invite people to events Respond to site advertisements Other

How often do you visit your social networking website profile? Several times a day About once a day Every few days Once a week Once a month Less than once a month Never/ Don't know

Information Overload 43

How often do you change your profile? Never Once a year Once a quarter/semester Monthly Weekly Several times per week Daily

Approximately how many hours per week do you use social networking websites? Less than 1 1-3 hours 4-6 hours 7-10 hours 11-13 hours 14-16 hours More than 16 hours

How many friends do you currently have at all the social networking websites you use? None 1–50 51-100 101-200 201-300 301-500 More than 500

How frequently do you send personal messages or wall posts in social networking websites? Several times a day Once a day

Information Overload 44 Several times a week Once a week Less than once a week

How many groups do you actively participate in at all the social networking websites you use? None 1-5 6-10 More than 10

What is your class standing? Senior or final year Freshman or first year Other

Are you currently a full-time or part-time student? Part-time is fewer than 12 credit hours per quarter/semester. Full Time Part Time

What is your cumulative GPA? A AB+ B BC+ C C- or lower Decline to answer

Information Overload 45

What is your gender? Female Male

To be eligible for the Amazon.com gift card drawing, please enter your e-mail address.

Information Overload 46

Appendix D: Statistics Tables

Classification

Gender

FR FR JR JR SO SO SR SR

F M F M F M F M Total

Total 2243 1564 1694 1143 2403 1602 3440 2454 16543

Table 8. Enrollment statistics for the University of North Carolina, Spring 2009

Information Overload 47 Information Source Distributions Class Assignments 5

4

3

Mean SD Std Err Mean upper 95% lower 95% N

3.6058824 1.0002776 0.0542477 3.7125868 3.4991779 340

Courseware Mean SD Std Err Mean upper 95% lower 95% N

3.0352941 1.0412955 0.0564722 3.1463741 2.9242141 340

E-mail Mean SD Std Err Mean upper 95% lower 95% N

3.4735294 1.170888 0.0635003 3.5984337 3.3486251 340

2

1

5

4

3

2

1

5

4

3

2

1

Information Overload 48

5

4

3

Instant Messaging Mean 2.4674556 SD 1.0280084 Std Err Mean 0.0559163 upper 95% 2.5774445 lower 95% 2.3574667 N 338

2

1

5

4

3

Social Networking Sites Mean 3.0882353 SD 1.1665861 Std Err Mean 0.063267 upper 95% 3.2126807 lower 95% 2.9637899 N 340

2

1

5

4

3

2

1

Other Internet uses Mean 3.0617647 SD 1.0638924 Std Err Mean 0.0576977 upper 95% 3.1752552 lower 95% 2.9482742 N 340

Information Overload 49

5

4

3

Newspaper Mean SD Std Err Mean upper 95% lower 95% N

2.6342183 1.0272084 0.0557903 2.7439582 2.5244784 339

Television Mean SD Std Err Mean upper 95% lower 95% N

2.9056047 1.1422227 0.062037 3.027632 2.7835774 339

Telephone Calls Mean SD Std Err Mean upper 95% lower 95% N

2.620178 1.0050213 0.054747 2.7278681 2.512488 337

2

1

5

4

3

2

1

5

4

3

2

1

Information Overload 50 Text Messaging and Voicemail Mean 2.6135693 SD 1.0524381 Std Err Mean 0.0571606 upper 95% 2.7260046 lower 95% 2.501134 N 339

5

4

3

2

1

Employment Mean SD Std Err Mean upper 95% lower 95% N

5

4

3

3.2117647 1.0708706 0.0580761 3.3259996 3.0975298 340

2

1

Other Extracurricular Activities Mean 3.1745562 SD 1.0985574 Std Err Mean 0.0597536 upper 95% 3.2920933 lower 95% 3.0570191 N 338

5

4

3

2

1

1) 2) 3) 4) 5)

Key Strongly Disagree Disagree Neutral/Undecided Agree Strongly Agree

Table 9. Response distributions to items about information sources

Information Overload 51

SNS Behavior Distributions 5

4

3

2

1

7 6 5 4 3 2 1

7 6 5 4 3 2 1

Visit Frequency 1) Several times a day 2) About once a day 3) Every few days 4) Once a week 5) Once a month 6) Less than once a month 7) Never Mean Std Dev Std Err Mean upper 95% lower 95% N Change Frequency 1) Never 2) Yearly 3) Semester 4) Monthly 5) Weekly 6) SeveralWeek 7) Daily

1.6748466 0.9004849 0.0498732 1.7729618 1.5767315 326

Mean Std Dev Std Err Mean upper 95% lower 95% N Hours/Wk 1) LessThan1 2) 1-3 3) 4-6 4) 7-10 5) 11-13 6) 14-16 7) 16+

3.6984615 0.9882789 0.0548198 3.8063093 3.5906137 325

Mean Std Dev Std Err Mean upper 95% lower 95% N

2.6080247 1.2078422 0.0671023 2.7400375 2.4760119 324

Information Overload 52

7 6 5

Friends 1) None 2) 1-50 3) 51-100 4) 101-200 5) 201-300 6) 301-500 7) 500+

4 3 2

5

4

Mean 5.9417178 Std Dev 1.2744744 Std Err Mean 0.0705866 upper 95% 6.0805821 lower 95% 5.8028535 N 326 Personal Messages and Wall Posts 1) SeveralDay 2) Daily 3) SeveralWeek 4) Weekly 5) LessWeek

3

2

1

4 3.5 3 2.5 2

Mean Std Dev Std Err Mean upper 95% lower 95% N Activity in Groups 1) None 2) 1-5 3) 6-10 4) 10+ Mean Std Dev Std Err Mean upper 95% lower 95% N

2.9783951 1.2377558 0.0687642 3.1136773 2.8431128 324

1.6707692 0.6844217 0.0379649 1.745458 1.5960804 325

1.5 1

Table 10. Response distributions SNS usage behavior items

Information Overload 53

Coping Strategy Distributions Ignore

Yes

Frequencies Response No Yes Total

Count Prob 231 0.67544 111 0.32456 342 1.00000

Frequencies Response No Yes Total

Count Prob 28 0.08211 313 0.91789 341 1.00000

Frequencies Response No Yes Total

Count Prob 109 0.32059 231 0.67941 340 1.00000

No

Filter

Yes

No

Eliminate

Yes

No

Information Overload 54

Delegate

Yes

Frequencies Response No Yes Total

Count Prob 212 0.62170 129 0.37830 341 1.00000

Frequencies Response No Yes Total

Count Prob 31 0.09064 311 0.90936 342 1.00000

Response No Yes Total

Count Prob 125 0.36982 213 0.63018 338 1.00000

No

Multitask

Yes

No

More Frequent

Yes

No

Information Overload 55 Frequencies Less Frequent

Yes

Frequencies Response No Yes Total

Count Prob 230 0.67251 112 0.32749 342 1.00000

Frequencies Response No Yes Total

Count Prob 47 0.13824 293 0.86176 340 1.00000

Frequencies Response No Yes Total

Count Prob 93 0.27273 248 0.72727 341 1.00000

No

Organize

Yes

No

Consolidate

Yes

No

Information Overload 56 Technical

Yes

Frequencies Response No Yes Total

Count Prob 185 0.54412 155 0.45588 340 1.00000

No

Table 11. Response distributions to coping strategy items

Information Overload 57 SNS Usage Correlations Nonparametric: Spearman's ρ Variable by Variable SNS (as a source) Feel Overloaded Visit Frequency Feel Overloaded Hours/Week Feel Overloaded PM/Wall Posts Feel Overloaded Groups 2 Feel Overloaded Friends Feel Overloaded Change Frequency Feel Overloaded

Spearman ρ 0.1270 0.0612 0.0612 0.0442 0.0360 0.0321 -0.0276

Prob>|ρ| 0.0191 0.2705 0.2721 0.4279 0.5174 0.5639 0.6204

Plot

Table 12. Correlation tables between SNS usage behaviors and feeling information overload.

Information Overload 58

Sources and Feelings of Information Overload Nonparametric: Spearman's ρ Variable by Variable Spearman ρ Class Assignments Feel Overloaded 0.3778 Courseware Feel Overloaded 0.3589 E-mail Feel Overloaded 0.3410 Other Internet Feel Overloaded 0.2366 TV Feel Overloaded 0.2494 Work Feel Overloaded 0.2875 Extr Feel Overloaded 0.2384 Text/Voice Feel Overloaded 0.2086 Phone Feel Overloaded 0.1574 Paper Feel Overloaded 0.1275 SNS (as a source) Feel Overloaded 0.1270 IM Feel Overloaded 0.1258

Prob>|ρ| <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0001 0.0038 0.0189 0.0191 0.0207

Plot

Table 13. Correlations between information sources and feelings of information overload