CYBERPSYCHOLOGY & BEHAVIOR

Volume 10, Number 4, 2007© Mary Ann Liebert, Inc.DOI: 10.1089/cpb.2007.9990

Electronic Media Use, Reading, and Academic Distractibility in College Youth

LAURA E. LEVINE, Ph.D., BRADLEY M. WAITE, Ph.D., and LAURA L. BOWMAN, Ph.D.

ABSTRACT

Activities that require focused attention, such as reading, are declining among Americanyouth, while activities that depend on multitasking, such as instant messaging (IMing), areincreasing. We hypothesized that more time spent IMing would relate to greater difficulty inconcentrating on less externally stimulating tasks (e.g., academic reading). As hypothesized,the amount of time that young people spent IMing was significantly related to higher ratingsof distractibility for academic tasks, while amount of time spent reading books was nega-tively related to distractibility. The distracting nature and the context of IMing in this popu-lation are described.

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INTRODUCTION

ACTIVITIES THAT REQUIRE intense, focused atten-tion, such as reading novels, are decreasing

among young people, while those that require thedivision of attention, such as instant messaging (IMing), are on the rise.1,2 A recent Kaiser FamilyFoundation (KFF) study of 2,032 young people aged8–18 found that “As new media technologies . . . be-come available, [young people] don’t . . . (or can’t)increase the number of hours they spend with me-dia—so they are increasingly becoming media mul-titaskers, IMing while doing homework and watch-ing TV.”3 IMing has become a major part of youngpeople’s lives since emerging as a major mode of in-teraction in the late 1990s. KFF’s 1999 survey ofyouth media use did not even ask about IMing, butby 2003–2004, IMing had become the second mostpopular computer activity after computer games,averaging 27 minutes per day among 15- to 18-year-olds.3

The nature of IMing

IMing is a communication tool that allows an in-dividual to communicate in separate typed conver-sations with many people at the same time whileonline using the computer. Each user develops a“buddy list” of people from whom that person willaccept instant messages (IMs). When users activatetheir IM software, these messages appear on theircomputer screen whenever someone is contactingthem. Instant messagers may be notified with a pop-up at the bottom of their screen when people ontheir buddy list are active or idle in IM. IMing cre-ates multiple interruptions and multitasking de-mands that might put stress on cognitive process-ing.

The interruptive nature of IMing has been of con-cern in the context of the work world. For example,researchers studying performance issues on theNavy’s Tomahawk missile control found an unin-tended effect. Sailors’ attention to the IMing used

Psychology Department, Central Connecticut State University, New Britain, Connecticut.

by the researchers to assess their performance ac-tually interfered significantly with the sailors’ abil-ity to carry out missile control.4 “Advances in com-puter technologies . . . allow people to performmultiple activities at the same time. However, peo-ple’s cognitive capabilities have not increased.”5 Asa result, interruptions have been found to cause se-rious problems for effective functioning in work sit-uations such as piloting a plane.5

What impact might all of this multitasking and con-stant interruption have on young people’s academicactivity? Teens are reporting difficulty with concen-trating on their schoolwork, with 15-year-olds expe-riencing more difficulty concentrating than 10-year-olds.6 Larson attributed this developmental differenceto a decrease in intrinsic motivation in school-basedtasks. However, it could also be that teens are multi-tasking while doing their schoolwork or that overtime, the multitasking that young people are doing istaking a toll on their ability to focus attention on oneactivity in depth. “Habitual multitasking may condi-tion their brain to an overexcited state, making it dif-ficult to focus even when they want to.”7

Little research has been done on the relationshipbetween the use of interactive media and the abil-ity to focus attention. In this study, we examine therelationship between one of these new interactivetechnologies, IMing, and college students’ percep-tions of their own ability to focus on academic tasks.Our goals in the present study are to examine (a)the amount of IMing being done by young collegestudents in relation to other media use; (b) the na-ture of IMing in this population: how they are us-ing this technology; and (c) the relationship betweenIMing and distractibility for academic tasks. We hy-pothesized that greater amounts of time spent IM-ing would be related to greater difficulty in con-centrating on less externally stimulating tasks,particularly on academic reading.

METHOD

Participants

One hundred fifteen female and 46 male collegestudents, aged 17 to 20 years (mean age � 18.37years, SD � 0.64), completed the measures for thisstudy. Students were primarily white/non-His-panic (83%) from working- and middle-class fami-lies. Fifty-eight percent lived on campus. Studentswere enrolled in general psychology classes and re-ceived course credit for their participation; studentacademic majors were well distributed and camefrom all the schools in the University.

Measures and procedure

Students completed a 55-item questionnaire de-signed to measure various aspects of their electronicmedia use, reading (nonelectronic), and dis-tractibility for academic tasks. Demographic datawere also reported.

Amount of IMing

In order to place IMing in the overall context ofparticipants’ media use, students reported theiramount of Internet use, IMing, television viewing,video/computer game playing, music listening, aswell as their frequency of reading books for plea-sure, reading newspapers, and reading magazines.Responses for electronic media were made on aseven-point scale corresponding to the following in-tervals: 0, 1–7, 8–14, 15–21, 22–28, 29–35, 36 or more.Each nonzero choice (except 36 or more) encom-passes exactly 7 hours; the arithmetic midpoints ofeach are spaced equal intervals apart. We thustreated these data as interval scaled for analytic pur-poses. Responses for reading books, newspapers,and magazines were made on an eight-point scalecorresponding to the following intervals: 0, � 1, 1–2,3–5, 6–9, 10–13, 14–17, 18 or more.

Nature of IMing

Participants reported on the nature of their useof IM in two ways: descriptions of general use anddescriptions of their most recent IM session. Forgeneral use, students reported how often their IMsoftware was on when their computer was on: never(1) to very often (5). Students also reported two mea-sures designed to estimate the level of potential dis-ruption experienced while IMing: (a) the number ofpeople (if any) they typically IMed at the same time(open-ended response) and (b) whether they typi-cally responded right away when they were work-ing on their computer and received an IM: never (1)to always (5).

To examine the context of a “typical” IM session,participants described their most recent IM session.Students reported how long ago their most recentIM session was using a six-point ordinal scale (to-day, this week, last week, 2–3 weeks ago, 1–3months ago, � 3 months ago). They also reportedthe number of people with whom they IMed dur-ing that session, the length of time they IMed, andwhat else they were doing while IMing. Studentsrated their feelings of distractibility during the IMsession on 3 seven-point bipolar scales (focused-dis-tracted, attentive-preoccupied, and engaged-unin-volved).

MEDIA USE AND DISTRACTIBILITY 561

Distractibility for academic tasks

Students completed five-point Likert scales—strongly agree (1) to strongly disagree (5)-for sevenitems designed to measure distractibility for acade-mic tasks (e.g., “I get distracted easily when read-ing class assignments,” “I feel impatient when I readmy textbooks”). We designed these items specifi-cally to measure academic distractibility, that is, dis-tractibility relating to specific typical class relatedactivities.

RESULTS

Principal components analysis (PCA) for distractibilityfor academic tasks

We conducted a PCA on the seven items designedto measure distractibility for academic tasks. Twocomponents were extracted. The first had an eigen-value of 2.37 and explained 34% of the variance.Four items loaded above 0.6 on this factor. The items(and factor loadings) were “I find it easy to focuson assigned readings” (�0.691), “I feel impatientwhen I read my textbooks” (0.768), “I get distractedeasily when reading class assignments” (0.779), and“I rarely do the assigned readings for my classes”(0.623). We labeled the factor as “distractibility foracademic tasks” and retained it for use in furtheranalyses. A separate analysis indicated acceptableinternal consistency of these four academic dis-tractibility items (a � 0.74). To assess the validity ofour scale, we correlated a separate group of stu-dents’ (N � 97) scores on our Distractibility for Aca-demic Tasks scale with standard measures of dis-tractibility and impulsiveness, namely the BarrattImpulsiveness Scale8,9 and the Internal RestlessnessScale.10 Pearson correlations between our academicdistractibility measure and these two standard mea-sures were 0.521 (p � 0.001) and 0.479 (p � 0.001) re-spectively, indicating that our measure of academicdistractibility had acceptable construct validity. Asecond factor had an eigenvalue of 1.35 and ex-plained 19% of the variance. Two items loadedabove 0.6 on this factor. These two items reflectedself-appraisals of writing ability and as such wereoutside of the focus of this paper. Thus, we droppedthis factor from further analyses.

Testing gender differences

A preliminary multivariant analysis of variance(MANOVA) comparing all media use variables anddistractibility for academic tasks by gender was sig-nificant, Pillai’s F(11, 131) � 3.567, p � 0.001, �2 �

.230. However, follow-up univariate one-wayanalyses of variance (ANOVAs) demonstrated thatthere was only one variable with a significant gen-der difference. Male students played significantlymore video/computer games (M � 2.15, SD � 1.00)than did female students (M � 1.46, SD � 0.59), F(1,143) � 26.185, p � 0.001. All other univariateANOVAs were nonsignificant (p � 0.05). Therefore,we decided to collapse our data between gendersfor all further analyses.

Amount of IMing

In order to envision the overall context of mediause by our sample of young persons, we present de-scriptive media use data in Table 1. Students re-ported that their most commonly used media werethe Internet, IMing, and listening to music. Whenasked about their reasons for using the Internet, usefor IMing was the second highest endorsed reason(77% reporting IMing as “very often” or “often” areason for their Internet use). This percentage wassurpassed only by use for research (79%). The per-centage of students reporting that they “very often”or “often” use the Internet for IMing exceeded thepercent who use it for e-mail (74%).

Nature of IMing

We wanted to describe how students are usingIM. The frequencies reported in this section are thepercentage of students who endorsed “very often”or “often” for the indicated items; we use the term“frequently” in this section to represent this per-centage. The great majority of students (90.1%) re-ported that they frequently IM. Nearly three quar-ters (73.4%) reported that they frequently had theirIM turned on when their computer was on. A typ-ical IM session was reported to last 75.2 minutes(SD � 34.62) with a total of 2.93 different people(SD � 1.38). Sixty-three percent reported that theyfrequently respond to IMs right away when they areworking on the computer. When asked about theirmost recent IM session, 90% reported that it was“today” or “this week.” Thirty percent reported thatduring this most recent IM session, they were do-ing academic work at that same time. Of those do-ing academic work, 87% reported doing the acade-mic work online or on the computer. Seventy-threepercent reported that they were doing other activi-ties in addition to IMing. Students reported IMingduring the most recent IM session with a mean of3.91 different people (SD � 4.58), most frequentlywith friends (96%).

We combined the three bipolar adjective pairs de-signed to measure students’ rating of their own fo-

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cus and distractibility during the most recent IMsession and labeled this new variable “distractibil-ity during most recent IM session” Scores on thecombined distractibility variable could range from3 to 21. Observed distractibility scores ranged from3 to 16 (M � 9.13, SD � 2.82). Chronbach’s alpha forthis variable was 0.69. Using Pearson correlations,we found that students who report being quick torespond when someone IMs them were signifi-cantly more likely to report feeling distractible dur-ing their most recent IM session (r � 0.187, p �0.009). Distractibility during the most recent IM ses-sion was not significantly correlated (p � 0.05) withthe frequency of having the IM on when the com-puter is on (r � 0.057), the number of people IMedduring the most recent session (r � �0.051), thelength of the most recent IM session (r � �0.020),or the number of other activities that the student re-ported doing during the IM session (r � �0.119)

Zero-order correlations of media variables anddistractibility for academic tasks

At the zero-order, distractibility for academictasks (factor 1) was significantly (p � 0.05) nega-tively correlated with reported frequency of read-ing books for pleasure and reading magazines andwas significantly positively correlated with fre-quency of IMing and listening to music. Descriptivestatistics and Pearson correlations among media usevariables and distractibility for academic tasks arepresented in Table 1. Given the nature of the mea-surement scale for the reading variables, we also cal-culated Spearman’s rho for the zero-order correla-tions. The results followed the same pattern, so wedecided to report the Pearson correlations and con-duct a parametric regression analysis.

Multiple regression analysis predicting distractibilityfor academic tasks

A multiple regression analysis using electronicand nonelectronic media use variables (e.g., fre-quency of reading books, newspapers, and maga-zines; frequency of IMing, Internet use, watchingtelevision, playing video/computer games, and lis-tening to music; the number of people the studenttypically IMs at the same time; and how quickly thestudent responds to IMs) to predict distractibilityfor academic tasks was conducted. All variables ex-cept for two had no more than three cases of miss-ing data. The two with more missing data measuredthe number of different people with whom the stu-dent typically IMed and the frequency that they re-sponded “right away” when IMed. These variableshad usable data for 145 and 150 out of 161 possiblecases respectively. We used a mean substitutiontechnique to handle missing data, although addi-tional analyses yielded essentially identical regres-sion results using pairwise or listwise deletions. Theregression was significant, F(10, 150) � 4.257, p �0.000, R2 � 0.221. Distractibility was significantlynegatively predicted by the frequency of readingbooks for pleasure (� � �0.347, p � 0.000) and sig-nificantly positively predicted by the amount of IM-ing (� � 0.290, p � 0.019). See Table 2 for regressiondetails.

DISCUSSION

When examining the correlates of students’ self-described distractibility for academic reading, ourhypothesis was confirmed. The amount of time theyspent IMing was significantly related to more dis-

LEVINE ET AL.564

TABLE 2. REGRESSION ANALYSIS SUMMARY FOR MEDIA USE VARIABLES

PREDICTING DISTRACTIBILITY FOR ACADEMIC TASKS

Variable B SEB �

Read books �0.319 0.068 �0.347**Read newspapers �0.046 0.090 �0.041Read magazines �0.145 0.080 �0.145a

Watch television 0.054 0.088 0.050Internet use �0.085 0.083 �0.124Video/computer games �0.038 0.093 �0.031Listen to music 0.078 0.046 0.131Instant message 0.173 0.073 0.290*Respond quickly to IM? 0.042 0.098 0.033N people IM with? �0.086 0.058 �0.114

Note: R2 � 0.221 (N � 161, p � 0.001).ap � 0.07; *p � 0.019; **p � 0.001.

tractibility for academic reading, while amount oftime spent reading books was negatively related todistractibility. In addition, distractibility during IMsessions was positively related to their likelihood ofresponding right away when IMed.

There are three ways in which IMing might in-terfere with academic reading: (a) displacement oftime available for study, (b) direct interferencewhile studying, and (c) development of a cognitivestyle of short and shifting attention. The first possi-bility is that Internet use, and IMing in particular,displaces the amount of time spent on activities suchas reading.3,11–14 We found that time spent on IM-ing was the third most frequent use of media. Eventhis finding is somewhat deceptive because the sec-ond highest reason for using the Internet, after re-search, was IMing. Ninety percent of our sample re-ported using IMing frequently and for an averageof 75 minutes, so these students were spending con-siderable time in this activity.

There was also evidence that some students wereIMing while carrying out academic tasks, whichwould likely provide a direct interference with fo-cus on those tasks.15–17 The distracting, multitask-ing nature of IMing was apparent. Most (63%) re-sponded right away whenever they received aninstant message and were IMing three or four peo-ple at the same time. The majority were involved inother activities while IMing, with 30% doing acad-emic work at the same time.

The findings are also consistent with the thirdpossibility, that IMing helps to create a cognitivestyle based on quick, superficial multitasking ratherthan in-depth focus on one task such as reading. Theidea that cognitive style may be shaped by experi-ences with fast-moving media has found support inresearch on children who watch a great deal of tele-vision and/or watch it from early in life. Levine andWaite found that the more television childrenwatched, the more likely their teachers were to ratethem as impulsive and inattentive in the class-room.18 Christakis et al. found that greater amountsof television viewed by children when they wereone and three years of age were associated with at-tentional problems at age seven.19 We know thatadolescent brains are continuing to develop, partic-ularly in the area of the prefrontal cortex, which hasbeen linked to attention control.20 We can speculatethat this brain development may be affected by fre-quent activities such as IMing to change their stylesof attentional focus and cognitive processing.

This study was designed as an exploratory, de-scriptive look at the distracting nature of IMing andother media use. A more extensive, standardizedmeasure of academic distractibility would add tothe evidence presented here. The correlational na-

ture of this study prevents us from determiningcausality. Future experimental studies should be de-signed to test the relative validity of each of the threepossible explanations of the link between dis-tractibility and IMing.

Will we think in a different way because of ouruse of multitasking, interruptive media? Will stu-dents find increasing difficulty with traditionalmodes of learning through reading books and arti-cles? Will depth and intensity of thought be ex-changed for speed? Thomas Friedman of the NewYork Times describes the current tendency towardthe use of “continuous partial attention” as “whenyou are on the Internet or cell phone or Blackberrywhile also watching TV, typing on your computerand answering a question from your kid. That is,you are multitasking your way through the day,continuously devoting only partial attention to eachact or person you encounter. . . . Who can think orwrite or innovate under such conditions?” He spec-ulates that eventually “we [will] all get diagnosedwith some version of attention deficit disorder.”21

It is possible that new approaches to learning willemerge. For example, action video games have beenfound to improve aspects of visual attention.22 Per-haps positive results may also be found for IMingand multitasking. It is clear that this new technol-ogy is growing and that we must understand theimpact it will have on our youth.

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Address reprint requests to:Dr. Laura E. Levine

Psychology DepartmentCentral Connecticut State University

1615 Stanley St.New Britain, CT 06050

E-mail: LevineL@ccsu.edu

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