Internet use and multitasking among older adolescents: An experience sampling approach
Highlights
► Internet use is usually measured by self-report, which may be subject to recall bias. ► We used experience-sampling method to measure internet use. ► Total daily internet use was less than typically reported. ► Multitasking accounted for over half of internet use time. ► Internet use may be over-reported due to multitasking.
Introduction
Internet use among college students has grown exponentially in the last decade. The vast majority of adolescents have internet access, and most report daily use (Lenhart, Purcell, Smith, & Zickuhr, 2010). Today’s college student may have access to the Internet by home computers, laptops, as well as smart phones. Students use the internet for a variety of reasons, including communication, academic work and entertainment (Borzekowski and Rickert, 2001, Colley and Maltby, 2008). Many media devices allow adolescents to engage in all of these pursuits simultaneously, often called “media multitasking” (Levine, Waite, & Bowman, 2007). For example, a college student may be working on an academic assignment while chatting online and watching a TV show via streaming on the computer (Levine et al., 2007).
Efforts to assess daily internet use have traditionally relied on self-report (Lenhart, 2009, Lenhart and Madden, 2007, Lenhart et al., 2005). The Pew Internet and American Life Project have collected critical data monitoring internet use and trends within technology use. Approximately 63% of teens go online every day, while 36% go online more than one time a day (Lenhart and Madden, 2007, Lenhart et al., 2005, Richardson et al., 2010). The Kaiser Family Foundation have also collected large datasets describing internet use trends: 2009 estimates suggest that adolescents’ daily time spent on the computer for non-academic purposes was approximately 1 h and 40 min (Jones, Johnson-Yale, Millermaier, & Perez, 2009).
The accuracy of such self-reported use is unclear, a 2005 study found modest overestimation of total time spent on the computer over the course of a day (Hunley et al., 2005). An understanding of how the internet is used on a daily basis, such as frequency of multitasking, is also less understood. A real-time examination of internet use and online activities remains elusive and may contribute to development of more accurate ways to measure and understand internet use. Such a study could provide an excellent complement to existing datasets by providing an understanding of the concurrent validity of self-report.
Experience sampling method (ESM), also called ecological momentary assessment (EMA), is characterized by a collection of data in real-world environments: assessments that focus on individual’s current or very recent status or behaviors. ESM is well suited for rich description and understanding the most complete description of the phenomenon within the daily life of the individual. ESM methods have been used in a variety of investigations of behaviors that ESM avoids the reliance on retrospective reports which may be subject to biases that challenge their reliability and validity (Jones & Johnston, 2011). Further, this approach has the advantage of collecting data within the participant’s own habitat, thus enhancing the external validity of the results (Trull & Ebner-Priemer, 2009). Multiple assessments over time are the norm; this approach is particularly effective for behaviors that occur intermittently (Shiffman et al., 2009, Trull and Ebner-Priemer, 2009). ESM is well suited to track moods, thoughts, symptoms or behaviors believed to change over time (Ebner-Priemer & Trull, 2009).
The ESM approach using electronic media presents some advantages over more traditional methods using paper diaries, as with paper diaries the researcher cannot ensure that the diary was completed at the specified times. Using this method, the researcher contacts the participant, often using cell phones or personal digital assistants (PDAs), to ask questions about activities or thoughts that are taking place at that moment. College students may access the internet with various devices during a typical day, such as using a phone, a personal laptop computer, or a university computer. Thus, using cell phones to collect data regarding current internet use via ESM has the advantage that participants can report any current internet use. This presents an advantage over methods that rely on tracking computer use time on only one device, such as on a personal laptop computer.
Despite these advantages, the role of ESM in understanding daily internet use is not known. ESM may provide a novel way to assess how well self-report and ESM measured internet use align. While both methods rely on participant self-report, ESM methods provide an opportunity for real-time self-report in the moment, which reduces the burden of recall bias needed when reporting about internet use over the course of an entire day. ESM also provides a new method to assess not only how much internet use is taking place, but what activities are occurring throughout a day. Given the challenges in measuring internet use in today’s multimedia society, ESM may provide new insights into this phenomenon.
We hypothesized that if self-reported internet use and ESM measured internet use were strongly correlated, that would support the use of either method as an accurate depiction of daily internet use. If these two measures diverged, consideration must be given to why. To include measures to explore possible divergence in these two measures, we included assessments of daily internet use activities.
The purpose of this study was to examine college students’ internet use time and online activities. Our three aims include: (1) to determine an accurate measure of college students’ daily internet use time using ESM, (2) to compare daily ESM internet use time to self-report, and (3) to determine the frequency of internet use activities and multitasking.
Section snippets
Setting and subjects
This study took place at a large state university and received approval from the University of Wisconsin Institutional Review Board. Potential subjects were identified within a communications classroom that is a requirement for several majors and a general distribution requirement for many departments. Inclusion criteria required students to be current undergraduates between the ages of 18 and 23. Subjects were required to have a cellular phone with texting ability. Recent campus data reports
Participants
From a classroom of 375 students, 273 participants (72.8%) completed the online survey for extra credit. From this population, 193 (71%) were recruited into the ESM study. All eligible participants owned a cell phone with texting ability. A total of 3 participants did not respond to any texts and were dropped from all analyses as nonresponders. Among 190 participants who provided data, 189 completed our goal of 75% of texts completed. Overall, 93.2%, 95% CI [91.8%, 94.5%] of text messages were
Overview
The purpose of this study was to examine college students’ internet use time and online activities. We used experience sampling method (ESM) to pursue our aims of assessing college students’ daily internet use and comparing this to self-report, and determining the frequency of internet use activities and multitasking. Overall, we found that total internet use time was approximately 1 h per day and ESM internet time had low correlation with self-reported internet use of approximately 3.5 h per day.
Conclusion
Our goal for this study was to assess college students’ daily internet use with a novel approach of ESM, and to place these results in the context of traditional methods of self-reported daily internet use. We found that results for ESM measured internet use were consistent across several analytic approaches, and lower than self-reported internet use rates. We cannot confirm with certainty which method produced the most accurate results. However, we can conclude that further study is needed to
Acknowledgments
Funding for this project was provided in part by the University of Wisconsin Graduate School. The funders had no role in study design, data collection writing or decision to submit the article for publication. The authors would like to acknowledge the contributions of Katie Bare, BA, Greg Downey, PhD, Sandon Jurowski, BS and Ben Longoria, BS to this project.
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